bluuebunny/crossref_metadata_2025 huggingface dataset:
EFFECTS OF OCEAN TIDE MODELS ON GNSS-ESTIMATED ZTD AND PWV IN TURKEY
Authors: Gurbuz G. , Jin S. , Mekik C.
Published: December 2015

Abstract. Global Navigation Satellite System (GNSS) observations can precisely estimate the total zenith tropospheric delay (ZTD) and precipitable water vapour (PWV) for weather prediction and atmospheric research as a continuous and all-weather technique. However, apart from GNSS technique itself, estimations of ZTD and PWV are subject to effects of geophysical models with large uncertainties, particularly imprecise ocean tide models in Turkey. In this paper, GNSS data from Jan. 1st to Dec. 31st of 2014 are processed at 4 co-located GNSS stations (GISM, DIYB, GANM, and ADAN) with radiosonde from Turkish Met-Office along with several nearby IGS stations. The GAMIT/GLOBK software has been used to process GNSS data of 30-second sample using the Vienna Mapping Function and 10° elevation cut-off angle. Also tidal and non-tidal atmospheric pressure loadings (ATML) at the observation level are also applied in GAMIT/GLOBK. Several widely used ocean tide models are used to evaluate their effects on GNSS-estimated ZTD and PWV estimation, such as IERS recommended FES2004, NAO99b from a barotropic hydrodynamic model, CSR4.0 obtained from TOPEX/Poseidon altimetry with the model FES94.1 as the reference model and GOT00 which is again long wavelength adjustments of FES94.1 using TOPEX/Poseidon data at 0.5 by 0.5 degree grid. The ZTD and PWV computed from radiosonde profile observations are regarded as reference values for the comparison and validation. In the processing phase, five different strategies are taken without ocean tide model and with four aforementioned ocean tide models, respectively, which are used to evaluate ocean tide models effects on GNSS-estimated ZTD and PWV estimation through comparing with co-located Radiosonde. Results showed that ocean tide models have greatly affected the estimation of the ZTD in centimeter level and thus the precipitable water vapour in millimeter level, respectively at stations near coasts. The ocean tide model FES2004 that is the product of assimilation of the altimetric data of ERS2, TOPEX/POSEIDON and the data of a global tide gauge network, gave the most accurate results when compared to radiosonde with ±1.99 mm in PWV at stations near coastline. While other ocean tides models agree each other at millimeter level in PWV. However, at inland GNSS stations, ocean tide models have less effects on GNSS-estimated ZTD and PWV, e.g., with ±1.0 mm in ZTD and ±0.1 mm in PWV.
INCORPOARATION OF GEOSENSOR NETWORKS INTO INTERNET OF THINGS FOR ENVIRONMENTAL MONITORING
Authors: Habibi R. , Alesheikh A. A.
Published: December 2015

Abstract. Thanks to the recent advances of miniaturization and the falling costs for sensors and also communication technologies, Internet specially, the number of internet-connected things growth tremendously. Moreover, geosensors with capability of generating high spatial and temporal resolution data, measuring a vast diversity of environmental data and automated operations provide powerful abilities to environmental monitoring tasks. Geosensor nodes are intuitively heterogeneous in terms of the hardware capabilities and communication protocols to take part in the Internet of Things scenarios. Therefore, ensuring interoperability is an important step. With this respect, the focus of this paper is particularly on incorporation of geosensor networks into Internet of things through an architecture for monitoring real-time environmental data with use of OGC Sensor Web Enablement standards. This approach and its applicability is discussed in the context of an air pollution monitoring scenario.
PRECISE 3D GEO-LOCATION OF UAV IMAGES USING GEO-REFERENCED DATA
Authors: Hamidi M. , Samadzadegan F.
Published: December 2015

Abstract. In most of UAV applications it is essential to determine the exterior orientation of on-board sensors and precise ground locations of images acquired by them. This paper presents a precise methodology for 3D geo-location of UAV images using geo-referenced data. The fundamental concept behind this geo-location process is using database matching technique for refining the coarse initial attitude and position parameters of the camera derived from the navigation data. These refined exterior orientation parameters are then used for geo-locating entire image frame using rigorous collinearity model in a backward scheme. A forwards geo-locating procedure also is proposed based on a ray-DSM intersection method for the cases where ground location of specific image targets (and not the entire frame) is required. Experimental results demonstrated the potential of the proposed method in accurate geo-location of UAV images. Applying this method, an RMSE of about 14 m in horizontal and 3D positions has been obtained.
AN EFFECTIVE HYBRID SUPPORT VECTOR REGRESSION WITH CHAOS-EMBEDDED BIOGEOGRAPHY-BASED OPTIMIZATION STRATEGY FOR PREDICTION OF EARTHQUAKE-TRIGGERED SLOPE DEFORMATIONS
Authors: Heidari A. A. , Mirvahabi S. S. , Homayouni S.
Published: December 2015

