Search results for: public image

Authors: Kozik Renata, Leśniak Agnieszka, Plebankiewicz Edyta

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Contracting authorities in the public sector are obligated to apply the principles provided for in the Polish law for the evaluation and selection of contractors. To analyze the methods of contractors, applied in practice by public clients, the notices of contract award results for construction works were analyzed. The analysis shows that the procedure selected more and more often is open to competitive bidding, where the assessment of the competence of contractors is not very precise, as well as non-competitive bidding, i.e. single source procurement. The share of procurement procedures, where the only criterion is price, is increasing. The solution to the problems existing here might be the introduction of one of the forms of pre-selection of contractors. The article also briefly discusses verification systems for companies applying for public contracts used in EU countries.

Keywords: certification, contractors selection, open tendering, public investors

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Authors: Javier Parra-Domínguez, Juan Manuel Corchado

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At present, public efficiency is a concept that intends to maximize return on public investment focus on minimizing the use of resources and maximizing the outputs. The concept takes into account statistical criteria drawn up according to techniques such as DEA (Data Envelopment Analysis). The purpose of the current work is to consider, more precisely, the theoretical application of CBR (Case-Based Reasoning) from economics and computer science, as a preliminary step to improving the efficiency of law enforcement agencies (public sector). With the aim of increasing the efficiency of the public sector, we have entered into a phase whose main objective is the implementation of new technologies. Our main conclusion is that the application of computer techniques, such as CBR, has become key to the efficiency of the public sector, which continues to require economic valuation based on methodologies such as DEA. As a theoretical result and conclusion, the incorporation of CBR systems will reduce the number of inputs and increase, theoretically, the number of outputs generated based on previous computer knowledge.

Keywords: case-based reasoning, knowledge, police, public efficiency

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Authors: Merve Kurt

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How women should behave in public spaces and how they should be dressed was a loaded issues in the Ottoman Empire. They pointed to what kind of state the Ottoman State was. One of such public space was Mesires, promenades. Women's visibility and invisibility, their morals were reflected and linked to the society as a whole. How the public space and private space is defined, what were the lines that separates them, how much blurred these lines were discussed in this paper. Moreover, all these points were strengthened by the primary sources from archives dating to the end of the 19th century.

Keywords: Mesire, Ottoman Empire, Ottoman women, public spaces

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Authors: Janpen Srijan, Nahathai Tanmang, Thanit Purathanang, Anun Dowchern, Saksit Summart, Seangduan Kampimpa

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This paper presents the resistance reader program based on image processing by using MATLAB. The proposed program is divided into six parts; the first part is the web camera; the second part is a watt selection before shooting the resistor; the third part is a part of finding the position of the color on the mid-point of resistor; the fourth part is a part of identifying color code of the resistor; the fifth part is a part of taking the number of values for each color for resistance calculation and the last part is a part of displaying result of resistance value. The experimental result of the resistance reader program based on image processing was able to display the resistance value of resistor. The accuracy of proposed program is 85 percent for 1 watt resistor. It has 15 percent of reading error because a problem with the color code of some resistor was too bright.

Keywords: resistance reader program, image processing, resistor, MATLAB

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Authors: Konstantinos C. Kartsakalis, Angeliki Skoura, Vasileios Megalooikonomou

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The fuzzy composition of objects depicted in images acquired through MR imaging or the use of bio-scanners has often been a point of controversy for field experts attempting to effectively delineate between the visualized objects. Modern approaches in medical image segmentation tend to consider fuzziness as a characteristic and inherent feature of the depicted object, instead of an undesirable trait. In this paper, a novel technique for efficient image retrieval in the context of images in which segmented objects are either crisp or fuzzily bounded is presented. Moreover, the proposed method is applied in the case of multiple, even conflicting, segmentations from field experts. Experimental results demonstrate the efficiency of the suggested method in retrieving similar objects from the aforementioned categories while taking into account the fuzzy nature of the depicted data.

