Search results for: distance image

Authors: Shih-Ting Yang, Chih-Yun Lin, Ming-Yu Li, Jhong-Ting Syue, Wei-Ming Huang

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Global positioning system (GPS) has become increasing precise in recent years, and the location-based service (LBS) has developed rapidly. Take the example of finding a parking lot (such as Parking apps). The location-based service can offer immediate information about a nearby parking lot, including the information about remaining parking spaces. However, it cannot provide expected search results according to the requirement situations of users. For that reason, this paper develops a “Location-based Search Approach according to Users’ Application Scenario” according to the location-based search and demand determination to help users obtain the information consistent with their requirements. The “Location-based Search Approach based on Users’ Application Scenario” of this paper consists of one mechanism and three kernel modules. First, in the Information Pre-processing Mechanism (IPM), this paper uses the cosine theorem to categorize the locations of users. Then, in the Information Category Evaluation Module (ICEM), the kNN (k-Nearest Neighbor) is employed to classify the browsing records of users. After that, in the Information Volume Level Determination Module (IVLDM), this paper makes a comparison between the number of users’ clicking the information at different locations and the average number of users’ clicking the information at a specific location, so as to evaluate the urgency of demand; then, the two-dimensional space is used to estimate the application situations of users. For the last step, in the Location-based Search Module (LBSM), this paper compares all search results and the average number of characters of the search results, categorizes the search results with the Manhattan Distance, and selects the results according to the application scenario of users. Additionally, this paper develops a Web-based system according to the methodology to demonstrate practical application of this paper. The application scenario-based estimate and the location-based search are used to evaluate the type and abundance of the information expected by the public at specific location, so that information demanders can obtain the information consistent with their application situations at specific location.

Keywords: data mining, knowledge management, location-based service, user application scenario

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Authors: Atiq Zaman

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The high contamination rate in the recycling waste stream is one of the major problems in Australia. In addition, a lack of reliable waste data makes it even more difficult for designing and implementing an effective waste management plan. This article conceptualizes the opportunity to improve resource productivity by integrating smart resource tracking system (SRTS) into the Australian household waste management system. The application of the smart resource tracking system will be implemented through the following ways: (i) mobile application-based resource tracking system used to measure the household’s material flow; (ii) RFID, smart image and weighing system used to track waste generation, recycling and contamination; (iii) informing and motivating manufacturer and retailers to improve their problematic products’ packaging; and (iv) ensure quality and reliable data through open-sourced cloud data for public use. The smart mobile application, imaging, radio-frequency identification (RFID) and weighing technologies are not new, but the very straightforward idea of using these technologies in the household resource consumption, waste bins and collection trucks will open up a new era of accurately measuring and effectively managing our waste. The idea will bring the most urgently needed reliable, data and clarity on household consumption, recycling behaviour and waste management practices in the context of available local infrastructure and policies. Therefore, the findings of this study would be very important for decision makers to improve resource productivity in the waste industry by using smart resource tracking system.

Keywords: smart devices, mobile application, smart sensors, resource tracking, waste management, resource productivity

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Authors: Denise C. I. Maior-Barron

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This conference presentation proposes to discuss the Japanese tourist perception of Marie Antoinette, at the heritage site which represents the home par excellence of the last Queen of France: Petit Trianon, Versailles. The underpinning analysis has a two-fold aim of firstly identifying the elements that contributed at the said perception and secondly of placing this in the wider context of tabi (travel) culture. The contribution of the presentation lies in its relevance to the analysis of postmodern trends of Japanese travel culture in relation to the consumption of European cultural heritage, through an insight into Japanese contemporary perception of heritage sites and their associated historical figures subject to controversy. Based upon the author’s doctoral studies field research at Petit Trianon - survey led in situ between 2010-2012, applied with the questionnaire method on a total of 307 respondents out of which 53 Japanese nationals - the media sources that were revealed to have had a direct influence on these nationals’ perception of Marie Antoinette, were Riyoko Ikeda’s shōjo manga La Rose de Versailles (1972) and Sofia Coppola’s film Marie-Antoinette (2006). The interpretation of the survey results through an assessment of visitor discourse determined the research methodology to be qualitative as opposed to quantitative, thus what confirmed the empirical hypothesis of the survey was a pattern of perception instead of percentages. Consequently, the interpretation focused on the answers to the questions relating to the image of Marie Antoinette in relation to historical knowledge, cultural background and last but not least media influences.

Keywords: cultural heritage, manga, film, tabi

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Authors: Adel Menchawy, Noha Labib

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Many cities have quarters that confer on them sense of identity and place through its cultural history. They are often vital part of the cities charm and appeal, their functional and visual qualities are important to the city’s image and identity. Brownfield sites present an important part of our built landscape. They provide tangible and intangible links to our past and have great potential to play significant roles in the future of our cities, towns and rural environments. Brownfield sites are places that were previously industrial factories or areas that might have had waste kept at that location or been exposed to many types of hazards. Thus its redevelopment revitalizes and strengthens towns and communities as it helps in economic growth, builds community pride and protects public health and the environment Three case studies are discussed in this paper; the first one is the city of Sterling which was developed and revitalized entirely and became a city with identity after it was derelict, the Second is the city of Castlefield with was a place no one was eager to visit now it became a touristic area. And finally the city of Cleveland which adopted a strategy that transferred it from being a polluted, derelict place into a mixed use development city Brownfield revitalization offers a great opportunity to transfer the city from being derelict, useless and contaminated into a place where tourists would love to come. Also it will increase the economy of the place, increase the social level, it can improve energy efficiency, reduce natural consumption, clean air, water and land and take advantage of existing buildings and sites and transfers them into an adaptive reuse after being remediated

