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Fulltext Life After Death in a Chinese Community

MOHD HAFIZOL AMIN BIN RAMLI, NUR AMELIA BINTI MAZLAN, SITI AIDA BINTI AZMI, MUHD SARJI BIN AWANG BULAT, PARVEEN KAUR

Trends in Undergraduate Research, 2018;1(1):0-0.
MyJurnal

According to San Fillipo (2006), death is not the end of one’s existence, but rather than a transition from one life to another. However, it is different based on how the society and individuals see the concept of death itself and how they understand about it. Thus, this article aims to explore the understanding of the relationship between culture and religion that become their identity in terms of death and life after. Qualitative approach is adopted for this study. Indeed, interview and empirical observation were used to obtain quality data.

Matched MeSH terms: Data Accuracy
Crash severity along rural mountainous highways in Malaysia: An application of a combined decision tree and logistic regression model

Rusli R, Haque MM, Saifuzzaman M, King M

Traffic Inj Prev, 2018;19(7):741-748.
PMID: 29932734 DOI: 10.1080/15389588.2018.1482537

OBJECTIVE: Traffic crashes along mountainous highways may lead to injuries and fatalities more often than along highways on plain topography; however, research focusing on the injury outcome of such crashes is relatively scant. The objective of this study was to investigate the factors affecting the likelihood that traffic crashes along rural mountainous highways result in injuries.
METHOD: This study proposes a combination of decision tree and logistic regression techniques to model crash severity (injury vs. noninjury), because the combined approach allows the specification of nonlinearities and interactions in addition to main effects. Both a scobit model and a random parameters logit model, respectively accounting for an imbalance response variable and unobserved heterogeneities, are tested and compared. The study data set contains a total of 5 years of crash data (2008-2012) on selected mountainous highways in Malaysia. To enrich the data quality, an extensive field survey was conducted to collect detailed information on horizontal alignment, longitudinal grades, cross-section elements, and roadside features. In addition, weather condition data from the meteorology department were merged using the time stamp and proximity measures in AutoCAD-Geolocation.
RESULTS: The random parameters logit model is found to outperform both the standard logit and scobit models, suggesting the importance of accounting for unobserved heterogeneity in crash severity models. Results suggest that proportion of segment lengths with simple curves, presence of horizontal curves along steep gradients, highway segments with unsealed shoulders, and highway segments with cliffs along both sides are positively associated with injury-producing crashes along rural mountainous highways. Interestingly, crashes during rainy conditions are associated with crashes that are less likely to involve injury. It is also found that the likelihood of injury-producing crashes decreases for rear-end collisions but increases for head-on collisions and crashes involving heavy vehicles. A higher order interaction suggests that single-vehicle crashes involving light and medium-sized vehicles are less severe along straight sections compared to road sections with horizontal curves. One the other hand, crash severity is higher when heavy vehicles are involved in crashes as single vehicles traveling along straight segments of rural mountainous highways.
CONCLUSION: In addition to unobserved heterogeneity, it is important to account for higher order interactions to have a better understanding of factors that influence crash severity. A proper understanding of these factors will help develop targeted countermeasures to improve road safety along rural mountainous highways.

Matched MeSH terms: Data Accuracy
Improving routine health data in Indonesia: Utilising the WHO data quality tool for Aplikasi Satu Data Kesehatan

Sanjaya GY, Fauziah K, Pratama RA, Fitriani NA, Setiawan MY, Fauziah IA, et al.

