bluuebunny/crossref_metadata_2025 huggingface dataset:
Retention of high-potential employees in a development finance company
Authors: Letchmiah Lishani , Thomas Adèle
Published: September 2017

Orientation: The loss of high-potential employees was a concern to leaders at a South African development finance company. The research question that guided the study was: How can high-potential employees be retained in the company?Research purpose: The objective of the study was to identify factors that positively impact the retention of high-potential employees in a development finance company.Motivation for the study: The organisation that comprised the unit of study had prioritised employee development to retain high-potential employees, thereby aiming to build a strong talent pipeline and a sustainable knowledge base. A prevalent concern was that there were no formal retention programmes for high-potential employees. Accordingly, organisational leaders could benefit from understanding those retention factors that may serve to retain such employees.Research design, approach and method: A qualitative methodology promoted a deeper understanding of a social problem through a case study. Eleven purposefully chosen highpotential employees provided insights into factors they considered to be important in their retention. A content analysis of the data resulted in clusters of themes that addressed the research objective.Main findings: The following factors appeared to influence the retention of high-potential employees: leadership and organisational culture, organisational purpose, developmental opportunities, meaningful work and collegiality.Practical and managerial implications: Leaders in the company should consider factors that could influence the retention of high-potential employees. Such factors should be built into formal retention strategies based on the intrinsic needs of employees; the strengths that the organisational culture provides could be leveraged in this regard.Contribution: The practical value of the study was the highlighting of the factors that can be leveraged to retain high-potential employees in a development finance company.
Dyke–Davidoff–Masson syndrome with crossed cerebellar atrophy
Authors: Khaladkar Sanjay M. , Chauhan Shishir , Patil Abhijit M. , Gandage Siddappa G. , Chauhan Kalra Surbhi
Published: September 2017

Dyke–Davidoff–Masson syndrome is a rare condition with classical, clinical and radiological changes – mental retardation, hemiparesis, facial asymmetry, seizures and cerebral hemiatrophy with calvarial changes. Contralateral cerebellar atrophy is rare and occurs if insult occurs after 1 month of age. We report a case of a 6-year-old female child presenting with right-sided hemiparesis, convulsions and left cerebral hemiatrophy with an old infarct in left middle cerebral artery (MCA) territory, ipsilateral calvarial thickening and right (crossed) cerebellar atrophy.
Локально ограниченные финально преднепрерывные конечномерные квазипредставления связных локально компактных групп
Authors: Shtern Alexander Isaakovich
Published: September 2017

Получено описание строения всех конечномерных локально ограниченных финально преднепрерывных квазипредставлений произвольных связных локально компактных групп.
Библиография: 40 названий.
Степени отображений между трехмерными сферическими многообразиями
Authors: Goncalves Daciberg Lima , Wong Peter , Zhao Xuezhi
Published: September 2017

Пусть $D(M,N)$ - множество целых чисел, реализуемых как степени отображений между замкнутыми связными ориентируемыми многообразиями $M$ и $N$ равной размерности. Для замкнутых трехмерных многообразий $M$ и $N$ с $S^3$-геометрией степень такого отображения удовлетворяет соотношению $\operatorname{deg} f\equiv \overline {\operatorname{deg}}\psi \mod |\pi_1(N)|$, где $0\le \overline {\operatorname{deg}}\psi<|\pi_1(N)|$ и $\overline {\operatorname{deg}}\psi$ зависит только от индуцированного гомоморфизма $\psi=f_{\pi}$ фундаментальных групп. В статье явно вычислено множество значений $\{\overline{\operatorname{deg}}\psi\}$ в том случае, когда $\psi$ сюръективен, а также показано, как найти $\overline{\operatorname{deg}}(\psi)$ в случае произвольного гомоморфизма. Это приводит к полному определению множества $D(M,N)$.
Библиография: 22 названия.
Tentatives pour dynamiser un réseau d’épidémiosurveillance : les contrôles à l’introduction en Charente-Maritime
Authors: Boucard Claude , Stroh Patrick , Vindrinet Robert
Published: September 2017

L’arrêt de la vaccination anti-aphteuse obligatoire priva le réseau d’épidémiosurveillance d’une source de financement majeure et de contacts entre ses divers acteurs.

Afin de poursuivre l’animation de ce réseau, une politique évolutive en faveur des contrôles sur les animaux introduits dans les cheptels suscita l’intérêt, à divers titres, des membres du réseau. Aidé par des subventions du Conseil Général de Charente-Maritime, il fut possible d’élargir progressivement les dépistages tandis que les contreparties des éleveurs, financières ou techniques, s’étoffaient.