Keywords: Brownfield Revitalization, Sustainable Brownfield, Historical conservation, Adaptive reuse

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Authors: Mazifah Simis, Azahan Awang, Kadir Arifin

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The brownfield regeneration is being implemented in developped countries. However, as a group 1 developing country in the South East Asia, the rapid development and increasing number of urban population in Malaysia have urged the needs to incorporate the brownfield regeneration into its physical planning development. The increasing number of urban ex-landfills is seen as a new resource that could overcome the issues of inadequate urban green space provisions. With regards to the new development approach in urban planning, this perception study aims to identify the sustainable planning approach based on what the stakeholders have in mind. Respondents consist of 375 local communities within four urban ex-landfill areas and 61 landscape architect and town planner officers in the Malaysian Local Authorities. Three main objectives are set to be achieved, which are (i) to identify ex-landfill issues that need to be overcome prior to the ex-landfill redevelopment (ii) to identify the most suitable types of ex-landfill redevelopment, and (iii) to identify the priority function for ex-landfill redevelopment as the public parks. From the data gathered through the survey method, the order of priorities based on stakeholders' perception was produced. The results show different perception among the stakeholders, but they agreed to the development of the public park as the main development. Hence, this study attempts to produce an integrated approach as a model for sustainable ex-landfill redevelopment that could be accepted by the stakeholders as a beneficial future development that could change the image of 296 ex-landfills in Malaysia into the urban public parks by the year 2020.

Keywords: brownfield regeneration, ex-landfill redevelopment, integrated approach, stakeholders' perception

Procedia PDF Downloads 347

Authors: V. Thomas, O. Delaune, W. Hennig, S. Hoover

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Measurement of radioactive isotopes of atmospheric xenon is used to detect, locate and identify any confined nuclear tests as part of the Comprehensive Nuclear Test-Ban Treaty (CTBT). In this context, the Alternative Energies and French Atomic Energy Commission (CEA) has developed a fixed device to continuously measure the concentration of these fission products, the SPALAX process. During its atmospheric transport, the radioactive xenon will undergo a significant dilution between the source point and the measurement station. Regarding the distance between fixed stations located all over the globe, the typical volume activities measured are near 1 mBq m⁻³. To avoid the constraints induced by atmospheric dilution, the development of a mobile detection system is in progress; this system will allow on-site measurements in order to confirm or infringe a suspicious measurement detected by a fixed station. Furthermore, this system will use beta/gamma coincidence measurement technique in order to drastically reduce environmental background (which masks such activities). The detector prototype consists of a gas cell surrounded by two large silicon wafers, coupled with two square NaI(Tl) detectors. The gas cell has a sample volume of 30 cm³ and the silicon wafers are 500 µm thick with an active surface area of 3600 mm². In order to minimize leakage current, each wafer has been segmented into four independent silicon pixels. This cell is sandwiched between two low background NaI(Tl) detectors (70x70x40 mm³ crystal). The expected Minimal Detectable Concentration (MDC) for each radio-xenon is in the order of 1-10 mBq m⁻³. Three 4-channels digital acquisition modules (Pixie-NET) are used to process all the signals. Time synchronization is ensured by a dedicated PTP-network, using the IEEE 1588 Precision Time Protocol. We would like to present this system from its simulation to the laboratory tests.

Keywords: beta/gamma coincidence technique, low level measurement, radioxenon, silicon pixels

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Authors: Iwan Cony Setiadi, Aulia M. T. Nasution

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The multispectral imaging (MSI) technique has been used for skin analysis, especially for distant mapping of in-vivo skin chromophores by analyzing spectral data at each reflected image pixel. For ergonomic purpose, our multispectral imaging system is decomposed in two parts: a light source compartment based on LED with 11 different wavelenghts and a monochromatic 8-Bit CCD camera with C-Mount Objective Lens. The software based on GUI MATLAB to control the system was also developed. Our system provides 11 monoband images and is coupled with a software reconstructing hyperspectral cubes from these multispectral images. In this paper, we proposed a new method to build a hyperspectral reflectance cube based on artificial neural network algorithm. After preliminary corrections, a neural network is trained using the 32 natural color from X-Rite Color Checker Passport. The learning procedure involves acquisition, by a spectrophotometer. This neural network is then used to retrieve a megapixel multispectral cube between 380 and 880 nm with a 5 nm resolution from a low-spectral-resolution multispectral acquisition. As hyperspectral cubes contain spectra for each pixel; comparison should be done between the theoretical values from the spectrophotometer and the reconstructed spectrum. To evaluate the performance of reconstruction, we used the Goodness of Fit Coefficient (GFC) and Root Mean Squared Error (RMSE). To validate reconstruction, the set of 8 colour patches reconstructed by our MSI system and the one recorded by the spectrophotometer were compared. The average GFC was 0.9990 (standard deviation = 0.0010) and the average RMSE is 0.2167 (standard deviation = 0.064).

Keywords: multispectral imaging, reflectance cube, spectral reconstruction, artificial neural network

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Authors: Salah Hadjout, Mohamed Zouidi

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In Algeria, several works carried out in recent years have shown the importance of fusarium head blight in durum wheat. Indeed, this disease is caused by a complex of Fusarium genus pathogens. The research carried out reports that F. culmorum is the main species infecting cereals. These informations motivated our interest in the field evaluation of the behavior of some durum wheat genotypes (parental varieties and lines) with regard to fusarium head blight, mainly caused by four F. culmorum isolates. Our research work focused on following the evolution of symptom development throughout the grain filling, after artificial inoculation of ears by Fusarium isolates in order to establish a first image on the differences in genotype behavior to fusarium haed blight. Field disease assessment criteria are: disease assessment using a grading scale, thousand grain weight measurement and AUDPC. The results obtained revealed that the varieties and lines resulting from crosses had a quite different level of sensitivity to F. culmorum species and no genotype showed complete resistance in our culture conditions. Among the material tested, some lines showed higher resistance than their parents. The results also show a slight behavioral variability also linked to the aggressiveness of the Fusarium species studied in this work. Our results open very important research perspectives on fusarium head blight, in particular the search for toxins produced by Fusarium species.

