Search results for: image narrative

Authors: Paweł Konieczka, Lech Raczyński, Wojciech Wiślicki, Oleksandr Fedoruk, Konrad Klimaszewski, Przemysław Kopka, Wojciech Krzemień, Roman Shopa, Jakub Baran, Aurélien Coussat, Neha Chug, Catalina Curceanu, Eryk Czerwiński, Meysam Dadgar, Kamil Dulski, Aleksander Gajos, Beatrix C. Hiesmayr, Krzysztof Kacprzak, łukasz Kapłon, Grzegorz Korcyl, Tomasz Kozik, Deepak Kumar, Szymon Niedźwiecki, Dominik Panek, Szymon Parzych, Elena Pérez Del Río, Sushil Sharma, Shivani Shivani, Magdalena Skurzok, Ewa łucja Stępień, Faranak Tayefi, Paweł Moskal

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This paper develops the transformation of non-image data into 2-dimensional matrices, as a preparation stage for classification based on convolutional neural networks (CNNs). In positron emission tomography (PET) studies, CNN may be applied directly to the reconstructed distribution of radioactive tracers injected into the patient's body, as a pattern recognition tool. Nonetheless, much PET data still exists in non-image format and this fact opens a question on whether they can be used for training CNN. In this contribution, the main focus of this paper is the problem of processing vectors with a small number of features in comparison to the number of pixels in the output images. The proposed methodology was applied to the classification of PET coincidence events.

Keywords: convolutional neural network, kernel principal component analysis, medical imaging, positron emission tomography

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Authors: Ana Avila Bohorquez

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Elite (Netflix, 2018-) is the second original series produced by Netflix in Spain. Premiered in 2018, it became an international success, both critically and among audiences. Reviewers praised its use of teen drama tropes with a more progressive twist. Netflix announced that the first season had been streamed by over 20 million accounts within its first month of release. This paper aims to determine what characteristics led to Elite’s international success, finding the elements of its narrative and visual design that resonate with global audiences. After reviewing the bibliography about transnational fiction, questionnaires sent to international audience members through social media shed light on what these characteristics are. Additionally, interviews with the creative team were performed in order to compare their point of view with the audiences’ perception. Even though Elite can be considered a Spanish show from its inception, it's setting in the “fantasy” world of the rich and its lack of social realism so common among Spanish productions managed to attract global audiences, to whom it has appealed on a more emotional level.

Keywords: elite, global television, Netflix, teen drama, transnational fiction

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Authors: Zhao Gao, Eran Edirisinghe

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The production of an accurate sketch of a suspect based on a verbal description obtained from a witness is an essential task for most criminal investigations. The criminal investigation system employs specifically trained professional artists to manually draw a facial image of the suspect according to the descriptions of an eyewitness for subsequent identification. Within the advancement of Deep Learning, Recurrent Neural Networks (RNN) have shown great promise in Natural Language Processing (NLP) tasks. Additionally, Generative Adversarial Networks (GAN) have also proven to be very effective in image generation. In this study, a trained GAN conditioned on textual features such as keywords automatically encoded from a verbal description of a human face using an RNN is used to generate photo-realistic facial images for criminal investigations. The intention of the proposed system is to map corresponding features into text generated from verbal descriptions. With this, it becomes possible to generate many reasonably accurate alternatives to which the witness can use to hopefully identify a suspect from. This reduces subjectivity in decision making both by the eyewitness and the artist while giving an opportunity for the witness to evaluate and reconsider decisions. Furthermore, the proposed approach benefits law enforcement agencies by reducing the time taken to physically draw each potential sketch, thus increasing response times and mitigating potentially malicious human intervention. With publically available 'CelebFaces Attributes Dataset' (CelebA) and additionally providing verbal description as training data, the proposed architecture is able to effectively produce facial structures from given text. Word Embeddings are learnt by applying the RNN architecture in order to perform semantic parsing, the output of which is fed into the GAN for synthesizing photo-realistic images. Rather than the grid search method, a metaheuristic search based on genetic algorithms is applied to evolve the network with the intent of achieving optimal hyperparameters in a fraction the time of a typical brute force approach. With the exception of the ‘CelebA’ training database, further novel test cases are supplied to the network for evaluation. Witness reports detailing criminals from Interpol or other law enforcement agencies are sampled on the network. Using the descriptions provided, samples are generated and compared with the ground truth images of a criminal in order to calculate the similarities. Two factors are used for performance evaluation: The Structural Similarity Index (SSIM) and the Peak Signal-to-Noise Ratio (PSNR). A high percentile output from this performance matrix should attribute to demonstrating the accuracy, in hope of proving that the proposed approach can be an effective tool for law enforcement agencies. The proposed approach to criminal facial image generation has potential to increase the ratio of criminal cases that can be ultimately resolved using eyewitness information gathering.