L’accueil de cette action varie selon l’espèce et le risque sanitaire ressenti. Les résultats essentiels furent une modification de l'offre des commerçants de bétail privilégiant des animaux sains, la mise en œuvre par les éleveurs de dispositions réglementaires essentielles à la protection sanitaire de leur cheptel, et la confirmation du rôle d’interlocuteur et d’interface essentiel des vétérinaires sanitaires entre les pouvoirs et les éleveurs.
Des modèles de zoonoses aux chimères humanisées, l’importance de la physiopathologie expérimentale en pathologie infectieuse à l’ère de la post-génomique
Authors: Alonso Jean-Michel
Published: September 2017

L’étude des mécanismes de déclenchement et de l’évolution des maladies infectieuses nécessite une approche à la fois épidémiologique et physio-pathologique. De l’étude des zoonoses où les pathogènes ont une spécificité d’hôte peu restreinte à celle des infections opportunistes où par définition, les pathogènes évoluent selon les conditions environnementales, la physiopathologie expérimentale révèle le potentiel adaptatif des micro-organismes par leur plasticité génétique. Le décriptage des génomes des pathogènes et de leurs hôtes montre que les interactions entre les déterminants infectieux et les molécules réceptrices de l’hôte n’impliquent souvent que quelques gènes, facilement modifiés par des mécanismes de mutation et de recombinaison. La connaissance de ces interactions précises grâce aux modèles in vivo permet de mieux appréhender la biodiversité et l’évolution des génomes et d’en déduire de nouvelles stratégies thérapeutiques et préventives des maladies infectieuses.
Modélisation de la croissance de Listeria monocytogenes dans les aliments
Authors: Augustin Jean-Christophe , Carlier Vincent Richard Didier
Published: September 2017

Les modèles de microbiologie prévisionnelle permettent de simuler la croissance des populations de Listeria monocytogenes dans les aliments. L’approche progressive avec interactions semble la plus fiable pour simuler ces comportements, mais celle-ci se heurte encore à certaines limites comme l’aspect stochastique de la modélisation de la croissance ou l’intégration de l’effet de traitements induisant des stress bactériens. Malgré cela, l’outil se révèle utile dans la détermination des durées de vie des denrées alimentaires.
A modified automated protocol for EBER in situ hybridization staining of xenograft tissue
Authors: Aziz N. , Ahmad M. , Soo-Beng Khoo A.
Published: September 2017

Introduction: Epstein-Barr virus encoded RNA (EBER) in situ hybridization (ISH) is a method for the identification of Epstein-Barr virus (EBV) infection in tissue sections. In our experience, the currently available automated EBER ISH staining protocol using the Bond-Max immunostainer is not suitable for xenograft tissue sample due to high background staining which impairs the interpretation of the staining. Methods: Here we describe a modified automated EBER ISH staining protocol for xenografts which involves the substitution of reagents for detecting the EBER probe. Results: This modified protocol significantly improved the quality and speed of the staining. Conclusion: The method described here will be useful for EBER ISH staining of xenograft tissue samples.
Intelligence neurocircuitry: cortical and subcortical structures
Authors: Damiani D. , Pereira L. , Damiani D. , Nascimento A.
Published: September 2017

The authors describe the brain regions involved in the process of intelligence using as a basis, the models of the theory of frontoparietal integration (P-FIT Model). They also correlate the model described with functional areas of Brodmann, integrating them into the tertiary brain areas and address the subcortical structures involved in cognitive processes, including the memory. The studies performed by functional magnetic resonance, also unmask various regions related with intelligence, neither previously described by Brodmann nor even in conventional models of learning. The anterior insular cortex presents itself as the most recent tertiary area to be considered. Subcortical structures, when injured, mimick injuries to the cerebral cortex, demonstrating their great participation in cognition. The topographies of aphasia and the functioning mechanisms of the bearers of learning disorders, including dyslexic, dysgraphia and dyscalculic should be reconsidered. A better understanding of this topographic anatomy may clarify the mechanisms used in those individuals with cerebral lesions.
Isolation and cryopreservation of adipose tissue derived stem cells from different adipose tissues in obese patients
Authors: Freitas D. , Aguiar A. , Janz F. , Milléo F. , Favero G.
Published: September 2017

Introduction: Adult stem cells (ASCs) are a population of tissue-resident cells that have the capacity for self-renewal and differentiation into different cell types with potential for cell therapies. New approaches for ASCs isolation, including many tissue sources and new protocols that are more effective and less expensive are under investigation. Thus this work aim is to isolate, maintain in cell culture and evaluate cryopreservation protocols for adipose derived stem cells (ADSCs) from different tissues such as subcutaneous adipose tissue, visceral mesenteric and omental visceral taken from the same individual. Material and Methods: The techniques of mechanical and enzymatic dissociation were used, in order to investigate the most appropriated method to ADSCs isolation. Dimethylsulfoxide (DMSO) and dimethylformamide (DMF) in different concentrations were tested as cryoprotectors in 24, 48 and 72 hours thawing protocols. The samples were collected from obese patients with associated diseases undergoing bariatric surgery, between 30 to 45 years old. Results: Among 10 collected samples it was possible to measure cell viability from 4 patients. The higher cell rate was obtained from the visceral tissue of omentum. Conclusion: DMSO was the more efficient cryopreservant for this condition. This adipose tissue source could be explored for ADSCs isolation and future clinical investigations.
High khat dose and long-term exposure impairs spermatogenesis: experimental study using rabbit model
Authors: Nyongesa A. , Patel N. , Wango E. , Onyango D.
Published: September 2017

