Displaying publications 81 - 100 of 118 in total

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  1. A comparison of two global positioning system devices for team-sport running protocols
    Willmott AGB, James CA, Bliss A, Leftwich RA, Maxwell NS
    J Biomech, 2019 01 23;83:324-328.
    PMID: 30563764 DOI: 10.1016/j.jbiomech.2018.11.044
    The comparability and reliability of global positioning system (GPS) devices during running protocols associated with team-sports was investigated. Fourteen moderately-trained males completed 690 m of straight-line movements, a 570 m change of direction (COD) course and a 642.5 m team-sport simulated circuit (TSSC); on two occasions. Participants wore a FieldWiz GPS device and a Catapult MinimaxX S4 10-Hz GPS device. Typical error of measurement (TE) and coefficient of variation (CV%) were calculated between GPS devices, for the variables of total distance and peak speed. Reliability comparisons were made within FieldWiz GPS devices, between sessions. Small TE were observed between FieldWiz and Catapult GPS devices for total distance and peak speed during straight-line (16.9 m [2%], 1.2 km·h-1 [4%]), COD (31.8 m [6%], 0.4 km·h-1 [2%]) and TSSC protocols (12.9 m [2%], 0.5 km·h-1 [2%]), respectively, with no significant mean bias (p > 0.05). Small TE were also observed for the FieldWiz GPS device between sessions (p > 0.05) for straight-line (9.6 m [1%], 0.2 km·h-1 [1%]), COD (12.8 m [2%], 0.2 km·h-1 [1%]) and TSSC protocols (6.9 m [1%], 0.6 km·h-1 [2%]), respectively. Data from the FieldWiz GPS device appears comparable to established devices and reliable across a range of movement patterns associated with team-sports.
    Matched MeSH terms: Geographic Information Systems/instrumentation*
  2. Fulltext Association between Availability of Neighborhood Fast Food Outlets and Overweight Among 5⁻18 Year-Old Children in Peninsular Malaysia: A Cross-Sectional Study
    Chee Cheong K, Yoon Ling C, Kuang Hock L, Mohd Ghazali S, Chien Huey T, Che Ibrahim MK, et al.
    Int J Environ Res Public Health, 2019 02 18;16(4).
    PMID: 30781699 DOI: 10.3390/ijerph16040593
    A growing number of fast-food outlets in close proximity to residential areas raises a question as to its impact on childhood overweight and obesity. This study aimed at determining the relationship between the availability of fast-food outlets that were in close proximity to residential areas and overweight among Malaysian children aged 5 to 18 years. Measurement data on the weight and height of 5544 children (2797 boys, 2747 girls) were obtained from the National Health and Morbidity Survey 2011. Overweight (including obesity) is defined as BMI-for-age z-score > +1 SD based on the WHO growth reference. Geographic information system geospatial analysis was performed to determine the number of fast-food outlets within 1000 m radius from the children's residential address. Multiple logistic regression was conducted to examine the association between the availability of fast-food outlets (none or more than one outlet) and overweight with adjustment for age, sex, ethnicity, monthly household income, parental educational level, residential area and supermarket density. Our results showed that the prevalence of overweight was 25.0% and there was a statistically significant association between the density of fast-food outlets and overweight (odds ratio: 1.23, 95% confidence interval: 1.03, 1.47). Our study suggested that the availability of fast-food outlets with close proximity in residential areas was significantly associated with being overweight among children. Limiting the number of fast-food outlets in residential areas could have a significant effect in reducing the prevalence of overweight among Malaysian children.
    Matched MeSH terms: Geographic Information Systems
  3. Vehicular traffic noise prediction and propagation modelling using neural networks and geospatial information system
    Ahmed AA, Pradhan B
    Environ Monit Assess, 2019 Feb 26;191(3):190.