Keywords: fuzzy object, fuzzy image segmentation, motion descriptors, MRI imaging, object-based image retrieval

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Authors: Xinrui Gao

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This research aims to explore the potential of shifting urban villages to public housing in China. In common practice, the central and local governments established two divided systems of urban redevelopment and public housing, including aims, design ideas, policy, headquarters, and branch offices. In most cases, the urban regeneration and public housing projects satisfy only the selected part of the society who can afford it (urban regeneration) or meet the requirements (public housing), which fail to cover the housing demand. However, there are many similarities between these two types of housing under the background of a shared economy, especially in target groups, affordable prices, and efficient use of spaces. Shenzhen always takes the lead in China’s urban regeneration and housing reformation. There are some top-down approaches to transforming housing in the urban village into public housing at present. These new approaches will provide a good chance to evaluate existing practices and explore the future development path of urban villages; while at the same time it could positively influence the housing problem in China.

Keywords: urban village, public housing, sharing economy, urban redevelopment

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Authors: Chhabi Nigam, S. Ramakrishnan

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This paper brings out the analysis of the airborne Synthetic Aperture Radar (SAR) data to study the impact of Doppler centroid on Image quality and geocoding accuracy from the perspective of Stripmap mode of data acquisition. Although in Stripmap mode of data acquisition radar beam points at 90 degrees broad side (side looking), shift in the Doppler centroid is invariable due to platform motion. In-accurate estimation of Doppler centroid leads to poor image quality and image miss-registration. The effect of Doppler centroid is analyzed in this paper using multiple sets of data collected from airborne platform. Occurrences of ghost (ambiguous) targets and their power levels have been analyzed that impacts appropriate choice of PRF. Effect of aircraft attitudes (roll, pitch and yaw) on the Doppler centroid is also analyzed with the collected data sets. Various stages of the RDA (Range Doppler Algorithm) algorithm used for image formation in Stripmap mode, range compression, Doppler centroid estimation, azimuth compression, range cell migration correction are analyzed to find the performance limits and the dependence of the imaging geometry on the final image. The ability of Doppler centroid estimation to enhance the imaging accuracy for registration are also illustrated in this paper. The paper also tries to bring out the processing of low squint SAR data, the challenges and the performance limits imposed by the imaging geometry and the platform dynamics on the final image quality metrics. Finally, the effect on various terrain types, including land, water and bright scatters is also presented.

Keywords: ambiguous target, Doppler Centroid, image registration, Airborne SAR

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Authors: Snehal G. Teli, R. J. Shelke

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CNN and MultiUNet models are the framework for the proposed method for enhancing and reconstructing underwater images. Multiscale merging of features and regeneration are both performed by the MultiUNet. CNN collects relevant features. Extensive tests on benchmark datasets show that the proposed strategy performs better than the latest methods. As a result of this work, underwater images can be represented and interpreted in a number of underwater applications with greater clarity. This strategy will advance underwater exploration and marine research by enhancing real-time underwater image processing systems, underwater robotic vision, and underwater surveillance.

Keywords: convolutional neural network, image enhancement, machine learning, multiunet, underwater images

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Authors: Sangeeta Palekar, Neeraj Rangwani, Akash Poddar, Jayu Kalambe

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The bio-medical analysis is an indispensable procedure for identifying health-related diseases like diabetes. Monitoring the glucose level in our body regularly helps us identify hyperglycemia and hypoglycemia, which can cause severe medical problems like nerve damage or kidney diseases. This paper presents a method for predicting the glucose concentration in blood samples using image processing and machine learning algorithms. The glucose solution is prepared by the glucose oxidase (GOD) and peroxidase (POD) method. An experimental database is generated based on the colorimetric technique. The image of the glucose solution is captured by the raspberry pi camera and analyzed using image processing by extracting the RGB, HSV, LUX color space values. Regression algorithms like multiple linear regression, decision tree, RandomForest, and XGBoost were used to predict the unknown glucose concentration. The multiple linear regression algorithm predicts the results with 97% accuracy. The image processing and machine learning-based approach reduce the hardware complexities of existing platforms.