Keywords: fusarium head blight, durum wheat, Fusarium culmorum, field disease assessment criteria, Algeria

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Authors: Anna Vanderbruggen, Kai Bachmann, Martin Rudolph, Rodrigo Serna

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Recycling of lithium-ion batteries has attracted a lot of attention in recent years and focuses primarily on valuable metals such as cobalt, nickel, and lithium. Despite the growth in graphite consumption and the fact that it is classified as a critical raw material in the European Union, USA, and Australia, there is little work focusing on graphite recycling. Thus, graphite is usually considered waste in recycling treatments, where graphite particles are concentrated in the “black mass”, a fine fraction below 1mm, which also contains the foils and the active cathode particles such as LiCoO2 or LiNiMnCoO2. To characterize the material, various analytical methods are applied, including X-Ray Fluorescence (XRF), X-Ray Diffraction (XRD), Atomic Absorption Spectrometry (AAS), and SEM-based automated mineralogy. The latter consists of the combination of a scanning electron microscopy (SEM) image analysis and energy-dispersive X-ray spectroscopy (EDS). It is a powerful and well-known method for primary material characterization; however, it has not yet been applied to secondary material such as black mass, which is a challenging material to analyze due to fine alloy particles and to the lack of an existing dedicated database. The aim of this research is to characterize the black mass depending on the metals recycling process in order to understand the liberation mechanisms of the active particles from the foils and their effect on the graphite particle surfaces and to understand their impact on the subsequent graphite flotation. Three industrial processes were taken into account: purely mechanical, pyrolysis-mechanical, and mechanical-hydrometallurgy. In summary, this article explores various and common challenges for graphite and secondary material characterization.

Keywords: automated mineralogy, characterization, graphite, lithium ion battery, recycling

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Authors: Jameela Ali, Hamid A. Jalab, Loay E. George, Abdul Rahim Ahmad, Azizah Suliman, Karim Al-Jashamy

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Red blood cells (RBC) are the most common types of blood cells and are the most intensively studied in cell biology. The lack of RBCs is a condition in which the amount of hemoglobin level is lower than normal and is referred to as “anemia”. Abnormalities in RBCs will affect the exchange of oxygen. This paper presents a comparative study for various techniques for classifyig the red blood cells as normal, or abnormal (anemic) using WEKA. WEKA is an open source consists of different machine learning algorithms for data mining applications. The algorithm tested are Radial Basis Function neural network, Support vector machine, and K-Nearest Neighbors algorithm. Two sets of combined features were utilized for classification of blood cells images. The first set, exclusively consist of geometrical features, was used to identify whether the tested blood cell has a spherical shape or non-spherical cells. While the second set, consist mainly of textural features was used to recognize the types of the spherical cells. We have provided an evaluation based on applying these classification methods to our RBCs image dataset which were obtained from Serdang Hospital-Malaysia, and measuring the accuracy of test results. The best achieved classification rates are 97%, 98%, and 79% for Support vector machines, Radial Basis Function neural network, and K-Nearest Neighbors algorithm respectively

Keywords: red blood cells, classification, radial basis function neural networks, suport vector machine, k-nearest neighbors algorithm

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Authors: Rao Fu, Jie Chen, Shutian Zeng, Yiping Zhuang, Agus Sudjianto

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Generative Adversarial Net (GAN) has proved to be a powerful machine learning tool in image data analysis and generation. In this paper, we propose to use Conditional Generative Adversarial Net (CGAN) to learn and simulate time series data. The conditions include both categorical and continuous variables with different auxiliary information. Our simulation studies show that CGAN has the capability to learn different types of normal and heavy-tailed distributions, as well as dependent structures of different time series. It also has the capability to generate conditional predictive distributions consistent with training data distributions. We also provide an in-depth discussion on the rationale behind GAN and the neural networks as hierarchical splines to establish a clear connection with existing statistical methods of distribution generation. In practice, CGAN has a wide range of applications in market risk and counterparty risk analysis: it can be applied to learn historical data and generate scenarios for the calculation of Value-at-Risk (VaR) and Expected Shortfall (ES), and it can also predict the movement of the market risk factors. We present a real data analysis including a backtesting to demonstrate that CGAN can outperform Historical Simulation (HS), a popular method in market risk analysis to calculate VaR. CGAN can also be applied in economic time series modeling and forecasting. In this regard, we have included an example of hypothetical shock analysis for economic models and the generation of potential CCAR scenarios by CGAN at the end of the paper.

Keywords: conditional generative adversarial net, market and credit risk management, neural network, time series

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Authors: Saoussen Dhib, Chris M. Mannaerts, Zoubeida Bargaoui, Ben H. P. Maathuis, Petra Budde

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In this study, a new method to delineate rain areas in northern Tunisia is presented. The proposed approach is based on the blending of the geostationary Meteosat Second Generation (MSG) infrared channel (IR) with the low-earth orbiting passive Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). To blend this two products, we need to apply two main steps. Firstly, we have to identify the rainy pixels. This step is achieved based on a classification using MSG channel IR 10.8 and the water vapor WV 0.62, applying a threshold on the temperature difference of less than 11 Kelvin which is an approximation of the clouds that have a high likelihood of precipitation. The second step consists on fitting the relation between IR cloud top temperature with the TMI rain rates. The correlation coefficient of these two variables has a negative tendency, meaning that with decreasing temperature there is an increase in rainfall intensity. The fitting equation will be applied for the whole day of MSG 15 minutes interval images which will be summed. To validate this combined product, daily extreme rainfall events occurred during the period 2007-2009 were selected, using a threshold criterion for large rainfall depth (> 50 mm/day) occurring at least at one rainfall station. Inverse distance interpolation method was applied to generate rainfall maps for the drier summer season (from May to October) and the wet winter season (from November to April). The evaluation results of the estimated rainfall combining MSG and TMI was very encouraging where all the events were detected rainy and the correlation coefficients were much better than previous evaluated products over the study area such as MSGMPE and PERSIANN products. The combined product showed a better performance during wet season. We notice also an overestimation of the maximal estimated rain for many events.