Med J Malaysia, 2024 Mar;79(2):176-183.
PMID: 38553923

INTRODUCTION: Assessment of data quality in the era of big data is crucial for effective data management and use. However, there are gaps in data quality assessment for routine health data to ensure accountability. Therefore, this research aims to improve the routine health data quality that have been collected and integrated into Aplikasi Satu Data Kesehatan (ASDK) as the primary health data system in Indonesia.
MATERIALS AND METHODS: This descriptive study utilises a desk review approach and employs the WHO Data Quality Assurance (DQA) Tool to assess data quality of ASDK. The analysis involves measuring eight health indicators from ASDK and Survei Status Gizi Indonesia (SSGI) conducted in 2022. The assessment focuses on various dimensions of data quality, including completeness of variables, consistency over time, consistency between indicators, outliers and external consistency.
RESULTS: Current study shows that routine health data in Indonesia performs high-quality data in terms of completeness and internal consistency. The dimension of data completeness demonstrates high levels of variable completeness with most variables achieving 100% of the completeness.
CONCLUSION: Based on the analysis of eight routine health data variables using five dimensions of data quality namely completeness of variables, consistency over time, consistency between indicators, outliers. and external consistency. It shows that completeness and internal consistency of data in ASDK has demonstrated a high data quality.

Matched MeSH terms: Data Accuracy*
Audit on data accuracy of the Malaysian Dialysis and Transplant Registry (MDTR)

Thong KM, Jalalonmuhali M, Choo CL, Yee SY, Yahya R, Jeremiah PN, et al.

Med J Malaysia, 2024 Mar;79(2):234-236.
PMID: 38553931

Diabetes mellitus is the main aetiology of end stage kidney disease (ESKD) in Malaysia. However, there may be concerns of over-reporting of diabetes mellitus as the cause of ESKD in the Malaysian Dialysis and Transplant Registry (MDTR). The objective of this audit is to assess the accuracy of data collected in the MDTR. There were 151 centres/source data providers (SDP) with a total of 1977 patients included in this audit. The audit showed that 80.2% of doctors' records matched the MDTR data. The results were comparable with published validation studies in other countries.

Matched MeSH terms: Data Accuracy
Practical Considerations for Using RNA Sequencing in Management of B-Lymphoblastic Leukemia: Malaysia-Singapore Acute Lymphoblastic Leukemia 2020 Implementation Strategy

Ni Chin WH, Li Z, Jiang N, Lim EH, Suang Lim JY, Lu Y, et al.

J Mol Diagn, 2021 10;23(10):1359-1372.
PMID: 34365011 DOI: 10.1016/j.jmoldx.2021.07.013

Despite the immense genetic heterogeneity of B-lymphoblastic leukemia [or precursor B-cell acute lymphoblastic leukemia (B-ALL)], RNA sequencing (RNA-Seq) could comprehensively interrogate its genetic drivers, assigning a specific molecular subtype in >90% of patients. However, study groups have only started to use RNA-Seq. For broader clinical use, technical, quality control, and appropriate performance validation are needed. We describe the development and validation of an RNA-Seq workflow for subtype classification, TPMT/NUDT15/TP53 variant discovery, and immunoglobulin heavy chain (IGH) disease clone identification for Malaysia-Singapore acute lymphoblastic leukemia (ALL) 2020. We validated this workflow in 377 patients in our preceding Malaysia-Singapore ALL 2003/Malaysia-Singapore ALL 2010 studies and proposed the quality control measures for RNA quality, library size, sequencing, and data analysis using the International Organization for Standardization 15189 quality and competence standard for medical laboratories. Compared with conventional methods, we achieved >95% accuracy in oncogene fusion identification, digital karyotyping, and TPMT and NUDT15 variant discovery. We found seven pathogenic TP53 mutations, confirmed with Sanger sequencing, which conferred a poorer outcome. Applying this workflow prospectively to the first 21 patients in Malaysia-Singapore ALL 2020, we identified the genetic drivers and IGH disease clones in >90% of patients with concordant TPMT, NUDT15, and TP53 variants using PCR-based methods. The median turnaround time was 12 days, which was clinically actionable. In conclusion, RNA-Seq workflow could be used clinically in management of B-cell ALL patients.

