Displaying publications 21 - 40 of 371 in total

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  1. Aliteh NA, Misron N, Aris I, Mohd Sidek R, Tashiro K, Wakiwaka H
    Sensors (Basel), 2018 Aug 01;18(8).
    PMID: 30071614 DOI: 10.3390/s18082496
    This paper aims to study a triple flat-type air coil inductive sensor that can identify two maturity stages of oil palm fruits, ripe and unripe, based on the resonance frequency and fruitlet capacitance changes. There are two types of triple structure that have been tested, namely Triple I and II. Triple I is a triple series coil with a fixed number of turns (n = 200) with different length, and Triple II is a coil with fixed length (l = 5 mm) and a different number of turns. The peak comparison between Triple I and II is using the coefficient of variation cv, which is defined as the ratio of the standard deviation to the mean to express the precision and repeatability of data. As the fruit ripens, the resonance frequency peaks from an inductance⁻frequency curve and shifts closer to the peak curve of the air, and the fruitlet capacitance decreases. The coefficient of the variation of the inductive oil palm fruit sensor shows that Triple I is smaller and more consistent in comparison with Triple II, for both resonance frequency and fruitlet capacitance. The development of this sensor proves the capability of an inductive element such as a coil, to be used as a sensor so as to determine the ripeness of the oil palm fresh fruit bunch sample.
    Matched MeSH terms: Data Collection
  2. 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: Data Collection
  3. Yang C, Simon G, See J, Berger MO, Wang W
    Sensors (Basel), 2020 May 27;20(11).
    PMID: 32471231 DOI: 10.3390/s20113045
    Collecting correlated scene images and camera poses is an essential step towards learning absolute camera pose regression models. While the acquisition of such data in living environments is relatively easy by following regular roads and paths, it is still a challenging task in constricted industrial environments. This is because industrial objects have varied sizes and inspections are usually carried out with non-constant motions. As a result, regression models are more sensitive to scene images with respect to viewpoints and distances. Motivated by this, we present a simple but efficient camera pose data collection method, WatchPose, to improve the generalization and robustness of camera pose regression models. Specifically, WatchPose tracks nested markers and visualizes viewpoints in an Augmented Reality- (AR) based manner to properly guide users to collect training data from broader camera-object distances and more diverse views around the objects. Experiments show that WatchPose can effectively improve the accuracy of existing camera pose regression models compared to the traditional data acquisition method. We also introduce a new dataset, Industrial10, to encourage the community to adapt camera pose regression methods for more complex environments.
    Matched MeSH terms: Data Collection
  4. Chua SL, Foo LK
    Sensors (Basel), 2017 Aug 18;17(8).
    PMID: 28820438 DOI: 10.3390/s17081902
    Activity recognition in smart homes aims to infer the particular activities of the inhabitant, the aim being to monitor their activities and identify any abnormalities, especially for those living alone. In order for a smart home to support its inhabitant, the recognition system needs to learn from observations acquired through sensors. One question that often arises is which sensors are useful and how many sensors are required to accurately recognise the inhabitant's activities? Many wrapper methods have been proposed and remain one of the popular evaluators for sensor selection due to its superior accuracy performance. However, they are prohibitively slow during the evaluation process and may run into the risk of overfitting due to the extent of the search. Motivated by this characteristic, this paper attempts to reduce the cost of the evaluation process and overfitting through tree alignment. The performance of our method is evaluated on two public datasets obtained in two distinct smart home environments.
    Matched MeSH terms: Data Collection
  5. Perumal L, Tso CP, Leng LT
    J Adv Res, 2016 May;7(3):445-52.
    PMID: 27222749 DOI: 10.1016/j.jare.2016.03.004
    This paper presents analysis of thin plates with holes within the context of XFEM. New integration techniques are developed for exact geometrical representation of the holes. Numerical and exact integration techniques are presented, with some limitations for the exact integration technique. Simulation results show that the proposed techniques help to reduce the solution error, due to the exact geometrical representation of the holes and utilization of appropriate quadrature rules. Discussion on minimum order of integration order needed to achieve good accuracy and convergence for the techniques presented in this work is also included.
    Matched MeSH terms: Data Collection
  6. Ardakani A, Seghatoleslam T, Habil H, Jameei F, Rashid R, Zahirodin A, et al.
    Iran J Public Health, 2016 Apr;45(4):451-9.
    PMID: 27252914
    Given that validity is the baseline of psychological assessments, there is a need to provide evidence-based data for construct validity of such scales to advance the clinicians for evaluating psychiatric morbidity in psychiatric and psychosomatic setting.
