Search results for: Image Quality

Authors: Muhittin Karaman, Murat Budakoglu

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In this study, derivation of lake bathymetry was evaluated using the high resolution Worldview-2 multispectral images in the very shallow hypersaline Lake Acıgöl which does not have a stable water table due to the wet-dry season changes and industrial usage. Every year, a great part of the lake water budget has been consumed for the industrial salt production in the evaporation ponds, which are generally located on the south and north shores of Lake Acıgöl. Therefore, determination of the water level changes from a perspective of remote sensing-based lake water by bathymetry studies has a great importance in the sustainability-control of the lake. While the water table interval is around 1 meter between dry and wet season, dissolved ion concentration, salinity and turbidity also show clear differences during these two distinct seasonal periods. At the same time, with the satellite data acquisition (June 9, 2013), a field study was conducted to collect the salinity values, Secchi disk depths and turbidity levels. Max depth, Secchi disk depth and salinity were determined as 1,7 m, 0,9 m and 43,11 ppt, respectively. Eight-band Worldview-2 image was corrected for atmospheric effects by ATCOR technique. For each sampling point in the image, mean reflectance values in 1*1, 3*3, 5*5, 7*7, 9*9, 11*11, 13*13, 15*15, 17*17, 19*19, 21*21, 51*51 pixel reflectance neighborhoods were calculated separately. A unique image has been derivated for each matrix resolution. Spectral values and depth relation were evaluated for these distinct resolution images. Correlation coefficients were determined for the 1x1 matrix: 0,98, 0,96, 0,95 and 0,90 for the 724 nm, 831 nm, 908 nm and 659 nm, respectively. While 15x5 matrix characteristics with 0,98, 0,97 and 0,97 correlation values for the 724 nm, 908 nm and 831 nm, respectively; 51x51 matrix shows 0,98, 0,97 and 0,96 correlation values for the 724 nm, 831 nm and 659 nm, respectively. Comparison of all matrix resolutions indicates that RedEdge band (724 nm) of the Worldview-2 satellite image has the best correlation with the saline shallow lake of Acıgöl in-situ depth.

Keywords: bathymetry, Worldview-2 satellite image, ATCOR technique, Lake Acıgöl, Denizli, Turkey

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Authors: Minu Lakra

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The present study was done on 100 (male=50 and female=50) teachers of physical education at tertiary level from Varanasi city. They were chosen according to the stratified sampling method. Data collection tool was Perceived Stress Scale: 14 items (Cohen, Kamarck and mermelstain 1983) and Quality of Life was developed by THE WHOQOL GROUP in 1991. Data was analyzed with the help of correlation. Findings explore that perceived stress and quality of life has been positively correlated in female teachers of higher education from physical education whereas in male teachers the relationship was found insignificant.

Keywords: higher education, male and female teachers , percieved stress, quality of life

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Authors: Magdalena Kostova-Panayotova, Neda-Maria Panayotova

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The article is focused on a problem that tends to be extremely characteristic and essential to European literature – the relations between the Balkan Peninsula and Europe and the stereotypes the Balkans evoke – a melting pot, a powder keg, a bridge, a crossroads, along with other negative definitions. The stereotypes and visions are examined as the layered images of a particular nation. The work deals with the Balkan writers’ way of confronting stereotypes by reversing the image of the ‘dark’ Balkans and the ‘bright’ Europe and thus establishing the Balkans as a place of beauty, music, and poetry. In many aspects, the European image of the Balkans (the so-called Balkanism) is comparable to the European attitude to the Orient (the so-called Orientalism). On the basis of the analysis of specific texts by Balkan authors, the article proves that the identity of the person of the late 20th and early 21st century is something individual and much more complicated than a patriotic self-definition because the identity of the contemporary person is multilayered. It is not flattering to be a bridge, a crossroads or a corner. However, a person is a creature of transition. Our idea demonstrates that the state of transition always brings both weakness and strength – it is the Balkans that connect Europe to the world.