    PMID: 30809746 DOI: 10.1007/s10661-019-7333-3
    This study proposes a neural network (NN) model to predict and simulate the propagation of vehicular traffic noise in a dense residential area at the New Klang Valley Expressway (NKVE) in Shah Alam, Malaysia. The proposed model comprises of two main simulation steps: that is, the prediction of vehicular traffic noise using NN and the simulation of the propagation of traffic noise emission using a mathematical model. First, the NN model was developed with the following selected noise predictors: the number of motorbikes, the sum of vehicles, car ratio, heavy vehicle ratio (e.g. truck, lorry and bus), highway density and a light detection and ranging (LiDAR)-derived digital surface model (DSM). Subsequently, NN and its hyperparameters were optimised by a systematic optimisation procedure based on a grid search approach. The noise propagation model was then developed in a geographic information system (GIS) using five variables, namely road geometry, barriers, distance, interaction of air particles and weather parameters. The noise measurement was conducted continuously at 15-min intervals and the data were analysed by taking the minimum, maximum and average values recorded during the day. The measurement was performed four times a day (i.e. morning, afternoon, evening, and midnight) over two days of the week (i.e. Sunday and Monday). An optimal radial basis function NN was used with 17 hidden layers. The learning rate and momentum values were 0.05 and 0.9, respectively. Finally, the accuracy of the proposed method achieved 78.4% with less than 4.02 dB (A) error in noise prediction. Overall, the proposed models were found to be promising tools for traffic noise assessment in dense urban areas.
    Matched MeSH terms: Geographic Information Systems
  4. Spatio-temporal simulation and prediction of land-use change using conventional and machine learning models: a review
    Aburas MM, Ahamad MSS, Omar NQ
    Environ Monit Assess, 2019 Mar 05;191(4):205.
    PMID: 30834982 DOI: 10.1007/s10661-019-7330-6
    Spatio-temporal land-use change modeling, simulation, and prediction have become one of the critical issues in the last three decades due to uncertainty, structure, flexibility, accuracy, the ability for improvement, and the capability for integration of available models. Therefore, many types of models such as dynamic, statistical, and machine learning (ML) models have been used in the geographic information system (GIS) environment to fulfill the high-performance requirements of land-use modeling. This paper provides a literature review on models for modeling, simulating, and predicting land-use change to determine the best approach that can realistically simulate land-use changes. Therefore, the general characteristics of conventional and ML models for land-use change are described, and the different techniques used in the design of these models are classified. The strengths and weaknesses of the various dynamic, statistical, and ML models are determined according to the analysis and discussion of the characteristics of these models. The results of the review confirm that ML models are the most powerful models for simulating land-use change because they can include all driving forces of land-use change in the simulation process and simulate linear and non-linear phenomena, which dynamic models and statistical models are unable to do. However, ML models also have limitations. For instance, some ML models are complex, the simulation rules cannot be changed, and it is difficult to understand how ML models work in a system. However, this can be solved via the use of programming languages such as Python, which in turn improve the simulation capabilities of the ML models.
    Matched MeSH terms: Geographic Information Systems
  5. Spatial and temporal risk quotient based river assessment for water resources management
    Wan Mohtar WHM, Abdul Maulud KN, Muhammad NS, Sharil S, Yaseen ZM
    Environ Pollut, 2019 May;248:133-144.
    PMID: 30784832 DOI: 10.1016/j.envpol.2019.02.011
    Malaysia depends heavily on rivers as a source for water supply, irrigation, and sustaining the livelihood of local communities. The evolution of land use in urban areas due to rapid development and the continuous problem of illegal discharge have had a serious adverse impact on the health of the country's waterways. Klang River requires extensive rehabilitation and remediation before its water could be utilised for a variety of purposes. A reliable and rigorous remediation work plan is needed to identify the sources and locations of streams that are constantly polluted. This study attempts to investigate the feasibility of utilising a temporal and spatial risk quotient (RQ) based analysis to make an accurate assessment of the current condition of the tributaries in the Klang River catchment area. The study relies on existing data sets on Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Total Suspended Solids (TSS), and Ammonia (NH3) to evaluate the water quality at thirty strategic locations. Analysis of ammonia pollution is not only based on the limit established for river health but was expanded to include the feasibility of using the water for water intake, recreational activities, and sustaining fish population. The temporal health of Klang River was evaluated using the Risk Matrix Approach (RMA) based on the frequency of RQ > 1 and associated colour-coded hazard impacts. By using the developed RMA, the hazard level for each parameter at each location was assessed and individually mapped using Geographic Information System (GIS). The developed risk hazard mapping has high potential as one of the essential tools in making decisions for a cost-effective river restoration and rehabilitation.