Introduction: This study investigated short- and long-term effects of khat (Catha edulis) on hypophyseal, epididymal and testicular morphology, body weight and temperature changes and haematological parameters of rabbits. Materials and Methods: Twenty five male New Zealand White rabbits, divided into five groups were used. First four groups were administered, via intra-gastric tube, 1.5, 4.5, 13.5 and 40.5 g/kg body weight respectively of khat extract thrice a week for 8 weeks while controls received normal saline. Short-term and long-term effects were evaluated for hypophyseal, epididymal and testicular morphology, body temperature as well as body weight changes, food consumption and haematological parameters. Data on haematological parameters, body weight changes, body temperature and food consumption was done using one-way ANOVA at 95% confidence interval using SPSS version 12.0. Results: There was vacuolation in spermatogonia and spermatocytes at high doses while epididymides and hypophyses were unaffected. A significant decrease (P<0.05) in body weight of treatment groups correlated with reduced food intake with increasing doses and chronicity of exposure. Packed cell volume, red blood cell count and haemoglobin concentration decreased while white blood cell count increased with increasing doses. Conclusion: Khat extract had direct effects on spermatogenesis compounded by poor body weight gain, hyperthermia and blood volume loss.
The 9-Item Physician Documentation Quality Instrument (PDQI-9) score is not useful in evaluating EMR (scribe) note quality in Emergency Medicine
Authors: Wang Andrew , Dunlop William , Rodda Hamish , Ben-Meir Michael , Staples Margaret , Walker Katherine J.
Published: September 2017

Background: Scribes are assisting Emergency Physicians by writing their electronic clinical notes at the bedside during consultations. They increase physician productivity and improve their working conditions. The quality of Emergency scribe notes is unevaluated and important to determine.

Objective: The primary objective of the study was to determine if the quality of Emergency Department scribe notes was equivalent to physician only notes, using the Physician Documentation Quality Instrument, Nine-item tool (PDQI-9).

Methods: This was a retrospective, observational study comparing 110 scribed to 110 non-scribed Emergency Physician notes written at Cabrini Emergency Department, Australia. Consultations during a randomised controlled trial of scribe/doctor productivity in 2016 were used. Emergency physicians and nurses rated randomly selected, blinded and de-identified notes, 2 raters per note. Comparisons were made between paired scribed and unscribed notes and between raters of each note. Characteristics of individual raters were examined. The ability of the tool to discriminate between good and poor notes was tested.

Results: The PDQI-9 tool has significant issues. Individual items had good internal consistency (Cronbach’s alpha=0.93), but there was very poor agreement between raters (Pearson’s r=0.07, p=0.270). There were substantial differences in PDQI-9 scores allocated by each rater, with some giving typically lower scores than others, F(25,206)=1.93, p=0.007. The tool was unable to distinguish good from poor notes, F(3,34)=1.15, p=0.342. There was no difference in PDQI-9 score between scribed and non-scribed notes.

Conclusions: The PDQI-9 documentation quality tool did not demonstrate reliability or validity in evaluating Emergency Medicine consultation notes. We found no evidence that scribed notes were of poorer quality than non-scribed notes, however Emergency scribe note quality has not yet been determined.

Citation: Walker KJ, Wang A, Dunlop W, Rodda H, Ben-Meir M, Staples M. The 9-Item Physician Documentation Quality Instrument (PDQI-9) score is not useful in evaluating EMR (scribe) note quality in Emergency Medicine. Appl Clin Inform 2017; 8: 981–993 https://doi.org/10.4338/ACI2017052017050080
Educational Activities for Acquiring Skills in the EEES adapted Degrees
Authors: Tolosa Santiago , Hidalgo Antonio , Ojalvo Evaristo A. , Guiberteau Agustina
Published: September 2017

The main objective of this paper is to describe the performance of a serial of training activities focused on the acquisition of skills by different groups of undergraduate students related to science as a branch of knowledge. Specifically, we used those activities where students receive knowledge, such as theoretical classes (T), computational (PC) and laboratory (PL) sessions, exercises (P), ECTS tutorials and bachelor thesis (TFG). Among the different activities, it must also be highlighted the undergraduate dissertation. The activities were conducted in different courses of the Chemistry degree of the University of Extremadura, in order to obtain information from the different competences that appear in the verification report of this title. Finally, the students filled out a survey giving their opinion about the skills acquired in each of the activities.

The results of the experience is that students achieve most of the skills considered in the title. Likewise, the results from the activities considered show that not all skills are achieved and other activities should be considered to cover those deficiencies. The activity that most contributes to the acquisition of transversal competences are laboratory practices, while for specific skills, the activities developed with large group of students (T and P) are the most significant. TFG is the activity that best covers most of competences, especially Basic and General.

