Displaying publications 1 - 20 of 77 in total

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  1. Zubair S, Fisal N, Baguda YS, Saleem K
    Sensors (Basel), 2013;13(10):13005-38.
    PMID: 24077319 DOI: 10.3390/s131013005
    Interest in the cognitive radio sensor network (CRSN) paradigm has gradually grown among researchers. This concept seeks to fuse the benefits of dynamic spectrum access into the sensor network, making it a potential player in the next generation (NextGen) network, which is characterized by ubiquity. Notwithstanding its massive potential, little research activity has been dedicated to the network layer. By contrast, we find recent research trends focusing on the physical layer, the link layer and the transport layers. The fact that the cross-layer approach is imperative, due to the resource-constrained nature of CRSNs, can make the design of unique solutions non-trivial in this respect. This paper seeks to explore possible design opportunities with wireless sensor networks (WSNs), cognitive radio ad-hoc networks (CRAHNs) and cross-layer considerations for implementing viable CRSN routing solutions. Additionally, a detailed performance evaluation of WSN routing strategies in a cognitive radio environment is performed to expose research gaps. With this work, we intend to lay a foundation for developing CRSN routing solutions and to establish a basis for future work in this area.
    Matched MeSH terms: Information Storage and Retrieval/methods*
  2. Zare MR, Mueen A, Seng WC
    J Digit Imaging, 2014 Feb;27(1):77-89.
    PMID: 24092327 DOI: 10.1007/s10278-013-9637-0
    The demand for automatically classification of medical X-ray images is rising faster than ever. In this paper, an approach is presented to gain high accuracy rate for those classes of medical database with high ratio of intraclass variability and interclass similarities. The classification framework was constructed via annotation using the following three techniques: annotation by binary classification, annotation by probabilistic latent semantic analysis, and annotation using top similar images. Next, final annotation was constructed by applying ranking similarity on annotated keywords made by each technique. The final annotation keywords were then divided into three levels according to the body region, specific bone structure in body region as well as imaging direction. Different weights were given to each level of the keywords; they are then used to calculate the weightage for each category of medical images based on their ground truth annotation. The weightage computed from the generated annotation of query image was compared with the weightage of each category of medical images, and then the query image would be assigned to the category with closest weightage to the query image. The average accuracy rate reported is 87.5 %.
    Matched MeSH terms: Information Storage and Retrieval/methods*
  3. Zaini MF, Sarudin A, Muhammad MM, Osman Z, Mohamed Redzwan HF, Al-Muhsin MA
    Data Brief, 2021 Jun;36:107013.
    PMID: 33898671 DOI: 10.1016/j.dib.2021.107013
    House Building Tips is the title of a classic text containing historical information on early house construction in Malay communities. These tips were written by a scholar with knowledge of house construction through observation of the surrounding environment. In Malaysia, written sources or records of house construction are scarce and underexposed. As such, this research was conducted to guarantee the written legacy of the construction of Malay houses. The purpose of this paper is to introduce a statistical data source of house building tips that is laden with Malay ingenuity and identity. The wordlists generated from this study can become a source of reference for the field of Malay architecture. Accordingly, this study utilises the quantitative method by applying the Linguistic Corpus Statistical Approach; these data utilise specific corpus development procedures, beginning with text collection, scanning and cleaning processes, text annotation, and data storing in plain text. Next, the data analysis procedure utilises a corpus software, LancsBox, to generate specialised wordlists. The bubble graphs are developed based on these wordlists through the Tableau software, and illustrate the most used lexical items with the raw and relative frequency values. This facilitates searches for, and the reading of, architectural words and architectural word references. These data represent written sources that need to be preserved and become points of reference concerning Malay architectural ingenuity and identity.
    Matched MeSH terms: Information Storage and Retrieval
  4. Zain JM, Fauzi AR
    PMID: 18003297
    This paper will study and evaluate watermarking technique by Zain and Fauzi [1]. Recommendations will then be made to enhance the technique especially in the aspect of recovery or reconstruction rate for medical images. A proposal will also be made for a better distribution of watermark to minimize the distortion of the Region of Interest (ROI). The final proposal will enhance AW-TDR in three aspects; firstly the image quality in the ROI will be improved as the maximum change is only 2 bits in every 4 pixels, or embedding rate of 0.5 bits/pixel. Secondly the recovery rate will also be better since the recovery bits are located outside the region of interest. The disadvantage in this is that, only manipulation done in the ROI will be detected. Thirdly the quality of the reconstructed image will be enhanced since the average of 2 x 2 pixels would be used to reconstruct the tampered image.
    Matched MeSH terms: Information Storage and Retrieval/methods*
  5. Zain JM, Fauzi AM, Aziz AA
    Conf Proc IEEE Eng Med Biol Soc, 2007 10 20;2006:5459-62.
    PMID: 17946306
    Digital watermarking medical images provides security to the images. The purpose of this study was to see whether digitally watermarked images changed clinical diagnoses when assessed by radiologists. We embedded 256 bits watermark to various medical images in the region of non-interest (RONI) and 480K bits in both region of interest (ROI) and RONI. Our results showed that watermarking medical images did not alter clinical diagnoses. In addition, there was no difference in image quality when visually assessed by the medical radiologists. We therefore concluded that digital watermarking medical images were safe in terms of preserving image quality for clinical purposes.
    Matched MeSH terms: Information Storage and Retrieval
  6. Zaidi SZ, Abidi SS, Manickam S
    PMID: 15460713
    This paper presents a case for an intelligent agent based framework for knowledge discovery in a distributed healthcare environment comprising multiple heterogeneous healthcare data repositories. Data-mediated knowledge discovery, especially from multiple heterogeneous data resources, is a tedious process and imposes significant operational constraints on end-users. We demonstrate that autonomous, reactive and proactive intelligent agents provide an opportunity to generate end-user oriented, packaged, value-added decision-support/strategic planning services for healthcare professionals, manages and policy makers, without the need for a priori technical knowledge. Since effective healthcare is grounded in good communication, experience sharing, continuous learning and proactive actions, we use intelligent agents to implement an Agent based Data Mining Infostructure that provides a suite of healthcare-oriented decision-support/strategic planning services.
    Matched MeSH terms: Information Storage and Retrieval/methods*
  7. Woon YL, Hor CP, Lee KY, Mohd Anuar SFZ, Mudin RN, Sheikh Ahmad MK, et al.
    BMC Public Health, 2018 08 02;18(1):946.
    PMID: 30068318 DOI: 10.1186/s12889-018-5849-z
    BACKGROUND: Epidemiologic measures of the dengue burden such as prevalence and incidence are important for policy-making and monitoring the progress of disease control. It is a common practice where epidemiologic and economic research estimate dengue burden based on notification data. However, a basic challenge in estimating the incidence of dengue is that a significant proportion of infected population are asymptomatic. It can be overcome by using mathematical models that relate observed prevalence and mortality to incidence. In this study, we estimate the trend of dengue incidence and hospitalization in Malaysia.