Keywords: combination, extreme, rainfall, TMI-MSG, Tunisia

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Authors: Rachida Benabbou, Sang Hun Park, Hee Chung Lee

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The world’s population is increasing with unprecedented speed, leading to fast growing urbanization pace. Cities since the Industrial revolution had evolved to fit the growing demand on infrastructure, roads, transportation, and housing. Through this evolution, cities had grown into grey, polluted, and vehicle-oriented urban areas with a significant lack of green spaces. Consequently, we ended up with low quality of life for citizens. Therefore, many cities, nowadays, are revising the way we think urbanism and try to grow into more livable and citizen-friendly, by creating change from the inside out. Thus, cities are trying to bring back nature in its crowded grey centers and regenerate many urban areas as green public spaces not only as a way to give new breath to the city, but also as a way to create change either in the environmental, social and economic levels. The city of Seoul is one of the fast growing global cities. Its population is over 12 million and it is expected to continue to grow to a point where the quality of life may seriously deteriorate. As most green areas in Seoul are located in the suburbs in form of mountains, the city’s urban areas suffer from lack of accessible green spaces in a walking distance. Understanding the gravity and consequences of this issue, Seoul city is undergoing major changes. Many of its projects are oriented to be green public spaces where citizens can enjoy the public life in healthy outdoors. The aim of this paper is to explore the results of urban conversions into green public spaces. Starting with different locations, nature, size, and scale, these conversions can lead to significant change in the surrounding areas, thus can be used as an efficient tool of regeneration for urban areas. Through a comparative analysis of three different types of urban conversions projects in the city of Seoul, we try to show the positive urban influence of the outcomes, in order to encourage cities to use green spaces as a strategic tool for urban regeneration and redevelopment.

Keywords: urban conversion, green public space, change, urban regeneration

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Authors: Yingisani Chabalala, Elhadi Adam, Khalid Adem Ali

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Mapping smallholder fruit plantations using optical data is challenging due to morphological landscape heterogeneity and crop types having overlapped spectral signatures. Furthermore, cloud covers limit the use of optical sensing, especially in subtropical climates where they are persistent. This research assessed the effectiveness of Sentinel-1 (S1) and Sentinel-2 (S2) data for mapping fruit trees and co-existing land-use types by using support vector machine (SVM) and random forest (RF) classifiers independently. These classifiers were also applied to fused data from the two sensors. Feature ranks were extracted using the RF mean decrease accuracy (MDA) and forward variable selection (FVS) to identify optimal spectral windows to classify fruit trees. Based on RF MDA and FVS, the SVM classifier resulted in relatively high classification accuracy with overall accuracy (OA) = 0.91.6% and kappa coefficient = 0.91% when applied to the fused satellite data. Application of SVM to S1, S2, S2 selected variables and S1S2 fusion independently produced OA = 27.64, Kappa coefficient = 0.13%; OA= 87%, Kappa coefficient = 86.89%; OA = 69.33, Kappa coefficient = 69. %; OA = 87.01%, Kappa coefficient = 87%, respectively. Results also indicated that the optimal spectral bands for fruit tree mapping are green (B3) and SWIR_2 (B10) for S2, whereas for S1, the vertical-horizontal (VH) polarization band. Including the textural metrics from the VV channel improved crop discrimination and co-existing land use cover types. The fusion approach proved robust and well-suited for accurate smallholder fruit plantation mapping.

Keywords: smallholder agriculture, fruit trees, data fusion, precision agriculture

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Authors: Júlia Cristina Bonaldo, Christophe L. Martin, Martiniano Piccico, Keith Beale, Roop Kishore, Severine Romero-Baivier

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Refractory composite materials employed in steel casting applications are prone to cracking and material damage because of the very high operating temperature (thermal shock) and mismatched properties of the constituent phases. The fracture behavior of a model MgO-C composite refractory is investigated to quantify and characterize its thermal shock resistance, employing a cold crushing test and Brazilian test with fractographic analysis. The discrete element method (DEM) is used to generate numerical refractory composites. The composite in DEM is represented by an assembly of bonded particle clusters forming perfectly spherical aggregates and single spherical particles. For the stresses to converge with a low standard deviation and a minimum number of particles to allow reasonable CPU calculation time, representative volume element (RVE) numerical packings are created with various numbers of particles. Key microscopic properties are calibrated sequentially by comparing stress-strain curves from crushing experimental data. Comparing simulations with experiments also allows for the evaluation of crack propagation, fracture energy, and strength. The crack propagation during Brazilian experimental tests is monitored with digital image correlation (DIC). Simulations and experiments reveal three distinct types of fracture. The crack may spread throughout the aggregate, at the aggregate-matrix interface, or throughout the matrix.

