Family support has a strong impact on individuals and there is no exception in substance abuse
recovery process. Family support manages to play a positive role in substance abuse problems. The
present study deals with the developing model of family support substance abuser with the
combination method of Geographic Information System (GIS) and statistical models. The data used
for this study was collected from seven districts in Terengganu with a constant number of
respondents. 35 respondents for each district were involved in this study. It was then processed using
factor analysis (FA) to develop index of family support. By using the developed indices, GIS tool was
used to plot the distribution map of family support indices according to each form of family support.
The result indicated that the highest index for all form of family support abuser was located in Besut
district. High level of family support is essential as an effort for rehabilitation process of substance
abusers.
Matched MeSH terms: Geographic Information Systems
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
Disability is termed as both evolving concept and manifestation of interaction between persons with disabilities (PWDs) and physical and environmental barriers that holds them back from contributing actively in a society. People who fall in this category will find themselves trapped in a such vulnerable condition as they may not be able to cope with their daily problems without high surveillance from their guardian. Development of a mobile apps and web GIS-based healthcare system in Ampang is proposed in this study as this application has a bright potential to assist PWDs in terms of accessibilities to reach healthcare centres. The main objectives of this paper are i) to study the needs assessment on the proposed system, ii) to develop a mobile and web GIS-based healthcare information system and iii) to evaluate the performance of the proposed system. Selected respondents agreed on the development of the prototype system, namely the mobile apps and web system. The system was created with main menus such as doctor home visits, ambulance and medication delivery. Medical support team can also perform analyses in the system for PWD needs such as shortest path analysis, buffering and view of the main menus.
Matched MeSH terms: Geographic Information Systems
Nowadays, one of the most important challenges in heterogeneous networks is the connection consistency between the mobile station and the base stations. Furthermore, along the roaming process between the mobile station and the base station, the system performance degrades significantly due to the interferences from neighboring base stations, handovers to inaccurate base station and inappropriate technology selection. In this paper, several algorithms are proposed to improve mobile station performance and seamless mobility across the long-term evolution (LTE) and Worldwide Interoperability for Microwave Access (WiMAX) technologies, along with a minimum number of redundant handovers. Firstly, the enhanced global positioning system (GPS) and the novel received signal strength (RSS) prediction approaches are suggested to predict the target base station accurately. Then, the multiple criteria with two thresholds algorithm is proposed to prioritize the selection between LTE and WiMAX as the target technology. In addition, this study also covers the intercell and cochannel interference reduction by adjusting the frequency reuse ratio 3 (FRR3) to work with LTE and WiMAX. The obtained results demonstrate high next base station prediction efficiency and high accuracy for both horizontal and vertical handovers. Moreover, the received signal strength is kept at levels higher than the threshold, while maintaining low connection cost and delay within acceptable levels. In order to highlight the combination of the proposed algorithms' performance, it is compared with the existing RSS and multiple criteria handover decision algorithms.
Matched MeSH terms: Geographic Information Systems
In the cold winter month of January 2012, two post graduate students from the Department of Community Health, Universiti Kebangsaan Malaysia (UKM), went on a two weeks field attachment with the Division of International Health (Public Health), Niigata University Graduate School of Medical & Dental Sciences (NU). This report is an account of our first hand learning experience about the public health system and culture in Niigata, Japan. Famously known as the 'Snow Country', Niigata prefecture is approximately 350 kilometers north of Tokyo, in the middle of the west coast of Honshu island, facing the Sea of Japan. It borders on the east with Fukushima prefecture, which was badly affected by the great tsunami disaster in March 2011. Niigata has a population of two and a half million, of which 21.3% is above the age of 65. Niigata University is located in Niigata City, the capital of Niigata prefecture. This attachment was under the UKM-Global Student Mobility Programme (Outbound) and it was taken as an opportunity to improve the memorandum of understanding between UKM and NU. The objectives were to gain knowledge and experience in various public health issues in a developed nation like Japan. Specifically, we were interested to learn about the local public health programmes, the influenza surveillance system, public health programmes for the elderly population, the Geographical Information System (GIS) and the Japanese culture in general. (Copied from article).
