Displaying publications 101 - 120 of 210 in total

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  1. Determination of potential fishing grounds of Rastrelliger kanagurta using satellite remote sensing and GIS Technique
    Suhartono Nurdin, Muzzneena Ahmad Mustapha, Tukimat Lihan, Mazlan Abd Ghaffar
    Sains Malaysiana, 2015;44:225-232.
    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
  2. Environmental planning strategies for optimum solid waste landfill siting
    Sumiani Y, Onn C, Mohd Din M, Wan Jaafar W
    Sains Malaysiana, 2009;38.
    The use of environmental planning tools for optimum solid waste landfill siting taking into account all environmental implications was carried out by applying Life Cycle Analysis (LCA) to enhance the research information obtained from initial analysis using Geographical Information Systems (GIS). The objective of this study is to identify the most eco-friendly landfill site by conducting a LCA analysis upon 5 potential GIS generated sites which incorporated eleven important criteria related to the social, environmental, and economical factors. The LCA analysis utilized the daily distance covered by collection trucks among the 5 selected landfill sites to generate inventory data on total energy usage for each landfill sites. The planning and selection of the potential sites were facilitated after conducting environmental impact analysis upon the inventory data which showed the least environmental impact.
    Matched MeSH terms: Geographic Information Systems
  3. Fulltext GIS based assessment on landslide hazard zonation: case study of Cameron Highlands – Gua Musang road Kelantan, Malaysia
    Mohamed M. GahGah, Juhari Mat Akhir, Abdul Ghani M. Rafek, Ibrahim Abdullah
    Sains Malaysiana, 2009;38(6):827-833.
    The aim of this study is to investigate the factors that cause landslides in the area along the new road between Cameron Highlands and Gua Musang. Landslide factors such as lineaments have been extracted from remote sensing data (Landsat TM image) using ERDAS software. A soil map has been produced using field work and laboratory analysis, and the lithology, roads, drainage pattern and rainfall have been digitized using ILWIS software together with the slope angle and elevation from the Digital Elevation Model (DEM). All these parameters, which are vital for landslide hazard assessment, have been integrated into the geographical information system (GIS) for further data processing. Weightage for these landslide relevant factors related to their influence in landslide occurrence using the heuristic method has been carried out. The results from this combination through a modified ‘index overlay with multi class maps’ model was used to produce a landslide hazard zonation map. Five classes of potential landslide hazard have been derived as the following: very low hazard zone 17.27%, low hazard zone 39.35%, medium hazard zone 25.1%, high hazard zone 15.35% and very high hazard zone 2.93%. The results from this work have been checked through the landslide inventory using available aerial photos interpretation and field work, and show that the slope and elevation have the most direct affect on landslide occurrence.
    Matched MeSH terms: Geographic Information Systems
  4. Spatial analysis of environmental factors influencing typhoid endemicity in Kelantan, Malaysia
    Shamsul Azhar Shah, Suzuki H, Mohd Rohaizat Hassan, Saito R, Nazarudin Safian, Shaharudin Idrus
    Sains Malaysiana, 2012;41:911-919.
    The determination of the high-risk area and clusters of typhoid cases is critical in typhoid control. The purpose of this study was to identify and describe the epidemiology and spatial distribution of typhoid in four selected districts in Kelantan using GIS (geographical information system). A total of 1215 (99%) of the cases were coordinated with GPS (global positioning system) and mapping was done using ArcGIS 9.2. Spatial analysis was performed to determine the cluster and high-risk area of typhoid. Results showed that typhoid incidence was not associated with race and sex. Most affected were from the age group of 5-14 followed by 15-24 year olds. Nine sub-districts were categorized as highly endemic. In addition typhoid has shown a significant tendency to cluster and a total of 22 hotspots were found in Kota Bharu, Bachok and Tumpat with a few sub districts identified as high risk for typhoid. No significant relationships between the treated water ratio and flood risk area were found with the cluster of cases. The cluster of typhoid cases in the endemic area did not appear to be related to environmental risk factors. Understanding the characteristics of these clusters would enable the prevention of typhoid disease in the future.
    Matched MeSH terms: Geographic Information Systems
  5. Geologic hazard risk assessment of slopeland villages in southern taiwan using remote sensing techniques
    Yang SR, Yeh YL
    Sains Malaysiana, 2015;44:1677-1683.
    Countering the dangers associated the present extreme climate not only requires continuous improvement of local disaster
    prevention engineering infrastructure but also needs an enhanced understanding of the causes of the disasters. This study
    investigates the geologic hazard risk of 53 slopeland villages in Pingtung county of southern Taiwan. First, remote sensing
    (RS) techniques were utilized to interpret environmental geology and geologic hazard zonation, including dip slope, fault,
    landslide and debris flow. GIS map overlay analysis was used to further identify the extent of the geologic hazard zonation.
    As a final step, field investigation is used to comprehend geologic, topographic conditions and the geologic hazard risk
    specific to each locality. Based on data analysis and field investigation results, this study successfully integrates RS, GIS
    and GPS techniques to construct a geologic hazard risk assessment method of slopeland village. The results of this study
    can be used to promote support for future disaster prevention and disaster mitigation efforts.
    Matched MeSH terms: Geographic Information Systems
  6. Evaluation of the spatial risk factors for high incidence of dengue fever and dengue hemorrhagic fever using GIS application
    Aziz Shafie
    Sains Malaysiana, 2011;40:1179-1186.