Matched MeSH terms: Data Accuracy
Label-free optical spectroscopy for characterizing binding properties of highly sensitive nanocrystalline cellulose-graphene oxide based nanocomposite towards nickel ion

Daniyal WMEMM, Fen YW, Abdullah J, Sadrolhosseini AR, Saleviter S, Omar NAS

Spectrochim Acta A Mol Biomol Spectrosc, 2019 Apr 05;212:25-31.
PMID: 30594850 DOI: 10.1016/j.saa.2018.12.031

Surface plasmon resonance (SPR) is a label-free optical spectroscopy that is widely used for biomolecular interaction analysis. In this work, SPR was used to characterize the binding properties of highly sensitive nanocrystalline cellulose-graphene oxide based nanocomposite (CTA-NCC/GO) towards nickel ion. The formation of CTA-NCC/GO nanocomposite has been confirmed by FT-IR. The SPR analysis result shows that the CTA-NCC/GO has high binding affinity towards Ni2+ from 0.01 until 0.1 ppm with binding affinity constant of 1.620 × 103 M-1. The sensitivity for the CTA-NCC/GO calculated was 1.509° ppm-1. The full width at half maximum (FWHM), data accuracy (DA), and signal-to-noise ratio (SNR) have also been determined using the obtained SPR curve. For the FWHM, the value was 2.25° at 0.01 until 0.08 ppm and decreases to 2.12° at 0.1 until 10 ppm. The DA for the SPR curves is the highest at 0.01 until 0.08 ppm and lowest at 0.1 until 10 ppm. The SNR curves mirrors the curves of SPR angle shift where the SNR increases with the Ni2+ concentrations. For the selectivity test, the CTA-NCC/GO has the abilities to differentiate Ni2+ in the mixture of metal ions.

Matched MeSH terms: Data Accuracy
Fulltext A data fusion method in wireless sensor networks

Izadi D, Abawajy JH, Ghanavati S, Herawan T

Sensors (Basel), 2015;15(2):2964-79.
PMID: 25635417 DOI: 10.3390/s150202964

The success of a Wireless Sensor Network (WSN) deployment strongly depends on the quality of service (QoS) it provides regarding issues such as data accuracy, data aggregation delays and network lifetime maximisation. This is especially challenging in data fusion mechanisms, where a small fraction of low quality data in the fusion input may negatively impact the overall fusion result. In this paper, we present a fuzzy-based data fusion approach for WSN with the aim of increasing the QoS whilst reducing the energy consumption of the sensor network. The proposed approach is able to distinguish and aggregate only true values of the collected data as such, thus reducing the burden of processing the entire data at the base station (BS). It is also able to eliminate redundant data and consequently reduce energy consumption thus increasing the network lifetime. We studied the effectiveness of the proposed data fusion approach experimentally and compared it with two baseline approaches in terms of data collection, number of transferred data packets and energy consumption. The results of the experiments show that the proposed approach achieves better results than the baseline approaches.

Matched MeSH terms: Data Accuracy
Fulltext Vision-Based Apple Classification for Smart Manufacturing

Ismail A, Idris MYI, Ayub MN, Por LY

Sensors (Basel), 2018 Dec 10;18(12).
PMID: 30544660 DOI: 10.3390/s18124353

Smart manufacturing enables an efficient manufacturing process by optimizing production and product transaction. The optimization is performed through data analytics that requires reliable and informative data as input. Therefore, in this paper, an accurate data capture approach based on a vision sensor is proposed. Three image recognition methods are studied to determine the best vision-based classification technique, namely Bag of Words (BOW), Spatial Pyramid Matching (SPM) and Convolutional Neural Network (CNN). The vision-based classifiers categorize the apple as defective and non-defective that can be used for automatic inspection, sorting and further analytics. A total of 550 apple images are collected to test the classifiers. The images consist of 275 non-defective and 275 defective apples. The defective category includes various types of defect and severity. The vision-based classifiers are trained and evaluated according to the K-fold cross-validation. The performances of the classifiers from 2-fold, 3-fold, 4-fold, 5-fold and 10-fold are compared. From the evaluation, SPM with SVM classifier attained 98.15% classification accuracy for 10-fold and outperformed the others. In terms of computational time, CNN with SVM classifier is the fastest. However, minimal time difference is observed between the computational time of CNN and SPM, which were separated by only 0.05 s.