Keywords: artificial intelligence glucose detection, glucose oxidase, peroxidase, image processing, machine learning

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Authors: Muhammad Feteha

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The socio-political Middle East scene has radically changed over the last decade, and one major contributor to this change was the Egyptian revolution of 2011. The massive impact of this revolution that originally started as a small protest in the Tahrir square has attracted more scholars to study the public space in Egypt, where it has become a necessity in order to understand and improve the socio-political conditions. The status of public space in Egypt has been deteriorating due to many reasons, including privatization and neglect. This paper studies one of the major problems of the contemporary public space in Cairo, which is the lack of identity. This takes place through a comparative analysis between selected case studies from both medieval and contemporary Cairo. The theoretical framework upon which the analysis is based views public space as a ‘container of social action’ and a ‘product of spatial practice’. Through the ‘deciphering of space’, differences in the socio-political role, symbolism, and identity of public spaces between both eras are shown. The paper aims to extract some lessons from public space in medieval Cairo, which was truly the ‘centerpiece of the public realm’ and a ‘fundamental expressions’ of the unique trans-dynastic architectural identity of Cairo. In addition, it suggests some strategies to revive the Cairene identity of public space instead of constructing new ones to be only ‘utilitarian spaces used for circulation’ and lack any identity.

Keywords: architectural identity, Cairene public space, Islamic architectural history, production of space

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Authors: Nur Imroatun Sholihat, Gresika Bunga Sylvana

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Currently, cyber attack became an incredibly serious problem due to its increasing trend all over the world. Therefore, information security becomes prominent for every organization including public sector organization. In Indonesia, unfortunately, Ministry of Finance (MoF) is the only public sector organization that has already formally established procedure to assess its information security adequacy by performing information security audits (November 2017). We assess the implementation of information security audits in the MoF using qualitative data obtained by interviewing IT auditors and by analysis of related documents. For this reason, information security audit practice in the MoF could become the acceptable benchmark for all other public sector organizations in Indonesia. This study is important because, to the best of the author’s knowledge, our research into information security audits practice in Indonesia’s public sector have not been found yet. Results showed that information security audits performed mostly by doing pentest (penetration testing) to MoF’s critical applications.

Keywords: information security audit, information technology, Ministry of Finance of Indonesia, public sector organization

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Authors: Marwah Mohsin, Thomas Beach, Alan Kwan, Mahdi Ismail

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This paper describes the differences in views on sustainable development between the general public and experts in a developing country, Iraq. This paper will answer the question: How do the views of the public differ from the generally accepted view of experts in the context of sustainable urban development in Iraq? In order to answer this question, the views of both the public and the experts will be analysed. These results are taken from a public survey and a Delphi questionnaire. These will be analysed using statistical methods in order to identify the significant differences. This will enable investigation of the different perceptions between the public perceptions and the experts’ views towards urban sustainable development factors. This is important due to the fact that different viewpoints between policy-makers and the public will impact on the acceptance by the public of any future sustainable development work that is undertaken. The brief findings of the statistical analysis show that the views of both the public and the experts are considered different in most of the variables except six variables show no differences. Those variables are ‘The importance of establishing sustainable cities in Iraq’, ‘Mitigate traffic congestion’, ‘Waste recycling and separating’, ‘Use wastewater recycling’, ‘Parks and green spaces’, and ‘Promote investment’.

Keywords: urban sustainability, experts views, public views, principle component analysis, PCA

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Authors: Keerti Kembhavi, M. R. Archana, V. Anjaneyappa

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Most asphalt pavement condition evaluation use rating frameworks in which asphalt pavement distress is estimated by type, extent, and severity. Rating is carried out by the pavement condition rating (PCR), which is tedious and expensive. This paper presents the development of a low-cost technique for image pavement distress analysis that permits the identification of pothole and cracks. The paper explores the application of image processing tools for the detection of potholes and cracks. Longitudinal cracking and pothole are detected using Fuzzy-C- Means (FCM) and proceeded with the Spectral Theory algorithm. The framework comprises three phases, including image acquisition, processing, and extraction of features. A digital camera (Gopro) with the holder is used to capture pavement distress images on a moving vehicle. FCM classifier and Spectral Theory algorithms are used to compute features and classify the longitudinal cracking and pothole. The Matlab2016Ra Image preparing tool kit utilizes performance analysis to identify the viability of pavement distress on selected urban stretches of Bengaluru city, India. The outcomes of image evaluation with the utilization semi-computerized image handling framework represented the features of longitudinal crack and pothole with an accuracy of about 80%. Further, the detected images are validated with the actual dimensions, and it is seen that dimension variability is about 0.46. The linear regression model y=1.171x-0.155 is obtained using the existing and experimental / image processing area. The R2 correlation square obtained from the best fit line is 0.807, which is considered in the linear regression model to be ‘large positive linear association’.