    In Malaysia, the incidence of Dengue Fever (DF) and Dengue Hemorrhagic Fever (DHF) have risen dramatically in the last twenty years. With the use of Geographical Information System an explanation for the spread and control of these diseases can be obtained. This study aims to develop a spatial modeling that can predict the risks for DF and DHF based on environmental factors such as physical surroundings, land use, rainfall, temperature and GIS application using logistic regression. A total of 16 variables were used in the process of spatial modeling development. At the significant level of 0.05, the results of logistic regression showed that only 10 out of 16 significant variables in the modeling process. The accuracy of the resulting model is 70.3%. A crucial feature of this study is a risk area map for incidence of DF and DHF in the study area. This study also highlights the application of spatial analysis in planning and implementing the process for the prevention and control activities of DF and DHF in Malaysia.
    Matched MeSH terms: Geographic Information Systems
  7. 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
  8. 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
  9. Construction of trace element in coal of china database management system: based on WebGIS
    Liu Yang, Xue Bai, Yinjie Hu, Qiqi Wang, Jun Deng
    Sains Malaysiana, 2017;46:2195-2204.
    The combination of geographic information system and mineral energy data management is helpful to promote the study of mineral energy and its ecological damage and environmental pollution caused by its development and utilization, which has important application value. The Trace Elements in Coal of China Database Management System (TECC) is established in this paper, applying the techniques of B/S three-layer structure, Oracle database, AJAX and WebGIS. TECC is the first database system which aims at managing the data of trace elements in coal in China. It includes data management and analysis module, document management module, trace elements in coal data maintenance module and authority management module. The data entry specification is put forward in the present study and the spatial data is included in TECC system. The system achieves the functions of data query, analysis, management, maintenance and map browsing, thematic map drawing as well as satellite video display, which lay the foundation for the analysis of large data of trace elements in coal. It is a practical platform for the acquisition, management, exchange and sharing of trace element research and geochemical research data of coal.
    Matched MeSH terms: Geographic Information Systems
  10. Demersal fish and shrimp abundance in relation to mangrove hydrogeomorphological metrics
    Jamizan A, Chong V
    Sains Malaysiana, 2017;46:9-19.
    Previous studies have found positive correlations between mangrove forest extent and fisheries yield but none of these univariate relationships provide a reliable estimate of yield from mangrove area. This study tests the hypothesis that the nursery ground value or natural production of fish and shrimps is related to the hydrogeomorphology settings of mangrove forests by using multivariate redundancy analysis (RDA). The hydrogeomorphological metrics of five mangrove forests imaged by satellite were measured using Geographical Information System (GIS). The RDA indicated that the metrics, including mangrove area, multiple waterways and creeks, mangrove-river interface, waterway surface area and sediment organic matter, influenced the diversity and abundance of fish and shrimps. Larger values of these metrics increase the abundance of economically important fish species of the families Lutjanidae, Haemulidae, Serranidae and economically-important penaeid shrimps. Sediment organic matter also significantly correlates with the distribution and abundance of fish that feed off the bottom such as the Leiognathidae, Clupeidae and Mullidae. Mangrove forests with combinations of large mangrove area, river surface area, high stream ordering and longest mangrove-river interface will provide greater role as nursery grounds for fish and shrimps.
    Matched MeSH terms: Geographic Information Systems
  11. 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
  12. Monitoring and assessment of urban growth patterns using spatio-temporal built-up area analysis
    Aburas MM, Ho YM, Ramli MF, Ash'aari ZH
    Environ Monit Assess, 2018 Feb 20;190(3):156.
    PMID: 29464400 DOI: 10.1007/s10661-018-6522-9
    The identification of spatio-temporal patterns of the urban growth phenomenon has become one of the most significant challenges in monitoring and assessing current and future trends of the urban growth issue. Therefore, spatio-temporal and quantitative techniques should be used hand in hand for a deeper understanding of various aspects of urban growth. The main purpose of this study is to monitor and assess the significant patterns of urban growth in Seremban using a spatio-temporal built-up area analysis. The concentric circles approach was used to measure the compactness and dispersion of built-up area by employing Shannon's Entropy method. The spatial directions approach was also utilised to measure the sustainability and speed of development, while the gradient approach was used to measure urban dynamics by employing landscape matrices. The overall results confirm that urban growth in Seremban is dispersed, unbalanced and unsustainable with a rapid speed of regional development. The main contribution of using existing methods with other methods is to provide several spatial and statistical dimensions that can help researchers, decision makers and local authorities understand the trend of growth and its patterns in order to take the appropriate decisions for future urban planning. For example, Shannon's Entropy findings indicate a high value of dispersion between the years 1990 and 2000 and from 2010 to 2016 with a growth rate of approximately 94 and 14%, respectively. Therefore, these results can help and support decision makers to implement alternative urban forms such as the compactness form to achieve an urban form that is more suitable and sustainable. The results of this study confirm the importance of using spatio-temporal built-up area and quantitative analysis to protect the sustainability of land use, as well as to improve the urban planning system via the effective monitoring and assessment of urban growth trends and patterns.
    Matched MeSH terms: Geographic Information Systems
  13. Unintended consequences of pharmacy information systems: A case study
    Rohani N, Yusof MM
    Int J Med Inform, 2023 Feb;170:104958.
    PMID: 36608630 DOI: 10.1016/j.ijmedinf.2022.104958
    BACKGROUND: Pharmacy information systems (PhIS) can cause medication errors that pharmacists may overlook due to their increased workload and lack of understanding of maintaining information quality. This study seeks to identify factors influencing unintended consequences of PhIS and how they affect the information quality, which can pose a risk to patient safety.

