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Authors: Alex Konrad

Abstract:

In 2017, about 4.5 million Muslims live in Germany. They can practice their faith openly, mostly in well-equipped community centers. At the same time, right-wing politicians and media allege that all Muslims tend to be radical and undemocratic. Both perspectives are rooted in an interacting development since the 1970s. German authorities closed the 'King Fahd Academy' international school in Bonn in summer 2017 because they accused the school administration of attracting Islamists. Only 30 years ago, German authorities and labor unions directed their requests for pastoral care of the Muslim communities in Germany to the Turkish and Saudi administrations. This study shows the leading and misleading tracks of Muslim life and its perception in Germany from a historical point of view. Most of the Muslims came as so-called 'Gastarbeiter' (migrant workers) from Turkey and Morocco to West Germany in the 1960s and 1970s. Until the late 1970s, German society recognized them as workforce solely and ignored their religious needs broadly. The Iranian Revolution of 1979 caused widespread hysteria about Islamic radicalization. Likewise, it shifted the German perception of migrant workers in Germany. For the first time, the majority society saw them as religious people. Media and self-proclaimed 'experts' on Islam suspected Muslims in Germany of subversive and undemocratic belief. On the upside, they obtained the opportunity to be heard by German society and authorities. In the ensuing decades, Muslims and Islamophiles fought a discursive struggle against right-wing politicians, 'experts' and media with monolithic views. In the 1990s, Muslims achieved to establish a solid infrastructure of Islamic community center throughout Germany. Their religious life became present and contributed to diversifying the common monolithic images of Muslims as insane fundamentalists in Germany. However, the media and many 'experts' promoted the fundamentalist narrative, which gained more and more acceptance in German society at the same time. This study uses archival sources from German authorities, Islamic communities, together with local and national media to get a close approach to the contemporary historical debates. In addition, contributions by Muslims and Islamophiles in Germany, for example in magazines, event reports, and internal communication, revealing their quotidian struggle for more acceptance are being used as sources. The inclusion of widely publicized books, documentaries and newspaper articles about Islam as a menace to Europe conduces to a balanced analysis of the contemporary debates and views. Theoretically, the study applies the Third Space approach. Muslims in Germany fight the othering by the German majority society. It was their chief purpose not to be marginalized in both spatial meanings, discursively and physically. Therefore, they established realities of life as hybrids in Germany. This study reconstructs the development of the perception of Muslims in Germany. It claims that self-proclaimed experts and politicians with monolithic views maintained the hegemonic discursive positions and coined the German images of Muslims. Nevertheless, Muslims in Germany accomplished that Muslim presence in Germany’s everyday life became an integral part of society and the public sphere. This is how Muslims hybridized religious spaces in Germany.

Keywords: experts, fundamentalism, Germany, hybridization, Islamophobia, migrant workers

Procedia PDF Downloads 226

Authors: Gülcan Taşkıran, Ayla Bayık Temel

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Background: Florence Nightingale, the modern founder of the nursing, is most famous for her role as a nurse. But not so much known about her contributions as a mathematician and statistician. Aim: In this conceptual article it is aimed to examine Florence Nightingale's statistics education, how she used her passion for statistics and applied statistical data in nursing care and her scientific contributions to statistical science. Design: Literature review method was used in the study. The databases of Istanbul University Library Search Engine, Turkish Medical Directory, Thesis Scanning Center of Higher Education Council, PubMed, Google Scholar, EBSCO Host, Web of Science were scanned to reach the studies. The keywords 'statistics' and 'Florence Nightingale' have been used in Turkish and English while being screened. As a result of the screening, totally 41 studies were examined from the national and international literature. Results: Florence Nightingale has interested in mathematics and statistics at her early ages and has received various training in these subjects. Lessons learned by Nightingale in a cultured family environment, her talent in mathematics and numbers, and her religious beliefs played a crucial role in the direction of the statistics. She was influenced by Quetelet's ideas in the formation of the statistical philosophy and received support from William Farr in her statistical studies. During the Crimean War, she applied statistical knowledge to nursing care, developed many statistical methods and graphics, so that she made revolutionary reforms in the health field. Conclusions: Nightingale's interest in statistics, her broad vision, the statistical ideas fused with religious beliefs, the innovative graphics she has developed and the extraordinary statistical projects that she carried out has been influential on the basis of her professional achievements. Florence Nightingale has also become a model for women in statistics. Today, using and teaching of statistics and research in nursing care practices and education programs continues with the light she gave.

Keywords: Crimean war, Florence Nightingale, nursing, statistics

Procedia PDF Downloads 292

Authors: Nuchanat Handumrongkul Danaya Darnsawasdi, Anantachai Aeka

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To be a model for performing oral presentations by the tour guides, this research has been conducted. In order to develop French language teaching and studying for tourism, its purpose is to analyze the content used by tour guides. The study employed audio recordings of these presentations as an interview method in authentic situations, having four guides as respondents and information providers. The data was analyzed through content analysis. The results found that the tour guides described eight important items by giving more importance to details at Wat Phra Kaew or the Temple of the Emerald Buddha than at the palaces. They preferred the buildings upon the upper terrace, Buddhist cosmology, the decoration techniques, the royal chapel, the mural paintings, Thai offerings to Buddha images, palaces with architectural features and functions including royal ceremonies and others. This information represents the Thai characteristics of each building and other related content. The findings were used as a manual for guides for how to describe a tourist attraction, especially the temple and other related cultural topics of interest.