Keywords: RNN, GAN, NLP, facial composition, criminal investigation

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Authors: Anahit Khananyan

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The results of the long-term Jungian analysis with female clients from Eastern and Asian countries, which belong to collectivist cultures, are summarised in the article. The goal of the paper is to describe the cultural complex, which was found by the author in the analysis of women of collectivistic culture. It was named “the repression of Animus”. Generally, C.G.Jung himself and the Post-Jungians studied conditions caused by the possession by Animus. The conditions and cases of the repressed Animus, depending on the type of culture and cultural complexes, as we know, were not widely disseminated. C.G. Jung discovered and recognized the Animus as the second component of a pair of opposites of the psyche of women – femininity and Animus. In the way of individuation, an awareness of manifestations of Animus plays an important role: understanding the differences between negative and positive Animus as well as the Animus and the Shadow, then standing the tension of the presence of a pair of opposites - femininity and Animus, acceptance of the tension of them, finding the balance between them and reconciliation of this opposites. All of the above are steps towards the realization of the Animus, its release Animua, and the healing of the psyche. In the paper, the author will share her experience of analyzing the women of different collectivist cultures and her experience of recognizing the repressed Animus during the analysis. Also, she will describe some peculiarities of upbringing and cultural traditions, which reflected the cultural complex of repression of Animus. This complex is manifested in the traditions of girls' upbringing in accordance with which an image of a woman with overly developed femininity and an absence or underdeveloped Animus is idealized and encouraged as well as an evaluating attitude towards females who have to correspond to this image and fulfill the role prescribed in this way in the family and society.

Keywords: analysis, cultural complex, animus, manifestation, culture

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Authors: S. Gharbi, S. Labidi, M. Mars, M. Chelli, F. Ladeb

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The purpose of this study is to reduce radiation dose for chest CT examination by including Tube Current Modulation (TCM) to a standard CT protocol. A scan of an anthropomorphic male Alderson phantom was performed on a 128-slice scanner. The estimation of effective dose (ED) in both scans with and without mAs modulation was done via multiplication of Dose Length Product (DLP) to a conversion factor. Results were compared to those measured with a CT-Expo software. The size specific dose estimation (SSDE) values were obtained by multiplication of the volume CT dose index (CTDIvol) with a conversion size factor related to the phantom’s effective diameter. Objective assessment of image quality was performed with Signal to Noise Ratio (SNR) measurements in phantom. SPSS software was used for data analysis. Results showed including CARE Dose 4D; ED was lowered by 48.35% and 51.51% using DLP and CT-expo, respectively. In addition, ED ranges between 7.01 mSv and 6.6 mSv in case of standard protocol, while it ranges between 3.62 mSv and 3.2 mSv with TCM. Similar results are found for SSDE; dose was higher without TCM of 16.25 mGy and was lower by 48.8% including TCM. The SNR values calculated were significantly different (p=0.03<0.05). The highest one is measured on images acquired with TCM and reconstructed with Filtered back projection (FBP). In conclusion, this study proves the potential of TCM technique in SSDE and ED reduction and in conserving image quality with high diagnostic reference level for thoracic CT examinations.