    MATERIALS AND METHODS: This qualitative, explanatory case study evaluated PhIS in ambulatory pharmacies in a hospital and a clinic. Data were collected through observations, interviews, and document analysis. We applied the socio-technical interactive analysis (ISTA) framework to investigate the socio-technical interactions of pharmacy information systems that lead to unintended consequences. We then adopted the human-organization-process-technology-fit (HOPT-fit) framework to identify their contributing and dominant factors, misfits, and mitigation measures.

    RESULTS: We identified 28 unintended consequences of PhIS, their key contributing factors, and their interrelations with the systems. The primary causes of unintended consequences include system rigidity and complexity, unclear knowledge, understanding, skills, and purpose of using the system, use of hybrid paper and electronic documentation, unclear and confusing transitions, additions and duplication of tasks and roles in the workflow, and time pressure, causing cognitive overload and workarounds. Recommended mitigating mechanisms include human factor principles in system design, data quality improvement for PhIS in terms of effective use of workspace, training, PhIS master data management, and communication by standardizing workarounds.

    CONCLUSION: Threats to information quality emerge in PhIS because of its poor design, a failure to coordinate its functions and clinical tasks, and pharmacists' lack of understanding of the system use. Therefore, safe system design, fostering awareness in maintaining the information quality of PhIS and cultivating its safe use in organizations is essential to ensure patient safety. The proposed evaluation approach facilitates the evaluator to identify complex socio-technical interactions and unintended consequences factors, impact, and mitigation mechanisms.