 
Theoretical Biomimetics: A biological design-driven concept for creative problem-solving as applied to the optimal sequencing of active learning techniques in educational theory
Authors: Carroll La Shun L.
Published: September 2017

The article introduces the author’s concept of applying principles of biological design to drive creative problem-solving.  It provides a brief background of the field of Biomimetics, which serves as a context for the reader to appreciate how it began with an established field upon which he constructed and adapted his concept to apply to human-made intangibles.  A discussion of Theoretical Biomimetics specifies the differences between it and its predecessor.  The final section provides the opportunity to see Theoretical Biomimetics in detail applied to education theory to address a problem related to student learning in higher education and how best to establish optimized sequences to implement evidence-based active-learning techniques to fill a void in the literature demonstrating from nature what has worked.  The originality lies in the author taking a multidisciplinary approach to synergize a sequence of existing active-learning techniques and apply them to a new area in a new way. 
Efficiency in Social Enterprises
Authors: Ballester-Miquel José Carlos , Perez-Ruiz Pilar , Hernandez-Gadea Javier , De juan Jordán Hugo , Guijarro García Maria
Published: September 2017

The aim of this article is to offer a review of the impact the different methodologies of analysis have on social enterprises, focusing the study on processes that establish a greater universality based on the degree of success achieved in their social objectives, the social reinvestment of their benefits and their democratic organisation, parameters that should favour the creation of a clear and simple method, as well as adaptable to change. The systematics will allow to establish systems for the measurement of the efficiency of social enterprises, in order to both organise objective procedures of comparison and offer support when applying for public aid derived from European and national funds set up for this purpose. The quantification of the social impact of the companies that constitute the social economy is vital to assess and follow up on their social mission.
The effectiveness of graphic representation techniques used by industrial designers for the conceptual presentation of new products
Authors: Felip Miralles Francisco
Published: September 2017

Graphic techniques are very important means for designers. They can improve the conceptual presentation of new products before a client or a company, stimulating the communication of their potential, defending their benefits and making clear their commercial viability. To choose the most suitable graphic languages is essential so that the client can understand the proposal, allowing this way to establish a dialogue with the designer itself in order to improve the solution. Today the multiplication of graphic media has made it possible for the designers to have a wide range of ways to conduct and present their ideas, but it may happen that the graphic techniques chosen may not always be the most appropriate.

This work aims to demonstrate the importance of graphic expression used as a tool for presenting ideas about new products, and evaluate the effectiveness of several graphic techniques in improving the client's understanding of the product, taking into account the conceptual clarity, the representation of the mode of use, the relationship with the user and the contextualization of the product in its habitat or use environment.
Spatial datasets of radionuclide contamination in the Ukrainian Chernobyl Exclusion Zone
Authors: Kashparov Valery , Levchuk Sviatoslav , Zhurba Marina , Protsak Valentyn , Khomutinin Yuri , Beresford Nicholas , Chaplow Jacqueline
Published: September 2017

Abstract. The data set "Spatial datasets of radionuclide contamination in the Ukrainian Chernobyl Exclusion Zone" was developed to enable data collected by the Ukrainian Institute of Agricultural Radiology after the Chernobyl accident to be made publicly available. Data for samples collected between May 1986 (immediately after Chernobyl) to 2014 are presented. The dataset includes, results from comprehensive soil sampling across the Exclusion Zone (includes 137Cs, 90Sr and soil property data), Pu-isotopes activity concentrations in soils (including distribution in the soil profile), analyses of "hot" (or fuel) particles from the CEZ (data from across Europe are also included), results of monitoring in the Ivankov region adjacent to the Exclusion Zone. Recently, the CEZ was suggested as a "Radioecological Observatory" i.e., a radioactively contaminated site that will provide a focus for joint, long-term, radioecological research which will help address challenges identified for the field of radioecology. For this to be successful, relevant data for the CEZ need to be made openly available; indeed the deficiency of open data has been highlighted as one of the causes for the lack of scientific consensus with regard to published studies from within the CEZ and more recently areas affected by the 2011 Fukushima accident. The data presented here are a first step in this process. The data and supporting documentation are freely available from the Environmental Information Data Centre under the terms and conditions of the Open Government Licence: https://doi.org/10.5285/782ec845-2135-4698-8881-b38823e533bf.
A COMPARISON OF CLOSE-RANGE PHOTOGRAMMETRY USING A NON-PROFESSIONAL CAMERAWITH FIELD SURVEYING FOR VPLUME ESTIMATION
Authors: Abbaszadeh S. , Rastiveis H.
Published: September 2017

Abstract. Rapid and accurate volume calculation is one of the most important requirements in many applications such as construction and mining industries. The accuracy of a calculated volume depends on the number of collected points on the object. Increasing the number of measured points undoubtedly requires higher cost and time. On the other hand, collecting surveying points might sometimes be difficult, dangerous or impossible. The aim of this study is to evaluate the close range photogrammetry (CRP) using a non-professional camera for DEM generation in comparison to the traditional field surveying technique (TST). For this purpose, a test area in Deralok hydropower planet site was considered and the process of DEM extraction in both methods was compared. The obtained results showed that although the CRP method in contrast with TST method was more time consuming, however, this method was able to successfully measure negative slops and berms and, consequently, calculated more accurate volume. Moreover, the relative error of 0.2% was reported.
AUTOMATIC CENTERLINE EXTRACTION OF COVERD ROADS BY SURROUNDING OBJECTS FROM HIGH RESOLUTION SATELLITE IMAGES
Authors: Kamangir H. , Momeni M. , Satari M.
Published: September 2017