    Matched MeSH terms: Data Collection
  7. Mousavi SM, Naghsh A, Abu-Bakar SA
    J Digit Imaging, 2014 Dec;27(6):714-29.
    PMID: 24871349 DOI: 10.1007/s10278-014-9700-5
    The ever-growing numbers of medical digital images and the need to share them among specialists and hospitals for better and more accurate diagnosis require that patients' privacy be protected. As a result of this, there is a need for medical image watermarking (MIW). However, MIW needs to be performed with special care for two reasons. Firstly, the watermarking procedure cannot compromise the quality of the image. Secondly, confidential patient information embedded within the image should be flawlessly retrievable without risk of error after image decompressing. Despite extensive research undertaken in this area, there is still no method available to fulfill all the requirements of MIW. This paper aims to provide a useful survey on watermarking and offer a clear perspective for interested researchers by analyzing the strengths and weaknesses of different existing methods.
    Matched MeSH terms: Data Collection/methods*; Data Collection/statistics & numerical data
  8. Arnulf JK, Larsen KR, Martinsen ØL, Bong CH
    PLoS One, 2014;9(9):e106361.
    PMID: 25184672 DOI: 10.1371/journal.pone.0106361
    Some disciplines in the social sciences rely heavily on collecting survey responses to detect empirical relationships among variables. We explored whether these relationships were a priori predictable from the semantic properties of the survey items, using language processing algorithms which are now available as new research methods. Language processing algorithms were used to calculate the semantic similarity among all items in state-of-the-art surveys from Organisational Behaviour research. These surveys covered areas such as transformational leadership, work motivation and work outcomes. This information was used to explain and predict the response patterns from real subjects. Semantic algorithms explained 60-86% of the variance in the response patterns and allowed remarkably precise prediction of survey responses from humans, except in a personality test. Even the relationships between independent and their purported dependent variables were accurately predicted. This raises concern about the empirical nature of data collected through some surveys if results are already given a priori through the way subjects are being asked. Survey response patterns seem heavily determined by semantics. Language algorithms may suggest these prior to administering a survey. This study suggests that semantic algorithms are becoming new tools for the social sciences, opening perspectives on survey responses that prevalent psychometric theory cannot explain.
    Matched MeSH terms: Data Collection*
  9. REID HA, LIM KJ
    Br Med J, 1957 Nov 30;2(5056):1266-72.
    PMID: 13479694
    Matched MeSH terms: Data Collection*
  10. HOLMES W
    Med J Malaya, 1955 Dec;10(2):178-80.
    PMID: 13308619
    Matched MeSH terms: Data Collection*
  11. Bilal M, Gani A, Lali MIU, Marjani M, Malik N
    Cyberpsychol Behav Soc Netw, 2019 Jul;22(7):433-450.
    PMID: 31074639 DOI: 10.1089/cyber.2018.0670
    Social media has taken an important place in the routine life of people. Every single second, users from all over the world are sharing interests, emotions, and other useful information that leads to the generation of huge volumes of user-generated data. Profiling users by extracting attribute information from social media data has been gaining importance with the increasing user-generated content over social media platforms. Meeting the user's satisfaction level for information collection is becoming more challenging and difficult. This is because of too much noise generated, which affects the process of information collection due to explosively increasing online data. Social profiling is an emerging approach to overcome the challenges faced in meeting user's demands by introducing the concept of personalized search while keeping in consideration user profiles generated using social network data. This study reviews and classifies research inferring users social profile attributes from social media data as individual and group profiling. The existing techniques along with utilized data sources, the limitations, and challenges are highlighted. The prominent approaches adopted include Machine Learning, Ontology, and Fuzzy logic. Social media data from Twitter and Facebook have been used by most of the studies to infer the social attributes of users. The studies show that user social attributes, including age, gender, home location, wellness, emotion, opinion, relation, influence, and so on, still need to be explored. This review gives researchers insights of the current state of literature and challenges for inferring user profile attributes using social media data.
    Matched MeSH terms: Data Collection/methods*
  12. Holland B
    Hum Biol, 1987 Jun;59(3):477-87.