Keywords: guide, guide presentation, Grand Palace, Buddhist cosmology

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Authors: O. Maranci, A. B. Tugrul

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Scintigraphy is an imaging method of nuclear events provoked by collisions or charged current interactions with radiation. It is used for diagnostic test used in nuclear medicine via radiopharmaceuticals emitting radiation which is captured by gamma cameras to form two-dimensional images. Liver scintigraphy is widely used in nuclear medicine.Tc-99m and Cr-51 gamma radioisotopes can be used for this purpose. Cr-51 usage is more important for patients’ organ dose that has higher energy and longer half-life as compared to Tc-99m. In this study, it is aimed to determine the required dose for critical organs of patient through liver scintigraphy via Cr-51 gamma radioisotope. Experimental studies were conducted on patients even though conducting experimental studies on patients is extremely difficult for determination of critical organ doses. Torso phantom was utilized to simulate the liver scintigraphy by using 20 mini packages of Cr-51 that were placed on the organ. The radioisotope was produced by irradiation in central thimble of TRIGA MARK II Reactor at 250 KW power. As the results of the study, critical organ doses were determined and evaluated with different critic organs.

Keywords: critical organ doses, liver, scintigraphy, TRIGA Mark-II

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Authors: Jae Won Lee, Kyung Hyun Min, Hong Jae Lee, Sang Cheon Lee

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To date, imaging techniques have attracted much attention in medicine because the detection of diseases at an early stage provides greater opportunities for successful treatment. Consequently, over the past few decades, diverse imaging modalities including magnetic resonance (MR), positron emission tomography, computed tomography, and ultrasound (US) have been developed and applied widely in the field of clinical diagnosis. However, each of the above-mentioned imaging modalities possesses unique strengths and intrinsic weaknesses, which limit their abilities to provide accurate information. Therefore, multimodal imaging systems may be a solution that can provide improved diagnostic performance. Among the current medical imaging modalities, US is a widely available real-time imaging modality. It has many advantages including safety, low cost and easy access for patients. However, its low spatial resolution precludes accurate discrimination of diseased region such as cancer sites. In contrast, MR has no tissue-penetrating limit and can provide images possessing exquisite soft tissue contrast and high spatial resolution. However, it cannot offer real-time images and needs a comparatively long imaging time. The characteristics of these imaging modalities may be considered complementary, and the modalities have been frequently combined for the clinical diagnostic process. Biominerals such as calcium carbonate (CaCO3) and calcium phosphate (CaP) exhibit pH-dependent dissolution behavior. They demonstrate pH-controlled drug release due to the dissolution of minerals in acidic pH conditions. In particular, the application of this mineralization technique to a US contrast agent has been reported recently. The CaCO3 mineral reacts with acids and decomposes to generate calcium dioxide (CO2) gas in an acidic environment. These gas-generating mineralized nanoparticles generated CO2 bubbles in the acidic environment of the tumor, thereby allowing for strong echogenic US imaging of tumor tissues. On the basis of this previous work, it was hypothesized that the loading of MR contrast agents into the CaCO3 mineralized nanoparticles may be a novel strategy in designing a contrast agent for dual imaging. Herein, CaCO3 mineralized nanoparticles that were capable of generating CO2 bubbles to trigger the release of entrapped MR contrast agents in response to tumoral acidic pH were developed for the purposes of US and MR dual-modality imaging of tumors. Gd2O3 nanoparticles were selected as an MR contrast agent. A key strategy employed in this study was to prepare Gd2O3 nanoparticle-loaded mineralized nanoparticles (Gd2O3-MNPs) using block copolymer-templated CaCO3 mineralization in the presence of calcium cations (Ca2+), carbonate anions (CO32-) and positively charged Gd2O3 nanoparticles. The CaCO3 core was considered suitable because it may effectively shield Gd2O3 nanoparticles from water molecules in the blood (pH 7.4) before decomposing to generate CO2 gas, triggering the release of Gd2O3 nanoparticles in tumor tissues (pH 6.4~7.4). The kinetics of CaCO3 dissolution and CO2 generation from the Gd2O3-MNPs were examined as a function of pH and pH-dependent in vitro magnetic relaxation; additionally, the echogenic properties were estimated to demonstrate the potential of the particles for the tumor-specific US and MR imaging.