Keywords: crack detection, pothole detection, spectral clustering, fuzzy-c-means

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Authors: Mirjana Ruppel, Rajendra Persad, Amit Bahl, Sanja Dogramadzi, Chris Melhuish, Lyndon Smith

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Multimodal image registration is a profoundly complex task which is why deep learning has been used widely to address it in recent years. However, two main challenges remain: Firstly, the lack of ground truth data calls for an unsupervised learning approach, which leads to the second challenge of defining a feasible loss function that can compare two images of different modalities to judge their level of alignment. To avoid this issue altogether we implement a generative adversarial network consisting of two registration networks GAB, GBA and two discrimination networks DA, DB connected by spatial transformation layers. GAB learns to generate a deformation field which registers an image of the modality B to an image of the modality A. To do that, it uses the feedback of the discriminator DB which is learning to judge the quality of alignment of the registered image B. GBA and DA learn a mapping from modality A to modality B. Additionally, a cycle-consistency loss is implemented. For this, both registration networks are employed twice, therefore resulting in images ˆA, ˆB which were registered to ˜B, ˜A which were registered to the initial image pair A, B. Thus the resulting and initial images of the same modality can be easily compared. A dataset of liver CT and MRI was used to evaluate the quality of our approach and to compare it against learning and non-learning based registration algorithms. Our approach leads to dice scores of up to 0.80 ± 0.01 and is therefore comparable to and slightly more successful than algorithms like SimpleElastix and VoxelMorph.

Keywords: cycle consistency, deformable multimodal image registration, deep learning, GAN

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Authors: Melanie Verhovnik

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Media shape the image of crime, peoples’ believes, attitudes and sometimes also behaviors. Media not only gives the impression that crime is increasing, it also suggest that very violent crime is more common than it actually is. It is also no wonder that humans are more afraid of being involved in a crime committed by strangers than committed by somebody they know – because this is the media construct. With the help of three case studies, the paper analyzes how media frames crime and criminals and gives valuable hints as to what better reporting could look like.

Keywords: court reporting, offenders in media, quantitative content analysis, victims in media

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Authors: Jacinta Ifeoma Obidile

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The study sought to ascertain from the opinions of the business educators, effective strategies for funding public tertiary institutions in Anambra State Nigeria, for effective functioning and delivery. Funding of tertiary institutions has become so important following the dilapidated state of most of the public tertiary institutions in Nigeria. Tertiary institutions are known for the production of competitive and competent workforce in the nation. Considering the state of public tertiary institutions currently, one wonders if their objectives are achieved. Many scholars have identified funding as one of the major barriers to effective functioning of tertiary institutions. Although federal and state governments have been supporting the tertiary institutions, but their support seems not to be adequate. This study therefore ascertained from the perspective of business educators, other strategies for funding public tertiary institutions in Anambra State Nigeria, for effective functioning and delivery. Survey research design was adopted for the study. A total of 104 business educators from the public tertiary institutions in the State constituted the population. There was no sampling, hence the whole population was used. Structured questionnaire validated by three experts with a reliability coefficient of 0.82 was the instrument for data collection. Data collected were analyzed using mean and standard deviation. Findings from the study revealed that public-private partnership and external aids were among the strategies considered effective for funding public tertiary institutions. It was therefore recommended among others that associations like alumni should be strongly instituted in each of the public tertiary institutions so as to assist in the funding of tertiary institutions for effective functioning and delivery.