Abstract. Earthquake can pose earth-shattering health hazards to the natural slops and land infrastructures. One of the chief consequences of the earthquakes can be land sliding, which is instigated by durable shaking. In this research, an efficient procedure is proposed to assist the prediction of earthquake-originated slope displacements (EIDS). New hybrid SVM-CBBO strategy is implemented to predict the EIDS. For this purpose, first, chaos paradigm is combined with initialization of BBO to enhance the diversification and intensification capacity of the conventional BBO optimizer. Then, chaotic BBO is developed as the searching scheme to investigate the best values of SVR parameters. In this paper, it will be confirmed that how the new computing approach is effective in prediction of EIDS. The outcomes affirm that the SVR-BBO strategy with chaos can be employed effectively as a predicting tool for evaluating the EIDS.
OBCHS: AN EFFECTIVE HARMONY SEARCH ALGORITHM WITH OPPOSITIONBASED CHAOS-ENHANCED INITIALIZATION FOR SOLVING UNCAPACITATED FACILITY LOCATION PROBLEMS
Authors: Heidari A. A. , Kazemizade O. , Abbaspour R. A.
Published: December 2015

Abstract. In this paper, a continuous harmony search (HS) approach is investigated for tackling the Uncapacitated Facility Location (UFL) task. This article proposes an efficient modified HS-based optimizer to improve the performance of HS on complex spatial tasks like UFL problems. For this aim, opposition-based learning (OBL) and chaotic patterns are utilized. The proposed technique is examined against several UFL benchmark challenges in specialized literature. Then, the modified HS is substantiated in detail and compared to the basic HS and some other methods. The results showed that new opposition-based chaotic HS (OBCHS) algorithm not only can exploit better solutions competently but it is able to outperform HS in solving UFL problems.
PRICISE TARGET GEOLOCATION BASED ON INTEGERATION OF THERMAL VIDEO IMAGERY AND RTK GPS IN UAVS
Authors: Hosseinpoor H. R. , Samadzadegan F. , Dadras Javan F.
Published: December 2015

Abstract. There are an increasingly large number of uses for Unmanned Aerial Vehicles (UAVs) from surveillance, mapping and target geolocation. However, most of commercial UAVs are equipped with low-cost navigation sensors such as C/A code GPS and a low-cost IMU on board, allowing a positioning accuracy of 5 to 10 meters. This low accuracy which implicates that it cannot be used in applications that require high precision data on cm-level. This paper presents a precise process for geolocation of ground targets based on thermal video imagery acquired by small UAV equipped with RTK GPS. The geolocation data is filtered using a linear Kalman filter, which provides a smoothed estimate of target location and target velocity. The accurate geo-locating of targets during image acquisition is conducted via traditional photogrammetric bundle adjustment equations using accurate exterior parameters achieved by on board IMU and RTK GPS sensors and Kalman filtering and interior orientation parameters of thermal camera from pre-flight laboratory calibration process.
EVALUATION OF SPATIAL AND TEMPORAL DISTRIBUTION CHANGES OF LST USING LANDSAT IMAGES (CASE STUDY:TEHRAN)
Authors: Kachar H. , Vafsian A. R. , Modiri M. , Enayati H. , Safdari Nezhad A. R.
Published: December 2015

Abstract. In traditional approach, the land surface temperature (LST) is estimated by the permanent or portable ground-based weather stations. Due to the lack of adequate distribution of weather stations, a uniform LST could not be achieved. Todays, With the development of remote sensing from space, satellite data offer the only possibility for measuring LST over the entire globe with sufficiently high temporal resolution and with complete spatially averaged rather than point values. the remote sensing imageries with relatively high spatial and temporal resolution are used as suitable tools to uniformly LST estimation. Time series, generated by remote sensed LST, provide a rich spatial-temporal infrastructure for heat island’s analysis. in this paper, a time series was generated by Landsat8 and Landsat7 satellite images to analysis the changes in the spatial and temporal distribution of the Tehran’s LST. In this process, The Normalized Difference Vegetation Index (NDVI) threshold method was applied to extract the LST; then the changes in spatial and temporal distribution of LST over the period 1999 to 2014 were evaluated by the statistical analysis. Finally, the achieved results show the very low temperature regions and the middle temperature regions were reduced by the rate of 0.54% and 5.67% respectively. On the other hand, the high temperature and the very high temperature regions were increased by 3.68% and 0.38% respectively. These results indicate an incremental procedure on the distribution of the hot regions in Tehran in this period. To quantitatively compare urban heat islands (UHI), an index called Urban Heat Island Ratio Index(URI) was calculated. It can reveal the intensity of the UHI within the urban area. The calculation of the index was based on the ratio of UHI area to urban area. The greater the index, the more intense the UHI was. Eventually, Considering URI between 1999 and 2014, an increasing about 0.03 was shown. The reasons responsible for the changes in spatio-temporal characteristics of the LST were the sharp increase in impervious surfaces, increased use of fossil fuels and greening policies.
A COMPARISON STUDY OF DIFFERENT MARKER SELECTION METHODS FOR SPECTRAL-SPATIAL CLASSIFICATION OF HYPERSPECTRAL IMAGES
Authors: Akbari D. , Safari A. R. , Homayouni S. , Khazai S.
Published: December 2015