Matched MeSH terms: Data Accuracy
Promoting Ethics and Integrity in Management Academic Research: Retraction Initiative

Ayodele FO, Yao L, Haron H

Sci Eng Ethics, 2019 04;25(2):357-382.
PMID: 29441445 DOI: 10.1007/s11948-017-9941-z

In the management academic research, academic advancement, job security, and the securing of research funds at one's university are judged mainly by one's output of publications in high impact journals. With bogus resumes filled with published journal articles, universities and other allied institutions are keen to recruit or sustain the appointment of such academics. This often places undue pressure on aspiring academics and on those already recruited to engage in research misconduct which often leads to research integrity. This structured review focuses on the ethics and integrity of management research through an analysis of retracted articles published from 2005 to 2016. The study employs a structured literature review methodology whereby retracted articles published between 2005 and 2016 in the field of management science were found using Crossref and Google Scholar. The searched articles were then streamlined by selecting articles based on their relevance and content in accordance with the inclusion criteria. Based on the analysed retracted articles, the study shows evidence of ethical misconduct among researchers of management science. Such misconduct includes data falsification, the duplication of submitted articles, plagiarism, data irregularity and incomplete citation practices. Interestingly, the analysed results indicate that the field of knowledge management includes the highest number of retracted articles, with plagiarism constituting the most significant ethical issue. Furthermore, the findings of this study show that ethical misconduct is not restricted to a particular geographic location; it occurs in numerous countries. In turn, avenues of further study on research misconduct in management research are proposed.

Matched MeSH terms: Data Accuracy
A Comparison of Various Imputation Methods for Missing Values in Air Quality Data

Nuryazmin Ahmat Zainuri, Abdul Aziz Jemain, Nora Muda

Sains Malaysiana, 2015;44:449-456.

This paper presents various imputation methods for air quality data specifically in Malaysia. The main objective was to
select the best method of imputation and to compare whether there was any difference in the methods used between stations
in Peninsular Malaysia. Missing data for various cases are randomly simulated with 5, 10, 15, 20, 25 and 30% missing.
Six methods used in this paper were mean and median substitution, expectation-maximization (EM) method, singular
value decomposition (SVD), K-nearest neighbour (KNN) method and sequential K-nearest neighbour (SKNN) method. The
performance of the imputations is compared using the performance indicator: The correlation coefficient (R), the index
of agreement (d) and the mean absolute error (MAE). Based on the result obtained, it can be concluded that EM, KNN
and SKNN are the three best methods. The same result are obtained for all the eight monitoring station used in this study.

Matched MeSH terms: Data Accuracy
Application of functional data analysis for the treatment of missing air quality data

Norshahida Shaadan, Sayang Mohd Deni, Abdul Aziz Jemain

Sains Malaysiana, 2015;44:1531-1540.

In most research including environmental research, missing recorded data often exists and has become a common problem for data quality. In this study, several imputation methods that have been designed based on the techniques for functional data analysis are introduced and the capability of the methods for estimating missing values is investigated. Single imputation methods and iterative imputation methods are conducted by means of curve estimation using regression and roughness penalty smoothing approaches. The performance of the methods is compared using a reference data set, the real PM10 data from an air quality monitoring station namely the Petaling Jaya station located at the western part of Peninsular Malaysia. A hundred of the missing data sets that have been generated from a reference data set with six different patterns of missing values are used to investigate the performance of the considered methods. The patterns are simulated according to three percentages (5, 10 and 15) of missing values with respect to two different sizes (3 and 7) of maximum gap lengths (consecutive missing points). By means of the mean absolute error, the index of agreement and the coefficient of determination as the performance indicators, the results have showed that the iterative imputation method using the roughness penalty approach is more flexible and superior to other methods.