    METHODS: This study is based entirely on the available secondary data sources on dengue in Malaysia. The age-specific incidence of dengue between 2001 and 2013 was estimated using the prevalence and mortality estimates in an incidence-prevalence-mortality (IPM) model. Data on dengue prevalence were extracted from six sero-surveys conducted in Malaysia between 2001 and 2013; while statistics on dengue notification and Case Fatality Rate were derived from National Dengue Surveillance System. Dengue hospitalization data for the years 2009 to 2013 were extracted from the Health Informatics Centre and the volumes of dengue hospitalization for hospitals with missing data were estimated with Poisson models.

    RESULTS: The dengue incidence in Malaysia varied from 69.9 to 93.4 per 1000 population (pkp) between 2001 and 2013.The temporal trend in incidence rate was decreasing since 2001. It has been reducing at an average rate of 2.57 pkp per year from 2001 to 2013 (p = 0.011). The age-specific incidence of dengue decreased steadily with dengue incidence reaching zero by age > 70 years. Dengue notification rate has remained stable since 2001 and the number of notified cases each year was only a small fraction of the incident cases (0.7 to 2.3%). Similarly, the dengue hospitalization was larger but still a small fraction of the incident cases (3.0 to 5.6%).

    CONCLUSION: Dengue incidence can be estimated with the use of sero-prevalence surveys and mortality data. This study highlights a reducing trend of dengue incidence in Malaysia and demonstrates the discrepancy between true dengue disease burden and cases reported by national surveillance system. Sero-prevalence studies with representative samples should be conducted regularly to allow better estimation of dengue burden in Malaysia.