Keywords: image, Slavs, Balkans, identity of the modern Balkan person

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Authors: Jameela Ali Alkrimi, Abdul Rahim Ahmad, Azizah Suliman, Loay E. George

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Red blood cells (RBCs) are among the most commonly and intensively studied type of blood cells in cell biology. The lack of RBCs is a condition characterized by lower than normal hemoglobin level; this condition is referred to as 'anemia'. In this study, a software was developed to isolate RBCs by using a machine learning approach to classify anemic RBCs in microscopic images. Several features of RBCs were extracted using image processing algorithms, including principal component analysis (PCA). With the proposed method, RBCs were isolated in 34 second from an image containing 18 to 27 cells. We also proposed that PCA could be performed to increase the speed and efficiency of classification. Our classifier algorithm yielded accuracy rates of 100%, 99.99%, and 96.50% for K-nearest neighbor (K-NN) algorithm, support vector machine (SVM), and neural network ANN, respectively. Classification was evaluated in highly sensitivity, specificity, and kappa statistical parameters. In conclusion, the classification results were obtained for a short time period with more efficient when PCA was used.

Keywords: red blood cells, pre-processing image algorithms, classification algorithms, principal component analysis PCA, confusion matrix, kappa statistical parameters, ROC

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Authors: Hamide Azimi Lolaty, Fateme Alsadat Ghanipoor, Azar Ramzani, Reza Ali Mohammadpoor, Alireza Babaei

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Background and Objective: Despite the merits behind orthognathic surgery, self-care training in such patients seems logical. The current research was performed pursuing the goal of outlining the effect of training mindfulness-based self-care on Self-Esteem (SE) and Body Image Concern (BIC) of orthognathic surgery candidate patients. Material and Methods: The present study was performed using a semi-experimental method with pre-and post-design in the control and intervention groups. The eligible patients to enter the Babol-based Shahid Beheshti Orthognathic Surgery Clinic were conveniently divided into two 25-person groups. The variables of Self-Esteem and Body Image Concern were measured before and after executing the eight 90-minute training sessions and in the follow-up period done three months after executing the intervention using Cooper Smith’s Self-Esteem Inventory (CSEI) and Body Image Concern Inventory (BICI). The data were analyzed using ANOVA and the independent t-test and using SPSS-26, the data were analyzed at a 0.05 level. Results: As a result of the intervention, the intervention group’s SE score critically changed on average from 25.4±7.31 in the pre-intervention to 31.16±7.05 in the post-intervention and to 40.45±3.51 in the follow-up period (P=0.01), the intervention group’s BIC score changed on average from 60.28±16.47 in the pre-intervention to 47.15±80.47 in the post-intervention and to 32.20 ± 10.73 in the follow-up period. This difference was meaningful (P=0.001). But due to time and the intervention interaction, the control group underwent this significant reduction with a delay. The study revealed the scores of the SE as 32± 6.84 and that of the BIC as 43.32±10.64 in the control group didn’t result in any meaningful statistical difference (P<0.05). Conclusion: Training mindfulness-based self-care exerts an effect on the SE and BIC of the patients undergoing orthognathic surgery. Therefore, it’s recommended to train mindfulness-based self-care for orthognathic surgery candidate patients.

Keywords: self-care, mindfulness, self-esteem, body image concern, orthognathic surgery

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Authors: Manirath Wongsim

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Information Quality (IQ) has become a critical, strategic issue in Accounting Information Systems (AIS) adoption. In order to implement AIS adoption successfully, it is important to consider the quality of information use throughout the adoption process, which seriously impacts the effectiveness of AIS adoption practice and the optimization of AIS adoption decisions. There is a growing need for research to provide insights into issues and solutions related to IQ in AIS adoption. The need for an integrated approach to improve IQ in AIS adoption, as well as the unique characteristics of accounting data, demands an AIS adoption specific IQ framework. This research aims to explore ways of managing information quality and AIS adoption to investigate the relationship between the IQ issues and AIS adoption process. This study has led to the development of a framework for understanding IQ management in AIS adoption. This research was done on 44 respondents as ten organisations from manufacturing firms in Thailand. The findings of the research’s empirical evidence suggest that IQ dimensions in AIS adoption to provide assistance in all process of decision making. This research provides empirical evidence that information quality of AIS adoption affect decision making and suggests that these variables should be considered in adopting AIS in order to improve the effectiveness of AIS.

Keywords: information quality, information quality dimensions, accounting information systems, accounting information system adoption

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Authors: Muhammad Imran Ahmad, Ruzelita Ngadiran, Mohd Nazrin Md Isa, Nor Ashidi Mat Isa, Mohd ZaizuIlyas, Raja Abdullah Raja Ahmad, Said Amirul Anwar Ab Hamid, Muzammil Jusoh

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This paper presents two technique, local feature extraction using image spectrum and low frequency spectrum modelling using GMM to capture the underlying statistical information to improve the performance of face recognition system. Local spectrum features are extracted using overlap sub block window that are mapping on the face image. For each of this block, spatial domain is transformed to frequency domain using DFT. A low frequency coefficient is preserved by discarding high frequency coefficients by applying rectangular mask on the spectrum of the facial image. Low frequency information is non Gaussian in the feature space and by using combination of several Gaussian function that has different statistical properties, the best feature representation can be model using probability density function. The recognition process is performed using maximum likelihood value computed using pre-calculate GMM components. The method is tested using FERET data sets and is able to achieved 92% recognition rates.