Abstract. This paper presents an automatic method to extract road centerline networks from high and very high resolution satellite images. The present paper addresses the automated extraction roads covered with multiple natural and artificial objects such as trees, vehicles and either shadows of buildings or trees. In order to have a precise road extraction, this method implements three stages including: classification of images based on maximum likelihood algorithm to categorize images into interested classes, modification process on classified images by connected component and morphological operators to extract pixels of desired objects by removing undesirable pixels of each class, and finally line extraction based on RANSAC algorithm. In order to evaluate performance of the proposed method, the generated results are compared with ground truth road map as a reference. The evaluation performance of the proposed method using representative test images show completeness values ranging between 77% and 93%.
VEGETATION MONITORING OF MASHHAD USING AN OBJECT-ORIENTED POST CLASSIFICATION COMPARISON METHOD
Authors: Khalili Moghadam N. , Delavar M. R. , Forati A.
Published: September 2017

Abstract. By and large, todays mega cities are confronting considerable urban development in which many new buildings are being constructed in fringe areas of these cities. This remarkable urban development will probably end in vegetation reduction even though each mega city requires adequate areas of vegetation, which is considered to be crucial and helpful for these cities from a wide variety of perspectives such as air pollution reduction, soil erosion prevention, and eco system as well as environmental protection. One of the optimum methods for monitoring this vital component of each city is multi-temporal satellite images acquisition and using change detection techniques. In this research, the vegetation and urban changes of Mashhad, Iran, were monitored using an object-oriented (marker-based watershed algorithm) post classification comparison (PCC) method. A Bi-temporal multi-spectral Landsat satellite image was used from the study area to detect the changes of urban and vegetation areas and to find a relation between these changes. The results of this research demonstrate that during 1987-2017, Mashhad urban area has increased about 22525 hectares and the vegetation area has decreased approximately 4903 hectares. These statistics substantiate the close relationship between urban development and vegetation reduction. Moreover, the overall accuracies of 85.5% and 91.2% were achieved for the first and the second image classification, respectively. In addition, the overall accuracy and kappa coefficient of change detection were assessed 84.1% and 70.3%, respectively.
DISTRIBUTED UNMIXING OF HYPERSPECTRAL DATAWITH SPARSITY CONSTRAINT
Authors: Khoshsokhan S. , Rajabi R. , Zayyani H.
Published: September 2017

Abstract. Spectral unmixing (SU) is a data processing problem in hyperspectral remote sensing. The significant challenge in the SU problem is how to identify endmembers and their weights, accurately. For estimation of signature and fractional abundance matrices in a blind problem, nonnegative matrix factorization (NMF) and its developments are used widely in the SU problem. One of the constraints which was added to NMF is sparsity constraint that was regularized by L1/2 norm. In this paper, a new algorithm based on distributed optimization has been used for spectral unmixing. In the proposed algorithm, a network including single-node clusters has been employed. Each pixel in hyperspectral images considered as a node in this network. The distributed unmixing with sparsity constraint has been optimized with diffusion LMS strategy, and then the update equations for fractional abundance and signature matrices are obtained. Simulation results based on defined performance metrics, illustrate advantage of the proposed algorithm in spectral unmixing of hyperspectral data compared with other methods. The results show that the AAD and SAD of the proposed approach are improved respectively about 6 and 27 percent toward distributed unmixing in SNR=25dB.
EVALUATION OF MOVING OBJECT DETECTION BASED ON VARIOUS INPUT
NOISE USING FIXED CAMERA
Authors: Kiaee N. , Hashemizadeh E. , Zarrinpanjeh N.
Published: September 2017

Abstract. Detecting and tracking objects in video has been as a research area of interest in the field of image processing and computer vision. This paper evaluates the performance of a novel method for object detection algorithm in video sequences. This process helps us to know the advantage of this method which is being used. The proposed framework compares the correct and wrong detection percentage of this algorithm. This method was evaluated with the collected data in the field of urban transport which include car and pedestrian in fixed camera situation. The results show that the accuracy of the algorithm will decreases because of image resolution reduction.
COMPARING INDEPENDENT COMPONENT ANALYSIS WITH PRINCIPLE COMPONENT ANALYSIS IN DETECTING ALTERATIONS OF PORPHYRY COPPER DEPOSIT (CASE STUDY: ARDESTAN AREA, CENTRAL IRAN)
Authors: Mahmoudishadi S. , Malian A. , Hosseinali F.
Published: September 2017

Abstract. The image processing techniques in transform domain are employed as analysis tools for enhancing the detection of mineral deposits. The process of decomposing the image into important components increases the probability of mineral extraction. In this study, the performance of Principal Component Analysis (PCA) and Independent Component Analysis (ICA) has been evaluated for the visible and near-infrared (VNIR) and Shortwave infrared (SWIR) subsystems of ASTER data. Ardestan is located in part of Central Iranian Volcanic Belt that hosts many well-known porphyry copper deposits. This research investigated the propylitic and argillic alteration zones and outer mineralogy zone in part of Ardestan region. The two mentioned approaches were applied to discriminate alteration zones from igneous bedrock using the major absorption of indicator minerals from alteration and mineralogy zones in spectral rang of ASTER bands. Specialized PC components (PC2, PC3 and PC6) were used to identify pyrite and argillic and propylitic zones that distinguish from igneous bedrock in RGB color composite image. Due to the eigenvalues, the components 2, 3 and 6 account for 4.26% ,0.9% and 0.09% of the total variance of the data for Ardestan scene, respectively. For the purpose of discriminating the alteration and mineralogy zones of porphyry copper deposit from bedrocks, those mentioned percentages of data in ICA independent components of IC2, IC3 and IC6 are more accurately separated than noisy bands of PCA. The results of ICA method conform to location of lithological units of Ardestan region, as well.
STACK NUMBER INFLUENCE ON THE ACCURACY OF ASTER GDEM (V2)
Authors: Mirzadeh S. M. J. , Alizadeh Naeini A. , Fatemi S. B.
Published: September 2017