    Matched MeSH terms: Geographic Information Systems
  6. Analysis of dental services distribution in Malaysia: a geographic information systems - based approach
    Md Bohari NF, Kruger E, John J, Tennant M
    Int Dent J, 2019 Jun;69(3):223-229.
    PMID: 30565655 DOI: 10.1111/idj.12454
    OBJECTIVE: The aim of this study was to analyse, in detail, the distribution of primary dental clinics in relation to the Malaysian population and relative population wealth, to test the hypothesis that an uneven distribution of dental services exists in Malaysia.

    METHOD: This 2016 study located every dental practice in Malaysia (private and public) and mapped these practices against population, using Geographic Information Systems (GIS) tools. Population clusters within 5, 10 and 20 km of a dental clinic were identified, and clinic-to-population ratios were ascertained. Population data were obtained from the Population and Housing Census of Malaysia 2010. Population relative wealth was obtained from the 2014 Report on Household Income and Basic Amenities Survey for Malaysia. The physical address for each dental practice in Malaysia was gathered from the Official Portal of Ministry of Health Malaysia. All data for analysis were extracted from the integrated database in Quantum GIS (QGIS) into Microsoft Excel.

    RESULT: The population of Malaysia (24.9 million) was distributed across 127 districts, with 119 (94%) having at least one dental clinic. Sixty-four districts had fewer than 10 dental clinics, and 11.3% of Malaysians did not reside in the catchment of 20 km from any dental clinic. The total dental clinic-to-population ratio was 1:9,000: for public dental clinics it was 1:38,000 and for private clinics it was 1:13,000.

    CONCLUSION: Dental services were distributed relative to high population density, were unevenly distributed across Malaysia and the majority of people with the highest inaccessibility to a dental service resided in Malaysian Borneo.

    Matched MeSH terms: Geographic Information Systems*
  7. Fulltext Evaluating Water Level Changes at Different Tidal Phases Using UAV Photogrammetry and GNSS Vertical Data
    Mohamad N, Abdul Khanan MF, Ahmad A, Md Din AH, Shahabi H
    Sensors (Basel), 2019 Aug 31;19(17).
    PMID: 31480412 DOI: 10.3390/s19173778
    Evaluating water level changes at intertidal zones is complicated because of dynamic tidal inundation. However, water level changes during different tidal phases could be evaluated using a digital surface model (DSM) captured by unmanned aerial vehicle (UAV) with higher vertical accuracy provided by a Global Navigation Satellite System (GNSS). Image acquisition using a multirotor UAV and vertical data collection from GNSS survey were conducted at Kilim River, Langkawi Island, Kedah, Malaysia during two different tidal phases, at high and low tides. Using the Structure from Motion (SFM) algorithm, a DSM and orthomosaics were produced as the main sources of data analysis. GNSS provided horizontal and vertical geo-referencing for both the DSM and orthomosaics during post-processing after field observation at the study area. The DSM vertical accuracy against the tidal data from a tide gauge was about 12.6 cm (0.126 m) for high tide and 34.5 cm (0.345 m) for low tide. Hence, the vertical accuracy of the DSM height is still within a tolerance of ±0.5 m (with GNSS positioning data). These results open new opportunities to explore more validation methods for water level changes using various aerial platforms besides Light Detection and Ranging (LiDAR) and tidal data in the future.
    Matched MeSH terms: Geographic Information Systems
  8. Projection the long-term ungauged rainfall using integrated Statistical Downscaling Model and Geographic Information System (SDSM-GIS) model
    Tukimat NNA, Ahmad Syukri NA, Malek MA
    Heliyon, 2019 Sep;5(9):e02456.