Keywords: refractory composite, fracture mechanics, crack propagation, DEM

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Authors: Anjaly Joseph, Elezebeth Mathews

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Transportation and urban planning is the least recognised area for physical activity promotion in India, unlike developed regions. Identifying the preferred transportation modalities and factors associated with it is essential to address these lacunae. The objective of the study was to assess the prevalence of modes of transportation to work, and its correlates among working adults in Ernakulam District, Kerala. A cross sectional study was conducted among 350 working individuals in the age group of 18-60 years, selected through multi-staged stratified random sampling in Ernakulam district of Kerala. The inclusion criteria were working individuals 18-60 years, workplace at a distance of more than 1 km from the home and who worked five or more days a week. Pregnant women/women on maternity leave and drivers (taxi drivers, autorickshaw drivers, and lorry drivers) were excluded. An interview schedule was used to capture the modes of transportation namely, public, private and active transportation, socio demographic details, travel behaviour, anthropometric measurements and health status. Nearly two-thirds (64 percent) of them used private transportation to work, while active commuters were only 6.6 percent. The correlates identified for active commuting compared to other modes were low socio-economic status (OR=0.22, CI=0.5-0.85) and presence of a driving license (OR=4.95, CI= 1.59-15.45). The correlates identified for public transportation compared to private transportation were female gender (OR= 17.79, CI= 6.26-50.31), low income (OR=0.33, CI= 0.11-0.93), being unmarried (OR=5.19, CI=1.46-8.37), presence of no or only one private vehicle in the house (OR=4.23, CI=1.24-20.54) and presence of convenient public transportation facility to workplace (OR=3.97, CI= 1.66-9.47). The association between body mass index (BMI) and public transportation were explored and found that public transport users had lesser BMI than private commuters (OR=2.30, CI=1.23-4.29). Policies that encourage active and public transportation needs to be introduced such as discouraging private vehicle through taxes, introduction of convenient and safe public transportation facility, walking/cycling paths, and paid parking facility.

Keywords: active transportation, correlates, India, public transportation, transportation modes

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Authors: Nazari Maryam, Gorji Saman

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For most competitions, athletes usually engage in a process called rapid weight loss (RWL) and subsequent rapid weight gain (RWG) in the days preceding the event. Besides the perfection of performance, weight regulation mediates a self-image of being “a real athlete” which is mentally important as a part of the pre-competition preparation. This feeling enhances the focus and commitment of the athlete. There is a large body of evidence that weight loss, particularly in combat sports, results in several health benefits. However, intentional weight loss beyond normal levels might have unknown negative special effects on the immune system. As the results show, a high prevalence (50%) of RWL is happening among combat athletes. It seems that energy deprivation and intense exercise to reach RWL results in altered blood cell distribution through modification of body composition that, in turn, changes B and T-Lymphocyte and/or CD4 T-Helper response. Moreover, it may diminish IgG antibody levels and modulate IgG glycosylation after this course. On the other hand, some studies show suppression of signaling and regulation of IgE antibody and chemokine production are responsible for immunodeficiency following a period of low-energy availability. Some researchers hypothesize that severe glutamine depletion, which occurs during exercise and calorie restriction, is responsible for this immune system weakness. However, supplementation by this amino acid is not prescribed yet. Therefore, weight loss is achieved not only through chronic strategies (body fat losses) but also through acute manipulations prior to competition should be supervised by a sports nutritionist to minimize side effects on the immune system and other body systems.

Keywords: athletes, immune system, rapid weight loss, weight loss strategies

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Authors: Ni̇sa Yeni̇kalayci, Türkan Aybi̇ke Akarca

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The ability of correlation the number and space relations, one of the basic scientific process skills, is being used in the transformation of a two-dimensional object into a three-dimensional image or in the expression of symmetry axes of the object. With this research, it is aimed to determine the ability of science students to establish number and space relations. The research was carried out with a total of 90 students studying in the first semester of the Science Education program of a state university located in the Turkey’s Black Sea Region in the fall semester of 2017-2018 academic year. An ‘Integrative Perception Test (IPT)’ was designed by the researchers to collect the data. Within the scope of IPT, the courses and workbooks specific to the field of science were scanned and the ones without symmetrical structure from the visual items belonging to the ‘Physics - Chemistry – Biology’ sub-fields were selected and listed. During the application, it was expected that students would imagine and draw images of the missing half of the visual items that were given incomplete in the first place. The data obtained from the test in which there are 30 images or pictures in total (f Physics = 10, f Chemistry = 10, f Biology = 10) were analyzed descriptively based on the drawings created by the students as ‘complete (2 points), incomplete/wrong (1 point), empty (0 point)’. For the teaching of new concepts in small aged groups, images or pictures showing symmetrical structures and similar applications can also be used.

Keywords: integrative perception, number and space relations, science education, scientific process skills

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Authors: Ahmet Erten, Adil Mustafa, Ayşenur Eser, Özlem Yalçın

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We present a new viscometer based on a microfluidic chip with elastic high aspect ratio micropillar arrays. The displacement of pillar tips in flow direction can be used to analyze viscosity of liquid. In our work, Computational Fluid Dynamics (CFD) is used to analyze pillar displacement of various micropillar array configurations in flow direction at different viscosities. Following CFD optimization, micro-CNC based rapid prototyping is used to fabricate molds for microfluidic chips. Microfluidic chips are fabricated out of polydimethylsiloxane (PDMS) using soft lithography methods with molds machined out of aluminum. Tip displacements of micropillar array (300 µm in diameter and 1400 µm in height) in flow direction are recorded using a microscope mounted camera, and the displacements are analyzed using image processing with an algorithm written in MATLAB. Experiments are performed with water-glycerol solutions mixed at 4 different ratios to attain 1 cP, 5 cP, 10 cP and 15 cP viscosities at room temperature. The prepared solutions are injected into the microfluidic chips using a syringe pump at flow rates from 10-100 mL / hr and the displacement versus flow rate is plotted for different viscosities. A displacement of around 1.5 µm was observed for 15 cP solution at 60 mL / hr while only a 1 µm displacement was observed for 10 cP solution. The presented viscometer design optimization is still in progress for better sensitivity and accuracy. Our microfluidic viscometer platform has potential for tailor made microfluidic chips to enable real time observation and control of viscosity changes in biological or chemical reactions.