Keywords: calcium carbonate, mineralization, ultrasound imaging, magnetic resonance imaging

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Authors: Uswah Khairuddin, Rubiyah Yusof, Nenny Ruthfalydia Rosli

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This paper presents a comparative study between k-Nearest Neighbour (k-NN) and Multi-Layer Perceptron Neural Network (MLP-NN) classifier using Genetic Algorithm (GA) as feature selector for wood recognition system. The features have been extracted from the images using Grey Level Co-Occurrence Matrix (GLCM). The use of GA based feature selection is mainly to ensure that the database used for training the features for the wood species pattern classifier consists of only optimized features. The feature selection process is aimed at selecting only the most discriminating features of the wood species to reduce the confusion for the pattern classifier. This feature selection approach maintains the ‘good’ features that minimizes the inter-class distance and maximizes the intra-class distance. Wrapper GA is used with k-NN classifier as fitness evaluator (GA-kNN). The results shows that k-NN is the best choice of classifier because it uses a very simple distance calculation algorithm and classification tasks can be done in a short time with good classification accuracy.

Keywords: feature selection, genetic algorithm, optimization, wood recognition system

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Authors: Mona Elsalamawy, Ashraf Ragab Mohamed, Abdellatif Elsayed Abosen

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This paper aims to evaluate the effectiveness of different crystalline coating materials concerning of chloride ions penetration. The concrete ages at the coating installation and its moisture conditions were addressed; where, these two factors may play a dominant role for the effectiveness of the used materials. Rapid chloride ions penetration test (RCPT) was conducted at different ages and moisture conditions according to the relevant standard. In addition, the contaminated area and the penetration depth of the chloride ions were investigated immediately after the RCPT test using chemical identifier, 0.1 M silver nitrate AgNO₃ solution. Results have shown that, the very low chloride ions penetrability, for the studied crystallization materials, were investigated only with the old age concrete (G1). The significant reduction in chloride ions’ penetrability was illustrated after 7 days of installing the crystalline coating layers. Using imageJ is more reliable to describe the contaminated area of chloride ions, where the distribution of aggregate and heterogeneous of cement mortar was considered in the images analysis.

Keywords: chloride permeability, contaminated area, crystalline waterproofing materials, RCPT, XRD

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Authors: Gaurav Verma

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Organoclay loaded (0-5 weight %) polyester-urethane (PU) coatings were prepared with a branched hydroxyl-bearing polyester and an aliphatic poly-isocyanate. TEM micrographs show partial exfoliation and intercalation of clay platelets in organoclay-polyester dispersions. AFM surface images reveals that the PU hard domains tend to regularise and also self-organise into spherical shapes of sizes 50 nm (0 wt %), 60 nm (2 wt %) and 190 nm (4 wt %) respectively. IR analysis shows that PU chains have increasing tendency to interact with exfoliated clay platelets through hydrogen bonding. This interaction strengthens inter-chain linkages in PU matrix and hence improves anti-ageing properties. 1000 hours of accelerated weathering was evaluated by ATR spectroscopy, while yellowing and overall discoloration was quantified by the Δb* and ΔE* values of the CIELab colour scale. Post-weathering surface properties also showed improvement as the loss of thickness and reduction in gloss in neat PU was 25% and 42%; while it was just 3.5% and 14% respectively for the 2 wt% nanocomposite coating. This work highlights the importance of modifying surface and bulk properties of PU coatings at nanoscale, which led to improved performance in accelerated weathering conditions.

Keywords: coatings, AFM, ageing, spectroscopy

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Authors: Wei Ji

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This study was conducted in the Kansas City metropolitan area of the United States, which has experienced significant urban sprawling in recent decades. The remote sensing of land cover changes in this area spanned over four decades from 1972 through 2010. The project was implemented in two stages: the first stage focused on detection of long-term trends of urban land cover change, while the second one examined how to detect the coupled effects of human impact and climate change on urban landscapes. For the first-stage study, six Landsat images were used with a time interval of about five years for the period from 1972 through 2001. Four major land cover types, built-up land, forestland, non-forest vegetation land, and surface water, were mapped using supervised image classification techniques. The study found that over the three decades the built-up lands in the study area were more than doubled, which was mainly at the expense of non-forest vegetation lands. Surprisingly and interestingly, the area also saw a significant gain in surface water coverage. This observation raised questions: How have human activities and precipitation variation jointly impacted surface water cover during recent decades? How can we detect such coupled impacts through remote sensing analysis? These questions led to the second stage of the study, in which we designed and developed approaches to detecting fine-scale surface waters and analyzing coupled effects of human impact and precipitation variation on the waters. To effectively detect urban landscape changes that might be jointly shaped by precipitation variation, our study proposed “urban wetscapes” (loosely-defined urban wetlands) as a new indicator for remote sensing detection. The study examined whether urban wetscape dynamics was a sensitive indicator of the coupled effects of the two driving forces. To better detect this indicator, a rule-based classification algorithm was developed to identify fine-scale, hidden wetlands that could not be appropriately detected based on their spectral differentiability by a traditional image classification. Three SPOT images for years 1992, 2008, and 2010, respectively were classified with this technique to generate the four types of land cover as described above. The spatial analyses of remotely-sensed wetscape changes were implemented at the scales of metropolitan, watershed, and sub-watershed, as well as based on the size of surface water bodies in order to accurately reveal urban wetscape change trends in relation to the driving forces. The study identified that urban wetscape dynamics varied in trend and magnitude from the metropolitan, watersheds, to sub-watersheds in response to human impacts at different scales. The study also found that increased precipitation in the region in the past decades swelled larger wetlands in particular while generally smaller wetlands decreased mainly due to human development activities. These results confirm that wetscape dynamics can effectively reveal the coupled effects of human impact and climate change on urban landscapes. As such, remote sensing of this indicator provides new insights into the relationships between urban land cover changes and driving forces.