    Matched MeSH terms: Information Storage and Retrieval
  8. Whaiduzzaman M, Haque MN, Rejaul Karim Chowdhury M, Gani A
    ScientificWorldJournal, 2014;2014:894362.
    PMID: 25032243 DOI: 10.1155/2014/894362
    Cloud computing is currently emerging as an ever-changing, growing paradigm that models "everything-as-a-service." Virtualised physical resources, infrastructure, and applications are supplied by service provisioning in the cloud. The evolution in the adoption of cloud computing is driven by clear and distinct promising features for both cloud users and cloud providers. However, the increasing number of cloud providers and the variety of service offerings have made it difficult for the customers to choose the best services. By employing successful service provisioning, the essential services required by customers, such as agility and availability, pricing, security and trust, and user metrics can be guaranteed by service provisioning. Hence, continuous service provisioning that satisfies the user requirements is a mandatory feature for the cloud user and vitally important in cloud computing service offerings. Therefore, we aim to review the state-of-the-art service provisioning objectives, essential services, topologies, user requirements, necessary metrics, and pricing mechanisms. We synthesize and summarize different provision techniques, approaches, and models through a comprehensive literature review. A thematic taxonomy of cloud service provisioning is presented after the systematic review. Finally, future research directions and open research issues are identified.
    Matched MeSH terms: Information Storage and Retrieval/methods*; Information Storage and Retrieval/standards
  9. Whaiduzzaman M, Gani A, Anuar NB, Shiraz M, Haque MN, Haque IT
    ScientificWorldJournal, 2014;2014:459375.
    PMID: 24696645 DOI: 10.1155/2014/459375
    Cloud computing (CC) has recently been receiving tremendous attention from the IT industry and academic researchers. CC leverages its unique services to cloud customers in a pay-as-you-go, anytime, anywhere manner. Cloud services provide dynamically scalable services through the Internet on demand. Therefore, service provisioning plays a key role in CC. The cloud customer must be able to select appropriate services according to his or her needs. Several approaches have been proposed to solve the service selection problem, including multicriteria decision analysis (MCDA). MCDA enables the user to choose from among a number of available choices. In this paper, we analyze the application of MCDA to service selection in CC. We identify and synthesize several MCDA techniques and provide a comprehensive analysis of this technology for general readers. In addition, we present a taxonomy derived from a survey of the current literature. Finally, we highlight several state-of-the-art practical aspects of MCDA implementation in cloud computing service selection. The contributions of this study are four-fold: (a) focusing on the state-of-the-art MCDA techniques, (b) highlighting the comparative analysis and suitability of several MCDA methods, (c) presenting a taxonomy through extensive literature review, and (d) analyzing and summarizing the cloud computing service selections in different scenarios.
    Matched MeSH terms: Information Storage and Retrieval/methods*
  10. Wang Z, Zhang F, Zhang X, Chan NW, Kung HT, Ariken M, et al.
    Sci Total Environ, 2021 Feb 12;775:145807.
    PMID: 33618298 DOI: 10.1016/j.scitotenv.2021.145807
    Soil salinization is an extremely serious land degradation problem in arid and semi-arid regions that hinders the sustainable development of agriculture and food security. Information and research on soil salinity using remote sensing (RS) technology provide a quick and accurate assessment and solutions to address this problem. This study aims to compare the capabilities of Landsat-8 OLI and Sentinel-2A MSI in RS prediction and exploration of the potential application of derivatives to RS prediction of salinized soils. It explores the ability of derivatives to be used in the Landsat-8 OLI and Sentinel-2A MSI multispectral data, and it was used as a data source as well as to address the adaptability