    Matched MeSH terms: Information Systems
  14. GIS-based air quality modelling: spatial prediction of PM10 for Selangor State, Malaysia using machine learning algorithms
    Tella A, Balogun AL
    Environ Sci Pollut Res Int, 2022 Dec;29(57):86109-86125.
    PMID: 34533750 DOI: 10.1007/s11356-021-16150-0
    Rapid urbanization has caused severe deterioration of air quality globally, leading to increased hospitalization and premature deaths. Therefore, accurate prediction of air quality is crucial for mitigation planning to support urban sustainability and resilience. Although some studies have predicted air pollutants such as particulate matter (PM) using machine learning algorithms (MLAs), there is a paucity of studies on spatial hazard assessment with respect to the air quality index (AQI). Incorporating PM in AQI studies is crucial because of its easily inhalable micro-size which has adverse impacts on ecology, environment, and human health. Accurate and timely prediction of the air quality index can ensure adequate intervention to aid air quality management. Therefore, this study undertakes a spatial hazard assessment of the air quality index using particulate matter with a diameter of 10 μm or lesser (PM10) in Selangor, Malaysia, by developing four machine learning models: eXtreme Gradient Boosting (XGBoost), random forest (RF), K-nearest neighbour (KNN), and Naive Bayes (NB). Spatially processed data such as NDVI, SAVI, BU, LST, Ws, slope, elevation, and road density was used for the modelling. The model was trained with 70% of the dataset, while 30% was used for cross-validation. Results showed that XGBoost has the highest overall accuracy and precision of 0.989 and 0.995, followed by random forest (0.989, 0.993), K-nearest neighbour (0.987, 0.984), and Naive Bayes (0.917, 0.922), respectively. The spatial air quality maps were generated by integrating the geographical information system (GIS) with the four MLAs, which correlated with Malaysia's air pollution index. The maps indicate that air quality in Selangor is satisfactory and posed no threats to health. Nevertheless, the two algorithms with the best performance (XGBoost and RF) indicate that a high percentage of the air quality is moderate. The study concludes that successful air pollution management policies such as green infrastructure practice, improvement of energy efficiency, and restrictions on heavy-duty vehicles can be adopted in Selangor and other Southeast Asian cities to prevent deterioration of air quality in the future.
    Matched MeSH terms: Geographic Information Systems
  15. Fulltext Application of medical information system to identify dengue outbreak factors: Insights from a hyperendemic city in Malaysia
    Keat-Chuan Ng C, Linus-Lojikip S, Mohamed K, Hss AS
    Int J Med Inform, 2023 Sep;177:105162.
    PMID: 37549500 DOI: 10.1016/j.ijmedinf.2023.105162
    BACKGROUND: Dengue is widespread globally, but it is more severe in hyperendemic regions where the virus, its vectors, and its human hosts naturally occur. The problem is particularly acute in cities, where outbreaks affect a large human population living in a wide array of socio-environmental conditions. Controlling outbreaks will rely largely on systematic data collection and analysis approaches to uncover nuances on a city-by-city basis due to the diversity of factors.

    OBJECTIVE: The main objective of this study is to consolidate and analyse the dengue case dataset amassed by the e-Dengue web-based information system, developed by the Ministry of Health Malaysia, to improve our epidemiological understanding.

    METHODS: We retrieved data from the e-Dengue system and integrated a total of 18,812 cases from 2012 to 2019 (8 years) with meteorological data, geoinformatics techniques, and socio-environmental observations to identify plausible factors that could have caused dengue outbreaks in Ipoh, a hyperendemic city in Malaysia.

    RESULTS: The rainfall trend characterised by a linearity of R2 > 0.99, termed the "wet-dry steps", may be the unifying factor for triggering dengue outbreaks, though it is still a hypothesis that needs further validation. Successful mapping of the dengue "reservoir" contact zones and spill-over diffusion revealed socio-environmental factors that may be controlled through preventive measures. Age is another factor to consider, as the platelet and white blood cell counts in the "below 5" age group are much greater than in other age groups.

    CONCLUSIONS: Our work demonstrates the novelty of the e-Dengue system, which can identify outbreak factors at high resolution when integrated with non-medical fields. Besides dengue, the techniques and insights laid out in this paper are valuable, at large, for advancing control strategies for other mosquito-borne diseases such as malaria, chikungunya, and zika in other hyperendemic cities elsewhere globally.