Matched MeSH terms: Geographic Information Systems
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
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
This study involves the adoption of the Geographic Information System (GIS) modeling approach to determine the quickest routes for fresh vegetable delivery. During transport, fresh vegetables mainly deteriorate on account of temperature and delivery time. Nonetheless, little attention has been directed to transportation issues in most areas within Kuala Lumpur. In addition, perishable food normally has a short shelf life, thus timely delivery significantly affects delivery costs. Therefore, selecting efficient routes would consequently reduce the total transportation costs. The regression model is applied in this study to determine the parameters that affect route selection with respect to the fastest delivery of fresh vegetables. For the purpose of this research, ArcGIS software with network analyst extension is adopted to solve the problem of complex networks. The final output of this research is a map of quickest routes with the best delivery times based on all variables. The variables tested from regression analysis are the most effective parameters to make the flow of road networks slower. The objective is to improve the delivery services by achieving the least drive time. The main findings of this research are that Land use such as residential area and population as variables are the effective parameters on drive time.
Matched MeSH terms: Geographic Information Systems
Perishable products must be transported quickly from its production area to the markets due to the climatic conditions of Malaysia. Deterioration of fresh produce is affected by temperature and delivery time. The cost to achieve such timely delivery of perishable food can affect the revenue of suppliers and retailers. Choosing an efficient delivery route at right time can reduce the total transportation cost. However, insufficient attention has been given to transportation issues with regards to fresh food delivery of greater Kuala Lumpur. The present study involves adoption of the Geographic Information System (GIS) modelling approach to determine the fastest delivery routes for fresh products to several hypermarkets. For this purpose, ArcGIS software was adopted for solving the problem of a complex road networks. With a goal of realizing the shortest time for delivery route planning, impedance function would be integrated by taking into account the time emphasized in the study. The main findings of this study include determination of efficient routes for delivery of fresh vegetables based on minimal drive time. It has been proposed that the fastest route model for delivery of fresh products is based on comparing two time frames within a day. The final output of this research was a map of quickest routes with best delivery time based on two time frames.
Matched MeSH terms: Geographic Information Systems*
In hilly forest area, aligning forest roads is the key towards an effective and sustainable forest management. Constraints in forest road planning are mainly due to environmental factors and topographical conditions. Selecting the criteria for planning forest road and setting the priorities, ranking them for environmental sustainability and reduce cost in road construction is important. Different criteria are required at different forest area since the quantifiable relationship between cause and effect to meet the goal are not comprehensively prioritized. In order to solve the problem, the relative importance factor from multi criteria basis, namely Analytic Hierarchy Process (AHP) was applied. Therefore, the objective of this study was to develop priorities and rank a selected criterion for planning forest road in hilly area using AHP approach. Four criteria had been identified to meet the goal of suitable forest road allocation namely slope, river crossing, elevation and existing forest road. The suitable criteria selected were sorted with weight in ranking order to minimize the impact of timber harvesting. Our results showed that the priorities and ranking were as follows; slope (w = 0.558), followed by river crossing (w = 0.303), elevation (w = 0.095) and lastly existing forest road (w = 0.044), respectively. Therefore, the relative preference factor developed in this study can be used by the Forestry Department for formulating suitable forest road allocation in hilly area simultaneously to be integrated with geographic information system technology.
Matched MeSH terms: Geographic Information Systems
Penggunaan tanah boleh mengakibatkan perubahan fungsi dari masa ke masa, sesuai dengan tujuan pembangunan. Kawasan Bandar Pekanbaru terdiri daripada 12 sub-kawasan persekutuan dengan jumlah keluasan kira-kira 632.26 km2. Tujuan kajian adalah untuk menganalisis perubahan guna tanah daripada aspek ruang dan masa. Data guna tanah yang diambil kira dalam analisis ini adalah peta guna tanah 1992 dan 2004. Hasil analisis dengan menggunakan perisian ArcView GIS versi 3.2 mendapati bahawa telah berlaku penurunan guna tanah signifikan, iaitu jenis perkebunan dan hutan tahun 2004. Peningkatan jenis lain-lain, penggunaan tanah seperti permukiman dan tumbuhan/semak tahun 2004 telah berlaku. Perubahan ini merupakan pengaruh daripada pembangunan bandar. Sebaliknya, pembangunan bandar boleh memberi impak negatif terhadap sekitaran jika pola perubahan guna tanah dirancang tanpa pengurusan yang baik.