Keywords: local features modelling, face recognition system, Gaussian mixture models, Feret

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Authors: Nartan Rajpriya

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City is a multiplex ecological system made up of social, economic and natural sub systems. Green space system is the foundation of the natural system. It is also suitable part of natural productivity in the urban structure. It is dispensable for constructing a high quality human settlements and a high standard ecocity. Ahmedabad is the fastest growing city of India. Today urban green space is under strong pressure in Ahmedabad city. Due to increasing urbanization, combined with a spatial planning policy of densification, more people face the prospect of living in less green residential environments. In this research analyzes the importance of available Green Space at Bodakdev Park, Ahmedabad, using remote sensing and GIS technologies. High resolution IKONOS image and LISS IV data has been used in this project. This research answers the questions like: • Temporal changes in urban green space area. • Proximity to heavy traffic or roads or any recreational facilities. • Importance in terms of health. • Availability of quality infrastructure. • Available green space per area, per sq. km and per total population. This projects incorporates softwares like ArcGIS, Ecognition and ERDAS Imagine, GPS technologies etc. Methodology includes the field work and collection of other relevant data while preparation of land use maps using the IKONOS imagery which is corrected using GPS.

Keywords: urban green space, ecocity, IKONOS, LISS IV

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Authors: Selaphares Jatico Tajale

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This research aims to understand the notions of quality education by conducting case studies among internationally-accredited Christian schools in Southeast Asia. Five internationally-accredited Christian schools from Cambodia, Indonesia, Malaysia, The Philippines, and Singapore will be chosen as cases for this study. This study will utilize the processes of interviews, filling up of questionnaires, and writing of reflections in order to obtain data and relevant information. These processes will be conducted through multi-sectoral respondents such as administrators, academic heads, and faculty. This study employs five aspects within the realm of education as guides in the formulation of questionnaire and guide questions in the interview, namely: a) school context, b) classroom, c) quality assurance, d) stakeholders, e) faculty and staff. Guide interview questions and questions in the questionnaires are formulated to uncover information on how those five aspects were managed to achieve desired student learning outcomes and uncover other information useful for the study.

Keywords: internationally-accredited, notions of quality education, quality education, quality education in Southeast Asia

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Authors: Fathi Alwafie

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In this paper we present the simulation of the propagation characteristics of the picocellular propagation channel environment. The first aim has been to find a correct description of the environment for received wave. The result of the first investigations is that the environment of the indoor wave significantly changes as we change the electric parameters of material constructions. A modified 3D ray tracing image method tool has been utilized for the coverage prediction. A detailed analysis of the dependence of the indoor wave on the wide-band characteristics of the channel: Root Mean Square (RMS) delay spread characteristics and mean excess delay, is also investigated.

Keywords: propagation, ray tracing, network, mobile computing

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Authors: Preethi Sudarshanie Dassanayake, R. A. Sudath Weerasiri

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Objective: The objective of this study were to find out highest expectation and perception,highest gap between perception and expectation of service quality, and to find out such gaps between perception and expectation with regard to service quality dimensions were whether statistically significant. Methodology: This study carried out at the Out Patient Department (OPD) of the Veterinary Teaching Hospital (VTH), University of Peradeniya. Modified version of SERVQUAL with 22-pairs of items regarding expectation and perception of service quality in dimensions of tangible, reliability, responsiveness, assurance and empathy were included in Part 1 and the Part 2 of the questionnaire consisted of questions regarding socio-demographic factors. Sample size was 200 and sampling procedure was Systematic Random Sampling. Customers above 18 years of age, able to read, write and understand Sinhala or English language, visits more than twice in last six months and who willing to respond were selected. Findings: The analysis revealed customers expectations of service higher than the perceived for all 22- items of the SERVQUAL. This high expectation suggests that there is sufficient room for further improvement of service quality in all five dimensions. Originality/Value of the Paper: This study gave a new insight for poorly researched area of veterinary health service quality in Sri Lankan context. It provides hospital administrators and policy makers to develop strategies for further improvement of service quality according to customers' view.