    PMID: 31687558 DOI: 10.1016/j.heliyon.2019.e02456
    An accuracy in the hydrological modelling will be affected when having limited data sources especially at ungauged areas. Due to this matter, it will not receiving any significant attention especially on the potential hydrologic extremes. Thus, the objective was to analyse the accuracy of the long-term projected rainfall at ungauged rainfall station using integrated Statistical Downscaling Model and Geographic Information System (SDSM-GIS) model. The SDSM was used as a climate agent to predict the changes of the climate trend in Δ2030s by gauged and ungauged stations. There were five predictors set have been selected to form the local climate at the region which provided by NCEP (validated) and CanESM2-RCP4.5 (projected). According to the statistical analyses, the SDSM was controlled to produce reliable validated results with lesser %MAE (<23%) and higher R. The projected rainfall was suspected to decrease 14% in Δ2030s. All the RCPs agreed the long term rainfall pattern was consistent to the historical with lower annual rainfall intensity. The RCP8.5 shows the least rainfall changes. These findings then used to compare the accuracy of monthly rainfall at control station (Stn 2). The GIS-Kriging method being as an interpolation agent was successfully to produce similar rainfall trend with the control station. The accuracy was estimated to reach 84%. Comparing between ungauged and gauged stations, the small %MAE in the projected monthly results between gauged and ungauged stations as a proved the integrated SDSM-GIS model can producing a reliable long-term rainfall generation at ungauged station.
    Matched MeSH terms: Geographic Information Systems
  9. Fulltext Spatial clustering of cholera in Sabah, Malaysia
    Syed Sharizman Syed Abdul Rahim, Shamsul Azhar Shah, Zahir Izuan Azhar, Mohammad Saffree Jeffree, Mohd Rohaizat Hassan, Nazarudin Safian
    Malaysian Journal of Medicine and Health Sciences, 2019;15(106):54-54.
    MyJurnal
    Introduction: Cholera epidemics can produce devastating public health outcomes. Cholera distribution is influenced by temperature, precipitation, elevation, distance to the coastline and oceanic environmental factors such as sea surface temperature, sea surface height and ocean chlorophyll concentration. The purpose of this study is to describe the spatial epidemiology of cholera in the four districts of Sabah. Methods: This is a retrospective review of 4 years (2011 to 2014) data from the districts of Kota Kinabalu, Penampang, Putatan and Papar, Sabah. All reported cases of cholera from those areas are included. Coordinates for locations of the cases are based on home addresses. SPSS v20, ArcGIS v10 and CrimeStat IV were used for data analysis and mapping. Results: Cholera showed several clustering of cases, such as in 2011 and 2014 in Kota Kinabalu. In the year 2011 and 2013, Penampang and Papar districts had the nearest neighbour index of less than 1, but p value was not significant, meaning the pattern did not appear to be significant. Nearest neighbour hierarchical clustering analysis further revealed cholera had 7 clusters, of those 6 were first order and 1 was a second order cluster. Conclusion: Cholera shows disease clustering which could mean it is due to its common point source or localised human to human transmission. Using GIS as a tool may help in surveillance and control of cholera infections.
    Matched MeSH terms: Geographic Information Systems
  10. Fulltext Left-handed metamaterial bandpass filter for GPS, Earth Exploration-Satellite and WiMAX frequency sensing applications
    Alam MJ, Ahamed E, Faruque MRI, Islam MT, Tamim AM
    PLoS One, 2019;14(11):e0224478.
    PMID: 31714917 DOI: 10.1371/journal.pone.0224478
    Interferences and accuracy problem are one of the most talked issues in today's world for sensor technology. To deal with this contention, a microstrip framework consisting of a dual mode double negative (DNG) metamaterial based bandpass filter is presented in this article. To obtain the ultimate noise reduction bandpass filter, the proposed structure has to go through a series of development process, where the characteristics of the structure are tested to the limit. This filter is built on Rogers RT-5880 substrate with a 50Ω microstrip line. To pursue the elementary mode of resonant frequency, the ground layer of the structure is kept partially filled and a gradual analysis is executed on the prospective metamaterial (resonator) unit cell. Depending on the developed unit cell, the filter is constructed and fabricated to verify the concept, concentrating on GPS (1.55GHz), Earth Exploration-Satellite (2.70GHz) and WiMAX (3.60GHz) bands of frequencies. Moreover, the structure is investigated using Nicolson-Ross-Weir (NRW) approach to justify the metamaterial characteristics, and also tested on S-parameters, current distribution, electric and magnetic fields and quality factor. Having a propitious architecture and DNG characteristics, the proposed structure is suitable for bandpass filter for GPS, Earth Exploration-Satellite and WiMAX frequency sensing applications.