Keywords: anthropomorphic phantom, computed tomography, CT-expo, radiation dose

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Authors: Akrem Sellami, Imed Riadh Farah

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Hyperspectral imagery (HSI) typically provides a wealth of information captured in a wide range of the electromagnetic spectrum for each pixel in the image. Hence, a pixel in HSI is a high-dimensional vector of intensities with a large spectral range and a high spectral resolution. Therefore, the semantic interpretation is a challenging task of HSI analysis. We focused in this paper on object classification as HSI semantic interpretation. However, HSI classification still faces some issues, among which are the following: The spatial variability of spectral signatures, the high number of spectral bands, and the high cost of true sample labeling. Therefore, the high number of spectral bands and the low number of training samples pose the problem of the curse of dimensionality. In order to resolve this problem, we propose to introduce the process of dimensionality reduction trying to improve the classification of HSI. The presented approach is a semi-supervised band selection method based on spatial hypergraph embedding model to represent higher order relationships with different weights of the spatial neighbors corresponding to the centroid of pixel. This semi-supervised band selection has been developed to select useful bands for object classification. The presented approach is evaluated on AVIRIS and ROSIS HSIs and compared to other dimensionality reduction methods. The experimental results demonstrate the efficacy of our approach compared to many existing dimensionality reduction methods for HSI classification.

Keywords: dimensionality reduction, hyperspectral image, semantic interpretation, spatial hypergraph

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Authors: H. Nouri, S. Chavoshi Borujeni, S. Anderson, S. Beecham, P. Sutton

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The potential risk of salt leaching through wastewater irrigation is of concern for most local governments and city councils. Despite the necessity of salinity monitoring and management in urban greenery, most attention has been on agricultural fields. This study was defined to investigate the capability and feasibility of monitoring and predicting soil salinity using near sensing and remote sensing approaches using EM38 surveys, and high-resolution multispectral image of WorldView3. Veale Gardens within the Adelaide Parklands was selected as the experimental site. The results of the near sensing investigation were validated by testing soil salinity samples in the laboratory. Over 30 band combinations forming salinity indices were tested using image processing techniques. The outcomes of the remote sensing and near sensing approaches were compared to examine whether remotely sensed salinity indicators could map and predict the spatial variation of soil salinity through a potential statistical model. Statistical analysis was undertaken using the Stata 13 statistical package on over 52,000 points. Several regression models were fitted to the data, and the mixed effect modelling was selected the most appropriate one as it takes to account the systematic observation-specific unobserved heterogeneity. Results showed that SAVI (Soil Adjusted Vegetation Index) was the only salinity index that could be considered as a predictor for soil salinity but further investigation is needed. However, near sensing was found as a rapid, practical and realistically accurate approach for salinity mapping of heterogeneous urban vegetation.

Keywords: WorldView3, remote sensing, EM38, near sensing, urban green spaces, green smart cities

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Authors: Ana L. M. Pavan, Guilherme Giacomini, Allan F. F. Alves, Marcela De Oliveira, Fernando A. B. Neto, Maria E. D. Rosa, Andre P. Trindade, Diana R. De Pina

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Mammography is a worldwide image modality used to diagnose breast cancer, even in asymptomatic women. Due to its large availability, mammograms can be used to measure breast density and to predict cancer development. Women with increased mammographic density have a four- to sixfold increase in their risk of developing breast cancer. Therefore, studies have been made to accurately quantify mammographic breast density. In clinical routine, radiologists perform image evaluations through BIRADS (Breast Imaging Reporting and Data System) assessment. However, this method has inter and intraindividual variability. An automatic objective method to measure breast density could relieve radiologist’s workload by providing a first aid opinion. However, pectoral muscle is a high density tissue, with similar characteristics of fibroglandular tissues. It is consequently hard to automatically quantify mammographic breast density. Therefore, a pre-processing is needed to segment the pectoral muscle which may erroneously be quantified as fibroglandular tissue. The aim of this work was to develop an automatic algorithm to segment and extract pectoral muscle in digital mammograms. The database consisted of thirty medio-lateral oblique incidence digital mammography from São Paulo Medical School. This study was developed with ethical approval from the authors’ institutions and national review panels under protocol number 3720-2010. An algorithm was developed, in Matlab® platform, for the pre-processing of images. The algorithm uses image processing tools to automatically segment and extract the pectoral muscle of mammograms. Firstly, it was applied thresholding technique to remove non-biological information from image. Then, the Hough transform is applied, to find the limit of the pectoral muscle, followed by active contour method. Seed of active contour is applied in the limit of pectoral muscle found by Hough transform. An experienced radiologist also manually performed the pectoral muscle segmentation. Both methods, manual and automatic, were compared using the Jaccard index and Bland-Altman statistics. The comparison between manual and the developed automatic method presented a Jaccard similarity coefficient greater than 90% for all analyzed images, showing the efficiency and accuracy of segmentation of the proposed method. The Bland-Altman statistics compared both methods in relation to area (mm²) of segmented pectoral muscle. The statistic showed data within the 95% confidence interval, enhancing the accuracy of segmentation compared to the manual method. Thus, the method proved to be accurate and robust, segmenting rapidly and freely from intra and inter-observer variability. It is concluded that the proposed method may be used reliably to segment pectoral muscle in digital mammography in clinical routine. The segmentation of the pectoral muscle is very important for further quantifications of fibroglandular tissue volume present in the breast.

