bluuebunny/crossref_metadata_2025 huggingface dataset:
On facing the God-question in a pastoral theology of compassion: From imperialistic omni-categories to theopaschitic pathos-categories
Authors: Louw Daniel J.
Published: December 2015

Many scholars in the 20th century warned against static, ontological and metaphysicalschemata of interpretation, stemming from Hellenistic thinking with its impact on God images in Christian reflection. Against the background of new spiritual and philosophica lphenomena like apatheism and anatheism, the question regarding the appropriateness o fexisting categories for God within the framework of pastoral theology surfaces. A paradigm shift from omni-categories to pathos-categories is proposed in order to deal with issues like human suffering, dignity and justice. In this regard, theopaschitic theology can play adecisive role in the reframing of existing static God-images stemming predominantly from the Roman-Greco world. The notion of a ‘sustainable God’ is introduced in order to reframe God’s compassionate presence (ta splanchna) in terms of a continuum of infinitive interventions (infiniscience and the pneumatology of to-be-with).Die dinamika van die God-vraagstuk in ’n pastorale teologie van medelye en omgee: Vanafimperialistiese omni-kategorieë na teopasgitiese patos-kategorieë. Navorsers het telkemale in die twintigste eeu teen die impak van statiese, ontologiese en metafisiese skemas van interpretasie gewaarsku. Teïstiese denke is grootliks deur Hellenistiese denkkategorieë bepaal. Teen die agtergrond van nuwe filosofiese verskynsels soos apateïsme en anateïsme en die invloed daarvan op die verskillende vorms van spiritualiteitsdenke, duik die vraag op na die toepaslikheid en relevansie van bestaande, geykte denkkategorië vir die Christelike verstaan van God. Die vraagstuk van lyding, menswaardigheid en geregtigheid stel nuwe eise aan ’n pastorale teologie wat met kontekstuele lewensvraagstukke erns maak. In die lig hiervan word ’n paradigmaskuif in teologisering, vanaf omni-kategorieë na patos-kategorieë voorgestel. Dit word beredeneer dat ’n teopasgitiese teologie ’n belangrike bydrae kan lewer om statiese Godskonsepte, wat grootliks vanuit die Romeinse en Griekse denkwêreld gekom het, in die rigting van ’n meer dinamiese Godsverstaan te skuif. Die gedagte van die ‘volhoubaarheid van God’ word aan ’n nuwe verstaan van die medelye van God (ta splanchna) verbind. Vandaar die voorstel vir ’n paradigmaskuif vanaf almag en alwetendheid na ’n patosvolle, infinitiewe omgee-identifikasie (die pneumatologiese volhoubaarheid van daar-wees-vir).
Newly wed in Wittenberg 1523 – And committed to the Lutheran Reformation
Authors: Potgieter Raymond
Published: December 2015

Protestant teaching questioned the redemptive value of Roman Catholic spirituality of the 16th century. Consequently many monks and nuns were led to leave their monasteries and convents. Elisabeth von Meseritz was a nun who found her way to Wittenberg. There she married and wrote the first protestant hymn as a woman clearly supportive of the Lutheran Reformation. The simplicity of Elisabeth’s story is a projection from one major event of her life to another ignoring the complexity of contexts and influences upon her which continued to shape her life. Instead of only focusing on the obvious highpoints of her story this article allows for the development of a fuller story that enriches understanding of an early protestant of the 16th century, a woman of the Lutheran Reformation.Pas getroud in Wittenberg 1523 – en toegewyd tot die Lutherse Reformasie. Protestantse leerstellings het die heilswaarde van die Rooms-Katolieke spiritualiteit van die sestiende eeu bevraagteken. Baie monnike en nonne het gevolglik hulle kloosters verlaat. Een van hulle was Elisabeth von Meseritz wat haar pad na Wittenberg gevind het. Daar is sy getroud en het die eerste protestantse lied as ’n vrou geskryf wat duidelik ondersteunend van die Lutherse Hervorming was. Die eenvoud van Elisabeth se storie is ’n projeksie van die een belangrike gebeurtenis van haar lewe na die volgende. Dit het die kompleksiteit van die konteks en die invloede wat voortgegaan het om haar lewe te vorm, geïgnoreer. In plaas daarvan om net op die voor die hand liggend hooftrekke van haar storie te fokus, maak hierdie artikel voorsiening vir die ontwikkeling van ’n verrykende storie met begrip vir die vroeë Protestantse sestiende eeuse vrou van die Lutherse Hervorming.
Comparison of postoperative complications in advanced head and neck cancer patients receiving neoadjuvant chemotherapy followed by surgery versus surgery alone
Authors: Joshi Poonam , Joshi Amit , Prabhash Kumar , Noronha Vanita , Chaturvedi Pankaj
Published: December 2015