Keywords: urban land cover, human impact, climate change, rule-based classification, across-scale analysis

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Authors: Cherifi Mehdi, Lahdir Mourad, Ameur Soltane

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Image compression is the heart of several multimedia techniques. It is used to reduce the number of bits required to represent an image. Meteosat Second Generation (MSG) satellite allows the acquisition of 12 image files every 15 minutes and that results in a large databases sizes. In this paper, a novel image compression method based on the arithmetic coding with the sorted Run Length Coding (SRLC) for MSG images is proposed. The SRLC allows us to find the occurrence of the consecutive pixels of the original image to create a sorted run. The arithmetic coding allows the encoding of the sorted data of the previous stage to retrieve a unique code word that represents a binary code stream in the sorted order to boost the compression ratio. Through this article, we show that our method can perform the best results concerning compression ratio and bit rate unlike the method based on the Run Length Coding (RLC) and the arithmetic coding. Evaluation criteria like the compression ratio and the bit rate allow the confirmation of the efficiency of our method of image compression.

Keywords: image compression, arithmetic coding, Run Length Coding, RLC, Sorted Run Length Coding, SRLC, Meteosat Second Generation, MSG

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Authors: Amit Kumar, Himanshu Singal, Arnav Bhavsar

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In this modern era of automation, most of the academic exams and competitive exams are Multiple Choice Questions (MCQ). The responses of these MCQ based exams are recorded in the Optical Mark Reader (OMR) sheet. Evaluation of the OMR sheet requires separate specialized machines for scanning and marking. The sheets used by these machines are special and costs more than a normal sheet. Available process is non-economical and dependent on paper thickness, scanning quality, paper orientation, special hardware and customized software. This study tries to tackle the problem of evaluating the OMR sheet without any special hardware and making the whole process economical. We propose an image processing based algorithm which can be used to read and evaluate the scanned OMR sheets with no special hardware required. It will eliminate the use of special OMR sheet. Responses recorded in normal sheet is enough for evaluation. The proposed system takes care of color, brightness, rotation, little imperfections in the OMR sheet images.

Keywords: OMR, image processing, hough circle trans-form, interpolation, detection, binary thresholding

Procedia PDF Downloads 171

Authors: Cemre Polat, Mustafa Soyler, Bulent Yaniktepe, Coskun Ozalp

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In this study, it was aimed to control the flow actively by giving an oscillating rotational motion to a vertically placed cylinder, and flow characteristics were determined. In the study, firstly, the flow structure around the flat cylinder was investigated with dye experiments, and then the cylinders with different oscillation angles (θ = 60°, θ = 120°, and θ = 180°) and different rotation speeds (15 rpm and 30 rpm) the flow structure around it was examined. Thus, the effectiveness of oscillation and rotation speed in flow control has been investigated. In the dye experiments, the dye/water mixture obtained by mixing Rhodamine 6G in powder form with water, which shines under laser light and allows detailed observation of the flow structure, was used. During the experiments, the dye was injected into the flow with the help of a thin needle at a distance that would not affect the flow from the front of the cylinder. In dye experiments, 100 frames per second were taken with a Canon brand EOS M50 (24MP) digital mirrorless camera at a resolution of 1280 * 720 pixels. Then, the images taken were analyzed, and the pictures representing the flow structure for each experiment were obtained. As a result of the study, it was observed that no separation points were formed at 180° swing angle at 15 rpm speed, 120° and 180° swing angle at 30 rpm, and the flow was controlled according to the fixed cylinder.

Keywords: active flow control, cylinder, flow visualization rotationally oscillating

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Authors: Samira Taleb, Sakina Aoun, Slimane Ziani, Zoheir Mentouri, Adel Boudiaf

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Rolling is a pressure treatment technique that modifies the shape of steel ingots or billets between rotating rollers. During this process, defects may form on the surface of the rolled sheets and are likely to affect the performance and quality of the finished product. In our study, we developed a method for detecting surface hole defects using a pixel classification approach. This work includes several steps. First, we performed image preprocessing to delimit areas with and without hole defects on the sheet image. Then, we developed the histograms of each area to generate the gray level membership intervals of the pixels that characterize each area. As we noticed an intersection between the characteristics of the gray level intervals of the images of the two areas, we finally performed a learning step based on a series of detection tests to refine the membership intervals of each area, and to choose the defect detection criterion in order to optimize the recognition of the surface hole.