Abstract. An effective approach based on the Minimum Spanning Forest (MSF), grown from automatically selected markers using Support Vector Machines (SVM), has been proposed for spectral-spatial classification of hyperspectral images by Tarabalka et al. This paper aims at improving this approach by using image segmentation to integrate the spatial information into marker selection process. In this study, the markers are extracted from the classification maps, obtained by both SVM and segmentation algorithms, and then are used to build the MSF. The segmentation algorithms are the watershed, expectation maximization (EM) and hierarchical clustering. These algorithms are used in parallel and independently to segment the image. Moreover, the pixels of each class, with the largest population in the classification map, are kept for each region of the segmentation map. Lastly, the most reliable classified pixels are chosen from among the exiting pixels as markers. Two benchmark urban hyperspectral datasets are used for evaluation: Washington DC Mall and Berlin. The results of our experiments indicate that, compared to the original MSF approach, the marker selection using segmentation algorithms leads in more accurate classification maps.
AUTOMATIC URBAN ILLEGAL BUILDING DETECTION USING MULTI-TEMPORAL SATELLITE IMAGES AND GEOSPATIAL INFORMATION SYSTEMS
Authors: Khalili Moghadam N. , Delavar M. R. , Hanachee P.
Published: December 2015

Abstract. With the unprecedented growth of urban population and urban development, we are faced with the growing trend of illegal building (IB) construction. Field visit, as the currently used method of IB detection, is time and man power consuming, in addition to its high cost. Therefore, an automatic IB detection is required. Acquiring multi-temporal satellite images and using image processing techniques for automatic change detection is one of the optimum methods which can be used in IB monitoring. In this research an automatic method of IB detection has been proposed. Two-temporal panchromatic satellite images of IRS-P5 of the study area in a part of Tehran, the city map and an updated spatial database of existing buildings were used to detect the suspected IBs. In the pre-processing step, the images were geometrically and radiometrically corrected. In the next step, the changed pixels were detected using K-means clustering technique because of its quickness and less user’s intervention required. Then, all the changed pixels of each building were identified and the change percentage of each building with the standard threshold of changes was compared to detect the buildings which are under construction. Finally, the IBs were detected by checking the municipality database. The unmatched constructed buildings with municipal database will be field checked to identify the IBs. The results show that out of 343 buildings appeared in the images; only 19 buildings were detected as under construction and three of them as unlicensed buildings. Furthermore, the overall accuracies of 83%, 79% and 75% were obtained for K-means change detection, detection of under construction buildings and IBs detection, respectively.
3D SURFACE GENERATION FROM AERIAL THERMAL IMAGERY
Authors: Khodaei B. , Samadzadegan F. , Dadras Javan F. , Hasani H.
Published: December 2015

Abstract. Aerial thermal imagery has been recently applied to quantitative analysis of several scenes. For the mapping purpose based on aerial thermal imagery, high accuracy photogrammetric process is necessary. However, due to low geometric resolution and low contrast of thermal imaging sensors, there are some challenges in precise 3D measurement of objects. In this paper the potential of thermal video in 3D surface generation is evaluated. In the pre-processing step, thermal camera is geometrically calibrated using a calibration grid based on emissivity differences between the background and the targets. Then, Digital Surface Model (DSM) generation from thermal video imagery is performed in four steps. Initially, frames are extracted from video, then tie points are generated by Scale-Invariant Feature Transform (SIFT) algorithm. Bundle adjustment is then applied and the camera position and orientation parameters are determined. Finally, multi-resolution dense image matching algorithm is used to create 3D point cloud of the scene. Potential of the proposed method is evaluated based on thermal imaging cover an industrial area. The thermal camera has 640×480 Uncooled Focal Plane Array (UFPA) sensor, equipped with a 25 mm lens which mounted in the Unmanned Aerial Vehicle (UAV). The obtained results show the comparable accuracy of 3D model generated based on thermal images with respect to DSM generated from visible images, however thermal based DSM is somehow smoother with lower level of texture. Comparing the generated DSM with the 9 measured GCPs in the area shows the Root Mean Square Error (RMSE) value is smaller than 5 decimetres in both X and Y directions and 1.6 meters for the Z direction.
REGISTRATION OF OPTICAL AND SAR SATELLITE IMAGES BASED ON GEOMETRIC FEATURE TEMPLATES
Authors: Merkle N. , Müller R. , Reinartz P.
Published: December 2015

Abstract. Image registration is required for different remote sensing applications, like change detection or image fusion. Since research studies have shown the outstanding absolute geometric accuracy of high resolution radar satellites images like TerraSAR-X, the importance of SAR images as source for geolocation enhancement has increased. Due to this fact, multi-sensor image to image registration of optical and SAR images can be used for the improvement of the absolute geometric processing and accuracy of optical images with TerraSAR-X as reference. In comparison to the common optical and SAR image registration methods the proposed method is a combination of intensity-based and feature-based approaches. The proposed method avoids the direct and often difficult detection of features from the SAR images. SAR-like templates are generated from features detected from the optical image. These templates are used for an intensity-based matching with the SAR image. The results of the matching process are ground control points, which are used for the estimation of translation parameters followed by a subpixel translation of the optical image. The proposed image registration method is tested for two pairs of TerraSAR-X and QuickBird images and one pair of TerraSAR-X andWorldView-2 images of a suburban area. The results show that with the proposed method the geometric accuracy of optical images can be enhanced.
THE ASSESSMENT OF ORTHOPHOTO QUALITY WITH RESPECT TO THE STRUCTURE OF DIGITAL ELEVATION MODEL
Authors: Modiri M. , Enayati H. , Ebrahimikia M.
Published: December 2015