Background: Head and neck cancer is the third most common cancer in India with 60% presenting in advanced stages. There is the emerging role of neoadjuvant chemotherapy (NACT) in the management of these advanced cancers. There is a general perception that complication rates are higher with the use of NACT. Materials and Methods: This is a retrospectively collected data of head and neck cancer patients operated at our hospital from March 2013 to September 2014. A total of 205 patients were included in the study. These patients were studied in two groups. Group 1 included 153 patients who underwent surgery alone, and Group 2 included 52 patients who received 2-3 cycles of NACT followed by surgery. Results: The mean age of the population was 51 years in the Group 1 and 45 years in Group 2. The hospital stay and readmissions in postoperative period were similar in the two groups. In this study, the complication rate was 37.9% in the surgery patients and 30.8% in the NACT patients (P = 0.424). Conclusion: The postoperative complication rates in patients who received NACT followed by surgery were not significantly different from those who underwent surgery.
Stretchable and Highly Conductive Carbon Nanotube-Graphene Hybrid Yarns for Wearable Systems
Authors: Muzahir Abbas Syed , Foroughi Javad , Ranga Yogesh , Matekovits Ladislau , Esselle Karu , Hay Stuart , Heimlich Michael , Safaei Farzad
Published: December 2015

Carbon Nanotubes (CNTs) have emerged as potential candidates for replacement of conventional metals due to their significant mechanical, electrical, thermal properties and non-oxidizing abilities [1, 2]. The density of CNT composites is about five times lower than copper and around half that of aluminium. Moreover, their thermal conductivity is about ten times that of copper. With the above mentioned distinguishing features, CNTs have been of interest in medical, electronics and antenna applications [3]. CNTs are drawn into yarns by pulling and twisting them from CNT forests. Previously we have presented microwave characterization of CNT yarns [4]. Our results have shown that the CNT yarns exhibits frequency independent resistive behavior and is beneficial for wide-band applications such as ultra-wideband (UWB) and wireless body area networks [4]. Electrical conductivity of a CNT yarn depends on the properties, loading and aspect ratio of the CNTs. It also depends upon the twist angle and the characteristics of the conductive network. By doping or adding materials, such as gold, silver or NiCr, electrical conductivity of CNTs can by varied. In [5], highly conductive carbon nanotube-graphene hybrid yarns are reported. They are obtained by drawing vertically aligned multi-walled carbon nanotubes (MWCNT) into long MWCNT sheets.
Estimation and Tracking of Knee Angle Trajectory using Inertial Sensors and a Smartphone Application
Authors: GROVER JASKARAN , NATARAJAN VENKAT
Published: December 2015

We demonstrate a practical solution to track the 2-D knee angle trajectory of a user in real-time using inertial sensors embedded in a wearable knee-band wirelessly coupled with a mobile device, by mathematically modeling the knee as a hinge joint. We show how the bias of gyroscopes can be automatically computed to eliminate manual calibration and combined with a computationally simple Kalman filter model for tracking the knee-angle on a power constrained mobile device. Finally, we visualize the 2-D knee motion trajectory in real-time using an avatar on an Android phone.
WISEglass: Smart eyeglasses recognising context
Authors: Wahl Florian , Freund Martin , Amft Oliver
Published: December 2015

We investigated how regular eyeglasses could be extended with multi-modal sensing and processing functions to support context-awareness applications. Our aim was to leverage eyeglasses as a platform for acquiring and processing context information according to the wearer’s needs. The WISEglass architecture consists of inertial motion, environmental light, and pulse sensors, processing and wireless data transmission functionality, besides a rechargeable battery. We implemented prototypes of WISEglass and evaluated them in three application scenarios: daily activity recognition, screen-use detection, and heart rate estimation. We conducted a daily activity study with nine participants, each wearing WISEglass and recording for one day. When evaluating daily activity recognition, we obtained 77 % average accuracy for continuous recognition using Gaussian Mixture Models and classifier reject to ignore null class data. Using the light sensor for detecting screen-use, yielded 80 % accuracy. Against a chest-worn ECG reference, our heart rate estimation showed an difference below 10 beats for stationary activities across the full recording day. We concluded that smart eyeglasses provide information from a single measurement spot that is relevant in various context recognition applications.
Driver’s ECG Signal Detection and Transmission by Impulse-Radio-Based Human Body Communication Technology
Authors: Wang Jianqing , Kato Taku , Anzai Daisuke
Published: December 2015

In this study, we developed a wearable electrocardiogram (ECG) sensor with human body communication (HBC) tech- nology for vital data transmission in a car. The ECG signals were modulated with wideband pulse signals between 10 and 60 MHz based on an impulse radio (IR) scheme, which provides a data rate as high as 1.25 Mbps. To apply the HBC-based wearable ECG in a moving car, we employed a moving average algorithm to reduce the noises produced in the received ECG signals due to the car's movement. As a result, we conrmed a real-time ECG transmission of driver in the moving car with a reasonable accuracy.
Support Vector Machines for Young and Older Gait Classification using Inertial Sensor Kinematics at Minimum Toe Clearance
Authors: Santhiranayagam Braveena , Lai Daniel , Begg Rezaul
Published: December 2015