of salinity prediction on a regional scale. The two-dimensional (2D) and three-dimensional (3D) optimal spectral indices are used to screen the bands that are most sensitive to soil salinity (0-10 cm), and RS data and topographic factors are combined with machine learning to construct a comprehensive soil salinity estimation model based on gray correlation analysis. The results are as follows: (1) The optimal spectral index (2D, 3D) can effectively consider possible combinations of the bands between the interaction effects and responding to sensitive bands of soil properties to circumvent the problem of applicability of spectral indices in different regions; (2) Both the Landsat-8 OLI and Sentinel-2A MSI multispectral RS data sources, after the first-order derivative techniques are all processed, show improvements in the prediction accuracy of the model; (3) The best performance/accuracy of the predictive model is for sentinel data under first-order derivatives. This study compared the capabilities of Landsat-8 OLI and Sentinel-2A MSI in RS prediction in finding the potential application of derivatives to RS prediction of salinized soils, with the results providing some theoretical basis and technical guidance for salinized soil prediction and environmental management planning.
    Matched MeSH terms: Information Storage and Retrieval
  11. Wan Nor Arifin, Muhamad Saiful Bahri Yusoff, Nyi Nyi Naing
    MyJurnal
    Introduction: Emotional intelligence (EI) is deemed an important aspect of being good medical doctors. Universiti Sains Malaysia (USM) Emotional Quotient Inventory (USMEQ-i) is an EI inventory in Malay language developed primarily as medical student selection tool in USM. Although it was already validated by exploratory factor analysis (EFA), EFA is considered insufficient evidence of construct validity, thus confirmatory factor analysis (CFA) was conducted. Objectives: To determine measurement model validity and construct validity of USMEQ-i among medical degree program applicants in USM by CFA. Methods: USMEQ-i data file for medical degree program applicants in USM for year 2010/2011 and 2011/2012 academic sessions were obtained from Medical Education Department in USM. A random sample of 512 cases was drawn from the data file. Of the sample, only 453 cases were valid study sample after preliminary data screening and assumption checking. CFA was conducted on the sample using maximum likelihood (ML) estimation with bootstrapping technique due to violation of multivariate normality assumption. USMEQ-i measurement model was proposed as a second-order EI factor with seven first-order factors of EI and a Faking Index (FI) factor, with correlation between second-order EI factor and FI factor. Results: The proposed model could not be fit into the study sample data. EI factors and FI factor had to be analyzed separately due to non-positive definite problem. After modifications to the model, CFA of EI factors were suggestive of two-factor model instead of the proposed seven-factor model. Consciousness, Maturity and Control (CoMaCt). CFA of FI factor maintained one-factor model and also valid in term of construct. Conclusion: The modified USMEQ-i, which consisted of separate EI and FI models, was proven to have valid measurement models and reliable constructs. It is considered to be suitable for use among applicants to medical degree program in USM. However, its use as medical student selection tool may require further research, especially how predictive USMEQ-i scores with real performance of medical students, generalizability of the inventory and its stability over time.
    Matched MeSH terms: Information Storage and Retrieval
  12. Teoh SL, Chong HY, Abdul Aziz S, Chemi N, Othman AR, Md Zaki N, et al.
    Neuropsychiatr Dis Treat, 2017;13:1979-1987.
    PMID: 28814869 DOI: 10.2147/NDT.S137140
    INTRODUCTION: Schizophrenia (SCZ) is a highly debilitating disease despite its low prevalence. The economic burden associated with SCZ is substantial and mainly attributed to productivity loss. To improve the understanding of economic burden of SCZ in the low- and middle-income country regions, we aimed to determine the economic burden of SCZ in Malaysia.