Abstract. Orthophoto is an image which is being corrected geometrically so each object has to be situated on the corrected place consequently. Choosing the best DEM structure with respect to the area topographic is the most challenge which has more important role when dealing with rough surfaces displacements in duration of orthophoto procedures. The Lower DEM resolution makes points density lower and makes the procedure faster but cause to decreasing the product precision in compare to choosing the other one. However if a fine resolution DEM cause to very delicate displacement corrections aside of the other benefits but it makes to appear some undesired visualized errors like as elongation error especially in an areas which are hidden with some obstacles and there are lacks of data in an imaging. For preventing of such error in DEM structure calculation and earning the most benefits, we found and execute some solutions. In other word we answered to this question that what DEM resolution is the best for orthophoto production. In the following we have done some tests. First a dense DEM of a topographic area calculated and edited accurately then its density was reduced in some steps gradually. At each stage the root mean square error (RMSE) of interpolated heights of points which were laid in the distance between the corresponding DEMs pixels has been calculated respectively. Two interpolation methods (Nearest neighbour and Bilinear interpolation) have been used in this test. Decreasing the DEMs density or increasing the pixel size made the amounts of errors high and the rate of this changing dependent on the kind of topography directly. So we divided the area into some reasonable topographic classes then calculated our results for each class separately. The result of each strategy compared with each other and presented in both numerical tables and some illustrated images. Because of the relation between horizontal precision of orthophotos which are existed in the standard producing instruction and the accuracy of the DEM which are mostly related to its density, the suitable resolution for producing different scale orthophotos at each kind of topographic class have been calculated from mentioned methods consequences and shown as a final result.
SPATIAL AND STATISTICAL ANALYSIS OF LEPTOSPIROSIS IN GUILAN PROVINCE, IRAN
Authors: Mohammadi Nia A. , Alimohammadi A. , Habibi R. , Shirzadi M. R.
Published: December 2015

Abstract. The most underdiagnosed water-borne bacterial zoonosis in the world is Leptospirosis which especially impacts tropical and humid regions. According to World Health Organization (WHO), the number of human cases is not known precisely. Available reports showed that worldwide incidences vary from 0.1-1 per 100 000 per year in temperate climates to 10-100 per 100 000 in the humid tropics. Pathogenic bacteria that is spread by the urines of rats is the main reason of water and soil infections. Rice field farmers who are in contact with infected water or soil, contain the most burden of leptospirosis prevalence. In recent years, this zoonotic disease have been occurred in north of Iran endemically. Guilan as the second rice production province (average=750 000 000 Kg, 40% of country production) after Mazandaran, has one of the most rural population (Male=487 679, Female=496 022) and rice workers (47 621 insured workers) among Iran provinces. The main objectives of this study were to analyse yearly spatial distribution and the possible spatial clusters of leptospirosis to better understand epidemiological aspects of them in the province. Survey was performed during the period of 2009–2013 at rural district level throughout the study area. Global clustering methods including the average nearest neighbour distance, Moran’s I and General G indices were utilized to investigate the annual spatial distribution of diseases. At the end, significant spatial clusters have been detected with the objective of informing priority areas for public health planning and resource allocation.
A SURVEY OF SMART ELECTRICAL BOARDS IN UBIQUITOUS SENSOR NETWORKS FOR GEOMATICS APPLICATIONS
Authors: Moosavi S. M. R. , Sadeghi-Niaraki A.
Published: December 2015

Abstract. Nowadays more advanced sensor networks in various fields are developed. There are lots of online sensors spreading around the world. Sensor networks have been used in Geospatial Information Systems (GIS) since sensor networks have expanded. Health monitoring, environmental monitoring, traffic monitoring, etc, are the examples of its applications in Geomatics. Sensor network is an infrastructure comprised of sensing (measuring), computing, and communication elements that gives an administrator the ability to instrument, observe, and react to events and phenomena in a specified environment. This paper describes about development boards which can be used in sensor networks and their applications in Geomatics and their role in wireless sensor networks and also a comparison between various types of boards. Boards that are discussed in this paper are Arduino, Raspberry Pi, Beagle board, Cubieboard. The Boards because of their great potential are also known as single board computers. This paper is organized in four phases: First, Reviewing on ubiquitous computing and sensor networks. Second, introducing of some electrical boards. Then, defining some criterions for comparison. Finally, comparing the Ubiquitous boards.
A NOVEL IHS-GA FUSION METHOD BASED ON ENHANCEMENT VEGETATED AREA
Authors: Niazi S. , Mokhtarzade M. , Saeedzadeh F.
Published: December 2015