Keywords: expectation, perception, service quality, SERVQUAL, veterinary health care

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Authors: Mariem Kchaou, Wiem Khlif, Faiez Gargouri

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Modeling business processes is an essential task when evaluating, improving, or documenting existing business processes. To be efficient in such tasks, a business process model (BPM) must have high structural quality and high performance. Evidently, evaluating the performance of a business process model is a necessary step to reduce time, cost, while assessing the structural quality aims to improve the understandability and the modifiability of the BPMN model. To achieve these objectives, a set of structural and performance measures have been proposed. Since the diversity of measures, we propose a framework that integrates both structural and performance aspects for classifying them. Our measure classification is based on business process model perspectives (e.g., informational, functional, organizational, behavioral, and temporal), and the elements (activity, event, actor, etc.) involved in computing the measures. Then, we implement this framework in a tool assisting the structural quality and the performance of a business process. The tool helps the designers to select an appropriate subset of measures associated with the corresponding perspective and to calculate and interpret their values in order to improve the structural quality and the performance of the model.

Keywords: performance, structural quality, perspectives, tool, classification framework, measures

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Authors: Pornpong Porpraphant

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This paper aimed to demonstrate how work performance quality development activity carried out for employees in an organization could lead to the organizational success and competency as a whole. The case studies selected for this research were the Thai huge corporate including Siam Cement Group or SCG, PTT Public Company Limited, and Electricity Generating Authority of Thailand or EGAT. The in- depth interview was applied with the three main groups that included the facilitator group, the managerial group, and the operational officer group. The Plan- Do- Check- Act approach was also utilized as to build up a conceptual model in corporate management that fostered employees’ knowledge acquisition, resulting in an improved work performance.

Keywords: high performance organization, quality, work performance quality development

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Authors: Thierry Sammour Sawaya, Heikki Deschacht

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In commercial aircraft operations, almost half of the accidents happen during approach or landing phases. Automatic guidance and automatic landings have proven to bring significant safety value added for this challenging landing phase. This is why Airbus and ScioTeq have decided to work together to explore the capability of image-based landing solutions as additional landing aids to further expand the possibility to perform automatic approach and landing to runways where the current guiding systems are either not fitted or not optimum. Current systems for automated landing often depend on radio signals provided by airport ground infrastructure on the airport or satellite coverage. In addition, these radio signals may not always be available with the integrity and performance required for safe automatic landing. Being independent from these radio signals would widen the operations possibilities and increase the number of automated landings. Airbus and ScioTeq are joining their expertise in the field of Computer Vision in the European Program called Clean Sky 2 Large Passenger Aircraft, in which they are leading the IMBALS (IMage BAsed Landing Solutions) project. The ultimate goal of this project is to demonstrate, develop, validate and verify a certifiable automatic landing system guiding an airplane during the approach and landing phases based on an onboard camera system capturing images, enabling automatic landing independent from radio signals and without precision instrument for landing. In the frame of this project, ScioTeq is responsible for the development of the Image Processing Platform (IPP), while Airbus is responsible for defining the functional and system requirements as well as the testing and integration of the developed equipment in a Large Passenger Aircraft representative environment. The aim of this paper will be to describe the system as well as the associated methods and tools developed for validation and verification.

Keywords: aircraft landing system, aircraft safety, autoland, avionic system, computer vision, image processing

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Authors: Jaqueline Maria Ribeiro Vieira

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Different strategies and tools are available at the oil and gas industry for detecting and analyzing tension and possible fractures in borehole walls. Most of these techniques are based on manual observation of the captured borehole images. While this strategy may be possible and convenient with small images and few data, it may become difficult and suitable to errors when big databases of images must be treated. While the patterns may differ among the image area, depending on many characteristics (drilling strategy, rock components, rock strength, etc.). Previously we developed and proposed a novel strategy capable of detecting patterns at borehole images that may point to regions that have tension and breakout characteristics, based on segmented images. In this work we propose the inclusion of data-mining classification strategies in order to create a knowledge database of the segmented curves. These classifiers allow that, after some time using and manually pointing parts of borehole images that correspond to tension regions and breakout areas, the system will indicate and suggest automatically new candidate regions, with higher accuracy. We suggest the use of different classifiers methods, in order to achieve different knowledge data set configurations.