Keywords: classification, defect, surface, detection, hole

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Authors: Lin Chang

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Birmingham, England was a town in the late-eighteenth century and became the nation’s second largest city in the late nineteenth century. The city expanded rapidly in terms of its population and size. Three generations of artists from a local family, the Lines, made a large number of drawings and paintings depicting the growth and changes of their city. At first sight, the meaning of the pictures seems straight-forward: providing records of what were torn down and newly-built. However, except for being read as maps, the pictures reveal a struggle in vision as to whether unsightly manufactories and their smoking chimneys should be visualized and how far the borders of the town should have been positioned and understood as they continued to grow and encroached upon its immediate countryside. This art-historic paper examines some topographic views by the Lines family and explores how they, through unusual depiction of rural and urban scenery, manage to give form to the borderlands between the country and the city. This paper argues that while the idea of the country and the city seems to be common sense, the two realms actually pose difficulty for visual representation as to where exactly their borders are and the idea itself has dichotomized the way people consider landscape imageries to be.

Keywords: Birmingham, suburb, urban fringes, landscape

Procedia PDF Downloads 196

Authors: Cliff Shunsheng Han

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Identifying the direct allergy cause that can be easily mitigated is the foundation to stop the allergy epidemic that has been started in the seventies. It has confirmed that the personal and social hygiene practices are associated with the allergy prevalence. But direct causes have been found, and proposed translational measures have not been effective. This study, assisted by a particular case of allergies, has seen the direct cause of allergies, developed a valid test resulted in lasting relief for allergies, and constructed theory describing general relationship between microbiota and host immune system. Saliva samples were collected from a subject for three years during which time the person experienced yearlong allergy, seasonal allergy, and remission of allergy symptoms. Bacterial DNA was extracted and 16S rRNA genes were profiled with Illumina sequencing technology. The analyzing results indicate that the possible direct cause of allergy is the lacking probiotic bacteria in the oral cavity, such as genera Streptococcus and Veilonella, that can produce metabolites to pacify immune system. Targeted promotion of those bacteria with a compound designed for them, has led to lasting remissions of allergic rhinitis. During the development of the translational measure, the subject's oral biofilm was completely destructed by a moderate fever due to an unrelated respiratory infection. The incident not only facilitated the development of the heat based microbiota reseeding procedure but also indicated a possible natural switch that subsequently increases the efficacy of the immune system previously restrained by metabolites from microbiota. These results lead to the proposal of a Theory of Negative Trigger (TNT) to describe the relationship between oral probiotics and immune system, in which probiotics are the negative trigger that will release the power of immune system when removed by fever or modern lifestyles. This study could open doors leading to further understanding of how the immune system functions under the influence of microbiota as well as validate simple traditional practices for healthy living.

Keywords: oral microbiome, allergy, immune system, infection

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Authors: Leah Ning

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This paper discusses the development of a machine learning algorithm that accurately detects metastatic breast cancer (cancer has spread elsewhere from its origin part) in selected images that come from pathology scans of lymph node sections. Being able to develop an accurate artificial intelligence (AI) algorithm would help significantly in breast cancer diagnosis since manual examination of lymph node scans is both tedious and oftentimes highly subjective. The usage of AI in the diagnosis process provides a much more straightforward, reliable, and efficient method for medical professionals and would enable faster diagnosis and, therefore, more immediate treatment. The overall approach used was to train a convolution neural network (CNN) based on a set of pathology scan data and use the trained model to binarily classify if a new scan were benign or malignant, outputting a 0 or a 1, respectively. The final model’s prediction accuracy is very high, with 100% for the train set and over 70% for the test set. Being able to have such high accuracy using an AI model is monumental in regard to medical pathology and cancer detection. Having AI as a new tool capable of quick detection will significantly help medical professionals and patients suffering from cancer.

Keywords: breast cancer detection, AI, machine learning, algorithm

Procedia PDF Downloads 89

Authors: Janella Salamania, Marcedon Fernandez, Matthew Villanueva Henry Ramos

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Titanium nitrite (TiN) a popular functional and decorative coating because of its golden yellow color, high hardness and superior wear resistance. It is also being studied as a diffusion barrier in integrated circuits due to its known chemical stability and low resistivity. While there have been numerous deposition methods done for TiN, most required the heating of substrates at high temperatures. In this work, TiN films are deposited on silicon (111) and (100) substrates without substrate heating using a patented magnetized sheet plasma source. Films were successfully deposited without substrate heating at various target bias, while maintaining a constant 25% N2 to Ar ratio, and deposition of time of 30 minutes. The resulting films exhibited a golden yellow color which is characteristic of TiN. X-ray diffraction patterns show the formation of TiN predominantly oriented in the (111) direction regardless of substrate used. EDX data also confirms the 1:1 stoichiometry of titanium an nitrogen. Ellipsometry measurements estimate the thickness to range from 28 nm to 33 nm. SEM images were also taken to observe the morphology of the film.