Matched MeSH terms: Data Accuracy
Fulltext The Accuracy of the Patient Health Questionnaire-9 Algorithm for Screening to Detect Major Depression: An Individual Participant Data Meta-Analysis

He C, Levis B, Riehm KE, Saadat N, Levis AW, Azar M, et al.

Psychother Psychosom, 2020;89(1):25-37.
PMID: 31593971 DOI: 10.1159/000502294

BACKGROUND: Screening for major depression with the Patient Health Questionnaire-9 (PHQ-9) can be done using a cutoff or the PHQ-9 diagnostic algorithm. Many primary studies publish results for only one approach, and previous meta-analyses of the algorithm approach included only a subset of primary studies that collected data and could have published results.
OBJECTIVE: To use an individual participant data meta-analysis to evaluate the accuracy of two PHQ-9 diagnostic algorithms for detecting major depression and compare accuracy between the algorithms and the standard PHQ-9 cutoff score of ≥10.
METHODS: Medline, Medline In-Process and Other Non-Indexed Citations, PsycINFO, Web of Science (January 1, 2000, to February 7, 2015). Eligible studies that classified current major depression status using a validated diagnostic interview.
RESULTS: Data were included for 54 of 72 identified eligible studies (n participants = 16,688, n cases = 2,091). Among studies that used a semi-structured interview, pooled sensitivity and specificity (95% confidence interval) were 0.57 (0.49, 0.64) and 0.95 (0.94, 0.97) for the original algorithm and 0.61 (0.54, 0.68) and 0.95 (0.93, 0.96) for a modified algorithm. Algorithm sensitivity was 0.22-0.24 lower compared to fully structured interviews and 0.06-0.07 lower compared to the Mini International Neuropsychiatric Interview. Specificity was similar across reference standards. For PHQ-9 cutoff of ≥10 compared to semi-structured interviews, sensitivity and specificity (95% confidence interval) were 0.88 (0.82-0.92) and 0.86 (0.82-0.88).
CONCLUSIONS: The cutoff score approach appears to be a better option than a PHQ-9 algorithm for detecting major depression.

Matched MeSH terms: Data Accuracy*
The Kinetics of Enzyme Mixtures

Brown S, Muhamad N, C Pedley K, C Simcock D

Mol Biol Res Commun, 2014 Mar;3(1):21-32.
PMID: 27843974

Even purified enzyme preparations are often heterogeneous. For example, preparations of aspartate aminotransferase or cytochrome oxidase can consist of several different forms of the enzyme. For this reason we consider how different the kinetics of the reactions catalysed by a mixture of forms of an enzyme must be to provide some indication of the characteristics of the species present. Based on the standard Michaelis-Menten model, we show that if the Michaelis constants (Km) of two isoforms differ by a factor of at least 20 the steady-state kinetics can be used to characterise the mixture. However, even if heterogeneity is reflected in the kinetic data, the proportions of the different forms of the enzyme cannot be estimated from the kinetic data alone. Consequently, the heterogeneity of enzyme preparations is rarely reflected in measurements of their steady-state kinetics unless the species present have significantly different kinetic properties. This has two implications: (1) it is difficult, but not impossible, to detect molecular heterogeneity using kinetic data and (2) even when it is possible, a considerable quantity of high quality data is required.

Matched MeSH terms: Data Accuracy
Fulltext "It's Valid and Reliable" Is Not Enough: Critical Appraisal of Reporting of Measures in Trials Evaluating Patient Decision Aids

Sepucha KR, Matlock DD, Wills CE, Ropka M, Joseph-Williams N, Stacey D, et al.