The present study investigates the inertial sensor kinematics obtained at a critical toe-control event, Minimum Toe Clearance (MTC), to classify dierent age groups. Fourteen young and fourteen older adults performed treadmill walking at their preferred walking speed, wearing a shoe-mount inertial sensor unit measuring tri-axial acceleration and triaxial angular velocities. Three dimensional (3D) position-time data was obtained using high accurate motion capture system. MTC timing within a gait cycle (MTCTime), calculated using 3D motion capture data, was used to extract inertial sensor kinematics at MTC event. Mean and standard deviation of three inertial sensor acceleration features and three angular velocity features were compared between young and older individuals using t-tests. Young adults' mean anterior-posterior acceleration was greater than older adults (p=0.002). Further, standard deviations (SD) of all three accelerations and angular velocity about medio-lateral axis were greater in Older adults. The inertial sensor kinematics obtained at MTCTime were able to classify young and older adults gait with 91.2% accuracy using a Support Vector Machine (SVM) classifier. The findings of the present study suggest that by employing SVM techniques, a portable inertial sensor system could be used to identify gait degeneration due to ageing and has the potential for wider applications in gait identification for falls-risk minimization.
Modelling and Simulation for Major Incidents
Authors: Pacciani Eleonora , Borri Alessandro , Soave Paolo Maurizio , Gui Daniele , Magalini Sabina , Panunzi Simona , Roberto Gaz Claudio , Gaudio Pasquale , Malizia Andrea , Gaetano Andrea De
Published: December 2015

In recent years, there has been a rise in Major Incidents with big impact on the citizens health and the society. Without the possibility of conducting live experiments when it comes to physical and/or toxic trauma, only an accurate in silico reconstruction allows us to identify organizational solutions with the best possible chance of success, in correlation with the limitations on available resources (e.g. medical team, first responders, treatments, transports, and hospitals availability) and with the variability of the characteristic of event (e.g. type of incident, severity of the event and type of lesions).Utilizing modelling and simulation techniques, a simplified mathematical model of physiological evolution for patients involved in physical and toxic trauma incident scenarios has been developed and implemented. The model formalizes the dynamics, operating standards and practices of medical response and the main emergency service in the chain of emergency management during a Major Incident.
Разделение систем гидродинамического типа на блочно-треугольно взаимодействующие подсистемы
Authors: Tunitsky Dmitry Vasilievich
Published: December 2015

Статья посвящена системам $n$ неоднородных уравнений гидродинамического типа с двумя независимыми переменными. Для таких систем имеет место восходящая к Риману геометрическая формализация, позволяющая поставить в соответствие системе гидродинамического типа векторное поле и поле линейных операторов, действующее на соответствующем касательном расслоении. В терминах этих полей получен ряд признаков разделения неоднородных систем гидродинамического типа на блочно-треугольно взаимодействующие подсистемы. Эти признаки дополняют известные результаты О. И. Богоявленского о разделении однородных систем гидродинамического типа на невзаимодействующие подсистемы.
Библиография: 16 наименований.
Интегральное уравнение Наттолла и асимптотическая формула Бернштейна для комплексного веса
Authors: Ikonomov Nikolay Rumenov , Kovacheva Ralitza Krumova , Suetin Sergey Pavlovich
Published: December 2015

Получено интегральное уравнение Наттолла при условии, что соответствующая комплекснозначная функция $\sigma(x)$ не обращается в нуль и принадлежит классу Дини-Липшица. С помощью этого уравнения для многочленов, ортогональных на единичном отрезке $\Delta=[-1,1]$ относительно
комплекснозначного веса $h(x)=\sigma(x)/\sqrt{1-x^2}$, получен комплексный аналог классических асимптотических формул Бернштейна.
Библиография: 30 наименований.
Бесконечные детерминантные меры и эргодическое разложение бесконечных мер Пикрелла. I. Построение бесконечных детерминантных мер
Authors: Bufetov Aleksandr Igorevich
Published: December 2015

Эта работа - первая в серии из трех. В работе дано явное описание эргодического разложения бесконечных мер Пикрелла на пространстве бесконечных комплексных матриц. Ключевую роль играет конструкция
$\sigma$-конечных аналогов детерминантных мер на пространствах конфигураций, в частности, бесконечного бесселева процесса, скейлингового предела $\sigma$-конечных аналогов ортогональных полиномиальных ансамблей Якоби. Основной результат отождествляет бесконечный бесселев процесс с разлагающей мерой бесконечной меры Пикрелла.
Библиография: 45 наименований.
WHO/ FAO/ OIE tripartite coordination for the control and prevention of zoonotic influenza viruses. Example of OFFLU, global network of veterinary expertise
Authors: Dauphin Gwenaëlle
Published: December 2015

Au cours des dix dernières années, on a de plus en plus pris conscience du potentiel qu’ont les infections animales par l’influenza à causer une maladie sérieuse chez l’homme. Ceci a été à la fois le résultat d’observations plus fréquentes d’infections par des influenza zoonotiques chez l’homme et de la circulation intense de souches influenza avec un potentiel pandémique dans le réservoir animal. OFFLU (Réseau OIE/ FAO d’expertise sur l’influenza animal) a été créé comme une réponse à la dissémination majeure du sous-type H5N1 du virus influenza aviaire à caractère zoonotique. OFFLU est un partenariat formel entre l’OIE (Organisation Mondiale de la Santé Animale) et la division de santé et production animales de la FAO (Organisation de l’Alimentation et de l’Agriculture des Nations Unies) afin de maintenir un réseau actif d’expertise sur l’influenza animal. L’un des quatre objectifs d’OFFLU est spécifiquement de collaborer avec le réseau influenza de l’OMS (Organisation Mondiale de la Santé) sur les problèmes relatifs à l’interface animal-homme, y compris la préparation des vaccins humains. Une collaboration technique plus forte, à la fois institutionnelle et nationale, parmi les scientifiques des secteurs de la santé animale et de la santé publique a été établie au travers de discussions techniques conjointes, de partage de l’information et du développement et de l’utilisation d’outils communs.
DETECTION OF BUILT-UP AREAS USING POLARIMETRIC SYNTHETIC APERTURE RADAR DATA AND HYPERSPECTRAL IMAGE
Authors: Bordbari R. , Maghsoudi Y. , Salehi M.
Published: December 2015