Keywords: coatings, nitrides, coatings, reactive magnetron sputtering, thin films

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Authors: Yanwen Li, Shuguo Xie

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In electromagnetic imaging, because of the diffraction limited system, the pixel values could change slowly near the edge of the image targets and they also change with the location in the same target. Using traditional digital image segmentation methods to segment electromagnetic gradient images could result in lots of errors because of this change in pixel values. To address this issue, this paper proposes a novel image segmentation and extraction algorithm based on Mean-Shift and dictionary learning. Firstly, the preliminary segmentation results from adaptive bandwidth Mean-Shift algorithm are expanded, merged and extracted. Then the overlap rate of the extracted image block is detected before determining a segmentation region with a single complete target. Last, the gradient edge of the extracted targets is recovered and reconstructed by using a dictionary-learning algorithm, while the final segmentation results are obtained which are very close to the gradient target in the original image. Both the experimental results and the simulated results show that the segmentation results are very accurate. The Dice coefficients are improved by 70% to 80% compared with the Mean-Shift only method.

Keywords: gradient image, segmentation and extract, mean-shift algorithm, dictionary iearning

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Authors: Bhuyain Mobarok Hossain

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Image classification and localization research is currently an important strategy in the field of computer vision. The evolution and advancement of deep learning and convolutional neural networks (CNN) have greatly improved the capabilities of object detection and image-based classification. Target detection is important to research in the field of computer vision, especially in video surveillance systems. To solve this problem, we will be applying a convolutional neural network of multiple scales at multiple locations in the image in one sliding window. Most translation networks move away from the bounding box around the area of interest. In contrast to this architecture, we consider the problem to be a classification problem where each pixel of the image is a separate section. Image classification is the method of predicting an individual category or specifying by a shoal of data points. Image classification is a part of the classification problem, including any labels throughout the image. The image can be classified as a day or night shot. Or, likewise, images of cars and motorbikes will be automatically placed in their collection. The deep learning of image classification generally includes convolutional layers; the invention of it is referred to as a convolutional neural network (CNN).

Keywords: image classification, object detection, localization, particle filter

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Authors: Sapora Sipon, Mohd Fo’ad Sakdan, Che Su Mustaffa, Najib Ahmad Marzuki, Mohamad Sukeri Khalid, Mohd Taib Ariffin, Husni Mohd Radzi, Salhah Abdullah

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Flood disasters occur throughout the world including Malaysia. The major flood disaster that hit Malaysia in the 2014-2015 episodes proved the psychosocial and mental health consequences such as vivid images of destruction, upheaval, death and loss of lives. Flood, flood survivors reported that flood has changed one looks at their religious belief. The main objective of this paper is to investigate the changes in religious belief after the 2014-2015 Malaysia flood disaster. The total population of 1300 respondents who experienced the 2014-2015 Malaysia flood were surveyed a month after the disaster. The questionnaires were used to measure religiosity and stress. The results provide compelling evidence that religion played an important role in the lives of Malaysia flood disasters’ survivor where more than half of the respondents (>75%) experiencing the strengthening of their religious belief. It was also reported the victims’ strengthening of their religious belief proved to be a powerful factor in reducing stress in the aftermath of the flood.

Keywords: religious belief, flood disaster, humanity, society

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Authors: Yuet Wah Echo Yeung

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Working with people from minority ethnic groups, refugees and asylum seeking communities who have limited proficiency in the language of the host country often presents a major challenge for social workers. Because of language differences, social workers need to work with interpreters to ensure accurate information is collected for their assessment and intervention. Drawing from social learning theory, this paper discusses how role play was used as an experiential learning exercise in a training session to help social work students develop skills when working with interpreters. Social learning theory posits that learning is a cognitive process that takes place in a social context when people observe, imitate and model others’ behaviours. The roleplay also helped students understand the role of the interpreter and the challenges they may face when they rely on interpreters to communicate with service users and their family. The first part of the session involved role play. A tutor played the role of social worker and deliberately behaved in an unprofessional manner and used inappropriate body language when working alongside the interpreter during a home visit. The purpose of the roleplay is not to provide a positive role model for students to ‘imitate’ social worker’s behaviours. Rather it aims to active and provoke internal thinking process and encourages students to critically consider the impacts of poor practice on relationship building and the intervention process. Having critically reflected on the implications for poor practice, students were then asked to play the role of social worker and demonstrate what good practice should look like. At the end of the session, students remarked that they learnt a lot by observing the good and bad example; it showed them what not to do. The exercise served to remind students how practitioners can easily slip into bad habits and of the importance of respect for the cultural difference when working with people from different cultural backgrounds.

Keywords: role play, social learning theory, social work practice, working with interpreters

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Authors: Guankai Lin, Wei Tong, Hong Zhu

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The electric current induced Joule heating effects have been investigated in La₀.₈Ba₀.₂MnO₃ ultrathin films deposited on LaAlO₃(001) single crystal substrate with smaller lattice constant by using the sol-gel method. By applying moderate bias currents (~ 10 mA), it is found that Joule self-heating simply gives rise to a temperature deviation between the thermostat and the test sample, but the intrinsic ρ(T) relationship measured at a low current (0.1 mA) changes little. However, it is noteworthy that the low-temperature transport behavior degrades from metallic to insulating state after applying higher bias currents ( > 31 mA) in a vacuum. Furthermore, metallic transport can be recovered by placing the degraded film in air. The results clearly suggest that the oxygen vacancy in the La₀.₈Ba₀.₂MnO₃ films is controllable in different atmospheres, particularly with the aid of the Joule self-heating. According to the SEM images, we attribute the controlled oxygen vacancy to the nano-sized labyrinth pattern of the films, where the large surface-to-volume ratio plays a curial role.