Matched MeSH terms: Geographic Information Systems
Tuberculosis (TB) is known as a disease that prone to spatial clustering. Recent development has seen a sharp rise in the number of epidemiologic studies employing Geographical Information System (GIS), particularly in identifying TB clusters and evidences of etiologic factors. The aim of this systematic review is to determine evidence of TB clustering, type of spatial analysis commonly used and the application of GIS in TB surveillance and control. A literature search of articles published in English language between 2000 and November 2015 was performed using MEDLINE and Science Direct using relevant search terms related to spatial analysis in studies of TB cluster. The search strategy was adapted and developed for each database using appropriate subject headings and keywords. The literature reviewed showed strong evidence of TB clustering occurred in high risk areas in both developed and developing countries. Spatial scan statistics were the most commonly used analysis and proved useful in TB surveillance through detection of outbreak, early warning and identifying area of increased TB transmission. Among others are targeted screening and assessment of TB program using GIS technology. However there were limitations on suitability of utilizing aggregated data such as national cencus that were pre-collected in explaining the present spatial distribution among population at risk. Spatial boundaries determined by zip code may be too large for metropolitan area or too small for country. Nevertheless, GIS is a powerful tool in aiding TB control and prevention in developing countries and should be used for real-time surveillance and decision making.
Matched MeSH terms: Geographic Information Systems
The aim of this paper is to review the potentialities and major methodological challenges
of integrating remote sensing (RS) and geographic information system (GIS) with socioeconomic data
from published articles or book chapters. RS and GIS combined with social science (SS)(termed as
geoinformation technology) serve many applications for sustainable management and monitoring of
the environment. This combined approach gives more accurate results than the single one. It makes
information available about the trend and pattern of land use and land cover change (LUCC) with
socioeconomic variables like population, demographic or income. This combined study which links
RS and GIS with socioeconomic data can also be used successfully for monitoring transmission rate
of disease and mapping or preparing vulnerability index. For impact assessment and modelling, this
combined technology provides better results than the single one. There are some methodological
problems for the researchers to link completely two different disciplines as the object of study and
observational unit is completely different. However, this interdisciplinary study is gaining popularity
day by day to researchers from different disciplines as well as decision makers.
Matched MeSH terms: Geographic Information Systems
Penyakit denggi merupakan penyakit bawaan vektor yang menjadi salah satu ancaman utama kesihatan awam di Malaysia. Pemetaan taburan kes denggi daripada aspek reruang-masa boleh menjadi kaedah yang berguna dalam menilai risiko denggi kepada masyarakat. Kajian ini bertujuan untuk memetakan taburan reruang dan reruang-masa kes-kes denggi di dalam daerah Seremban, dijalankan dengan Sistem Maklumat Geografi (GIS) khususnya analisis reruang dan reruang-masa. Analisis taburan reruang menggunakan Indeks Moran, purata kejiranan terdekat (ANN) dan anggaran kepadatan Kernel. Analisis reruang-masa ditentukan dengan indeks kekerapan, jangka masa dan intensiti untuk mengenal pasti kawasan berisiko denggi mengikut masa. Sejumlah 6076 kes denggi dicatatkan di Pejabat Kesihatan Daerah Seremban dari tahun 2003 hingga 2009. Kadar insiden denggi adalah tinggi pada tahun 2003, 2008 dan 2009 dengan nisbah denggi : denggi berdarah adalah 21.6:1. Indeks Moran menunjukkan kes denggi berlaku dalam pengelompokan dengan skor Z adalah 16.384 (p=0.000). Analisis ANN dengan 0.264 (p= 0.000) dengan purata jarak insiden antara kes denggi di dalam kawasan kejiranan adalah 55 m. Anggaran kepadatan Kernel menunjukkan lokasi kawasan panas kes denggi tertumpu di Nilai dan Ampangan. Analisis reruang masa dengan purata nilai tertinggi indeks kekerapan, jangka masa dan intensiti masing-masing melebihi 0.023, 0.614 dan 0.657 di kawasan berisiko tinggi denggi di Nilai, Seremban dan Ampangan. Pengawalan denggi perlu diberi tumpuan kepada kawasan berisiko tinggi ini.