Keywords: strategies, funding, tertiary institutions, business educators

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Authors: Mohamed A. Almoghalis, Osman M. Hegazy, Ibrahim F. Imam, Ali H. Elbastawessy

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This paper presents a new hyperspectral image segmentation scheme with respect to both spatial and spectral contexts. The scheme uses the 8-pixels spatial pattern to build a weight structure that holds the number of outlier bands for each pixel among its neighborhood windows in different directions. The number of outlier bands for a pixel is obtained using bands quartile box plots profile among spatial 8-pixels pattern windows. The quartile box plot weight structure represents the spatial-spectral context in the image. Instead of starting segmentation process by single pixels, the proposed methodology starts by pixels groups that proved to share the same spectral features with respect to their spatial context. As a result, the segmentation scheme starts with Jigsaw pieces that build a mosaic image. The following step builds a model for each Jigsaw piece in the mosaic image. Each Jigsaw piece will be merged with another Jigsaw piece using KNN applied to their bands' quartile box plots profiles. The scheme iterates till required number of segments reached. Experiments use two data sets obtained from Earth Observer 1 (EO-1) sensor for Egypt and France. Initial results qualitative analysis showed encouraging results compared with ground truth. Quantitative analysis for the results will be included in the final paper.

Keywords: hyperspectral image segmentation, image processing, remote sensing, box plot

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Authors: François Chiocchio, Mahshid Gharibpour

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Regardless of the extent to which succession management is implemented in the private sector, it is still overlooked in the public sector. Traditional succession management is evolving providing a better alignment between business strategies and HR strategies. Succession management brings sustainable effectiveness for succession programs through career path development, knowledge and skill transfer, job retention, as well as high-potential candidates’ empowerment for upcoming vacancies. By way of a systematic literature review, we bring into focus strategic succession management in public organizations and discuss best ways of implementation. 

Keywords: succession management, strategic succession management, public organization, succession management model

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Authors: Abdelkader Guendouz, Fatima Zohra Adel

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Since about two decades, the Algerian government created a new instrument in the field of its fiscal policy, which is the FRR (Fonds de Régulation des Recettes). The FRR is a sovereign fund, which the initial role was saving the surplus generated by the fixation of a referential oil price to establish the state budget in the aim equilibrium between budgetary incomes and public expenditures. After a while, the government turns to use this instrument in boosting the public investment more than keeping for funding a deficit budget in periods of crisis. This lead to ask some justified questions about the efficiency of this sovereign fund and its real role.

Keywords: FRR sovereign fund, public expenditures, public investment, efficiency

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Authors: Xiaoping Zhang, Fengying Yan

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The implementation of the 'Urban Design Management Measures' requires that the master urban design should aim at creating a livable urban space. However, to our best knowledge, the existing researches and practices of master urban design not only focus less on the livable space but also face a number of problems such as paying more attention to the image of the city, ignoring the people-oriented and lacking dynamic continuity. In order to make the master urban design can better guide the construction of city. Firstly, the paper proposes the livable city hierarchy system to meet the needs of different groups of people and then constructs the framework of livable goal-oriented master urban design based on the theory of livable content and the ideological origin of people-oriented. Secondly, the paper takes the master urban design practice of Zibo as a sample and puts forward the design strategy of strengthening the pattern, improve the quality of space, shape the feature, and establish a series of action plans based on the strategy of urban space development. Finally, the paper explores the method system of livable goal-oriented master urban design from the aspects of safety pattern, morphology pattern, neighborhood scale, open space, street space, public interface, style feature, public participation and action plans.

Keywords: livable, master urban design, public participation, zibo city

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Authors: Zihan Yu, Kohei Inoue, Kiichi Urahama

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We present a method for de-hazing images. A dark envelope image is derived with the bilateral minimum filter and a bright envelope is derived with the bilateral maximum filter. The ambient light and transmission of the scene are estimated from these two envelope images. An image without haze is reconstructed from the estimated ambient light and transmission.

Keywords: image dehazing, bilateral minimum filter, bilateral maximum filter, local contrast

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Authors: Jingpeng Gao, Xinrui Mao, Zhibin Deng

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Aiming at the low recognition rate on the composite signal modulation in low signal to noise ratio (SNR), this paper proposes a modulation recognition algorithm based on ICanny-CNN. Firstly, the radar signal is transformed into the time-frequency image by Choi-Williams Distribution (CWD). Secondly, we propose an image processing algorithm using the Guided Filter and the threshold selection method, which is combined with the hole filling and the mask operation. Finally, the shallow convolutional neural network (CNN) is combined with the idea of the depth-wise convolution (Dw Conv) and the point-wise convolution (Pw Conv). The proposed CNN is designed to complete image classification and realize modulation recognition of radar signal. The simulation results show that the proposed algorithm can reach 90.83% at 0dB and 71.52% at -8dB. Therefore, the proposed algorithm has a good classification and anti-noise performance in radar signal modulation recognition and other fields.