    METHODS: A retrospective study was conducted using a prevalence-based approach from a societal perspective in Malaysia with a 1 year period from 2013. We used micro-costing technique with bottom-up method and included direct medical cost, direct non-medical cost, and indirect cost. The main data source was medical chart review which was conducted in Hospital Kuala Lumpur (HKL). The medical charts were identified electronically by matching the unique patient's identification number registered under the National Mental Health Schizophrenia Registry and the list of patients in HKL in 2013. Other data sources were government documents, literatures, and local websites. To ensure robustness of result, probabilistic sensitivity analysis was conducted.

    RESULTS: The total estimated number of treated SCZ cases in Malaysia in 2015 was 15,104 with the total economic burden of USD 100 million (M) which was equivalent to 0.04% of the national gross domestic product. On average, the mean cost per patient was USD 6,594. Of the total economic burden of SCZ, 72% was attributed to indirect cost, costing at USD 72M, followed by direct medical cost (26%), costing at USD 26M, and direct non-medical cost (2%), costing at USD 1.7M.

    CONCLUSION: This study highlights the magnitude of economic burden of SCZ and informs the policy-makers that there is an inadequate support for SCZ patients. More resources should be allocated to improve the condition of SCZ patients and to reduce the economic burden.

    Matched MeSH terms: Information Storage and Retrieval
  13. Tao H, Rahman MA, Jing W, Li Y, Li J, Al-Saffar A, et al.
    Work, 2021;68(3):903-912.
    PMID: 33720867 DOI: 10.3233/WOR-203424
    BACKGROUND: Human-robot interaction (HRI) is becoming a current research field for providing granular real-time applications and services through physical observation. Robotic systems are designed to handle the roles of humans and assist them through intrinsic sensing and commutative interactions. These systems handle inputs from multiple sources, process them, and deliver reliable responses to the users without delay. Input analysis and processing is the prime concern for the robotic systems to understand and resolve the queries of the users.

    OBJECTIVES: In this manuscript, the Interaction Modeling and Classification Scheme (IMCS) is introduced to improve the accuracy of HRI. This scheme consists of two phases, namely error classification and input mapping. In the error classification process, the input is analyzed for its events and conditional discrepancies to assign appropriate responses in the input mapping phase. The joint process is aided by a linear learning model to analyze the different conditions in the event and input detection.

    RESULTS: The performance of the proposed scheme shows that it is capable of improving the interaction accuracy by reducing the ratio of errors and interaction response by leveraging the information extraction from the discrete and successive human inputs.

    CONCLUSION: The fetched data are analyzed by classifying the errors at the initial stage to achieve reliable responses.

    Matched MeSH terms: Information Storage and Retrieval
  14. Sukkar L, Talbot B, Jun M, Dempsey E, Walker R, Hooi L, et al.
    Can J Kidney Health Dis, 2019;6:2054358119879896.
    PMID: 31662874 DOI: 10.1177/2054358119879896
    Background: There are limited studies on the effects of statins on outcomes in the moderate chronic kidney disease (CKD) population and their trajectory to end-stage kidney disease.

    Objective: To examine the long-term effects of lipid-lowering therapy on all-cause mortality, cardiovascular morbidity, CKD progression, and socioeconomic well-being in Australian, New Zealand, and Malaysian SHARP (Study of Heart and Renal Protection) trial participants-a randomized controlled trial of a combination of simvastatin and ezetimibe, compared with placebo, for the reduction of cardiovascular events in moderate to severe CKD.

    Design: Protocol for an extended prospective observational follow-up.

    Setting: Australian, New Zealand, and Malaysian participating centers in patients with advanced CKD.

    Patients: All SHARP trial participants alive at the final study visit.

    Measurements: Primary outcomes were measured by participant self-report and verified by hospital administrative data. In addition, secondary outcomes were measured using a validated study questionnaire of health-related quality of life, a 56-item economic survey.