Abstract. Polarimetric synthetic aperture radar (POLSAR) is an advantageous data for information extraction about objects and structures by using the wave scattering and polarization properties. Hyperspectral remote sensing exploits the fact that all materials reflect, absorb, and emit electromagnetic energy, at specific wavelengths, in distinctive patterns related to their molecular composition. As a result of their fine spectral resolution, Hyperspectral image (HIS) sensors provide a significant amount of information about the physical and chemical composition of the materials occupying the pixel surface. In target detection applications, the main objective is to search the pixels of an HSI data cube for the presence of a specific material (target). In this research, a hierarchical constrained energy minimization (hCEM) method using 5 different adjusting parameters has been used for target detection from hyperspectral data. Furthermore, to detect the built-up areas from POLSAR data, building objects discriminated from surrounding natural media presented on the scene using Freeman polarimetric target decomposition (PTD) and the correlation coefficient between co-pol and cross-pol channels. Also, target detection method has been implemented based on the different polarization basis for using the more information. Finally a majority voting method has been used for fusing the target maps. The polarimetric image C-band SAR data acquired by Radarsat-2, over San Francisco Bay area was used for the evaluation of the proposed method.
TAGS EXTARCTION FROM SPATIAL DOCUMENTS IN SEARCH ENGINES
Authors: Borhaninejad S. , Hakimpour F. , Hamzei E.
Published: December 2015

Abstract. Nowadays the selective access to information on the Web is provided by search engines, but in the cases which the data includes spatial information the search task becomes more complex and search engines require special capabilities. The purpose of this study is to extract the information which lies in spatial documents. To that end, we implement and evaluate information extraction from GML documents and a retrieval method in an integrated approach. Our proposed system consists of three components: crawler, database and user interface. In crawler component, GML documents are discovered and their text is parsed for information extraction; storage. The database component is responsible for indexing of information which is collected by crawlers. Finally the user interface component provides the interaction between system and user. We have implemented this system as a pilot system on an Application Server as a simulation of Web. Our system as a spatial search engine provided searching capability throughout the GML documents and thus an important step to improve the efficiency of search engines has been taken.
GIS-BASED ROUTE FINDING USING ANT COLONY OPTIMIZATION AND URBAN TRAFFIC DATA FROM DIFFERENT SOURCES
Authors: Davoodi M. , Mesgari M. S.
Published: December 2015

Abstract. Nowadays traffic data is obtained from multiple sources including GPS, Video Vehicle Detectors (VVD), Automatic Number Plate Recognition (ANPR), Floating Car Data (FCD), VANETs, etc. All such data can be used for route finding. This paper proposes a model for finding the optimum route based on the integration of traffic data from different sources. Ant Colony Optimization is applied in this paper because the concept of this method (movement of ants in a network) is similar to urban road network and movements of cars. The results indicate that this model is capable of incorporating data from different sources, which may even be inconsistent.
TARGETED SATELLITE IMAGE CLASSIFICATION FOR URBAN MAP UPDATING USING GEOSPATIAL INFORMATION SYSTEM PLATFORM
Authors: Davoodianidaliki M. , Abedini A.
Published: December 2015

Abstract. Traditional map production and updating methods which usually involve field surveying and/or photogrammetry, while established and used for a long time, are time consuming and costly. Whereas satellite imagery have provided great amounts of data with high resolutions suitable for different geospatial applications. This paper focuses on taking advantage of geospatial information systems for enabling automated supervised classification of satellite images in urban areas. Such ability is provided through some attributes that determine whether features in current map have changed or not. The overall process consists of three stages: i: Geo database upgrade for addition of some attributes; ii: Classification by Support Vector Machine (SVM) and iii: Change analysis. The proposed method is applied on a sample data of Worldview 3 image of Hormozgan, Iran. The obtained results show that using such method not only can automate supervised classification but also can decrease misclassification errors through local training. Also its independent of classification method provides the ability to deploy other classification methods.
PSINSAR IMPROVEMENT USING AMPLITUDE DISPERSION INDEX OPTIMIZATION OF DUAL POLARIMETRY DATA
Authors: Esmaeili M. , Motagh M.
Published: December 2015