Keywords: Computational Fluid Dynamics (CFD), high aspect ratio, micropillar array, viscometer

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Authors: Zeinab Mirabulqasemi, Gholamali Hatam

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This article discusses the significance of mural paintings in Iranian culture, particularly within the context of religious tombs known as Imamzadehs. These tombs, dedicated to Shiite imams and other revered religious figures, serve as important religious and communal spaces. The tradition of tomb construction evolved from early Islamic practices, gradually transforming burial sites into places of worship. In the Gilan region of Iran, these tombs hold a revered status, serving as focal points for religious observances and social gatherings. The murals adorning these tombs often depict religious motifs, with a particular emphasis on events like the Day of Judgment and the martyrdom of the Imams, notably the saga of Ashura. These paintings also reflect the community's social perspectives and historical allegiances. Various architectural styles are employed in constructing these tombs, including Islamic, traditional, local, and aesthetic architecture. However, the region's climate poses challenges to the preservation of these structures and their murals. Despite these challenges, efforts are made to document and preserve these artworks to ensure their accessibility for future generations. This research also studies tomb paintings by adopting a multifaceted approach, including library research, image analysis, and field research. Finally, it examines the portrayal of significant figures such as the Shiite imams, prophets, and Imamzadehs within these murals, highlighting their thematic significance and cultural importance.

Keywords: cultural ritual, Shiite imams, mural, belief foundations, religious paintings

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Authors: Dusanee Suwankhong, Pranee Liamputtong

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Breast surgery leaves undesirable scars to all women who experienced mastectomy, despite the fact that this could be a principle approach to save one life. This paper explores how Thai women living with breast cancer perceived and experienced a scarred body after breast surgery. In-depth interviews and drawing methods were employed among 20 women diagnosed with breast cancer. The interviewed data were analysed using thematic analysis method. The results showed that all women with breast cancer who underwent breast surgery perceived and experienced scar as a persisting and visible side-effect. This disfigurement appearance presented a negative image of feminine identity and led to emotional burdens among women. They responded to being scarred in different ways relating to their perceptions of body and changes. The older group had less embarrassed feelings towards being scarred comparing to the younger one. All women tried to seek means to cope with such physical impairment and keep balance life related to their condition. For example, they relied on Buddhism practice and tried to heal the keloid using natural products. Scars appeared to be an unpleasant effect for women who underwent breast mastectomy. Nurses and health care professionals in the local health service sectors need to pay close attention to how the women see the scarred body and their experiences of living with the distorted feminine appearance, and to provide sensitive support that meets the needs of these vulnerable women. The suitable supports can reduce the sense of embarrassment and increase their sense of self-confidence about their social femininity.

Keywords: breast surgery, emotional response, qualitative study, scars, Thai women

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Authors: Jacintha Menezes, Ramalingam Dharmalingam, Palaiahnakote Shivakumara

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In the recent years, Omani acid lime cultivation and production has been affected by Citrus greening or Huanglongbing (HLB) disease. HLB disease is one of the most destructive diseases for citrus, with no remedies or countermeasures to stop the disease. Currently used Polymerase chain reaction (PCR) and enzyme-linked immunosorbent assay (ELISA) HLB detection tests require lengthy and labor-intensive laboratory procedures. Furthermore, the equipment and staff needed to carry out the laboratory procedures are frequently specialized hence making them a less optimal solution for the detection of the disease. The current research uses hyperspectral imaging technology for automatic detection of citrus trees with HLB disease. Omani citrus tree leaf images were captured through portable Specim IQ hyperspectral camera. The research considered healthy, nutrition deficient, and HLB infected leaf samples based on the Polymerase chain reaction (PCR) test. The highresolution image samples were sliced to into sub cubes. The sub cubes were further processed to obtain RGB images with spatial features. Similarly, RGB spectral slices were obtained through a moving window on the wavelength. The resized spectral-Spatial RGB images were given to Convolution Neural Networks for deep features extraction. The current research was able to classify a given sample to the appropriate class with 92.86% accuracy indicating the effectiveness of the proposed techniques. The significant bands with a difference in three types of leaves are found to be 560nm, 678nm, 726 nm and 750nm.

Keywords: huanglongbing (HLB), hyperspectral imaging (HSI), · omani citrus, CNN

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Authors: P. Bauer, K. Mougin, V. Vignal, A. Buch, P. Ponthiaux, D. Faye

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Nowadays, noble metallic nanostructures with unique morphology are widely used as new sensors due to their fascinating optical, electronic and catalytic properties. Among various shapes, dendritic nanostructures have attracted much attention because of their large surface-to-volume ratio, high sensitivity and special texture with sharp tips and nanoscale junctions. Several methods have been developed to fabricate those specific structures such as electrodeposition, photochemical way, seed-mediated growth or wet chemical method. The present study deals with a novel approach for a controlled growth pattern-directed organisation of Au flower-like crystals (NFs) deposited onto stainless steel plates to achieve large-scale functional surfaces. This technique consists in the deposition of a soft nanoporous template on which Au NFs are grown by electroplating and seed-mediated method. Size, morphology, and interstructure distance have been controlled by a site selective nucleation process. Dendritic Au nanostructures have appeared as excellent Raman-active candidates due to the presence of very sharp tips of multi-branched Au nanoparticles that leads to a large local field enhancement and a good SERS sensitivity. In addition, these structures have also been used as electrochemical sensors to detect traces of molecules present in a solution. A correlation of the number of active sites on the surface and the current charge by both colorimetric method and cyclic voltammetry of gold structures have allowed a calibration of the system. This device represents a first step for the fabrication of MEMs platform that could ultimately be integrated into a lab-on-chip system. It also opens pathways to several technologically large-scale nanomaterials fabrication such as hierarchically ordered crystal architectures for sensor applications.