Keywords: active contour, fibroglandular tissue, hough transform, pectoral muscle

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Authors: Lison Carlier

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The English language that is taught in school or used in media nowadays is defined as 'standard English,' although unstandardized Englishes, or 'parallel' Englishes, are practiced throughout the world. The existence of these 'parallel' Englishes has challenged standardization by imposing its own specific vocabulary or grammar. These non-standard languages tend to be regarded as inferior and, therefore, pose a problem regarding their translation. In the USA, 'slanguage', or slang, is a good example of a 'parallel' language. It consists of a particular set of vocabulary, used mostly in speech, and rarely in writing. Qualified as vulgar, often reduced to an urban language spoken by young people from lower classes, slanguage – or the language that is often first spoken between youths – is still the most common language used in the English-speaking world. Moreover, it appears that the prime meaning of 'informal' (as in an informal language) – a language that is spoken with persons the speaker knows – has been put aside and replaced in the general mind by the idea of vulgarity and non-appropriateness, when in fact informality is a sign of intimacy, not of vulgarity. When it comes to translating American slang, the main problem a translator encounters is the image and the cultural background usually associated with this 'parallel' language. Indeed, one will have, unwillingly, a predisposition to categorize a speaker of a 'parallel' language as being part of a particular group of people. The way one sees a speaker using it is paramount, and needs to be transposed into the target language. This paper will conduct an analysis of American slang – its use, perception and the image it gives of its speakers – and its translation into French, using the novel Is Everyone Hanging Out Without Me? (and other concerns) by way of example. In her autobiography/personal essay book, comedy writer, actress and author Mindy Kaling speaks with a very familiar English, including slang, which participates in the construction of her own voice and style, and enables a deeper connection with her readers.

Keywords: translation, English, slang, French

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Authors: Kayode A. Olaniyi, Olabanji F. Omotoye, Adeola A. Ogunleye

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The skew detection and correction form an important part of digital document analysis. This is because uncompensated skew can deteriorate document features and can complicate further document image processing steps. Efficient text document analysis and digitization can rarely be achieved when a document is skewed even at a small angle. Once the documents have been digitized through the scanning system and binarization also achieved, document skew correction is required before further image analysis. Research efforts have been put in this area with algorithms developed to eliminate document skew. Skew angle correction algorithms can be compared based on performance criteria. Most important performance criteria are accuracy of skew angle detection, range of skew angle for detection, speed of processing the image, computational complexity and consequently memory space used. The standard Hough Transform has successfully been implemented for text documentation skew angle estimation application. However, the standard Hough Transform algorithm level of accuracy depends largely on how much fine the step size for the angle used. This consequently consumes more time and memory space for increase accuracy and, especially where number of pixels is considerable large. Whenever the Hough transform is used, there is always a tradeoff between accuracy and speed. So a more efficient solution is needed that optimizes space as well as time. In this paper, an improved Hough transform (HT) technique that optimizes space as well as time to robustly detect document skew is presented. The modified algorithm of Hough Transform presents solution to the contradiction between the memory space, running time and accuracy. Our algorithm starts with the first step of angle estimation accurate up to zero decimal place using the standard Hough Transform algorithm achieving minimal running time and space but lacks relative accuracy. Then to increase accuracy, suppose estimated angle found using the basic Hough algorithm is x degree, we then run again basic algorithm from range between ±x degrees with accuracy of one decimal place. Same process is iterated till level of desired accuracy is achieved. The procedure of our skew estimation and correction algorithm of text images is implemented using MATLAB. The memory space estimation and process time are also tabulated with skew angle assumption of within 00 and 450. The simulation results which is demonstrated in Matlab show the high performance of our algorithms with less computational time and memory space used in detecting document skew for a variety of documents with different levels of complexity.