Med Decis Making, 2014 07;34(5):560-6.
PMID: 24713692 DOI: 10.1177/0272989X14528381

BACKGROUND: This review systematically appraises the quality of reporting of measures used in trials to evaluate the effectiveness of patient decision aids (PtDAs) and presents recommendations for minimum reporting standards.
METHODS: We reviewed measures of decision quality and decision process in 86 randomized controlled trials (RCTs) from the 2011 Cochrane Collaboration systematic review of PtDAs. Data on development of the measures, reliability, validity, responsiveness, precision, interpretability, feasibility, and acceptability were independently abstracted by 2 reviewers.
RESULTS: Information from 178 instances of use of measures was abstracted. Very few studies reported data on the performance of measures, with reliability (21%) and validity (16%) being the most common. Studies using new measures were less likely to include information about their psychometric performance. The review was limited to reporting of measures in studies included in the Cochrane review and did not consult prior publications.
CONCLUSIONS: Very little is reported about the development or performance of measures used to evaluate the effectiveness of PtDAs in published trials. Minimum reporting standards are proposed to enable authors to prepare study reports, editors and reviewers to evaluate submitted papers, and readers to appraise published studies.

Matched MeSH terms: Data Accuracy
Fulltext Modeling the Physical Properties of Gamma Alumina Catalyst Carrier Based on an Artificial Neural Network

Majdi HS, Saud AN, Saud SN

Materials (Basel), 2019 May 29;12(11).
PMID: 31146451 DOI: 10.3390/ma12111752

Porous γ-alumina is widely used as a catalyst carrier due to its chemical properties. These properties are strongly correlated with the physical properties of the material, such as porosity, density, shrinkage, and surface area. This study presents a technique that is less time consuming than other techniques to predict the values of the above-mentioned physical properties of porous γ-alumina via an artificial neural network (ANN) numerical model. The experimental data that was implemented was determined based on 30 samples that varied in terms of sintering temperature, yeast concentration, and socking time. Of the 30 experimental samples, 25 samples were used for training purposes, while the other five samples were used for the execution of the experimental procedure. The results showed that the prediction and experimental data were in good agreement, and it was concluded that the proposed model is proficient at providing high accuracy estimation data derived from any complex analytical equation.

Matched MeSH terms: Data Accuracy
Fulltext Cross-sectional survey of multi-centre patient registries in malaysia

Sharmini S, Jamaiyah H, Jaya Purany SP

Malays Fam Physician, 2010;5(1):13-8.
PMID: 25606180 MyJurnal

This survey set out to describe patient registries available in the country, to determine their security features, data confidentiality, extent of outputs produced and data quality of the registries.

Matched MeSH terms: Data Accuracy
Fulltext Performance of women entrepreneurs: a result on formation of human capital and emulous factors

Nor Azira Ayob, Sity Daud, Nurul Nadia Abu Hassan

Malaysian Journal of Social Sciences and Humanities, 2018;3(3):173-188.
MyJurnal

Human resource development comprises skills, abilities, creativity and talent are amongst factors in
human capital as well as emulous aspect. Hence, the emphasis on human capital development and
emulous aspect is important to become a good leader for family, community and country. It is also
important in ensuring entrepreneurs can compete in market economy today and they are able to meet
customer demand. Thus, the objectives are the emphasis on the factors that are able to contribute in
improving human capital and emulous of women. This is because, the right factor will enable the government to carry out in accordance with the factors that have been identified. In obtaining the
factors contribute to human capital development, the survey method was conducted on 145 respondents
among Bumiputera women entrepreneurs in Melaka state and supported with qualitative data from 10
informants. The findings through exploratory factor analysis found that there are four main factors that
contribute to human capital development among Bumiputera women entrepreneurs which are
education and training, experience, social support and creativity, while three main factors that
contribute to emulous among Bumiputera women entrepreneurs are financial assistance, facilities and
infrastructure and commitment. Thus, the government is advised to emphasize on education and
training as well as financial assistance to improve their abilities on human capital and emulous that is
appropriate to support the women entrepreneurs need to increase their performance.