Keywords: modulation recognition, image processing, composite signal, improved Canny algorithm

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Authors: Shaherah Jordan, Paula Vandergert

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The discussion on public charging infrastructure is usually framed around the ‘chicken-egg’ challenge of consumers feeling reluctant to purchase without the necessary infrastructure and policymakers reluctant to invest in the infrastructure without the demand. However, public charging infrastructure may be more crucial to electric vehicle (EV) adoption than previously thought. Historically, access to residential charging was thought to be a major factor in potential for growth in the EV market as it offered a guaranteed place for a vehicle to be charged. The purpose of this study is to understand how the built environment may encourage uptake of EVs by seeking a correlation between EV ownership and public charging points in an urban and densely populated city such as London. Using a statistical approach with data from the Department for Transport and Zap-Map, a statistically significant correlation was found between the total (slow, fast and rapid) number of public charging points and a number of EV registrations per borough – with the strongest correlation found between EV registrations and rapid chargers. This research does not explicitly prove that there is a cause and effect relationship between public charging points EVs but challenges some of the previous literature which indicates that public charging infrastructure is not as important as home charging. Furthermore, the study provides strong evidence that public charging points play a functional and psychological role in the adoption of EVs and supports the notion that the built environment can influence human behaviour.

Keywords: behaviour change, electric vehicles, public charging infrastructure, transportation

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Authors: Aime Philombe Zapji Ymele

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Servicing public debt is a significant budgetary burden. In the sense that the payment of interest charges is a liability on the balance sheet of the public budget and affects fiscal policy. Interest charges can sometimes become a burden if they crowd out private activities. In order to analyse and understand the determinants of the debt burden and its impact on the sustainability of public finances, the present work focuses on OECD countries. It is noted from the literature that the factors that determine interest charges are macroeconomic (inflation, GDP growth, and interest rates) and public finances (primary balance and public debt). After analysing a panel of 33 OECD countries and using ordinary least squares (OLS), we find that public debt, inflation, and long-term interest rates are positively correlated with interest charges. An increase in any of these variables leads to an increase in debt charges. On the other hand, a growth in GDP is negatively associated with interest charges. Indeed, an increase in GDP generates enough revenue to meet the repayment of debt charges. According to the empirical analysis, we can say that, despite the large and growing debt-to-GDP ratio of major OECD countries, interest charges are not a threat to the sustainability of public finances. However, it is important for these countries to reduce the ratio of public debt to GDP because, in the face of the many challenges (health, aging population, etc.) that are looming on the horizon, an increase in interest rates could bring with it considerable burdens that would threaten the budgetary balance of these states.

Keywords: interest charges, sustainability, public debt, interest rates

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Authors: Seda Sahin, Emin Akata

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Obturator foramen is a specific structure in pelvic bone images and recognition of it is a new concept in medical image processing. Moreover, segmentation of bone structures such as obturator foramen plays an essential role for clinical research in orthopedics. In this paper, we present a novel method to analyze the similarity between the substructures of the imaged region and a hand drawn template, on hip radiographs to detect obturator foramen accurately with integrated usage of Marker-controlled Watershed segmentation and Zernike moment feature descriptor. Marker-controlled Watershed segmentation is applied to seperate obturator foramen from the background effectively. Zernike moment feature descriptor is used to provide matching between binary template image and the segmented binary image for obturator foramens for final extraction. The proposed method is tested on randomly selected 100 hip radiographs. The experimental results represent that our method is able to segment obturator foramens with % 96 accuracy.