Matched MeSH terms: Geographic Information Systems
Analysis of relationship between sea surface temperature (SST) and Chlorophyll-a (chl-a) improves our understanding on the variability and productivity of the marine environment, which is important for exploring fishery resources. Monthly level 3 and daily level 1 images of Moderate Resolution Imaging Spectroradiometer Satellite (MODIS) derived SST and chl-a from July 2002 to June 2011 around the archipelagic waters of Spermonde Indonesia were used to investigate the relationship between SST and chl-a and to forecast the potential fishing ground of Rastrelliger kanagurta. The results indicated that there was positive correlation between SST and chl-a (R=0.3, p<0.05). Positive correlation was also found between SST and chl-a with the catch of R. kanagurta (R=0.7, p<0.05). The potential fishing grounds of R. kanagurta were found located along the coast (at accuracy of 76.9%). This study indicated that, with the integration of remote sensing technology, statistical modeling and geographic information systems (GIS) technique were able to determine the relationship between SST and chl-a and also able to forecast aggregation of R. kanagurta. This may contribute in decision making and reducing search hunting time and cost in fishing activities.
Matched MeSH terms: Geographic Information Systems
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*
Kejadian kebakaran hutan yang memberikan implikasi negatif terhadap ekosistem hutan, kepelbagaian biologi, kualiti udara dan struktur tanah dapat dikurangkan melalui sistem pengurusan bencana yang berkesan. Mekanisme pengurusan bencana dapat dibangunkan melalui sistem amaran awal yang tepat serta sistem penyampaian maklumat yang cekap. Penyelidikan ini cuba memberi tumpuan kepada pemetaan potensi kebakaran hutan serta penyampaian maklumat kepada
pengguna melalui aplikasi WebGIS. Teknologi georuang dan permodelan matematik digunakan bagi mengenal pasti, mengelas serta memetakan kawasan hutan yang berpotensi untuk terbakar. Permodelan model proses analitik hierarki (AHP) serta teknologi georuang yang merangkumi penderiaan jauh, sistem maklumat geografi (GIS) dan pengumpulan data lapangan secara digital telah digunakan untuk negeri Selangor. AHP adalah suatu teknik yang dapat memodel sesuatu
keputusan yang meliputi objektif menyeluruh, dalam kajian ini untuk mencari kawasan yang berpotensi berlakunya kebakaran hutan. Tiga kriteria iaitu bahan bakar, bentuk topografi dan faktor manusia telah dipilih untuk membina satu reka bentuk hierarki berstruktur yang setiapnya diberikan pemberat. Kemudian hierarki ini dianalisis melalui satu siri perbandingan berpasangan yang diproses secara matematik dan keutamaan diberikan kepada kedudukan yang tinggi untuk mencapai hasil sumbangan pakar yang terlibat secara langsung dengan operasi pemadaman kebakaran hutan
yang terdiri daripada pegawai Jabatan Bomba dan Penyelamat Malaysia juga dinilai dalam model ini. Hasil kajian mendapati 65% daripada keseluruhan Selangor berpotensi rendah untuk terbakar sementara kawasan seluas 32.83 km persegi iaitu di Bestari Jaya, Ulu Tinggi dan Kuala Langat berpotensi melampau terbakar. Paparan maklumat melalui aplikasi WebGIS ini merupakan satu pendekatan terbaik bagi membantu proses membuat keputusan pada tahap keyakinan yang tinggi dan hampir menyamai keadaan sebenar. Agensi yang terlibat dalam pengurusan bencana
seperti Jawatankuasa Pengurusan dan Bantuan Bencana (JPBB) Daerah, Negeri dan Pusat serta Jabatan Bomba dan Penyelamat Malaysia dapat menggunakan hasil akhir kajian ini sebagai persediaan menghadapi ancaman kebakaran hutan pada masa akan datang.
Matched MeSH terms: Geographic Information Systems
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
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
Hand, foot and mouth disease (HFMD) is endemic in Sarawak, Malaysia. In this study, a geographical information system (GIS) was used to investigate the relationship between the reported HFMD cases and the spatial patterns in 11 districts of Sarawak from 2006 to 2012. Within this 7-years period, the highest number of reported HFMD cases occurred in 2006, followed by 2012, 2008, 2009, 2007, 2010 and 2011, in descending order. However, while there was no significant distribution pattern or clustering in the first part of the study period (2006 to 2011) based on Moran's I statistic, spatial autocorrelation (P = 0.068) was observed in 2012.
Matched MeSH terms: Geographic Information Systems