Keywords: image segmentation, oil well visualization, classifiers, data-mining, visual computer

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Authors: Apoorva Bamal, Agnieszka Indiana Olbert

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Floods are known to be one of the most devastating hydro-climatic events, impacting a wide range of stakeholders in terms of environmental, social and economic losses. With difference in inundation durations and level of impact, flood hazards are of different degrees and strength. Amongst various set of domains being impacted by floods, environmental degradation in terms of water quality deterioration is one of the majorly effected but less highlighted domains across the world. The degraded water quality is caused by numerous natural and anthropogenic factors that are both point and non-point sources of pollution. Therefore, it is essential to understand the nature and source of the water pollution due to flooding. The major impact of floods is not only on the physico-chemical water quality parameters, but also on the biological elements leading to a vivid influence on the aquatic ecosystem. This deteriorated water quality is impacting many water categories viz. agriculture, drinking water, aquatic habitat, and miscellaneous services requiring an appropriate water quality to survive. This study identifies, reviews, evaluates and assesses multiple researches done across the world to determine the impact of floods on water quality. With a detailed statistical analysis of top relevant researches, this study is a synopsis of the methods used in assessment of impact of floods on water quality in different geographies, and identifying the gaps for further abridgement. As per majority of the studies, different flood magnitudes have varied impact on the water quality parameters leading to either increased or decreased values as compared to the recommended values for various categories. There is also an evident shift of the biological elements in the impacted waters leading to a change in its phenology and inhabitants of the specified water body. This physical, chemical and biological water quality degradation by floods is dependent upon its duration, extent, magnitude and flow direction. Therefore, this research provides an overview into the multiple impacts of floods on water quality, along with a roadmap of way forward to an efficient and uniform linkage of floods and impacted water quality dynamics.

Keywords: floods, statistical analysis, water pollution, water quality

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Authors: Kldiashvili Ekaterina, Burduli Archil, Ghortlishvili Gocha

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Introduction – Medical information system (MIS) is at the heart of information technology (IT) implementation policies in healthcare systems around the world. Different architecture and application models of MIS are developed. Despite of obvious advantages and benefits, application of MIS in everyday practice is slow. Objective - On the background of analysis of the existing models of MIS in Georgia has been created a multi-user web-based approach. This presentation will present the architecture of the system and its application for image based second opinion consultations. Methods – The MIS has been created with .Net technology and SQL database architecture. It realizes local (intranet) and remote (internet) access to the system and management of databases. The MIS is fully operational approach, which is successfully used for medical data registration and management as well as for creation, editing and maintenance of the electronic medical records (EMR). Five hundred Georgian language electronic medical records from the cervical screening activity illustrated by images were selected for second opinion consultations. Results – The primary goal of the MIS is patient management. However, the system can be successfully applied for image based second opinion consultations. Discussion – The ideal of healthcare in the information age must be to create a situation where healthcare professionals spend more time creating knowledge from medical information and less time managing medical information. The application of easily available and adaptable technology and improvement of the infrastructure conditions is the basis for eHealth applications. Conclusion - The MIS is perspective and actual technology solution. It can be successfully and effectively used for image based second opinion consultations.

Keywords: digital images, medical information system, second opinion consultations, electronic medical record

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Authors: Gulsen Tozsin, Fatma Bakir, Cemil Acar, Ercument Koc

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Kurtbogazi Dam has gained special meaning for Ankara, Turkey for the last decade due to the rapid depletion of nearby resources of drinking water. In this study, the results of the analyses of Kurtbogazi Dam outlet water and the rivers flowing into the Kurtbogazi Dam were discussed for the period of last five years between 2008 and 2012. The quality of these surface water resources were evaluated in terms of pH, temperature, biochemical oxygen demand (BOD5), nitrate, phosphate and chlorine. They were classified according to the Council Directive (75/440/EEC). Moreover, the properties of these surface waters were assessed to determine the quality of water for drinking and irrigation purposes using Piper, US Salinity Laboratory and Wilcox diagrams. The results revealed that the quality of all the investigated water sources are generally at satisfactory level as surface water except for Pazar Stream in terms of ortho-phosphate and BOD5 concentration for 2008.