    Methods: Participants were followed up with alternating face-to-face visits and telephone calls on a 6-monthly basis until 5 years following their final SHARP Study visit. In addition, there were 6-monthly follow-up telephone calls in between these visits. Data linkage to health registries in Australia, New Zealand, and Malaysia was also performed.

    Results: The SHARP-Extended Review (SHARP-ER) cohort comprised 1136 SHARP participants with a median of 4.6 years of follow-up. Compared with all SHARP participants who originally participated in the Australian, New Zealand, and Malaysian regions, the SHARP-ER participants were younger (57.2 [48.3-66.4] vs 60.5 [50.3-70.7] years) with a lower proportion of men (61.5% vs 62.8%). There were a lower proportion of participants with hypertension (83.7% vs 85.0%) and diabetes (20.0% vs 23.5%).

    Limitations: As a long-term follow-up study, the surviving cohort of SHARP-ER is a selected group of the original study participants, which may limit the generalizability of the findings.

    Conclusion: The SHARP-ER study will contribute important evidence on the long-term outcomes of cholesterol-lowering therapy in patients with advanced CKD with a total of 10 years of follow-up. Novel analyses of the socioeconomic impact of CKD over time will guide resource allocation.

    Trial Registration: The SHARP trial was registered at ClinicalTrials.gov NCT00125593 and ISRCTN 54137607.