Keywords: dendritic, electroplating, gold, template

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Authors: Melis Inalpulat, Tugce Civelek, Unal Kizil, Levent Genc

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Livestock production is one of the most important components of rural economy. Due to the urban expansion, rural areas close to expanding cities transform into urban districts during the time. However, the legislations have some restrictions related to livestock farming in such administrative units since they tend to create environmental concerns like odor problems resulted from excessive manure production. Therefore, the existing animal operations should be moved from the settlement areas. This paper was focused on determination of suitable lands for livestock production in Canakkale province of Turkey using remote sensing (RS) data and GIS techniques. To achieve the goal, Formosat 2 and Landsat 8 imageries, Aster DEM, and 1:25000 scaled soil maps, village boundaries, and village livestock inventory records were used. The study was conducted using suitability analysis which evaluates the land in terms of limitations and potentials, and suitability range was categorized as Suitable (S) and Non-Suitable (NS). Limitations included the distances from main and crossroads, water resources and settlements, while potentials were appropriate values for slope, land use capability and land use land cover status. Village-based S land distribution results were presented, and compared with livestock inventories. Results showed that approximately 44230 ha area is inappropriate because of the distance limitations for roads and etc. (NS). Moreover, according to LULC map, 71052 ha area consists of forests, olive and other orchards, and thus, may not be suitable for building such structures (NS). In comparison, it was found that there are a total of 1228 ha S lands within study area. The village-based findings indicated that, in some villages livestock production continues on NS areas. Finally, it was suggested that organized livestock zones may be constructed to serve in more than one village after the detailed analysis complemented considering also political decisions, opinion of the local people, etc.

Keywords: GIS, livestock, LULC, remote sensing, suitable lands

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Authors: Vaia N. Koukou, Niki D. Martini, George P. Fountos, Christos M. Michail, Athanasios Bakas, Ioannis S. Kandarakis, George C. Nikiforidis

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Various substitute materials of calcifications are used in phantom measurements and simulation studies in mammography. These include calcium carbonate, calcium oxalate, hydroxyapatite and aluminum. The aim of this study is to compare the contrast-to-noise ratio (CNR) values of the different calcification types using the dual energy method. The constructed calcification phantom consisted of three different calcification types and thicknesses: hydroxyapatite, calcite and calcium oxalate of 100, 200, 300 thicknesses. The breast tissue equivalent materials were polyethylene and polymethyl methacrylate slabs simulating adipose tissue and glandular tissue, respectively. The total thickness was 4.2 cm with 50% fixed glandularity. The low- (LE) and high-energy (HE) images were obtained from a tungsten anode using 40 kV filtered with 0.1 mm cadmium and 70 kV filtered with 1 mm copper, respectively. A high resolution complementary metal-oxide-semiconductor (CMOS) active pixel sensor (APS) X-ray detector was used. The total mean glandular dose (MGD) and entrance surface dose (ESD) from the LE and HE images were constrained to typical levels (MGD=1.62 mGy and ESD=1.92 mGy). On average, the CNR of hydroxyapatite calcifications was 1.4 times that of calcite calcifications and 2.5 times that of calcium oxalate calcifications. The higher CNR values of hydroxyapatite are attributed to its attenuation properties compared to the other calcification materials, leading to higher contrast in the dual energy image. This work was supported by Grant Ε.040 from the Research Committee of the University of Patras (Programme K. Karatheodori).

Keywords: calcification materials, CNR, dual energy, X-rays

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Authors: Ilyes Athimni, Mouna Bouzazi, Mongi Boulehmi, Ahmed Ferchichi

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The principles of good governance, universal values, and digitization are among the tools to fight corruption and improve the quality of service delivery. In recent years, these tools have become one of the most controversial topics in the field of education and a concern of many international organizations and institutions against the problem of corruption. Corruption in the education sector, particularly in higher education, has negative impacts on the quality of education systems and on the quality of administrative or educational services. Currently, the health crisis due to the spread of the COVID-19 pandemic reveals the difficulties encountered by education systems in most countries of the world. Due to the poor governance of these systems, many educational institutions were unable to continue working remotely. To respond to these problems encountered by most education systems in many countries of the world, our initiative is to propose a methodology to reinvent education systems based on global values and digital technologies. This methodology includes a work strategy for educational institutions, whether in the provision of administrative services or in the teaching method, based on information and communication technologies (ICTs), intelligence artificial, and intelligent agents. In addition, we will propose a supervisory law that will be implemented and monitored by intelligent agents to improve accountability, transparency, and accountability in educational institutions. On the other hand, we will implement and evaluate a field experience by applying the proposed methodology in the operation of an educational institution and comparing it to the traditional methodology through the results of teaching an educational program. With these specifications, we can reinvent quality education systems. We also expect the results of our proposal to play an important role at local, regional, and international levels in motivating governments of countries around the world to change their university governance policies.