    Matched MeSH terms: Information Systems
  16. Heterogeneity of generalized pustular psoriasis in multiethnic Johor Bahru, Malaysia
    Tsai TF
    Br J Dermatol, 2023 Sep 15;189(4):361-362.
    PMID: 37379585 DOI: 10.1093/bjd/ljad197
    Matched MeSH terms: Information Systems
  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. The process-based stand growth model Formix 3-Q applied in a GIS environment for growth and yield analysis in a tropical rain forest
    Ditzer T, Glauner R, Förster M, Köhler P, Huth A
    Tree Physiol, 2000 Mar;20(5_6):367-381.
    PMID: 12651452
    Managing tropical rain forests is difficult because few long-term field data on forest growth and the impact of harvesting disturbance are available. Growth models may provide a valuable tool for managers of tropical forests, particularly if applied to the extended forest areas of up to 100,000 ha that typically constitute the so-called forest management units (FMUs). We used a stand growth model in a geographic information system (GIS) environment to simulate tropical rain forest growth at the FMU level. We applied the process-based rain forest growth model Formix 3-Q to the 55,000 ha Deramakot Forest Reserve (DFR) in Sabah, Malaysia. The FMU was considered to be composed of single and independent small-scale stands differing in site conditions and forest structure. Field data, which were analyzed with a GIS, comprised a terrestrial forest inventory, site and soil analyses (water, nutrients, slope), the interpretation of aerial photographs of the present vegetation and topographic maps. Different stand types were determined based on a classification of site quality (three classes), slopes (four classes), and present forest structure (four strata). The effects of site quality on tree allometry (height-diameter curve, biomass allometry, leaf area) and growth (increment size) are incorporated into Formix 3-Q. We derived allometric relations and growth factors for different site conditions from the field data. Climax forest structure at the stand level was shown to depend strongly on site conditions. Simulated successional pattern and climax structure were compared with field observations. Based on the current management plan for the DFR, harvesting scenarios were simulated for stands on different sites. The effects of harvesting guidelines on forest structure and the implications for sustainable forest management at Deramakot were analyzed. Based on the stand types and GIS analysis, we also simulated undisturbed regeneration of the logged-over forest in the DFR at the FMU level. The simulations predict slow recovery rates, and regeneration times far exceeding 100 years.
    Matched MeSH terms: Geographic Information Systems
  19. Fulltext Compact double-p slotted inset-fed microstrip patch antenna on high dielectric substrate
    Ahsan MR, Islam MT, Habib Ullah M, Mahadi WN, Latef TA
    ScientificWorldJournal, 2014;2014:909854.
    PMID: 25165750 DOI: 10.1155/2014/909854
    This paper presents a compact sized inset-fed rectangular microstrip patch antenna embedded with double-P slots. The proposed antenna has been designed and fabricated on ceramic-PTFE composite material substrate of high dielectric constant value. The measurement results from the fabricated prototype of the antenna show -10 dB reflection coefficient bandwidths of 200 MHz and 300 MHz with center resonant frequency of 1.5 GHz and 4 GHz, respectively. The fabricated antenna has attained gains of 3.52 dBi with 81% radiation efficiency and 5.72 dBi with 87% radiation efficiency for lower band and upper band, respectively. The measured E- and H-plane radiation patterns are also presented for better understanding. Good agreement between the simulation and measurement results and consistent radiation patterns make the proposed antenna suitable for GPS and C-band applications.
    Matched MeSH terms: Geographic Information Systems/instrumentation*
  20. Fulltext A novel vehicle stationary detection utilizing map matching and IMU sensors
    Amin MS, Reaz MB, Nasir SS, Bhuiyan MA, Ali MA
    ScientificWorldJournal, 2014;2014:597180.
    PMID: 25276855 DOI: 10.1155/2014/597180
    Precise navigation is a vital need for many modern vehicular applications. The global positioning system (GPS) cannot provide continuous navigation information in urban areas. The widely used inertial navigation system (INS) can provide full vehicle state at high rates. However, the accuracy diverges quickly in low cost microelectromechanical systems (MEMS) based INS due to bias, drift, noise, and other errors. These errors can be corrected in a stationary state. But detecting stationary state is a challenging task. A novel stationary state detection technique from the variation of acceleration, heading, and pitch and roll of an attitude heading reference system (AHRS) built from the inertial measurement unit (IMU) sensors is proposed. Besides, the map matching (MM) algorithm detects the intersections where the vehicle is likely to stop. Combining these two results, the stationary state is detected with a smaller timing window of 3 s. A longer timing window of 5 s is used when the stationary state is detected only from the AHRS. The experimental results show that the stationary state is correctly identified and the position error is reduced to 90% and outperforms previously reported work. The proposed algorithm would help to reduce INS errors and enhance the performance of the navigation system.
    Matched MeSH terms: Geographic Information Systems/standards*
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