Keywords: Kurtbogazi dam, water quality assessment, Ankara water, water supply

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Authors: Ahmed Elaksher, Islam Omar

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Accurate geometric relation algorithms are imperative in Earth and planetary satellite and aerial image processing, particularly for high-resolution images that are used for topographic mapping. Most of these satellites carry push-broom sensors. These sensors are optical scanners equipped with linear arrays of CCDs. These sensors have been deployed on most EOSs. In addition, the LROC is equipped with two push NACs that provide 0.5 meter-scale panchromatic images over a 5 km swath of the Moon. The HiRISE carried by the MRO and the HRSC carried by MEX are examples of push-broom sensor that produces images of the surface of Mars. Sensor models developed in photogrammetry relate image space coordinates in two or more images with the 3D coordinates of ground features. Rigorous sensor models use the actual interior orientation parameters and exterior orientation parameters of the camera, unlike approximate models. In this research, we generate a generic push-broom sensor model to process imageries acquired through linear array cameras and investigate its performance, advantages, and disadvantages in generating topographic models for the Earth, Mars, and the Moon. We also compare and contrast the utilization, effectiveness, and applicability of available photogrammetric techniques and softcopies with the developed model. We start by defining an image reference coordinate system to unify image coordinates from all three arrays. The transformation from an image coordinate system to a reference coordinate system involves a translation and three rotations. For any image point within the linear array, its image reference coordinates, the coordinates of the exposure center of the array in the ground coordinate system at the imaging epoch (t), and the corresponding ground point coordinates are related through the collinearity condition that states that all these three points must be on the same line. The rotation angles for each CCD array at the epoch t are defined and included in the transformation model. The exterior orientation parameters of an image line, i.e., coordinates of exposure station and rotation angles, are computed by a polynomial interpolation function in time (t). The parameter (t) is the time at a certain epoch from a certain orbit position. Depending on the types of observations, coordinates, and parameters may be treated as knowns or unknowns differently in various situations. The unknown coefficients are determined in a bundle adjustment. The orientation process starts by extracting the sensor position and, orientation and raw images from the PDS. The parameters of each image line are then estimated and imported into the push-broom sensor model. We also define tie points between image pairs to aid the bundle adjustment model, determine the refined camera parameters, and generate highly accurate topographic maps. The model was tested on different satellite images such as IKONOS, QuickBird, and WorldView-2, HiRISE. It was found that the accuracy of our model is comparable to those of commercial and open-source software, the computational efficiency of the developed model is high, the model could be used in different environments with various sensors, and the implementation process is much more cost-and effort-consuming.

Keywords: photogrammetry, push-broom sensors, IKONOS, HiRISE, collinearity condition

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Authors: Kwadwo Yeboah

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Background and Aims: The adoption of International Accounting Standards (IAS) is considered to be one of the most significant developments in the accounting profession. The adoption of IAS aims to improve financial reporting quality by ensuring that financial information is transparent and comparable across borders. However, there is a lack of research on the impact of IAS on financial reporting quality in emerging economies. This study aims to fill this gap by evaluating the impact of IAS on financial reporting quality in emerging economies. Methods: This study uses a sample of firms from emerging economies that have adopted IAS. The sample includes firms from different sectors and industries. The financial reporting quality of these firms is measured using financial ratios, such as earnings quality, financial leverage, and liquidity. The data is analyzed using a regression model that controls for firm-specific factors, such as size and profitability. Results: The results show that the adoption of IAS has a positive impact on financial reporting quality in emerging economies. Specifically, firms that adopt IAS exhibit higher earnings quality and lower financial leverage compared to firms that do not adopt IAS. Additionally, the adoption of IAS has a positive impact on liquidity, suggesting that firms that adopt IAS have better access to financing. Conclusions: The findings of this study suggest that the adoption of IAS has a positive impact on financial reporting quality in emerging economies. The results indicate that IAS adoption can improve transparency and comparability of financial information, which can enhance the ability of investors to make informed investment decisions. The study contributes to the literature by providing evidence of the impact of IAS adoption in emerging economies. The findings of this study have implications for policymakers and regulators in emerging economies, as they can use this evidence to support the adoption of IAS and improve financial reporting quality in their respective countries.

Keywords: accounting, international, standards, finance

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Authors: Igor Belykh

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Anti-scatter grids used in radiographic imaging for the contrast enhancement leave specific artifacts. Those artifacts may be visible or may cause Moiré effect when a digital image is resized on a diagnostic monitor. In this paper, we propose an automated grid artifacts detection and suppression algorithm which is still an actual problem. Grid artifacts detection is based on statistical approach in spatial domain. Grid artifacts suppression is based on Kaiser bandstop filter transfer function design and application avoiding ringing artifacts. Experimental results are discussed and concluded with description of advantages over existing approaches.

Keywords: grid, computed radiography, pattern recognition, image processing, filtering

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Authors: Pablo M. S. Vallejos

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The article aims to analyze the autobiographical practices of users on Instagram, observing the instrumentalization of image resources in the construction of visual narratives that make up that archive and digital diary. Through bibliographical review, discourse exploration and case studies, the research also aims to present a new theoretical perception about everyday records - edited with a collage of filters and aesthetic tools - that permeate that social network, understanding it as a platform fictionalizing and an expansion of life. In this way, therefore, the work reflects on possible futures in the elaboration of representations and identities in the context of digital spaces in the 21st century.