Abstract. Persistent Scatterer Interferometry for SAR data (PSInSAR) improves the ability of conventional InSAR time-series methods by detecting and analysing pixels where the portion of spatiotemporal decorrelations on the phase is negligible. Using dual/quad polarized SAR data provide us with an additional source of information to improve further the capability of InSAR analysis. In this paper, we present a method to enhance PSInSAR using polarimetric optimization method on multi-temporal polarimetric SAR data. The optimization process has been implemented to minimize the Amplitude dispersion Index (ADI) of pixels in SAR images over the time based on the best scattering mechanism. We evaluated the method on a dataset including 17 dual polarization SAR data (HH/VV) acquired by TerraSAR-X data from July 2013 to January 2014 over Tehran plain, Iran. The area has been affected by high rate (> 20 cm/yr.) of surface subsidence due to groundwater overexploitation. The effectiveness of the method is compared for both agricultural and urban regions affected by land subsidence. Furthermore single pole and optimized polarization results are compared together and with external observations from GPS measurements. The results reveal that using optimum scattering mechanism decreases the ADI values in urban and non-urban regions and increase the PS Candidate pixels (PSC) about three times and subsequently improves the PS density about 50% more than using single channel datasets.
GEOREFERENCING ON SYNTHETIC APERTURE RADAR IMAGERY
Authors: Esmaeilzade M. , Amini J. , Zakeri S.
Published: December 2015

Abstract. Due to the SAR1 geometry imaging, SAR images include geometric distortions that would be erroneous image information and the images should be geometrically calibrated. As the radar systems are side looking, geometric distortion such as shadow, foreshortening and layover are occurred. To compensate these geometric distortions, information about sensor position, imaging geometry and target altitude from ellipsoid should be available. In this paper, a method for geometric calibration of SAR images is proposed. The method uses Range-Doppler equations. In this method, for the image georeferencing, the DEM2 of SRTM with 30m pixel size is used and also exact ephemeris data of the sensor is required. In the algorithm proposed in this paper, first digital elevation model transmit to range and azimuth direction. By applying this process, errors caused by topography such as foreshortening and layover are removed in the transferred DEM. Then, the position of the corners on original image is found base on the transferred DEM. Next, original image registered to transfer DEM by 8 parameters projective transformation. The output is the georeferenced image that its geometric distortions are removed. The advantage of the method described in this article is that it does not require any control point as well as the need to attitude and rotational parameters of the sensor. Since the ground range resolution of used images are about 30m, the geocoded images using the method described in this paper have an accuracy about 20m (subpixel) in planimetry and about 30m in altimetry. 1 Synthetic Aperture Radar 2 Digital Elevation Model
PREDICTION OF WIND SPEEDS BASED ON DIGITAL ELEVATION MODELS USING BOOSTED REGRESSION TREES
Authors: Fischer P. , Etienne C. , Tian J. , Krauß T.
Published: December 2015

Abstract. In this paper a new approach is presented to predict maximum wind speeds using Gradient Boosted Regression Trees (GBRT). GBRT are a non-parametric regression technique used in various applications, suitable to make predictions without having an in-depth a-priori knowledge about the functional dependancies between the predictors and the response variables. Our aim is to predict maximum wind speeds based on predictors, which are derived from a digital elevation model (DEM). The predictors describe the orography of the Area-of-Interest (AoI) by various means like first and second order derivatives of the DEM, but also higher sophisticated classifications describing exposure and shelterness of the terrain to wind flux. In order to take the different scales into account which probably influence the streams and turbulences of wind flow over complex terrain, the predictors are computed on different spatial resolutions ranging from 30 m up to 2000 m. The geographic area used for examination of the approach is Switzerland, a mountainious region in the heart of europe, dominated by the alps, but also covering large valleys. The full workflow is described in this paper, which consists of data preparation using image processing techniques, model training using a state-of-the-art machine learning algorithm, in-depth analysis of the trained model, validation of the model and application of the model to generate a wind speed map.
CONSTRUCTION OF A CAUSEWAY BRIDGE ACROSS THE LAKE URMIA AND ITS INFLUENCE ON DRYING TREND OF THE LAKE
Authors: Ghadimi M. , Nezammahalleh M. A.
Published: December 2015

Abstract. Construction of a causeway bridge on the Lake Urmia accelerated the drying trend of the largest hyper-saline lake of the world. The objective of the research is to investigate the differences of precipitation and river discharge before and after initiation of the construction of the bridge in 2000. The study area was the watershed of the lake. The averages of the precipitation data in the two periods before and after the project have been interpolated by IDW based on GIS Geostatistical Analyst. The two interpolated precipitation layers were used to be plugged into Student T-test equation in GIS in a spatial basis. To do this, the study area was divided to 25 regions based on drainage sub-basins. Less than 30 sample areas were randomly selected as cases from each of the regions to put into the equation. The discharge data were also compared for the two periods. The results indicated that except in some limited areas, the precipitation differences in the two periods are significant. This means that there were little changes in precipitation and river discharge in the area and consequently the drying may be caused mainly by hydrodynamic changes in the lake due to construction of the causeway. However, it can be argued that the changes in the lake’s surface area are accompanied by changes in precipitation and river discharge. The t test statistic can be applied samples based on spatial analysis.
HADOOP-BASED DISTRIBUTED SYSTEM FOR ONLINE PREDICTION OF AIR POLLUTION BASED ON SUPPORT VECTOR MACHINE
Authors: Ghaemi Z. , Farnaghi M. , Alimohammadi A.
Published: December 2015