Abstract. In this research, the influence of stack number (STKN) on the accuracy of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global DEM (GDEM) has been investigated. For this purpose, two data sets of ASTER and Reference DEMs from two study areas with various topography (Bomehen and Tazehabad) were used. The Results show that in both study areas, STKN of 19 results in minimum error so that this minimum error has small difference with other STKN. The analysis of slope, STKN, and error values shows that there is no strong correlation between these parameters in both study areas. For example, the value of mean absolute error increase by changing the topography and the increase of slope values and height on cells but, the changes in STKN has no important effect on error values. Furthermore, according to high values of STKN, effect of slope on elevation accuracy has practically decreased. Also, there is no great correlation between the residual and STKN in ASTER GDEM.
SPATIAL RESOLUTION ASSESSMENT OF THE TELOPS AIRBORNE TIR IMAGERY
Authors: Mousakhani S. , Eslami M. , Saadatseresht M.
Published: September 2017

Abstract. Having a high spatial resolution of Thermal InfraRed (TIR) Sensors is a challenge in remote sensing applications. Airborne high spatial resolution TIR is a novel source of data that became available lately. Recent developments in spatial resolution of the TIR sensors have been an interesting topic for scientists. TIR sensors are very sensitive to the energies emitted from objects. Past researches have been shown that increasing the spatial resolution of an airborne image will decrease the spectral content of the data and will reduce the Signal to Noise Ratio (SNR). Therefore, in this paper a comprehensive assessment is adapted to estimate an appropriate spatial resolution of the TIR data (TELOPS TIR data), in consideration of the SNR. So, firstly, a low-pass filter is applied on TIR data and the achieved products fed to a classification method for analysing of the accuracy improvement. The obtained results show that, there is no significant change in classification accuracy by applying low-pass filter. Furthermore, estimation of the appropriate spatial resolution of the TIR data is evaluated for obtaining higher spectral content and SNR. For this purpose, different resolutions of the TIR data are created and fed to the maximum likelihood classification method separately. The results illustrated in the case of using images with ground pixel size four times greater than the original image, the classification accuracy is not reduced. Also, SNR and spectral contents are improved. But the corners sharpening is declined.
OBJECT-BASED AND SUPERVISED DETECTION OF POTHOLES AND CRACKS FROM THE PAVEMENT IMAGES ACQUIRED BY UAV
Authors: Pan Y. , Zhang X. , Sun M. , Zhao Q.
Published: September 2017

Abstract. Roads are the basic element of land transportation system. After construction, the quality of road will decrease because of the aging and deterioration of the road surface. In the end, some distresses will appear on the pavement, such as the most common potholes and cracks. In order to improve the efficiency of pavement inspection, nowadays some new forms of remote sensing data without destructive effect on the pavement are widely used to detect the pavement distresses, such as digital images, LiDAR and Radar. In our study, the digital pavement images acquired by Unmanned Aerial Vehicle (UAV) and four popular supervised learning algorithms (KNN, SVM, ANN, RF) were used to distinguish between the normal pavement and pavement damages (i.e. cracks and potholes). Each of learning algorithms was given a series of different parameters, and the classification accuracy and computational time as two assessment criteria of the algorithm performance were calculated. Finally, four best models for each kind of learning algorithms were selected based on the standard of highest accuracy and minimum running time.
THE EFFECT OF SHADOW AREA ON SGM ALGORITHM AND DISPARITY MAP
REFINEMENT FROM HIGH RESOLUTION SATELLITE STEREO IMAGES
Authors: Tatar N. , Saadatseresht M. , Arefi H.
Published: September 2017

Abstract. Semi Global Matching (SGM) algorithm is known as a high performance and reliable stereo matching algorithm in photogrammetry community. However, there are some challenges using this algorithm especially for high resolution satellite stereo images over urban areas and images with shadow areas. As it can be seen, unfortunately the SGM algorithm computes highly noisy disparity values for shadow areas around the tall neighborhood buildings due to mismatching in these lower entropy areas. In this paper, a new method is developed to refine the disparity map in shadow areas. The method is based on the integration of potential of panchromatic and multispectral image data to detect shadow areas in object level. In addition, a RANSAC plane fitting and morphological filtering are employed to refine the disparity map. The results on a stereo pair of GeoEye-1 captured over Qom city in Iran, shows a significant increase in the rate of matched pixels compared to standard SGM algorithm.
A NOVEL 3D INTELLIGENT FUZZY ALGORITHM BASED ON MINKOWSKI-CLUSTERING
Authors: Toori S. , Esmaeily A.
Published: September 2017