Keywords: visual culture, social media, autobiography, image

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Authors: Jimeng Shi, Mahek Jain, Giri Narasimhan

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Time Series Forecasting (TSF) is used to predict the target variables at a future time point based on the learning from previous time points. To keep the problem tractable, learning methods use data from a fixed-length window in the past as an explicit input. In this paper, we study how the performance of predictive models changes as a function of different look-back window sizes and different amounts of time to predict the future. We also consider the performance of the recent attention-based Transformer models, which have had good success in the image processing and natural language processing domains. In all, we compare four different deep learning methods (RNN, LSTM, GRU, and Transformer) along with a baseline method. The dataset (hourly) we used is the Beijing Air Quality Dataset from the UCI website, which includes a multivariate time series of many factors measured on an hourly basis for a period of 5 years (2010-14). For each model, we also report on the relationship between the performance and the look-back window sizes and the number of predicted time points into the future. Our experiments suggest that Transformer models have the best performance with the lowest Mean Average Errors (MAE = 14.599, 23.273) and Root Mean Square Errors (RSME = 23.573, 38.131) for most of our single-step and multi-steps predictions. The best size for the look-back window to predict 1 hour into the future appears to be one day, while 2 or 4 days perform the best to predict 3 hours into the future.

Keywords: air quality prediction, deep learning algorithms, time series forecasting, look-back window

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Authors: Eren Özceylan, Cihan Çetinkaya

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Quality function deployment (QFD) is a technique to assist transform the voice of the customer into engineering characteristics for a product/service. With the difference of existing studies, QFD is applied to an educational area that is a service sector which is not a manufacturing firm. The objective of the study is to design the undergraduate program according to students’ desire and expectations. To do so, third and fourth year students of industrial engineering department of Gaziantep University are considered as customers. Some suggestions about lecturers, courses, exams and facility for how to satisfy students’ demands are presented and as a result, sharing the materials of courses is the most important requirement among others.

Keywords: higher education, quality function deployment, quality house, voice of customer

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Authors: Abdulkader Helwan

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Rheumatoid joint inflammation is characterized as a perpetual incendiary issue which influences the joints by hurting body tissues Therefore, there is an urgent need for an effective intelligent identification system of knee Rheumatoid arthritis especially in its early stages. This paper is to develop a new intelligent system for the identification of Rheumatoid arthritis of the knee utilizing image processing techniques and neural classifier. The system involves two principle stages. The first one is the image processing stage in which the images are processed using some techniques such as RGB to gryascale conversion, rescaling, median filtering, background extracting, images subtracting, segmentation using canny edge detection, and features extraction using pattern averaging. The extracted features are used then as inputs for the neural network which classifies the X-ray knee images as normal or abnormal (arthritic) based on a backpropagation learning algorithm which involves training of the network on 400 X-ray normal and abnormal knee images. The system was tested on 400 x-ray images and the network shows good performance during that phase, resulting in a good identification rate 97%.

Keywords: rheumatoid arthritis, intelligent identification, neural classifier, segmentation, backpropoagation

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Authors: Sehreen Moorat, Mussarat Lakho

Abstract:

A method of artificial intelligence using digital mammograms data has been proposed in this paper for detection of breast cancer. Many researchers have developed techniques for the early detection of breast cancer; the early diagnosis helps to save many lives. The detection of breast cancer through mammography is effective method which detects the cancer before it is felt and increases the survival rate. In this paper, we have purposed image processing technique for enhancing the image to detect the graphical table data and markings. Texture features based on Gray-Level Co-Occurrence Matrix and intensity based features are extracted from the selected region. For classification purpose, neural network based supervised classifier system has been used which can discriminate between benign and malignant. Hence, 68 digital mammograms have been used to train the classifier. The obtained result proved that automated detection of breast cancer is beneficial for early diagnosis and increases the survival rates of breast cancer patients. The proposed system will help radiologist in the better interpretation of breast cancer.