Abstract. The critical impact of air pollution on human health and environment in one hand and the complexity of pollutant concentration behavior in the other hand lead the scientists to look for advance techniques for monitoring and predicting the urban air quality. Additionally, recent developments in data measurement techniques have led to collection of various types of data about air quality. Such data is extremely voluminous and to be useful it must be processed at high velocity. Due to the complexity of big data analysis especially for dynamic applications, online forecasting of pollutant concentration trends within a reasonable processing time is still an open problem. The purpose of this paper is to present an online forecasting approach based on Support Vector Machine (SVM) to predict the air quality one day in advance. In order to overcome the computational requirements for large-scale data analysis, distributed computing based on the Hadoop platform has been employed to leverage the processing power of multiple processing units. The MapReduce programming model is adopted for massive parallel processing in this study. Based on the online algorithm and Hadoop framework, an online forecasting system is designed to predict the air pollution of Tehran for the next 24 hours. The results have been assessed on the basis of Processing Time and Efficiency. Quite accurate predictions of air pollutant indicator levels within an acceptable processing time prove that the presented approach is very suitable to tackle large scale air pollution prediction problems.
INVESTIGATION THE BEHAVIOR OF MODIS OCEAN COLOR PRODUCTS UNDER THE 2008 RED TIDE IN THE EASTERN PERSIAN GULF
Authors: Ghanea M. , Moradi M. , Kabiri K.
Published: December 2015

Abstract. Biophysical properties of water undergo serious variations under red tide (RT) outbreak. During RT conditions, algal blooms spread out in the estuarine, marine and fresh waters due to different triggering factors such as nutrient loading, marine currents, and monsoonal winds. The Persian Gulf (PG) was a talent region subjected to different RTs in recent decade. A massive RT started from the Strait of Hormuz in October 2008 and extended towards the northern parts of the PG covering more than 1200 km of coastlines. The bloom of microorganism C. Polykrikoides was the main specie that generated large fish mortalities, and hampered marine industries, and water desalination appliances. Ocean color satellite data have many advantages to monitor and alarm RT occurrences, such as wide and continuous extent, short time of imagery, high accessibility, and appropriate estimation of ocean color parameters. Since 1999, MODerate Resolution Imaging Spectroradiometer (MODIS) satellite sensor has estimated satellite derived chlorophyll-a (Chl-a), normalized fluorescence line height (nFLH), and diffuse attenuation coefficient at 490nm (kd490). It provides a capability to study the behavior of these parameters during RT and normal conditions. This study monitors variations in satellite derived Chl-a, nFLH, and kd490 under both RT and normal conditions of the PG between 2002 and 2008. Up to now, daily and monthly variations in these products were no synchronously investigated under RT conditions in the PG. In doing so, the MODIS L1B products were provided from NASA data archive. They were corrected for Rayleigh scattering and gaseous absorption, and atmospheric interference in turbid coastal waters, and then converted to level 2 data. In addition, Enhanced Red Green Blue (ERGB) image was used to illustrate better water variations. ERGB image was built with three normalized leaving water radiance between 443 to 560nm. All the above data processes were applied by SeaDAS 7 software package. The Strait of Hormuz was selected as the study area in the eastern part of the PG. Images including high cloud coverage (>50%) over the study area were filtered out. The classification maps of the above products were shown during RT and normal periods. Monthly variations of mentioned products were calculated for the dates before, during, and after RT appearance. The results were demonstrated as time-series diagrams. All the above calculations and presentations were performed in Matlab 7 software package. The results show that MODIS Chl-a, nFLH, and kd490 increased during the 2008 RT. Based on the feedback of these parameters under RT conditions, hybrid ocean color index (HOCI) is defined. HOCI is able to display better water variations during RT outbreak. High values of HOCI show RT affected areas.
SENTINEL-1 IMAGE MATCHING USING STRONG SCATTERS
Authors: Ghannadi M. A. , Saadatseresht M. , Motagh M.
Published: December 2015

Abstract. The availability of new radar spaceborne sensors offers new interesting potentialities for the geomatics application: spatial and temporal change detection, generation of Digital Elevation Model(DEM) using radargrametry and interferometry. Since the start of the sentinel-1 mission to take images from different regions all over the world, the ability to use these images in variety domains has been treasured. This paper suggests a method for image matching using strong scatters. all the experiments are done on sentinel-1 stereo images from Jam, Bushehr, Iran.
SOIL FERTILITY EVALUATION FOR FERTILISER RECOMMENDATION USING HYPERION DATA
Authors:   Ranendu Ghosh, Padmanabhan N. , Patel K. C.
Published: December 2015

Abstract. Soil fertility characterised by nitrogen, phosphorus, potassium, calcium, magnesium and sulphur is traditionally measured from soil samples collected from the field. The process is very cumbersome and time intensive. Hyperspectral data available from Hyperion payload of EO 1 was used for facilitating preparation of soil fertility map of Udaipur district of Rajasthan state, India. Hyperion data was pre-processed for band and area sub setting, atmospheric correction and reflectance data preparation. Spectral analysis in the form of SFF and PPI were carried out for selecting the ground truth sites for soil sample collection. Soil samples collected from forty one sites were analysed for analysis of nutrient composition. Generation of correlogram followed by multiple regressions was done for identifying the most important bands and spectral parameters that can be used for nutrient map generation.
3D OBJECT CLASSIFICATION BASED ON THERMAL AND VISIBLE IMAGERY IN URBAN AREA
Authors: Hasani H. , Samadzadegan F.
Published: December 2015