Keywords: controlling oxygen vacancy, joule self-heating, manganite, sol-gel method

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Authors: Sanjay Singh, Sushil Kumar, Rashmi Jain

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Quantum registering is another pattern in computational hypothesis and a quantum mechanical framework has a few helpful properties like Entanglement. We plan to store data concerning the structure and substance of a basic picture in a quantum framework. Consider a variety of n qubits which we propose to use as our memory stockpiling. In recent years classical processing is switched to quantum image processing. Quantum image processing is an elegant approach to overcome the problems of its classical counter parts. Image storage, retrieval and its processing on quantum machines is an emerging area. Although quantum machines do not exist in physical reality but theoretical algorithms developed based on quantum entangled states gives new insights to process the classical images in quantum domain. Here in the present work, we give the brief overview, such that how entangled states can be useful for quantum image storage and retrieval. We discuss the properties of tripartite Greenberger-Horne-Zeilinger and W states and their usefulness to store the shapes which may consist three vertices. We also propose the techniques to store shapes having more than three vertices.

Keywords: Greenberger-Horne-Zeilinger, image storage and retrieval, quantum entanglement, W states

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Authors: Blessing Mavhuru, Nthaduleni Nethengwe, Hector Chikoore, Onyango Beneah Daniel Odhiambo

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The main objective of this study was to classify land use/cover and how it has changed in Nzhelele Valley Limpopo Province, South Africa. The study aimed to identify and analyse the types of land use/cover in the years 2005, 2010, and 2015 with a view to assess the impact on soil erosion over time. Using GIS, the changes within land use/cover were assessed through the classification of satellite images. The study area was classified into four major land cover/use classes, which are vegetation, gravel road, built up land and agricultural fields. Over the period 2005-2015 the resultant land use/cover demonstrated (i) a significant increase (12%) for vegetation cover, (ii) a significant decrease in agriculture (16%) land use/cover, (iii) increase in built-up land (1%), as well as (iv) an increase in gravel roads (3%). This study envisages assisting policy makers in decision making on land use management for Nzhelele Valley.

Keywords: land use, land cover, change, soil erosion

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Authors: Angely Sim Jia Wun, Sasa Arsovski

Abstract:

Numerous studies have been conducted on the segmentation of medical images. Segmenting the lungs is one of the common research topics in those studies. Our research stemmed from the lack of solutions for automatic bone, airway, and vessel segmentation, despite the existence of multiple lung segmentation techniques. Consequently, currently, available software tools used for medical image segmentation do not provide automatic lung, bone, airway, and vessel segmentation. This paper presents segmentation techniques along with an interactive software tool architecture for segmenting bone, lung, airway, and vessel tissues. Additionally, we propose a method for creating binary masks from automatically generated segments. The key contribution of our approach is the technique for automatic image thresholding using adjustable Hounsfield values and binary mask extraction. Generated binary masks can be successfully used as a training dataset for deep-learning solutions in medical image segmentation. In this paper, we also examine the current software tools used for medical image segmentation, discuss our approach, and identify its advantages.

Keywords: lung segmentation, binary masks, U-Net, medical software tools

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Authors: Abe D. Desta

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This study suggests a deep learning-based method for identifying and following moving objects in surveillance video. The proposed method uses a fast regional convolution neural network (F-RCNN) trained on a substantial dataset of vehicle images to first detect vehicles. A Kalman filter and a data association technique based on a Hungarian algorithm are then used to monitor the observed vehicles throughout time. However, in general, F-RCNN algorithms have been shown to be effective in achieving high detection accuracy and robustness in this research study. For example, in one study The study has shown that the vehicle detection and tracking, the system was able to achieve an accuracy of 97.4%. In this study, the F-RCNN algorithm was compared to other popular object detection algorithms and was found to outperform them in terms of both detection accuracy and speed. The presented system, which has application potential in actual surveillance systems, shows the usefulness of deep learning approaches in vehicle detection and tracking.

Keywords: artificial intelligence, computer vision, deep learning, fast-regional convolutional neural networks, feature extraction, vehicle tracking

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Authors: Mohammad Afkhami, Saeid Reza Ameli Ranani

Abstract:

Since the bitcoin invention in 2008, blockchain technology surpassed so many innovations that the pioneer networks such as Ethereum are adaptable to host a decentral bunch of information containing pictures, audio, video, domains, etc., or even a metaverse versatile avatar. Transformation of tangible goods into virtual assets, known as AR-utility of luxury products, and the intermixture of reality and virtuality organized a worldwide, semi-regulated, and decentralized marketplace for digital goods. Non-fungible tokens (NFTs) are doing a great help to artists worldwide, sharing diverse cultural outlooks by setting up a remote cross-cultural corporation potential and, at the same time, metamorphosizing the middleman role and ceasing the necessity of having a SWIFT-connected bank account. Under critical sanctions, a group of artists in Tehran did not take for granted such an opportunity to show off their artworks undisturbed, offering an introspective attitude, exerting Iranian motifs while intermingling westernized symbols. The cryptocurrency market has already acquired allocation, and interest in the global domain, paving the way for a flourishing enthusiasm among entrepreneurs who have been preoccupied with high-tech start-ups before. In a project found by Iranian female artists, we decipher the ups and downs of the new cyberculture and the environment it provides to fairly promote the artwork and obstacles it put forward in the way of interested entrepreneurs as we get through the details of starting up an NFT collection. An in-depth interview and empirical encounters with diverse Social Network Sites (SNS) and the strategies that other successful projects deploy to sell their artworks in an international and, at the same time, an anonymous market is the main focus, which shapes the paper fieldwork perspective. In conclusion, we discuss strategies for promoting an NFT project.

Keywords: NFT, metaverse, intercultural, art, illustration, start-up, entrepreneurship

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Authors: Fatma Abdedayem

Abstract:

We propose an extension to the famous method called Bag of words (BOW) which proved a successful role in the field of image categorization. Practically, this method based on representing image with visual words. In this work, firstly, we extract features from images using Spatial Pyramid Representation (SPR) and two dissimilar color descriptors which are opponent-SIFT and transformed-color-SIFT. Secondly, we fuse color local features by joining the two histograms coming from these descriptors. Thirdly, after collecting of all features, we generate multi-dictionaries coming from n random feature subsets that obtained by dividing all features into n random groups. Then, by using these dictionaries separately each image can be represented by n histograms which are lately concatenated horizontally and form the final histogram, that allows to combine Multiple Dictionaries (MDBoW). In the final step, in order to classify image we have applied Support Vector Machine (SVM) on the generated histograms. Experimentally, we have used two dissimilar image datasets in order to test our proposition: Caltech 256 and PASCAL VOC 2007.

Keywords: bag of words (BOW), color descriptors, multi-dictionaries, MDBoW

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Authors: Khue Do Phan

Abstract:

Nike has been confronted by the press with their harsh working conditions, underpayment and highly-labor intensive requirement to their manufacturing workers and hiring of underage workers in Vietnam, Nike's largest production center. To analyze this topic critically through an international relations perspective, theory of dependency will be used to criticize the notion of exploitation of resources from developed countries towards developing countries. Theory of economic liberalism will be used to support the notion private property, the free market and generally capitalism as beneficial to both developing and developed countries. Workers are mentally, physically and sexually abused in the factories. In addition to this, their working conditions consist of improper training, lack of safety equipment, exposure of chemicals (glues and pants), their average wage is below the minimum wage in their country; the workers have to work around 60 hours or more a week. Even Nike says that the conditions are regulated often to make sure the workers get a voice to have their work rights and safe working environment. The monitors come to analyze the factories but in the end talk to the employers, whom are the direct abusers to the employees. Health benefits are rarely granted to the employees; they are forced to pay their bills first then the company will reimburse them later. They would also get in trouble for using the bathroom, taking a lunch break or sick days off because this would mean it would decrease their hours of work, leading to an even lower wage and a really angry employer. Of course with the press criticizing Nike’s lack of respect for human rights and working rights, Nike has been working on policy making and implementation to deal with the abuses. Due to its large chains and a great number of outsourcing host countries, the changes that Nike wish or attempt to make have not be in effect as quickly nor spreading to all countries it holds accountable for in its outsourcing factories.

Keywords: dependency theory, economic liberalism, human rights, outsource

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Authors: Yu-Ching Cheng, Yi-Kai Juan, Daniel Castro

Abstract:

Energy consumption of buildings has been an increasing concern for researchers and practitioners in the last decade. Sustainable building renovation can reduce energy consumption and carbon dioxide emissions; meanwhile, it also can extend existing buildings useful life and facilitate environmental sustainability while providing social and economic benefits to the society. School buildings are different from other designed spaces as they are more crowded and host the largest portion of daily activities and occupants. Strategies that focus on reducing energy use but also improve the students’ learning environment becomes a significant subject in sustainable school buildings development. A decision model is developed in this study to solve complicated and large-scale combinational, discrete and determinate problems such as school renovation projects. The task of this model is to automatically search for the most cost-effective (lower cost and higher quality) renovation strategies. In this study, the search process of optimal school building renovation solutions is by nature a large-scale zero-one programming determinate problem. A* is suitable for solving deterministic problems due to its stable and effective search process, and genetic algorithms (GA) provides opportunities to acquire global optimal solutions in a short time via its indeterminate search process based on probability. These two algorithms are combined in this study to consider trade-offs between renovation cost and improved quality, this decision model is able to evaluate current school environmental conditions and suggest an optimal scheme of sustainable school buildings renovation strategies. Through adoption of this decision model, school managers can overcome existing limitations and transform school buildings into spaces more beneficial to students and friendly to the environment.

Keywords: decision model, school buildings, sustainable renovation, genetic algorithm, A* search algorithm

Procedia PDF Downloads 117