    PMID: 3610122
    The effects of breast-feeding on infant health and mortality, particularly in the developing nations, are a matter of controversy and importance. The Malaysian Family Life Survey (MFLS) of over 1200 women has recently been the source of a great deal of valuable information on the influence of breast-feeding and interacting social variables on the incidence of infant mortality. Accuracy of reporting of breast-feeding duration is a key issue in the validity of studies of breast-feeding and infant mortality. This paper presents an illustrative analysis of the quality of breast-feeding data from the Malaysian Family Life Survey, using logit model schedules. Lesthaeghe and Page derived a logit model schedule of breast-feeding, summarizing empirical experience. This family of model breast-feeding duration curves is similar to the logit model life tables developed by Brass, and was intended for similar applications. To verify the MFLS retrospective breast-feeding reports, the observed median duration and variability were calculated for ethnic group/cohort subsets, and expected duration distribution curves were generated from the model using these observed parameter values. The expected curve generated from the model fit the observed curve of breast-feeding discontinuation extremely closely. Thus it is unlikely that any significant distortion of the pattern of discontinuation of breast-feeding occurred in data collection. Extensions of this method of data quality checking to other duration distributions are suggested.
    Matched MeSH terms: Data Collection/standards*
  13. Misron N, Harun NH, Lee YK, Sidek RM, Aris I, Wakiwaka H, et al.
    Sensors (Basel), 2014;14(2):2431-48.
    PMID: 24496313 DOI: 10.3390/s140202431
    Among palm oil millers, the ripeness of oil palm Fresh Fruit Bunch (FFB) is determined through visual inspection. To increase the productivity of the millers, many researchers have proposed with a new detection method to replace the conventional one. The sensitivity of such a sensor plays a crucial role in determining the effectiveness of the method. In our preliminary study a novel oil palm fruit sensor to detect the maturity of oil palm fruit bunches is proposed. The design of the proposed air coil sensor based on an inductive sensor is further investigated to improve its sensitivity. This paper investigates the results pertaining to the effects of the air coil structure of an oil palm fruit sensor, taking consideration of the used copper wire diameter ranging from 0.10 mm to 0.18 mm with 60 turns. The flat-type shape of air coil was used on twenty samples of fruitlets from two categories, namely ripe and unripe. Samples are tested with frequencies ranging from 20 Hz to 120 MHz. The sensitivity of the sensor between air to fruitlet samples increases as the coil diameter increases. As for the sensitivity differences between ripe and unripe samples, the 5 mm air coil length with the 0.12 mm coil diameter provides the highest percentage difference between samples and it is amongst the highest deviation value between samples. The result from this study is important to improve the sensitivity of the inductive oil palm fruit sensor mainly with regards to the design of the air coil structure. The efficiency of the sensor to determine the maturity of the oil palm FFB and the ripening process of the fruitlet could further be enhanced.
    Matched MeSH terms: Data Collection
  14. Hannan MA, Arebey M, Begum RA, Basri H, Al Mamun MA
    Waste Manag, 2016 Apr;50:10-9.
    PMID: 26868844 DOI: 10.1016/j.wasman.2016.01.046
    This paper presents a CBIR system to investigate the use of image retrieval with an extracted texture from the image of a bin to detect the bin level. Various similarity distances like Euclidean, Bhattacharyya, Chi-squared, Cosine, and EMD are used with the CBIR system for calculating and comparing the distance between a query image and the images in a database to obtain the highest performance. In this study, the performance metrics is based on two quantitative evaluation criteria. The first one is the average retrieval rate based on the precision-recall graph and the second is the use of F1 measure which is the weighted harmonic mean of precision and recall. In case of feature extraction, texture is used as an image feature for bin level detection system. Various experiments are conducted with different features extraction techniques like Gabor wavelet filter, gray level co-occurrence matrix (GLCM), and gray level aura matrix (GLAM) to identify the level of the bin and its surrounding area. Intensive tests are conducted among 250bin images to assess the accuracy of the proposed feature extraction techniques. The average retrieval rate is used to evaluate the performance of the retrieval system. The result shows that, the EMD distance achieved high accuracy and provides better performance than the other distances.
    Matched MeSH terms: Data Collection
  15. Teoh TGK
    Med J Malaysia, 1999 Mar;54(1):151-2.
    PMID: 10972021
    Matched MeSH terms: Data Collection
  16. Cheku Nurul Hasmaria Cheku Yahaya, Md Gapar Md Johar
    MyJurnal
    This paper aims to presents the implementation of Organizational Memory Information System (OMIS) framework in managing knowledge in organization. OMIS providing a way for organization to leveraging tacit knowledge in capturing, codifying, storing and transferring knowledge. Every year data, information and knowledge had increased then becomes wasted memories due to the retirement, replacement and resignation of staff. This can have a great impact if the knowledge is not used wisely for future purpose. This could give great impact when it is not used wisely. Organization become more efficient and competitive if they used the collections of memory in the form of collected data, information, and knowledge. Organizations which are not efficient will do the process, and study the same repeatedly. Implementation of this framework is a good way to increase effectiveness of knowledge sharing in university. But some knowledge is hard to capture especially tacit knowledge. Many organizations attempt to capture tacit knowledge and codify it so that it can be shared around the organization for greater value. So this paper is mainly focused on implementation of Organizational Memory Information System (OMIS) framework in order to manage knowledge more centralized and organized in organization.