Keywords: medical image analysis, segmentation of bone structures on hip radiographs, marker-controlled watershed segmentation, zernike moment feature descriptor

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Authors: Cynthia Pope

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Though traditional art has been strong on showcasing aesthetics to imbue pleasantries, modern public art has been breaking trends to push citizens beyond the pleasure of seeing beauty. Contemporary public sculpture, in particular, has been the impetus of provoking questions about community standards, identity, and race relations. A phenomenon involving Scaffold, a sculpture by artist Sam Durant, became the focal point of contention within Minneapolis, Minnesota, recently. With intentions to better understand the power public sculpture has to disrupt community identity, in this book, It will use primarily rhetorical theory to explain how all parties involved—The Walker Art Museum, the Dakota Nation, Durant, and local citizens—participated in a controversy touching on racial politics, identity, culture, history and public art. This mixed-methods case study examines the public artifact contextually through historical and cultural frameworks. Findings in this project will reveal Scaffold to be represented as a tool of empowered Caucasians to the exclusion of marginalized people. This project also informs the fields of public rhetoric and political identity, marginalized voices, and community and social justice initiatives to include the difficult topic of race and identity.

Keywords: public art controversy, technical communication, community narrative, ambient rhetoric

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Authors: Nantida Otakum

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The purpose of the study is to study the level of public consciousness of Suan Sunandha Rajabhat University undergraduate students. This study also compares differences in the level of public consciousness among undergraduate students who are different in sex and year of study. The research methodology employed a questionnaire as a quantitative method. The respondents were undergraduate students at Suan Sunandha Rajabhat University. Totally, 400 usable questionnaires were received. Descriptive and inferential statistics were used in data analysis. The results showed that the level of public consciousness of undergraduate students was at a good level in all aspects. The aspect of social participation was at the highest level, while the aspect of shared vision was at the lowest level. The results also indicated that undergraduate students with differences in sex and year of study were not significantly different in public consciousness level.

Keywords: participation, public consciousness, Suan Sunandha Rajabhat University, undergraduate students

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Authors: Mayssa Bensalah, Atef Boujelben, Mouna Baklouti, Mohamed Abid

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Image segmentation has a fundamental role in analysis and interpretation for many applications. The automated segmentation of organs and tissues throughout the body using computed imaging has been rapidly increasing. Indeed, it represents one of the most important parts of clinical diagnostic tools. In this paper, we discuss a thorough literature review of recent methods of tumour segmentation from medical images which are briefly explained with the recent contribution of various researchers. This study was followed by comparing these methods in order to define new directions to develop and improve the performance of the segmentation of the tumour area from medical images.

Keywords: features extraction, image segmentation, medical images, tumor detection

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Authors: Iqra Yaseen

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One of the well-known areas of computer science and engineering, image processing in the context of computer vision has been essential to automation. In remote sensing, medical science, and many other fields, it has made it easier to uncover previously undiscovered facts. Grading of diverse items is now possible because of neural network algorithms, categorization, and digital image processing. Its use in the classification of agricultural products, particularly in the grading of seeds or grains and their cultivars, is widely recognized. A grading and sorting system enables the preservation of time, consistency, and uniformity. Global population growth has led to an increase in demand for food staples, biofuel, and other agricultural products. To meet this demand, available resources must be used and managed more effectively. Image processing is rapidly growing in the field of agriculture. Many applications have been developed using this approach for crop identification and classification, land and disease detection and for measuring other parameters of crop. Vegetation localization is the base of performing these task. Vegetation helps to identify the area where the crop is present. The productivity of the agriculture industry can be increased via image processing that is based upon Unmanned Aerial Vehicle photography and satellite. In this paper we use the machine learning techniques like Convolutional Neural Network, deep learning, image processing, classification, You Only Live Once to UAV imaging dataset to divide the crop into distinct groups and choose the best way to use it.

Keywords: image processing, UAV, YOLO, CNN, deep learning, classification

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Authors: Sheema Shuja Khattak, Gule Saman, Imran Khan, Abdus Salam

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Image segmentation plays an important role in medical imaging applications. Therefore, accurate methods are needed for the successful segmentation of medical images for diagnosis and detection of various diseases. In this paper, we have used maximum entropy to achieve image segmentation. Maximum entropy has been calculated using Shannon, Renyi, and Tsallis entropies. This work has novelty based on the detection of skin lesion caused by the bite of a parasite called Sand Fly causing the disease is called Cutaneous Leishmaniasis.

Keywords: shannon, maximum entropy, Renyi, Tsallis entropy

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