Abstract. Pan sharpening methods aim to produce a more informative image containing the positive aspects of both source images. However, the pan sharpening process usually introduces some spectral and spatial distortions in the resulting fused image. The amount of these distortions varies highly depending on the pan sharpening technique as well as the type of data. Among the existing pan sharpening methods, the Intensity-Hue-Saturation (IHS) technique is the most widely used for its efficiency and high spatial resolution. When the IHS method is used for IKONOS or QuickBird imagery, there is a significant color distortion which is mainly due to the wavelengths range of the panchromatic image. Regarding the fact that in the green vegetated regions panchromatic gray values are much larger than the gray values of intensity image. A novel method is proposed which spatially adjusts the intensity image in vegetated areas. To do so the normalized difference vegetation index (NDVI) is used to identify vegetation areas where the green band is enhanced according to the red and NIR bands. In this way an intensity image is obtained in which the gray values are comparable to the panchromatic image. Beside the genetic optimization algorithm is used to find the optimum weight parameters in order to gain the best intensity image. Visual and statistical analysis proved the efficiency of the proposed method as it significantly improved the fusion quality in comparison to conventional IHS technique. The accuracy of the proposed pan sharpening technique was also evaluated in terms of different spatial and spectral metrics. In this study, 7 metrics (Correlation Coefficient, ERGAS, RASE, RMSE, SAM, SID and Spatial Coefficient) have been used in order to determine the quality of the pan-sharpened images. Experiments were conducted on two different data sets obtained by two different imaging sensors, IKONOS and QuickBird. The result of this showed that the evaluation metrics are more promising for our fused image in comparison to other pan sharpening methods.
USING SATELLITE OBSERVATION FOR EARLY WARNING OF CONVECTIVE STORM IN TEHRAN
Authors: Owlad E.
Published: December 2015

Abstract. Severe convective storms are responsible for large amount of damage each year around the world. They form an important part of the climate system by redistributing heat, moisture, and trace gases, as well as producing large quantities of precipitation. As these extreme and rare events are in mesoscale there is many uncertainty in predicting them and we can’t rely on just models. On the other hand, remote sensing has a large application in Meteorology and near real time weather forecasting, especially in rare and extreme events like convective storms that might be difficult to predict with atmospheric models. On second of June 2014, near 12UTC a sudden and strong convective storm occurred in Tehran province that was not predicted, and caused economic and human losses. In This research we used satellite observations along with synoptic station measurements to predict and monitor this storm. Results from MODIS data show an increase in the amount of cloudiness and also aerosol optical depth and sudden decrease in cloud top temperature few hours before the storm occurs. EUMETSAT images show the governing of convection before the storm occurs. With combining the observation data that shows Lake of humidity and high temperature in low levels with satellite data that reveals instability in high levels that together caused this convective, we could track the storm and decrease the large amount of damage.
MOVING OBJECTS TRAJECTOTY PREDICTION BASED ON ARTIFICIAL NEURAL NETWORK APPROXIMATOR BY CONSIDERING INSTANTANEOUS REACTION TIME, CASE STUDY: CAR FOLLOWING
Authors: Poor Arab Moghadam M. , Pahlavani P.
Published: December 2015

Abstract. Car following models as well-known moving objects trajectory problems have been used for more than half a century in all traffic simulation software for describing driving behaviour in traffic flows. However, previous empirical studies and modeling about car following behavior had some important limitations. One of the main and clear defects of the introduced models was the very large number of parameters that made their calibration very time-consuming and costly. Also, any change in these parameters, even slight ones, severely disrupted the output. In this study, an artificial neural network approximator was used to introduce a trajectory model for vehicle movements. In this regard, the Levenberg-Marquardt back propagation function and the hyperbolic tangent sigmoid function were employed as the training and the transfer functions, respectively. One of the important aspects in identifying driver behavior is the reaction time. This parameter shows the period between the time the driver recognizes a stimulus and the time a suitable response is shown to that stimulus. In this paper, the actual data on car following from the NGSIM project was used to determine the performance of the proposed model. This dataset was used for the purpose of expanding behavioral algorithm in micro simulation. Sixty percent of the data was entered into the designed artificial neural network approximator as the training data, twenty percent as the testing data, and twenty percent as the evaluation data. A statistical and a micro simulation method were employed to show the accuracy of the proposed model. Moreover, the two popular Gipps and Helly models were implemented. Finally, it was shown that the accuracy of the proposed model was much higher - and its computational costs were lower - than those of other models when calibration operations were not performed on these models. Therefore, the proposed model can be used for displaying and predicting trajectories of moving objects being followed.
SEGMENTATION OF POLARIMETRIC SAR IMAGES USIG WAVELET TRANSFORMATION AND TEXTURE FEATURES
Authors: Rezaeian A. , Homayouni S. , Safari A.
Published: December 2015