Abstract. The spatial distribution of land cover in the urban area especially 3D objects (buildings and trees) is a fundamental dataset for urban planning, ecological research, disaster management, etc. According to recent advances in sensor technologies, several types of remotely sensed data are available from the same area. Data fusion has been widely investigated for integrating different source of data in classification of urban area. Thermal infrared imagery (TIR) contains information on emitted radiation and has unique radiometric properties. However, due to coarse spatial resolution of thermal data, its application has been restricted in urban areas. On the other hand, visible image (VIS) has high spatial resolution and information in visible spectrum. Consequently, there is a complementary relation between thermal and visible imagery in classification of urban area. This paper evaluates the potential of aerial thermal hyperspectral and visible imagery fusion in classification of urban area. In the pre-processing step, thermal imagery is resampled to the spatial resolution of visible image. Then feature level fusion is applied to construct hybrid feature space include visible bands, thermal hyperspectral bands, spatial and texture features and moreover Principle Component Analysis (PCA) transformation is applied to extract PCs. Due to high dimensionality of feature space, dimension reduction method is performed. Finally, Support Vector Machines (SVMs) classify the reduced hybrid feature space. The obtained results show using thermal imagery along with visible imagery, improved the classification accuracy up to 8% respect to visible image classification.
AN INTEGRATED RANSAC AND GRAPH BASED MISMATCH ELIMINATION APPROACH FOR WIDE-BASELINE IMAGE MATCHING
Authors: Hasheminasab M. , Ebadi H. , Sedaghat A.
Published: December 2015

Abstract. In this paper we propose an integrated approach in order to increase the precision of feature point matching. Many different algorithms have been developed as to optimizing the short-baseline image matching while because of illumination differences and viewpoints changes, wide-baseline image matching is so difficult to handle. Fortunately, the recent developments in the automatic extraction of local invariant features make wide-baseline image matching possible. The matching algorithms which are based on local feature similarity principle, using feature descriptor as to establish correspondence between feature point sets. To date, the most remarkable descriptor is the scale-invariant feature transform (SIFT) descriptor , which is invariant to image rotation and scale, and it remains robust across a substantial range of affine distortion, presence of noise, and changes in illumination. The epipolar constraint based on RANSAC (random sample consensus) method is a conventional model for mismatch elimination, particularly in computer vision. Because only the distance from the epipolar line is considered, there are a few false matches in the selected matching results based on epipolar geometry and RANSAC. Aguilariu et al. proposed Graph Transformation Matching (GTM) algorithm to remove outliers which has some difficulties when the mismatched points surrounded by the same local neighbor structure. In this study to overcome these limitations, which mentioned above, a new three step matching scheme is presented where the SIFT algorithm is used to obtain initial corresponding point sets. In the second step, in order to reduce the outliers, RANSAC algorithm is applied. Finally, to remove the remained mismatches, based on the adjacent K-NN graph, the GTM is implemented. Four different close range image datasets with changes in viewpoint are utilized to evaluate the performance of the proposed method and the experimental results indicate its robustness and capability.
LAKE URMIA BRIDGE STABILITY ASSESSMENT: RESULTS FROM TERRASAR-X SPOTLIGHT MODE IMAGES
Authors: Hosseini F. , Motagh M. , Vajedian S. , Sharifi M. A.
Published: December 2015

Abstract. In this study we investigate stability of Lake Urmia bridge, locally also known as Shahid Kalantari’s highway bridge, in northwest of Iran using high-resolution satellite radar imagery. The radar dataset includes 22 SAR images acquired in SpotLight mode from 2014 to 2015 in an ascending orbit by TerraSAR-X satellite. A high-resolution Digital Elevation Model (DEM) of the area was constructed from a pair of TanDEM-X bi-static data on June 2012 to remove the effect of topography from interferometry observations. The analysis of X-band interferograms shows high number of displacement fringes, which are interpreted as being caused by thermal dilation due to temperature differences in the imaged area between two SAR acquisitions. This effect, which can often be observed in single interferograms, have important impact on time-series products and should be considered for deformation analysis of bridge structures.
3D RECONSTRUCTION FROM MULTI-VIEW MEDICAL X-RAY IMAGES – REVIEW AND EVALUATION OF EXISTING METHODS
Authors: Hosseinian S. , Arefi H.
Published: December 2015