    Matched MeSH terms: Geographic Information Systems*
  11. Investment risk and natural resource potential in "Belt & Road Initiative" countries: A multi-criteria decision-making approach
    Hussain J, Zhou K, Guo S, Khan A
    Sci Total Environ, 2020 Mar 16;723:137981.
    PMID: 32208210 DOI: 10.1016/j.scitotenv.2020.137981
    Chinese enterprises that conduct overseas investment projects encounter diverse challenges that emerge from political, economic, social, and environmental risks in the host countries. To better assess the overseas investment risks faced by Chinese enterprises, this study introduced and assessed novel aspects and an indicator system. Moreover, the "Technique for Order Preference by Similarity to Ideal Solution" (TOPSIS) method based on entropy weight was performed to generate a comprehensive assessment of China's foreign investment risk and natural resource potential in 63 "Belt & Road Initiative" (BRI) countries. This study aims to encourage Chinese enterprises to devise suitable overseas investment decision-making strategies concerning natural resource potential in host countries. A Geographic Information System (GIS) map was also created to assess the potential risks and opportunities for Chinese enterprises when making investment decisions in host countries. The findings indicate that the majority of countries in Central and Eastern Europe and other BRI countries such as Singapore, Malaysia, Nepal, Bhutan, Russia, Armenia, and the United Arab Emirates were the most suitable choices for Chinese enterprises engaging in overseas investment. Based on these results, Chinese enterprises could manage and execute BRI projects more effectively to minimise potential risks and maximise their investment benefits.
    Matched MeSH terms: Geographic Information Systems
  12. Scenario-based pollution discharge simulations and mapping using integrated QUAL2K-GIS
    Ahmad Kamal N, Muhammad NS, Abdullah J
    Environ Pollut, 2020 Apr;259:113909.
    PMID: 31927277 DOI: 10.1016/j.envpol.2020.113909
    Malaysia is a tropical country that is highly dependent on surface water for its raw water supply. Unfortunately, surface water is vulnerable to pollution, especially in developed and dense urban catchments. Therefore, in this study, a methodology was developed for an extensive temporal water quality index (WQI) and classification analysis, simulations of various pollutant discharge scenarios using QUAL2K software, and maps with NH3-N as the core pollutant using an integrated QUAL2K-GIS. It was found that most of the water quality stations are categorized as Class III (slightly polluted to polluted). These stations are surrounded by residential areas, industries, workshops, restaurants and wet markets that contribute to the poor water quality levels. Additionally, low WQI values were reported in 2010 owing to development and agricultural activities. However, the WQI values improved during the wet season. High concentrations of NH3-N were found in the basin, especially during dry weather conditions. Three scenarios were simulated, i.e. 10%, 50% and 70% of pollution discharge into Skudai river using a calibrated and validated QUAL2K model. Model performance was evaluated using the relative percentage difference. An inclusive graph showing the current conditions and pollution reduction scenarios with respect to the distance of Skudai river and its tributaries is developed to determine the WQI classification. Comprehensive water quality maps based on NH3-N as the core pollutant are developed using integrated QUAL2K-GIS to illustrate the overall condition of the Skudai river. High NH3-N in the Skudai River affects water treatment plant operations. Pollution control of more than 90% is required to improve the water quality classification to Class II. The methodology and analysis developed in this study can assist various stakeholders and authorities in identifying problematic areas and determining the required percentage of pollution reduction to improve the Skudai River water quality.
    Matched MeSH terms: Geographic Information Systems
  13. Fulltext Review of GPS collar deployments and performance on nonhuman primates
    Dore KM, Hansen MF, Klegarth AR, Fichtel C, Koch F, Springer A, et al.
    Primates, 2020 May;61(3):373-387.