Abstract. Polarimetric Synthetic Aperture Radar (PolSAR) sensors can collect useful observations from earth’s surfaces and phenomena for various remote sensing applications, such as land cover mapping, change and target detection. These data can be acquired without the limitations of weather conditions, sun illumination and dust particles. As result, SAR images, and in particular Polarimetric SAR (PolSAR) are powerful tools for various environmental applications. Unlike the optical images, SAR images suffer from the unavoidable speckle, which causes the segmentation of this data difficult. In this paper, we use the wavelet transformation for segmentation of PolSAR images. Our proposed method is based on the multi-resolution analysis of texture features is based on wavelet transformation. Here, we use the information of gray level value and the information of texture. First, we produce coherency or covariance matrices and then generate span image from them. In the next step of proposed method is texture feature extraction from sub-bands is generated from discrete wavelet transform (DWT). Finally, PolSAR image are segmented using clustering methods as fuzzy c-means (FCM) and k-means clustering. We have applied the proposed methodology to full polarimetric SAR images acquired by the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) L-band system, during July, in 2012 over an agricultural area in Winnipeg, Canada.
DEVELOPMENT OF NEUROMORPHIC SIFT OPERATOR WITH APPLICATION TO HIGH SPEED IMAGE MATCHING
Authors: Shankayi M. , Saadatseresht M. , Bitetto M. A. V.
Published: December 2015

Abstract. There was always a speed/accuracy challenge in photogrammetric mapping process, including feature detection and matching. Most of the researches have improved algorithm's speed with simplifications or software modifications which increase the accuracy of the image matching process. This research tries to improve speed without enhancing the accuracy of the same algorithm using Neuromorphic techniques. In this research we have developed a general design of a Neuromorphic ASIC to handle algorithms such as SIFT. We also have investigated neural assignment in each step of the SIFT algorithm. With a rough estimation based on delay of the used elements including MAC and comparator, we have estimated the resulting chip's performance for 3 scenarios, Full HD movie (Videogrammetry), 24 MP (UAV photogrammetry), and 88 MP image sequence. Our estimations led to approximate 3000 fps for Full HD movie, 250 fps for 24 MP image sequence and 68 fps for 88MP Ultracam image sequence which can be a huge improvement for current photogrammetric processing systems. We also estimated the power consumption of less than10 watts which is not comparable to current workflows.
REPRESENTATION OF GRADIENTS OF A SCALAR FIELD ON THE SPHERE USING A 2D FOURIER EXPRESSION
Authors: Sharifi M. A. , Ghobadi-Far K.
Published: December 2015

Abstract. Representation of data on the sphere is conventionally done using spherical harmonics. Making use of the Fourier series of the Legendre function in the SH representation results in a 2D Fourier expression. So far the 2D Fourier series representation on the sphere has been confined to a scalar field like geopotential or relief data. We show that if one views the 2D Fourier formulation as a representation in a rotated frame, instead of the original Earth-fixed frame, one can easily generalize the representation to any gradient of the scalar field. Indeed, the gradient and the scalar field itself are simply linked in the spectral domain using spectral transfers. We provide the spectral transfers of the first-, second- and third-order gradients of a scalar field in a local frame. Using three numerical examples based on gravity and geometrical quantities, we show the applicability of the presented formulation.
METHODS FOR GEOMETRIC DATA VALIDATION OF 3D CITY MODELS
Authors: Wagner D. , Alam N. , Wewetzer M. , Pries M. , Coors V.
Published: December 2015

Abstract. Geometric quality of 3D city models is crucial for data analysis and simulation tasks, which are part of modern applications of the data (e.g. potential heating energy consumption of city quarters, solar potential, etc.). Geometric quality in these contexts is however a different concept as it is for 2D maps. In the latter case, aspects such as positional or temporal accuracy and correctness represent typical quality metrics of the data. They are defined in ISO 19157 and should be mentioned as part of the metadata. 3D data has a far wider range of aspects which influence their quality, plus the idea of quality itself is application dependent. Thus, concepts for definition of quality are needed, including methods to validate these definitions. Quality on this sense means internal validation and detection of inconsistent or wrong geometry according to a predefined set of rules. A useful starting point would be to have correct geometry in accordance with ISO 19107. A valid solid should consist of planar faces which touch their neighbours exclusively in defined corner points and edges. No gaps between them are allowed, and the whole feature must be 2-manifold. In this paper, we present methods to validate common geometric requirements for building geometry. Different checks based on several algorithms have been implemented to validate a set of rules derived from the solid definition mentioned above (e.g. water tightness of the solid or planarity of its polygons), as they were developed for the software tool CityDoctor. The method of each check is specified, with a special focus on the discussion of tolerance values where they are necessary. The checks include polygon level checks to validate the correctness of each polygon, i.e. closeness of the bounding linear ring and planarity. On the solid level, which is only validated if the polygons have passed validation, correct polygon orientation is checked, after self-intersections outside of defined corner points and edges are detected, among additional criteria. Self-intersection might lead to different results, e.g. intersection points, lines or areas. Depending on the geometric constellation, they might represent gaps between bounding polygons of the solids, overlaps, or violations of the 2-manifoldness. Not least due to the floating point problem in digital numbers, tolerances must be considered in some algorithms, e.g. planarity and solid self-intersection. Effects of different tolerance values and their handling is discussed; recommendations for suitable values are given. The goal of the paper is to give a clear understanding of geometric validation in the context of 3D city models. This should also enable the data holder to get a better comprehension of the validation results and their consequences on the deployment fields of the validated data set.
INVISTIGATION ON CANOPY HEIGHT AND DENSITY DIFFERENTIATIONS IN THE MANAGED AND UNMANAGED FOREST STANDS USING LIDAR DATA (CASE STUDY: SHASTKALATEH FOREST, GORGAN)
Authors: Shataee Sh. , Mohammadi J.
Published: December 2015