Keywords: medical imaging, cancer, processing, neural network

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Authors: M. Dasgupta, S. Banerjee

Abstract:

Content Based Image Retrieval (CBIR) coupled with Case Based Reasoning (CBR) is a paradigm that is becoming increasingly popular in the diagnosis and therapy planning of medical ailments utilizing the digital content of medical images. This paper presents a survey of some of the promising approaches used in the detection of abnormalities in retina images as well in mammographic screening and detection of regions of interest in MRI scans of the brain. We also describe our proposed algorithm to detect hard exudates in fundus images of the retina of Diabetic Retinopathy patients.

Keywords: case based reasoning, exudates, retina image, similarity based retrieval

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Authors: O. Gubnitsyna, O. Zakoretskaya, O. Russova

Abstract:

It is generally recognized that the main task of modern society is human development. The quality of human capital has been identified as a key driver of economic development in the region. In this article, considered the quality of human capital as one of the main types of social and economic potential for the region’s development. The phenomenon of human capital represents both material and intellectual components of human activity. It is show that the necessary population characterized by certain quantitative and qualitative indicators (qualification and professional structure, education or social general condition and others) and is an necessary resource for the development of the regional economy. The connection of the regional goals with the quality of human capital is discussed in the article and a number of recommendations on its improvement were given. Solving the tasks stated in the article, the authors used analytical and statistical methods of research, scientific publications of domestic and foreign scientists on this issue. The results can be used in this implementation of the concept of regional development.

Keywords: human capital, the quality of human capital, economic development, social general condition

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Authors: Qasim Kriri, Harsh B. Desai

Abstract:

Water supply and sanitation in Saudi Arabia is portrayed by difficulties and accomplishments. One of the fundamental difficulties is water shortage. With a specific end goal to beat water shortage, significant ventures have been attempted in sea water desalination, water circulation, sewerage, and wastewater treatment. The motivation behind Statistical Process Control (SPC) is to decide whether the execution of a procedure is keeping up an acceptable quality level [AQL]. SPC is an analytical decision-making method. A fundamental apparatus in the SPC is the Control Charts, which follow the inconstancy in the estimations of the item quality attributes. By utilizing the suitable outline, administration can decide whether changes should be made with a specific end goal to keep the procedure in charge. The two most important quality factors in the distilled water which were taken into consideration were pH (Potential of Hydrogen) and TDS (Total Dissolved Solids). There were three stages at which the quality checks were done. The stages were as follows: (1) Water at the source, (2) water after chemical treatment & (3) water which is sent for packing. The upper specification limit, central limit and lower specification limit are taken as per Saudi water standards. The procedure capacity to accomplish the particulars set for the quality attributes of Berain water Factory chose to be focused by the proposed SPC system.

Keywords: acceptable quality level, statistical quality control, control charts, process charts

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Authors: Ali Hamza

Abstract:

Accurate segmentation of breast ultrasound images is of paramount importance in enhancing the diagnostic capabilities of breast cancer detection. This study presents an approach utilizing the U-Net architecture for segmenting breast ultrasound images aimed at improving the accuracy and reliability of mass identification within the breast tissue. The proposed method encompasses a multi-stage process. Initially, preprocessing techniques are employed to refine image quality and diminish noise interference. Subsequently, the U-Net architecture, a deep learning convolutional neural network (CNN), is employed for pixel-wise segmentation of regions of interest corresponding to potential breast masses. The U-Net's distinctive architecture, characterized by a contracting and expansive pathway, enables accurate boundary delineation and detailed feature extraction. To evaluate the effectiveness of the proposed approach, an extensive dataset of breast ultrasound images is employed, encompassing diverse cases. Quantitative performance metrics such as the Dice coefficient, Jaccard index, sensitivity, specificity, and Hausdorff distance are employed to comprehensively assess the segmentation accuracy. Comparative analyses against traditional segmentation methods showcase the superiority of the U-Net architecture in capturing intricate details and accurately segmenting breast masses. The outcomes of this study emphasize the potential of the U-Net-based segmentation approach in bolstering breast ultrasound image analysis. The method's ability to reliably pinpoint mass boundaries holds promise for aiding radiologists in precise diagnosis and treatment planning. However, further validation and integration within clinical workflows are necessary to ascertain their practical clinical utility and facilitate seamless adoption by healthcare professionals. In conclusion, leveraging the U-Net architecture for breast ultrasound image segmentation showcases a robust framework that can significantly enhance diagnostic accuracy and advance the field of breast cancer detection. This approach represents a pivotal step towards empowering medical professionals with a more potent tool for early and accurate breast cancer diagnosis.

Keywords: mage segmentation, U-Net, deep learning, breast cancer detection, diagnostic accuracy, mass identification, convolutional neural network

Procedia PDF Downloads 64