    Matched MeSH terms: Information Storage and Retrieval
  15. Sookhak M, Akhunzada A, Gani A, Khurram Khan M, Anuar NB
    ScientificWorldJournal, 2014;2014:269357.
    PMID: 25121114 DOI: 10.1155/2014/269357
    Cloud computing is a significant shift of computational paradigm where computing as a utility and storing data remotely have a great potential. Enterprise and businesses are now more interested in outsourcing their data to the cloud to lessen the burden of local data storage and maintenance. However, the outsourced data and the computation outcomes are not continuously trustworthy due to the lack of control and physical possession of the data owners. To better streamline this issue, researchers have now focused on designing remote data auditing (RDA) techniques. The majority of these techniques, however, are only applicable for static archive data and are not subject to audit the dynamically updated outsourced data. We propose an effectual RDA technique based on algebraic signature properties for cloud storage system and also present a new data structure capable of efficiently supporting dynamic data operations like append, insert, modify, and delete. Moreover, this data structure empowers our method to be applicable for large-scale data with minimum computation cost. The comparative analysis with the state-of-the-art RDA schemes shows that the proposed scheme is secure and highly efficient in terms of the computation and communication overhead on the auditor and server.
    Matched MeSH terms: Information Storage and Retrieval/methods*
  16. Shekhawat KS, Chauhan A
    Indian J Dent Res, 2019 3 23;30(1):125-126.
    PMID: 30900670 DOI: 10.4103/ijdr.IJDR_27_17
    Counting citations have been the usual norm to determine the impact of any research and/or scholar. However, with majority of the scholarly activities happening on the World Wide Web, traditional counting of citations is now being termed "slower." The recent explosion of online data storage for many articles may serve as a pool which uses social media sites to navigate. Altmetrics has been proposed as the new entity which aims to change the focus of the scholarly reward system to value and encourage web-native scholarship. This paper makes an attempt to understand altmetrics.
    Matched MeSH terms: Information Storage and Retrieval
  17. Shah PA, Hasbullah HB, Lawal IA, Aminu Mu'azu A, Tang Jung L
    ScientificWorldJournal, 2014;2014:506028.
    PMID: 24688398 DOI: 10.1155/2014/506028
    Due to the proliferation of handheld mobile devices, multimedia applications like Voice over IP (VoIP), video conferencing, network music, and online gaming are gaining popularity in recent years. These applications are well known to be delay sensitive and resource demanding. The mobility of mobile devices, running these applications, across different networks causes delay and service disruption. Mobile IPv6 was proposed to provide mobility support to IPv6-based mobile nodes for continuous communication when they roam across different networks. However, the Route Optimization procedure in Mobile IPv6 involves the verification of mobile node's reachability at the home address and at the care-of address (home test and care-of test) that results in higher handover delays and signalling overhead. This paper presents an enhanced procedure, time-based one-time password Route Optimization (TOTP-RO), for Mobile IPv6 Route Optimization that uses the concepts of shared secret Token, time based one-time password (TOTP) along with verification of the mobile node via direct communication and maintaining the status of correspondent node's compatibility. The TOTP-RO was implemented in network simulator (NS-2) and an analytical analysis was also made. Analysis showed that TOTP-RO has lower handover delays, packet loss, and signalling overhead with an increased level of security as compared to the standard Mobile IPv6's Return-Routability-based Route Optimization (RR-RO).
    Matched MeSH terms: Information Storage and Retrieval/methods*
  18. Seng WC, Mirisaee SH
    J Med Syst, 2011 Aug;35(4):571-8.
    PMID: 20703533 DOI: 10.1007/s10916-009-9393-3
    Content-based image retrieval techniques have been extensively studied for the past few years. With the growth of digital medical image databases, the demand for content-based analysis and retrieval tools has been increasing remarkably. Blood cell image is a key diagnostic tool for hematologists. An automated system that can retrieved relevant blood cell images correctly and efficiently would save the effort and time of hematologists. The purpose of this work is to develop such a content-based image retrieval system. Global color histogram and wavelet-based methods are used in the prototype. The system allows users to search by providing a query image and select one of four implemented methods. The obtained results demonstrate the proposed extended query refinement has the potential to capture a user's high level query and perception subjectivity by dynamically giving better query combinations. Color-based methods performed better than wavelet-based methods with regard to precision, recall rate and retrieval time. Shape and density of blood cells are suggested as measurements for future improvement. The system developed is useful for undergraduate education.
    Matched MeSH terms: Information Storage and Retrieval/methods*
  19. Sanusi NSNM, Rosli R, Halim MAA, Chan KL, Nagappan J, Azizi N, et al.
    Database (Oxford), 2018 01 01;2018.
    PMID: 30239681 DOI: 10.1093/database/bay095
    A set of Elaeis guineensis genes had been generated by combining two gene prediction pipelines: Fgenesh++ developed by Softberry and Seqping by the Malaysian Palm Oil Board. PalmXplore was developed to provide a scalable data repository and a user-friendly search engine system to efficiently store, manage and retrieve the oil palm gene sequences and annotations. Information deposited in PalmXplore includes predicted genes, their genomic coordinates, as well as the annotations derived from external databases, such as Pfam, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. Information about genes related to important traits, such as those involved in fatty acid biosynthesis (FAB) and disease resistance, is also provided. The system offers Basic Local Alignment Search Tool homology search, where the results can be downloaded or visualized in the oil palm genome browser (MYPalmViewer). PalmXplore is regularly updated offering new features, improvements to genome annotation and new genomic sequences. The system is freely accessible at http://palmxplore.mpob.gov.my.
    Matched MeSH terms: Information Storage and Retrieval
  20. Samimi P, Ravana SD
    ScientificWorldJournal, 2014;2014:135641.
    PMID: 24977172 DOI: 10.1155/2014/135641
    Test collection is used to evaluate the information retrieval systems in laboratory-based evaluation experimentation. In a classic setting, generating relevance judgments involves human assessors and is a costly and time consuming task. Researchers and practitioners are still being challenged in performing reliable and low-cost evaluation of retrieval systems. Crowdsourcing as a novel method of data acquisition is broadly used in many research fields. It has been proven that crowdsourcing is an inexpensive and quick solution as well as a reliable alternative for creating relevance judgments. One of the crowdsourcing applications in IR is to judge relevancy of query document pair. In order to have a successful crowdsourcing experiment, the relevance judgment tasks should be designed precisely to emphasize quality control. This paper is intended to explore different factors that have an influence on the accuracy of relevance judgments accomplished by workers and how to intensify the reliability of judgments in crowdsourcing experiment.
    Matched MeSH terms: Information Storage and Retrieval/methods*
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