Abstract. Forest management plans are interesting to keep the forest stand natural composite and structure after silvicultural and management treatments. In order to investigate on stand differences made by management treatments, comparing of these stands with unmanaged stands as natural forests is necessary. Aerial laser scanners are providing suitable 3D information to map the horizontal and vertical characteristics of forest structures. In this study, different of canopy height and canopy cover variances between managed and unmanaged forest stands as well as in two dominant forest types were investigated using Lidar data in Dr. Bahramnia forest, Northern Iran. The in-situ information was gathered from 308 circular plots by a random systematic sampling designs. The low lidar cloud point data were used to generate accurate DEM and DSM models and plot-based height statistics metrics and canopy cover characteristics. The significant analyses were done by independent T-test between two stands in same dominant forest types. Results showed that there are no significant differences between canopy cover mean in two stands as well as forest types. Result of statistically analysis on height characteristics showed that there are a decreasing the forest height and its variance in the managed forest compared to unmanaged stands. In addition, there is a significant difference between maximum, range, and mean heights of two stands in 99 percent confidence level. However, there is no significant difference between standard deviation and canopy height variance of managed and unmanged stands. These results showd that accomplished management treatments and cuttings could lead to reducing of height variances and converting multi-layers stands to two or single layers. Results are also showed that the canopy cover densities in the managed forest stands are changing from high dense cover to dense cover.
AN ONTOLOGY-BASED TOURISM RECOMMENDER SYSTEM BASED ON SPREADING ACTIVATION MODEL
Authors: Bahramian Z. , Ali Abbaspour R.
Published: December 2015

Abstract. A tourist has time and budget limitations; hence, he needs to select points of interest (POIs) optimally. Since the available information about POIs is overloading, it is difficult for a tourist to select the most appreciate ones considering preferences. In this paper, a new travel recommender system is proposed to overcome information overload problem. A recommender system (RS) evaluates the overwhelming number of POIs and provides personalized recommendations to users based on their preferences. A content-based recommendation system is proposed, which uses the information about the user’s preferences and POIs and calculates a degree of similarity between them. It selects POIs, which have highest similarity with the user’s preferences. The proposed content-based recommender system is enhanced using the ontological information about tourism domain to represent both the user profile and the recommendable POIs. The proposed ontology-based recommendation process is performed in three steps including: ontology-based content analyzer, ontology-based profile learner, and ontology-based filtering component. User’s feedback adapts the user’s preferences using Spreading Activation (SA) strategy. It shows the proposed recommender system is effective and improves the overall performance of the traditional content-based recommender systems.
Discipline-Specific Language Instruction for International Students in Introductory Economics
Authors: Nguyen Trien T. , Williams Julia , Trimarchi Angela
Published: December 2015

This paper explores student perceptions of the effects of pairing discipline-specific language instruction with the traditional method of course delivery in economics. Our research involved teaching content-based English as an additional language (EAL) tutorials to a small group of ten international students taking first-year introductory economics courses. These voluntary participants completed pre- and post-treatment assessments with exit interviews at the end of the project. Assessment results and interviews suggest that students perceive that discipline-specific language instruction such as our EAL tutorials assists in the development of increased content and language proficiency. They also believe that vocabulary development is one of the most critical activities to support these goals; reading skills are also important but require more time and commitment than students can afford to give. Despite the students’ interest in the project, their heavy class schedules prevented many from participating; our group was limited to ten students which precludes any assurance of statistical significance. In spite of the limitations, we believe that the project can still contribute valuable qualitative lessons to the literature of content-based language instruction in which the discipline of economics has not been well represented.
Cette communication explore la manière dont les étudiants perçoivent les effets du jumelage de l’enseignement de la langue spécifique à une discipline avec l’enseignement d’un cours d’économie selon la méthode traditionnelle d’enseignement. Notre recherche a porté sur l’enseignement en tutorat de l’anglais langue additionnelle (ALA) fondé sur le contenu à un petit groupe de dix étudiants internationaux inscrits dans des cours de première année d’introduction à l’économie. Ces participants bénévoles ont complété une évaluation avant et après le cours et ont été interviewés à la fin du projet. Les résultats de l’évaluation et les entrevues suggèrent que les étudiants ont le sentiment que l’enseignement de la langue spécifique à une discipline, tel que nos cours d’ALA en tutorat, les aident à développer une meilleure compréhension du contenu du cours et de la langue. Ils pensent également que l’acquisition du vocabulaire est l’une des activités les plus importantes pour réaliser ces objectifs. Les compétences en lecture sont également importantes mais requièrent davantage de temps et d’engagement que ce que les étudiants sont en mesure de fournir. Malgré l’intérêt des étudiants dans le projet, leur emploi du temps très chargé a empêché plusieurs d’entre eux d’y participer. Notre groupe a été limité à dix étudiants, ce qui écarte toute assurance de signification statistique. Malgré ces limites, nous croyons que ce projet peut malgré tout apporter une contribution qualitative appréciable à la documentation qui existe sur l’enseignement de la langue spécifique à une discipline dans laquelle l’économie n’a pas souvent été représentée.
2015 Annual Pathology Research Day Abstracts
Authors: HNS WURJ
Published: December 2015