    PMID: 31965380 DOI: 10.1007/s10329-020-00793-7
    Over the past 20 years, GPS collars have emerged as powerful tools for the study of nonhuman primate (hereafter, "primate") movement ecology. As the size and cost of GPS collars have decreased and performance has improved, it is timely to review the use and success of GPS collar deployments on primates to date. Here we compile data on deployments and performance of GPS collars by brand and examine how these relate to characteristics of the primate species and field contexts in which they were deployed. The compiled results of 179 GPS collar deployments across 17 species by 16 research teams show these technologies can provide advantages, particularly in adding to the quality, quantity, and temporal span of data collection. However, aspects of this technology still require substantial improvement in order to make deployment on many primate species pragmatic economically. In particular, current limitations regarding battery lifespan relative to collar weight, the efficacy of remote drop-off mechanisms, and the ability to remotely retrieve data need to be addressed before the technology is likely to be widely adopted. Moreover, despite the increasing utility of GPS collars in the field, they remain substantially more expensive than VHF collars and tracking via handheld GPS units, and cost considerations of GPS collars may limit sample sizes and thereby the strength of inferences. Still, the overall high quality and quantity of data obtained, combined with the reduced need for on-the-ground tracking by field personnel, may help defray the high equipment cost. We argue that primatologists armed with the information in this review have much to gain from the recent, substantial improvements in GPS collar technology.
    Matched MeSH terms: Geographic Information Systems/statistics & numerical data*
  14. Fulltext SenseCrypt: A Security Framework for Mobile Crowd Sensing Applications
    Pius Owoh N, Mahinderjit Singh M
    Sensors (Basel), 2020 Jun 09;20(11).
    PMID: 32526843 DOI: 10.3390/s20113280
    The proliferation of mobile devices such as smartphones and tablets with embedded sensors and communication features has led to the introduction of a novel sensing paradigm called mobile crowd sensing. Despite its opportunities and advantages over traditional wireless sensor networks, mobile crowd sensing still faces security and privacy issues, among other challenges. Specifically, the security and privacy of sensitive location information of users remain lingering issues, considering the "on" and "off" state of global positioning system sensor in smartphones. To address this problem, this paper proposes "SenseCrypt", a framework that automatically annotates and signcrypts sensitive location information of mobile crowd sensing users. The framework relies on K-means algorithm and a certificateless aggregate signcryption scheme (CLASC). It incorporates spatial coding as the data compression technique and message query telemetry transport as the messaging protocol. Results presented in this paper show that the proposed framework incurs low computational cost and communication overhead. Also, the framework is robust against privileged insider attack, replay and forgery attacks. Confidentiality, integrity and non-repudiation are security services offered by the proposed framework.
    Matched MeSH terms: Geographic Information Systems
  15. Fulltext Landslide Susceptibility Mapping Using Machine Learning Algorithms and Remote Sensing Data in a Tropical Environment
    Nhu VH, Mohammadi A, Shahabi H, Ahmad BB, Al-Ansari N, Shirzadi A, et al.
    Int J Environ Res Public Health, 2020 07 08;17(14).
    PMID: 32650595 DOI: 10.3390/ijerph17144933
    We used AdaBoost (AB), alternating decision tree (ADTree), and their combination as an ensemble model (AB-ADTree) to spatially predict landslides in the Cameron Highlands, Malaysia. The models were trained with a database of 152 landslides compiled using Synthetic Aperture Radar Interferometry, Google Earth images, and field surveys, and 17 conditioning factors (slope, aspect, elevation, distance to road, distance to river, proximity to fault, road density, river density, normalized difference vegetation index, rainfall, land cover, lithology, soil types, curvature, profile curvature, stream power index, and topographic wetness index). We carried out the validation process using the area under the receiver operating characteristic curve (AUC) and several parametric and non-parametric performance metrics, including positive predictive value, negative predictive value, sensitivity, specificity, accuracy, root mean square error, and the Friedman and Wilcoxon sign rank tests. The AB model (AUC = 0.96) performed better than the ensemble AB-ADTree model (AUC = 0.94) and successfully outperformed the ADTree model (AUC = 0.59) in predicting landslide susceptibility. Our findings provide insights into the development of more efficient and accurate landslide predictive models that can be used by decision makers and land-use managers to mitigate landslide hazards.