    Matched MeSH terms: Data Collection
  17. Hasan NI, Mohd Taib A, Muhammad NS, Mat Yazid MR, Mutalib AA, Abang Hasbollah DZ
    PLoS One, 2020;15(12):e0243293.
    PMID: 33332375 DOI: 10.1371/journal.pone.0243293
    The main cause of problematic soil failure under a certain load is due to low bearing capacity and excessive settlement. With a growing interest in employing shallow foundation to support heavy structures, it is important to study the soil improvement techniques. The technique of using geosynthetic reinforcement is commonly applied over the last few decades. This paper aims to determine the effect of using geogrid Tensar BX1500 on the bearing capacity and settlement of strip footing for different types of soils, namely Al-Hamedat, Ba'shiqah, and Al-Rashidia in Mosul, Iraq. The analysis of reinforced and unreinforced soil foundations was conducted numerically and analytically. A series of conditions were tested by varying the number (N) and the width (b) of the geogrid layers. The results showed that the geogrid could improve the footing's bearing capacity and reduce settlement. The soil of the Al-Rashidia site was sandy and indicated better improvement than the other two sites' soils (clayey soils). The optimum geogrid width (b) was five times the footing width (B), while no optimum geogrid number (N) was obtained. Finally, the numerical results of the ultimate bearing capacity were compared with the analytical results, and the comparison showed good agreement between both the analyses and the optimum range published in the literature. The significant findings reveal that the geogrid reinforcement may induce improvement to the soil foundation, however, not directly subject to the width and number of the geogrid alone. The varying soil properties and footing size also contribute to both BCR and SRR values supported by the improvement factor calculations. Hence, the output complemented the benefit of applying reinforced soil foundations effectively.
    Matched MeSH terms: Data Collection
  18. Sirunyan AM, Tumasyan A, Adam W, Ambrogi F, Asilar E, Bergauer T, et al.
    Phys Rev Lett, 2018 May 18;120(20):201801.
    PMID: 29864370 DOI: 10.1103/PhysRevLett.120.201801
    A search for narrow resonances decaying to bottom quark-antiquark pairs is presented, using a data sample of proton-proton collisions at sqrt[s]=8  TeV corresponding to an integrated luminosity of 19.7  fb^{-1}. The search is extended to masses lower than those reached in typical searches for resonances decaying into jet pairs at the LHC, by taking advantage of triggers that identify jets originating from bottom quarks. No significant excess of events is observed above the background predictions. Limits are set on the product of cross section and branching fraction to bottom quarks for spin 0, 1, and 2 resonances in the mass range of 325-1200 GeV. These results improve on the limits for resonances decaying into jet pairs in the 325-500 GeV mass range.
    Matched MeSH terms: Data Collection
  19. Homaei MH, Salwana E, Shamshirband S
    Sensors (Basel), 2019 Jul 18;19(14).
    PMID: 31323905 DOI: 10.3390/s19143173
    "Internet of Things (IoT)" has emerged as a novel concept in the world of technology and communication. In modern network technologies, the capability of transmitting data through data communication networks (such as Internet or intranet) is provided for each organism (e.g. human beings, animals, things, and so forth). Due to the limited hardware and operational communication capability as well as small dimensions, IoT undergoes several challenges. Such inherent challenges not only cause fundamental restrictions in the efficiency of aggregation, transmission, and communication between nodes; but they also degrade routing performance. To cope with the reduced availability time and unstable communications among nodes, data aggregation, and transmission approaches in such networks are designed more intelligently. In this paper, a distributed method is proposed to set child balance among nodes. In this method, the height of the network graph increased through restricting the degree; and network congestion reduced as a result. In addition, a dynamic data aggregation approach based on Learning Automata was proposed for Routing Protocol for Low-Power and Lossy Networks (LA-RPL). More specifically, each node was equipped with learning automata in order to perform data aggregation and transmissions. Simulation and experimental results indicate that the LA-RPL has better efficiency than the basic methods used in terms of energy consumption, network control overhead, end-to-end delay, loss packet and aggregation rates.
    Matched MeSH terms: Data Collection
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