Abstract. Assessing and monitoring the state of the earth surface is a key requirement for global change research. In this paper, we propose a new consensus fuzzy clustering algorithm that is based on the Minkowski distance. This research concentrates on Tehran's vegetation mass and its changes during 29 years using remote sensing technology. The main purpose of this research is to evaluate the changes in vegetation mass using a new process by combination of intelligent NDVI fuzzy clustering and Minkowski distance operation. The dataset includes the images of Landsat8 and Landsat TM, from 1989 to 2016. For each year three images of three continuous days were used to identify vegetation impact and recovery. The result was a 3D NDVI image, with one dimension for each day NDVI. The next step was the classification procedure which is a complicated process of categorizing pixels into a finite number of separate classes, based on their data values. If a pixel satisfies a certain set of standards, the pixel is allocated to the class that corresponds to those criteria. This method is less sensitive to noise and can integrate solutions from multiple samples of data or attributes for processing data in the processing industry. The result was a fuzzy one dimensional image. This image was also computed for the next 28 years. The classification was done in both specified urban and natural park areas of Tehran. Experiments showed that our method worked better in classifying image pixels in comparison with the standard classification methods.
A FUZZY AUTOMATIC CAR DETECTION METHOD BASED ON HIGH RESOLUTION SATELLITE IMAGERY AND GEODESIC MORPHOLOGY
Authors: Zarrinpanjeh N. , Dadrassjavan F.
Published: September 2017

Abstract. Automatic car detection and recognition from aerial and satellite images is mostly practiced for the purpose of easy and fast traffic monitoring in cities and rural areas where direct approaches are proved to be costly and inefficient. Towards the goal of automatic car detection and in parallel with many other published solutions, in this paper, morphological operators and specifically Geodesic dilation are studied and applied on GeoEye-1 images to extract car items in accordance with available vector maps. The results of Geodesic dilation are then segmented and labeled to generate primitive car items to be introduced to a fuzzy decision making system, to be verified. The verification is performed inspecting major and minor axes of each region and the orientations of the cars with respect to the road direction. The proposed method is implemented and tested using GeoEye-1 pansharpen imagery. Generating the results it is observed that the proposed method is successful according to overall accuracy of 83%. It is also concluded that the results are sensitive to the quality of available vector map and to overcome the shortcomings of this method, it is recommended to consider spectral information in the process of hypothesis verification.
A GEOGRAPHIC WEIGHTED REGRESSION FOR RURAL HIGHWAYS CRASHES MODELLING USING THE GAUSSIAN AND TRICUBE KERNELS: A CASE STUDY OF USA RURAL HIGHWAYS
Authors: Aghayari M. , Pahlavani P. , Bigdeli B.
Published: September 2017

Abstract. Based on world health organization (WHO) report, driving incidents are counted as one of the eight initial reasons for death in the world. The purpose of this paper is to develop a method for regression on effective parameters of highway crashes. In the traditional methods, it was assumed that the data are completely independent and environment is homogenous while the crashes are spatial events which are occurring in geographic space and crashes have spatial data. Spatial data have spatial features such as spatial autocorrelation and spatial non-stationarity in a way working with them is going to be a bit difficult. The proposed method has implemented on a set of records of fatal crashes that have been occurred in highways connecting eight east states of US. This data have been recorded between the years 2007 and 2009. In this study, we have used GWR method with two Gaussian and Tricube kernels. The Number of casualties has been considered as dependent variable and number of persons in crash, road alignment, number of lanes, pavement type, surface condition, road fence, light condition, vehicle type, weather, drunk driver, speed limitation, harmful event, road profile, and junction type have been considered as explanatory variables according to previous studies in using GWR method. We have compered the results of implementation with OLS method. Results showed that R2 for OLS method is 0.0654 and for the proposed method is 0.9196 that implies the proposed GWR is better method for regression in rural highway crashes.
A CONTEXT-AWARE TOURISM RECOMMENDER SYSTEM BASED ON A SPREADING ACTIVATION METHOD
Authors: Bahramian Z. , Ali Abbaspour R. , Claramunt C.
Published: September 2017

Abstract. Users planning a trip to a given destination often search for the most appropriate points of interest location, this being a non-straightforward task as the range of information available is very large and not very well structured. The research presented by this paper introduces a context-aware tourism recommender system that overcomes the information overload problem by providing personalized recommendations based on the user’s preferences. It also incorporates contextual information to improve the recommendation process. As previous context-aware tourism recommender systems suffer from a lack of formal definition to represent contextual information and user’s preferences, the proposed system is enhanced using an ontology approach. We also apply a spreading activation technique to contextualize user preferences and learn the user profile dynamically according to the user’s feedback. The proposed method assigns more effect in the spreading process for nodes which their preference values are assigned directly by the user. The results show the overall performance of the proposed context-aware tourism recommender systems by an experimental application to the city of Tehran.
THE CRASH INTENSITY EVALUATION USING GENERAL CENTRALITY CRITERIONS AND A GEOGRAPHICALLY WEIGHTED REGRESSION
Authors: Ghadiriyan Arani M. , Pahlavani P. , Effati M. , Noori Alamooti F.
Published: September 2017