Matched MeSH terms: Data Accuracy
Fulltext Out of hospital cardiac arrest in Kuala Lumpur: incidence; adherence to protocol; and issues: a mixed method study

Mohd Said Nurumal, Sarah Sheikh Abdul Karim

Malaysian Journal of Public Health Medicine, 2015;15(3):0-0.
MyJurnal

Information regarding out of hospital cardiac arrest incidence including outcomes in Malaysia is limited and fragmented. This study aims to identify the incidence and adherence to protocol of out of hospital cardiac arrest and also to explore the issues faced by pre-hospital personnel in regards to the management of cardiac arrest victim in Kuala Lumpur, Malaysia. A mixed method approach combining qualitative and quantitative study design was used. Two hundred eighty five (285) pre-hospital care data sheet for out of hospital cardiac arrest during the year of 2011 were examined by using checklists to identify the incidence and adherence to protocol. Nine semi-structured interviews and two focus group discussions were performed. Based on the overall incidence for out of hospital cardiac arrest cases which occurred in 2011 (n=285), the survival rate was 16.8%. On the adherence to protocol, only 89 (41.8%) of the cases adhered to the given protocol and 124 did not adhere to such protocol. All the relevant qualitative data were merged into few categories relating to issues that could affect the management of out of hospital cardiac arrest performed by pre-hospital care team. The essential elements in the handling of out of hospital cardiac arrest by pre-hospital care teamwasto ensure increased survival rates and excellent outcomes. Measures are needed to strengthen the quick activation of the pre-hospital care service, prompt bystander cardiopulmonary resuscitation, early defibrillation and timely advanced cardiac life support, and also to address all other issues highlighted in the qualitative results of this study.

Matched MeSH terms: Data Accuracy
Fulltext Development of smart wireless detector system for gamma ray detection

Nolida Yussup, Nur Aira Abd. Rahman, Ismail Mustapha, Jaafar Abdullah, Mohd. Ashhar Khalid, Hearie Hassan, et al.

Jurnal Sains Nuklear Malaysia, 2012;24(1):43-47.
MyJurnal

Data transmission in field works especially that is related to industry, gas and chemical is paramount importance to ensure data accuracy and delivery time. A development of wireless detector system for remote data acquisition to be applied in conducting fieldwork in industry is described in this paper. A wireless communication which is applied in the project development is a viable and cost-effective method of transmitting data from the detector to the laptop on the site to facilitate data storage and analysis automatically, which can be used in various applications such as column scanning. The project involves hardware design for the detector and electronics parts besides programming for control board and user interface. A prototype of a wireless gamma scintillation detector is developed with capabilities of transmitting data to computer via radio frequency (RF) and recording the data within the 433MHz band at baud rate of 19200.

Matched MeSH terms: Data Accuracy
Fulltext The importance of human capital perspective in the learning management system (LMS) decision making process at universities

Norhaiza K, Rozainee K, Mohd Noor Abdul H, Phillip H, McGill T, Zainah Ahmad Z

Jurnal Psikologi Malaysia, 2016;30:102-113.

This research examined how managers in universities incorporate non-financial measures in their Learning Management Systems decision-making processes and particularly focused on the importance of the Human Capital perspective in LMS decision making processes. A mixed-methods approach to data collection was used involving both interviews and questionnaires. The qualitative data from the interviews were coded and analysed. A descriptive coding method using thematic analysis was used for the data coding. The qualitative data were analysed using an inductive approach where the categories of criteria and indicators were not determined before the interview. The participants in this research were five members of LMS decision-making teams at two different universities in Australia and 24 participants from different universities in Malaysia who were involved in LMS decision- making processes at their universities. The results of this research indicated that there was substantial support for using a multi-dimensional decision making model among IT decision makers at universities, particularly the Human Capital perspective and they believed that Human Capital measures are important and should be considered in a LMS decision making process.The research has both implications for theory and for practitioners where it contributes to the knowledge on LMS decision making in universities and IT decision making in general, and also in improving actual decision making practices.

Matched MeSH terms: Data Accuracy

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