    Matched MeSH terms: Geographic Information Systems
  16. InWalker: smart white cane for the blind
    Husin MH, Lim YK
    Disabil Rehabil Assist Technol, 2020 08;15(6):701-707.
    PMID: 31729282 DOI: 10.1080/17483107.2019.1615999
    Background/Purpose: Visual impairment is a disability more commonly caused by diseases that lead to several disadvantages to the daily activities amongst those blind. For almost a century since the white cane was first introduced, the cane has remained as the most reliable tool for those affected by blindness.Methods: By using a combination of the capabilities of Internet of Things (IoT) and existing devices, such as mobile phones, an InWalker system is proposed to expand the functionality of the typical white cane, so as to introduce several new features that enhance the safety and confidence amongst people who are blind. As such, this paper explores the existing works and projects to comprehend the motivation and the standard practices for each proposed feature. Each of the strength and drawback has been assessed thoroughly to refine the scope of this project.Results: The proposed project, InWalker, is an intelligent system that has an embedded board system with various sensors to enhance the usability of white cane. The inputs from the sensor are processed on a microcontroller, which then pass the data to a smartphone via Bluetooth for additional features, such as global positioning system (GPS) tracking and SMS services.Conclusions: Based on the initial user testing, the proposed system has successfully fulfilled most of the users' need.Implication for RehabilitationVisual impairment is a disability more commonly caused by diseases that lead to several disadvantages amongst those blind.The white cane has been seen as the most reliable tool for the visual impaired.This tool could be further improved with the integration of additional sensors that works with today's mobile devices.The proposed system, InWalker, is able to improve the overall quality of life among people who are blind through several features: obstacle detection, GPS tracking and a light illumination in dark environments for increased safety.
    Matched MeSH terms: Geographic Information Systems/instrumentation*
  17. Fulltext Spatial analysis and GIS in the study of COVID-19. A review
    Franch-Pardo I, Napoletano BM, Rosete-Verges F, Billa L
    Sci Total Environ, 2020 Oct 15;739:140033.
    PMID: 32534320 DOI: 10.1016/j.scitotenv.2020.140033
    This study entailed a review of 63 scientific articles on geospatial and spatial-statistical analysis of the geographical dimension of the 2019 coronavirus disease (COVID-19) pandemic. The diversity of themes identified in this paper can be grouped into the following categories of disease mapping: spatiotemporal analysis, health and social geography, environmental variables, data mining, and web-based mapping. Understanding the spatiotemporal dynamics of COVID-19 is essential for its mitigation, as it helps to clarify the extent and impact of the pandemic and can aid decision making, planning and community action. Health geography highlights the interaction of public health officials, affected actors and first responders to improve estimations of disease propagation and likelihoods of new outbreaks. Attempts at interdisciplinary correlation examine health policy interventions for the siting of health/sanitary services and controls, mapping/tracking of human movement, formulation of appropriate scientific and political responses and projection of spatial diffusion and temporal trends. This review concludes that, to fight COVID-19, it is important to face the challenges from an interdisciplinary perspective, with proactive planning, international solidarity and a global perspective. This review provides useful information and insight that can support future bibliographic queries, and also serves as a resource for understanding the evolution of tools used in the management of this major global pandemic of the 21 Century. It is hoped that its findings will inspire new reflections on the COVID-19 pandemic by readers.
    Matched MeSH terms: Geographic Information Systems
  18. Fulltext Do Termitaria Indicate the Presence of Groundwater? A Case Study of Hydrogeophysical Investigation on a Land Parcel with Termite Activity
    Ahmed JB, Salisu A, Pradhan B, Alamri AM
    Insects, 2020 Oct 24;11(11).