Abstract. Today, one of the social problems influencing on the lives of many people is the road traffic crashes especially the highway ones. In this regard, this paper focuses on highway of capital and the most populous city in the U.S. state of Georgia and the ninth largest metropolitan area in the United States namely Atlanta. Geographically weighted regression and general centrality criteria are the aspects of traffic used for this article. In the first step, in order to estimate of crash intensity, it is needed to extract the dual graph from the status of streets and highways to use general centrality criteria. With the help of the graph produced, the criteria are: Degree, Pageranks, Random walk, Eccentricity, Closeness, Betweenness, Clustering coefficient, Eigenvector, and Straightness. The intensity of crash point is counted for every highway by dividing the number of crashes in that highway to the total number of crashes. Intensity of crash point is calculated for each highway. Then, criteria and crash point were normalized and the correlation between them was calculated to determine the criteria that are not dependent on each other. The proposed hybrid approach is a good way to regression issues because these effective measures result to a more desirable output. R2 values for geographically weighted regression using the Gaussian kernel was 0.539 and also 0.684 was obtained using a triple-core cube. The results showed that the triple-core cube kernel is better for modeling the crash intensity.
A NEW HYBRID YIN-YANG-PAIR-PARTICLE SWARM OPTIMIZATION ALGORITHM FOR UNCAPACITATED WAREHOUSE LOCATION PROBLEMS
Authors: Heidari A. A. , Kazemizade O. , Hakimpour F.
Published: September 2017

Abstract. Yin-Yang-pair optimization (YYPO) is one of the latest metaheuristic algorithms (MA) proposed in 2015 that tries to inspire the philosophy of balance between conflicting concepts. Particle swarm optimizer (PSO) is one of the first population-based MA inspired by social behaviors of birds. In spite of PSO, the YYPO is not a nature inspired optimizer. It has a low complexity and starts with only two initial positions and can produce more points with regard to the dimension of target problem. Due to unique advantages of these methodologies and to mitigate the immature convergence and local optima (LO) stagnation problems in PSO, in this work, a continuous hybrid strategy based on the behaviors of PSO and YYPO is proposed to attain the suboptimal solutions of uncapacitated warehouse location (UWL) problems. This efficient hierarchical PSO-based optimizer (PSOYPO) can improve the effectiveness of PSO on spatial optimization tasks such as the family of UWL problems. The performance of the proposed PSOYPO is verified according to some UWL benchmark cases. These test cases have been used in several works to evaluate the efficacy of different MA. Then, the PSOYPO is compared to the standard PSO, genetic algorithm (GA), harmony search (HS), modified HS (OBCHS), and evolutionary simulated annealing (ESA). The experimental results demonstrate that the PSOYPO can reveal a better or competitive efficacy compared to the PSO and other MA.
GIS-BASED SITE SELECTION FOR UNDERGROUND NATURAL RESOURCES USING FUZZY AHP-OWA
Authors: Sabzevari A. R. , Delavar M. R.
Published: September 2017

Abstract. Fuel consumption has significantly increased due to the growth of the population. A solution to address this problem is the underground storage of natural gas. The first step to reach this goal is to select suitable places for the storage. In this study, site selection for the underground natural gas reservoirs has been performed using a multi-criteria decision-making in a GIS environment. The “Ordered Weighted Average” (OWA) operator is one of the multi-criteria decision-making methods for ranking the criteria and consideration of uncertainty in the interaction among the criteria. In this paper, Fuzzy AHP_OWA (FAHP_OWA) is used to determine optimal sites for the underground natural gas reservoirs. Fuzzy AHP_OWA considers the decision maker’s risk taking and risk aversion during the decision-making process. Gas consumption rate, temperature, distance from main transportation network, distance from gas production centers, population density and distance from gas distribution networks are the criteria used in this research. Results show that the northeast and west of Iran and the areas around Tehran (Tehran and Alborz Provinces) have a higher attraction for constructing a natural gas reservoir. The performance of the used method was also evaluated. This evaluation was performed using the location of the existing natural gas reservoirs in the country and the site selection maps for each of the quantifiers. It is verified that the method used in this study is capable of modeling different decision-making strategies used by the decision maker with about 88 percent of agreement between the modeling and test data.
ON A NEW FAMILY OF KALMAN FILTER ALGORITHMS FOR INTEGRATED NAVIGATION
Authors: Mahboub V. , Saadatseresht M. , Ardalan A. A.
Published: September 2017

Abstract. Here we present a review on a new family of Kalman filter algorithms which recently developed for integrated navigation. In particular it is useful for vision based navigation due to the type of data. Here we mainly focus on three algorithms namely weighted Total Kalman filter (WTKF), integrated Kalman filter (IKF) and constrained integrated Kalman filter (CIKF). The common characteristic of these algorithms is that they can consider the neglected random observed quantities which may appear in the dynamic model. Moreover, our approach makes use of condition equations and straightforward variance propagation rules. The WTKF algorithm can deal with problems with arbitrary weight matrixes. Both of the observation equations and system equations can be dynamic-errors-in-variables (DEIV) models in the IKF algorithms. In some problems a quadratic constraint may exist. They can be solved by CIKF algorithm. Finally, we compare four algorithms WTKF, IKF, CIKF and EKF in numerical examples.