2015 Annual Pathology Research Day Abstracts from 4th year undergraduate students from the Department of Pathology and Laboratory Medicine.
Providing Physical and Psychosocial Care on the Epilepsy Monitoring Unit
Authors: Lum Alysha
Published: December 2015

The Integrative Practicum (IP) is the final course for students in Western’s nursing program where we work alongside a registered nurse (referred to as a preceptor) and take on the full responsibilities of an independent practitioner. For my IP, I was placed on the Epilepsy Monitoring Unit (EMU) at University Hospital. During this time, one of the most critical areas of my growth was in delivering care that is sensitive to both physical and psychosocial needs. This article explores this learning experience in addition to providing a glimpse into the nature of nursing care on the EMU and with patients who have epilepsy.
The Impact of Environmental Management Plans on Firms’ Compliance with Governmental Regulations and Environmental Laws
Authors: Makelane Hlamulo Reply
Published: December 2015

Many developed and developing countries have enacted environmental laws and regulations to control water quality and the environment. However, human activities, such as agriculture, urban and industrial development, mining, and recreation, significantly alter the quality of natural environments and their potential use. The compliance of firms with environmental laws is of great concern to scientists, governments, and regulatory agencies. The presence of hazardous chemicals in water resources even in small amounts may cause massive environmental damage. Thus, governments pass environmental laws and regulations to monitor human activity and enforce compliance with environmental standards. This study investigates the potential to improve firms’ compliance with environmental standards by implementing an environmental management plan (EMP) within a public firm and a private firm in South Africa. EMP implementation is required to mitigate and manage environmental risk. This study asks the following research question: To what extent does EMP implementation enhance a firm’s compliance to environmental laws and regulations? Further, to what extent are the specific characteristics of a firm associated with various EMP categories? The study used methods of inspection, observation, impact assessment, implementation, and monitoring to answer the research question. In both firms under study, the results showed no compliance with environmental law during initial site inspection and impact assessment. However, the implementation of EMPs in both firms improved compliance with environmental laws to nearly one hundred percent. As a result, EMPs were successfully implemented and monitored, improving the firms’ compliance with environmental laws and reducing negative environmental impacts to an insignificant level.
3D-Printed PCL Scaffolds for the Cultivation of Mesenchymal Stem Cells
Authors: Steffens Daniela , Alvarenga Rezende Rodrigo , Santi Bruna , Alencar de Sena Pereira Frederico David , Inforçatti Neto Paulo , Lopes da Silva Jorge Vicente , Pranke Patricia
Published: December 2015

Introduction

Tissue engineering is a field which is currently under a great deal of investigation for the development and/or restoration of tissue and organs, through the combination of cell therapy with biomaterials. Rapid prototyping or additive manufacturing is a versatile technology which makes possible the fabrication of three dimensional (3D) structures from a wide range of materials with complex geometry and accuracy, such as scaffolds.

Aim

The aim of this study has been to investigate the interaction between mesenchymal stem cells with poly (ε-caprolactone) (PCL) biomaterials used for obtaining scaffolds through additive manufacturing.

Materials and Methods

Scanning electron microscopy, confocal microscopy and biological assays were performed to analyse the successful interaction between the cells and the biomaterials.

Results

As a result, the number of viable cells attached to the scaffolds was lower when compared to the control group; however, it was possible to observe cells in the scaffolds since day 1 of analysis, with regions of confluence after 21 days of seeding.

Conclusions

To conclude, these biomaterials are interesting if used as medical artifacts, principally in tissue with prolonged regeneration time and which requires 3D supports with good mechanical properties.
Songs from the Land of Eternal Summer: Beyond Duality in Japanese Brazilian Publication and Colonia Man'yôshû
Authors: Rivas Zelideth María
Published: December 2015

Upon arrival to Brazil in 1908, Japanese immigrants began creating a communal Japanese Brazilian narrative that acts as an alternative to Japanese and Brazilian histories and literatures. Pre-World War II immigrants, bound not only by their immigration experience but also by language, composed tanka poetry to capture the community's experiences vis-à-vis Japan and Brazil. These tanka were collected in the 1981 anthology Koronia man'yôshû 『コロニア万葉集』. In this article, I examine Japanese Brazilian communal formation through the publishing industry in Brazil and themes that the immigrants included in their anthology. I argue that as the community began to move beyond an image of itself as a “mini-Japan,” it produced alternative histories and narratives that influence both Brazilian and Japanese national literatures and histories, moving beyond a duality of identity rooted in both countries.