    PMID: 33114307 DOI: 10.3390/insects11110728
    Termite nests have long been suggested to be good indicators of groundwater but only a few studies are available to demonstrate the relationship between the two. This study therefore aims at investigating the most favourable spots for locating groundwater structures on a small parcel of land with conspicuous termite activity. To achieve this, geophysical soundings using the renowned vertical electrical sounding (VES) technique was carried out on the gridded study area. A total of nine VESs with one at the foot of a termitarium were conducted. The VES results were interpreted and assessed via two different techniques: (1) physical evaluation as performed by drillers in the field and (2) integration of primary and secondary geoelectrical parameters in a geographic information system (GIS). The result of the physical evaluation indicated a clear case of subjectivity in the interpretation but was consistent with the choice of VES points 1 and 6 (termitarium location) as being the most prospective points to be considered for drilling. Similarly, the integration of the geoelectrical parameters led to the mapping of the most prospective groundwater portion of the study area with the termitarium chiefly in the center of the most suitable region. This shows that termitaria are valuable landscape features that can be employed as biomarkers in the search of groundwater.
    Matched MeSH terms: Geographic Information Systems
  19. Fulltext A Multi-Sensor Comparative Analysis on the Suitability of Generated DEM from Sentinel-1 SAR Interferometry Using Statistical and Hydrological Models
    Mohammadi A, Karimzadeh S, Jalal SJ, Kamran KV, Shahabi H, Homayouni S, et al.
    Sensors (Basel), 2020 Dec 16;20(24).
    PMID: 33339435 DOI: 10.3390/s20247214
    Digital elevation model (DEM) plays a vital role in hydrological modelling and environmental studies. Many essential layers can be extracted from this land surface information, including slope, aspect, rivers, and curvature. Therefore, DEM quality and accuracy will affect the extracted features and the whole process of modeling. Despite freely available DEMs from various sources, many researchers generate this information for their areas from various observations. Sentinal-1 synthetic aperture radar (SAR) images are among the best Earth observations for DEM generation thanks to their availabilities, high-resolution, and C-band sensitivity to surface structure. This paper presents a comparative study, from a hydrological point of view, on the quality and reliability of the DEMs generated from Sentinel-1 data and DEMs from other sources such as AIRSAR, ALOS-PALSAR, TanDEM-X, and SRTM. To this end, pair of Sentinel-1 data were acquired and processed using the SAR interferometry technique to produce a DEM for two different study areas of a part of the Cameron Highlands, Pahang, Malaysia, a part of Sanandaj, Iran. Based on the estimated linear regression and standard errors, generating DEM from Sentinel-1 did not yield promising results. The river streams for all DEMs were extracted using geospatial analysis tool in a geographic information system (GIS) environment. The results indicated that because of the higher spatial resolution (compared to SRTM and TanDEM-X), more stream orders were delineated from AIRSAR and Sentinel-1 DEMs. Due to the shorter perpendicular baseline, the phase decorrelation in the created DEM resulted in a lot of noise. At the same time, results from ground control points (GCPs) showed that the created DEM from Sentinel-1 is not promising. Therefore, other DEMs' performance, such as 90-meters' TanDEM-X and 30-meters' SRTM, are better than Sentinel-1 DEM (with a better spatial resolution).
    Matched MeSH terms: Geographic Information Systems
  20. Mapping the Malaysian Smoking Cessation Clinics: A Geographic Information System-Based Study
    Md Bohari NF, Sabri NF, Wan Rasdi WND, Mohd Radzi NA, Bakri NN
    Asia Pac J Public Health, 2020 12 24;33(2-3):227-233.
    PMID: 33356376 DOI: 10.1177/1010539520982718
    Although geographic information system-based studies are particularly increasing in other sectors, few have embraced their full potential in health services allocation in Malaysia. This study aimed to produce a visual map on the distribution of smoking cessation clinics (SCCs) in Malaysia and analyze its pattern against the national population of smokers. SCC addresses were obtained from the government website and mapped using geographic information system tools. A total of 199 and 449 private and public SCCs was mapped throughout the country, respectively. The lowest SCC to smoker population ratio was in the state of Negeri Sembilan with 1:3000. The highest SCC to smoker population ratio was in Sabah with 1 SCC for 15 000 smokers. Almost 70% of SCCs were primary health clinics. Smoking cessation clinics were distributed throughout all the states in Malaysia except the state of Sabah.
    Matched MeSH terms: Geographic Information Systems
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