Abstract. The 3D concept is extremely important in clinical studies of human body. Accurate 3D models of bony structures are currently required in clinical routine for diagnosis, patient follow-up, surgical planning, computer assisted surgery and biomechanical applications. However, 3D conventional medical imaging techniques such as computed tomography (CT) scan and magnetic resonance imaging (MRI) have serious limitations such as using in non-weight-bearing positions, costs and high radiation dose(for CT). Therefore, 3D reconstruction methods from biplanar X-ray images have been taken into consideration as reliable alternative methods in order to achieve accurate 3D models with low dose radiation in weight-bearing positions. Different methods have been offered for 3D reconstruction from X-ray images using photogrammetry which should be assessed. In this paper, after demonstrating the principles of 3D reconstruction from X-ray images, different existing methods of 3D reconstruction of bony structures from radiographs are classified and evaluated with various metrics and their advantages and disadvantages are mentioned. Finally, a comparison has been done on the presented methods with respect to several metrics such as accuracy, reconstruction time and their applications. With regards to the research, each method has several advantages and disadvantages which should be considered for a specific application.
A LOW-COST AND PORTABLE SYSTEM FOR 3D RECONSTRUCTION OF TEXTURE-LESS OBJECTS
Authors: Hosseininaveh A. , Yazdan R. , Karami A. , Moradi M. , Ghorbani F.
Published: December 2015

Abstract. The optical methods for 3D modelling of objects can be classified into two categories including image-based and range-based methods. Structure from Motion is one of the image-based methods implemented in commercial software. In this paper, a low-cost and portable system for 3D modelling of texture-less objects is proposed. This system includes a rotating table designed and developed by using a stepper motor and a very light rotation plate. The system also has eight laser light sources with very dense and strong beams which provide a relatively appropriate pattern on texture-less objects. In this system, regarding to the step of stepper motor, images are semi automatically taken by a camera. The images can be used in structure from motion procedures implemented in Agisoft software.To evaluate the performance of the system, two dark objects were used. The point clouds of these objects were obtained by spraying a light powders on the objects and exploiting a GOM laser scanner. Then these objects were placed on the proposed turntable. Several convergent images were taken from each object while the laser light sources were projecting the pattern on the objects. Afterward, the images were imported in VisualSFM as a fully automatic software package for generating an accurate and complete point cloud. Finally, the obtained point clouds were compared to the point clouds generated by the GOM laser scanner. The results showed the ability of the proposed system to produce a complete 3D model from texture-less objects.
MONITORING IONOSPHERIC VARIATION FOR A DEFINITE PERIOD TIME IN TURKEY
Authors: Inyurt S. , Mekik C. , Yildirim O.
Published: December 2015

Abstract. Ionosphere has been studied by a number of scientists in recent years. Since GPS observations cannot provide TEC value directly, it can be estimated from combination of observations. In this study TEC values derived from GPS observations were produced variations with two hours increments from the eighth day to fifteenth day in months just after beginning of each season, namely January, April, July and October in 2014 for ZONG TUSAGA-Aktif station and 41 other stations (TUSAGA-Aktif, EUREF, IGS). TEC values computed by the Bernese 5.0 software were compared with the Global Ionosphere Model (GIM) TEC values regularly published by Center for Orbit Determination in Europe (CODE) and International Reference Ionosphere (IRI-2012) TEC values. As a result of this study, with the comparison of GPS TEC values to GIM TEC values, it has become obvious that GPS TEC values are quite similar to the GIM TEC values. The differences of TEC values derived from GPS TEC and GIM TEC change from 0.91 TECU (January) to 1.88 TECU (October). On the other hand, GPS TEC values are also compared with IRI TEC values, and found out that there is a considerable difference between the two TEC values ranging from 6.30 TECU (January) to 15.15 TECU (April). Moreover, TEC values derived from GPS measurements are attained similar to GIM TEC, but found to stray from IRI-2012 TEC values remarkably.
DETECTION AND MODELING OF TEMPERATURE INVERSION IN THE ATMOSPHERE USING MODIS IMAGES (CASE STUDY: KERMANSHAH)
Authors: Kachar H. , Mobasheri M. R. , Abkar A. A. , Rahim Zadegan M.
Published: December 2015

Abstract. Increase of temperature with height in the troposphere is called temperature inversion. Parameters such as strength and depth are characteristics of temperature inversion. Inversion strength is defined as the temperature difference between the surface and the top of the inversion and the depth of inversion is defined as the height of the inversion from the surface. The common approach in determination of these parameters is the use of Radiosonde where these measurements are too sparse. The main objective of this study is detection and modeling the temperature inversion using MODIS thermal infrared data. There are more than 180 days per year in which the temperature inversion conditions are present in Kermanshah city. Kermanshah weather station was selected as the study area. 90 inversion days was selected from 2007 to 2008 where the sky was clear and the Radiosonde data were available. Brightness temperature for all thermal infrared bands of MODIS was calculated for these days. Brightness temperature difference between any of the thermal infrared bands of MODIS and band 31 was found to be sensitive to strength and depth of temperature inversion. Then correlation coefficients between these pairs and the inversion depth and strength both calculated from Radiosonde were evaluated. The results showed poor linear correlation. This was found to be due to the change of the atmospheric water vapor content and the relatively weak temperature inversion strength and depth occurring in Kermanshah. The polynomial mathematical models and Artificial intelligence algorithms were deployed for detection and modeling the temperature inversion. A model with the lowest terms and highest possible accuracy was obtained. The Model was tested using 20 independent test data. Results indicate that the inversion strength can be estimated with RMSE of 0.84° C and R2 of 0.90. Also inversion depth can be estimated with RMSE of 54.56 m and R2 of 0.86.