Keywords: artificial intelligence, corruption in education, distance learning, education systems, ICTs, intelligent agents, good governance

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Authors: Nubwimana Rachel, Mugabowindekwe Maurice

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Trees play a crucial role in maintaining biodiversity and providing various ecological services. Traditional methods of counting trees are time-consuming, and there is a need for more efficient techniques. However, deep learning makes it feasible to identify the multi-scale elements hidden in aerial imagery. This research focuses on the application of deep learning techniques for tree detection and counting in both forest and non-forest areas through the exploration of the deep learning application for automated tree detection and counting using satellite imagery. The objective is to identify the most effective model for automated tree counting. We used different deep learning models such as YOLOV7, SSD, and UNET, along with Generative Adversarial Networks to generate synthetic samples for training and other augmentation techniques, including Random Resized Crop, AutoAugment, and Linear Contrast Enhancement. These models were trained and fine-tuned using satellite imagery to identify and count trees. The performance of the models was assessed through multiple trials; after training and fine-tuning the models, UNET demonstrated the best performance with a validation loss of 0.1211, validation accuracy of 0.9509, and validation precision of 0.9799. This research showcases the success of deep learning in accurate tree counting through remote sensing, particularly with the UNET model. It represents a significant contribution to the field by offering an efficient and precise alternative to conventional tree-counting methods.

Keywords: remote sensing, deep learning, tree counting, image segmentation, object detection, visualization

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Authors: Hamed Nafar, Sajad Rezaei, Hamid Behbahani

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Safety analysis of the roads through the accident rates which is one of the widely used tools has been resulted from the direct exposure method which is based on the ratio of the vehicle-kilometers traveled and vehicle-travel time. However, due to some fundamental flaws in its theories and difficulties in gaining access to the data required such as traffic volume, distance and duration of the trip, and various problems in determining the exposure in a specific time, place, and individual categories, there is a need for an algorithm for prioritizing the road safety so that with a new exposure method, the problems of the previous approaches would be resolved. In this way, an efficient application may lead to have more realistic comparisons and the new method would be applicable to a wider range of time, place, and individual categories. Therefore, an algorithm was introduced to prioritize the safety of roads using the quasi-induced exposure method and utilizing the analytical hierarchy process. For this research, 11 provinces of Iran were chosen as case study locations. A rural accidents database was created for these provinces, the validity of quasi-induced exposure method for Iran’s accidents database was explored, and the involvement ratio for different characteristics of the drivers and the vehicles was measured. Results showed that the quasi-induced exposure method was valid in determining the real exposure in the provinces under study. Results also showed a significant difference in the prioritization based on the new and traditional approaches. This difference mostly would stem from the perspective of the quasi-induced exposure method in determining the exposure, opinion of experts, and the quantity of accidents data. Overall, the results for this research showed that prioritization based on the new approach is more comprehensive and reliable compared to the prioritization in the traditional approach which is dependent on various parameters including the driver-vehicle characteristics.

Keywords: road safety, prioritizing, Quasi-induced exposure, Analytical Hierarchy Process

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Authors: Yichin Chen

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Taiwan is an island characterized by an active tectonics and high erosion rates. Monitoring the dynamic landscape of Taiwan is an important issue for disaster mitigation, geomorphological research, and watershed management. Long-term and high spatiotemporal landform data is essential for quantifying and simulating the geomorphological processes and developing warning systems. Recently, the advances in unmanned aerial vehicle (UAV) and computational photogrammetry technology have provided an effective way to rebuild and monitor the topography changes in high spatio-temporal resolutions. This study rebuilds the 30-years landform change in the Aiyuzi watershed in 1986-2017 by using the aerial photogrammetry-based techniques. The Aiyuzi watershed, located in central Taiwan and has an area of 3.99 Km², is famous for its frequent landslide and debris flow disasters. This study took the aerial photos by using UAV and collected multi-temporal historical, stereo photographs, taken by the Aerial Survey Office of Taiwan’s Forestry Bureau. To rebuild the orthoimages and digital surface models (DSMs), Pix4DMapper, a photogrammetry software, was used. Furthermore, to control model accuracy, a set of ground control points was surveyed by using eGPS. The results show that the generated DSMs have the ground sampling distance (GSD) of ~10 cm and ~0.3 cm from the UAV’s and historical photographs, respectively, and vertical error of ~1 m. By comparing the DSMs, there are many deep-seated landslides (with depth over 20 m) occurred on the upstream in the Aiyuzi watershed. Even though a large amount of sediment is delivered from the landslides, the steep main channel has sufficient capacity to transport sediment from the channel and to erode the river bed to ~20 m in depth. Most sediments are transported to the outlet of watershed and deposits on the downstream channel. This case study shows that UAV and photogrammetry technology are useful for topography change monitoring effectively.

Keywords: aerial photogrammetry, landslide, landform change, Taiwan

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Authors: Zonglin Yang, Tatsuya Akiyama, Kerry S. Williamson, Michael J. Franklin, Thiruvarangan Ramaraj

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Pseudomonas aeruginosa is an opportunistic pathogen that forms surface-associated microbial communities (biofilms) on artificial implant devices and on human tissue. Biofilm infections are difficult to treat with antibiotics, in part, because the bacteria in biofilms are physiologically heterogeneous. One measure of biological heterogeneity in a population of cells is to quantify the cellular concentrations of ribosomes, which can be probed with fluorescently labeled nucleic acids. The fluorescent signal intensity following fluorescence in situ hybridization (FISH) analysis correlates to the cellular level of ribosomes. The goals here are to provide computationally and statistically robust approaches to automatically quantify cellular heterogeneity in biofilms from a large library of epifluorescent microscopy FISH images. In this work, the initial steps were developed toward these goals by developing an automated biofilm detection approach for use with FISH images. The approach allows rapid identification of biofilm regions from FISH images that are counterstained with fluorescent dyes. This methodology provides advances over other computational methods, allowing subtraction of spurious signals and non-biological fluorescent substrata. This method will be a robust and user-friendly approach which will enable users to semi-automatically detect biofilm boundaries and extract intensity values from fluorescent images for quantitative analysis of biofilm heterogeneity.

Keywords: image informatics, Pseudomonas aeruginosa, biofilm, FISH, computer vision, data visualization

Procedia PDF Downloads 128