Keywords: hough-transform, skew-detection, skew-angle, skew-correction, text-document

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Authors: Budi Annisa Sidi

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Present-day Indonesia maintains a narrative of a culturally plural but unified nation. At the same time, multicultural policies extend different degrees of recognition, accommodation, toleration and even discrimination towards different socio-cultural groups. In conjunction with different ethnographic landscapes across regions in Indonesia, this approach leads to a varied experience and understanding of national identity and multiculturalism among people. As a result, governments seeking to maintain national unity while practicing multiculturalism have to juggle different expectations. This situation is examined through the microcosms of university students using questionnaires followed up by focus group discussions and personal interviews. A comparison between university students across four different provinces in Indonesia (Aceh, Jakarta, West Java and the Moluccas) highlights the influence of one’s surroundings on their perception of multiculturalism. Students in the more heterogeneous areas generally show more acceptance towards diversity compared to students in primarily homogenous areas who have little actual experience in dealing with diversity. Regardless of their environment, students claim to have positive feelings and a strong sense of attachment to Indonesia but hold different ideas of what constitutes an ideal Indonesian national identity.

Keywords: Indonesia, multiculturalism, national identity, nationalism

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Authors: Erfan Niazi, Marianne Fenech

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Red Blood Cells (RBCs) or erythrocytes tend to form chain-like aggregates under low shear rate called rouleaux. This is a reversible process and rouleaux disaggregate in high shear rates. Therefore, RBCs aggregation occurs in the microcirculation where low shear rates are present but does not occur under normal physiological conditions in large arteries. Numerical modeling of RBCs interactions is fundamental in analytical models of a blood flow in microcirculation. Population Balance Modeling (PBM) is particularly useful for studying problems where particles agglomerate and break in a two phase flow systems to find flow characteristics. In this method, the elementary particles lose their individual identity due to continuous destructions and recreations by break-up and agglomeration. The aim of this study is to find RBCs aggregation in a dynamic situation. Simplified PBM was used previously to find the aggregation rate on a static observation of the RBCs aggregation in a drop of blood under the microscope. To find aggregation rate in a dynamic situation we propose an experimental set up testing RBCs sedimentation. In this test, RBCs interact and aggregate to form rouleaux. In this configuration, disaggregation can be neglected due to low shear stress. A high-speed camera is used to acquire video-microscopic pictures of the process. The sizes of the aggregates and velocity of sedimentation are extracted using an image processing techniques. Based on the data collection from 5 healthy human blood samples, the aggregation rate was estimated as 2.7x10³(±0.3 x10³) 1/s.

Keywords: red blood cell, rouleaux, microfluidics, image processing, population balance modeling

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Authors: Pibool Waijittragum

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The purpose of this paper is to synthesize the research result of brand Identities of Thai Halal brands which related to the way of life for Thai Muslims. The results will be transforming to Thai Halal Brands packaging and label design. The expected benefit is an alternative of marketing strategy for brand building process for Halal products in Thailand. Four elements of marketing strategies which necessary for the brand identity creation is the research framework: consists of Attributes, Benefits, Values and Personality. The research methodology was applied using qualitative and quantitative; 19 marketing experts with dynamic roles in Thai consumer products were interviewed. In addition, a field survey of 122 Thai Muslims selected from 175 Muslim communities in Bangkok was studied. Data analysis will be according to 5 categories of Thai Halal product: 1) Meat 2) Vegetable and Fruits 3) Instant foods and Garnishing ingredient 4) Beverages, Desserts and Snacks 5) Hygienic daily products. The results will explain some suitable approach for brand Identities of Thai Halal brands as are: 1) Benefit approach as the characteristics of the product with its benefit. The brand identity created transform to the packaging design should be clear and display a fresh product 2) Value approach as the value of products that affect to consumers’ perception. The brand identity created transform to the packaging design should be simply look and using a trustful image 3) Personality approach as the reflection of consumers thought. The brand identity created transform to the packaging design should be sincere, enjoyable, merry, flamboyant look and using a humoristic image.

Keywords: marketing strategies, brand identity, packaging and label design, Thai Halal products

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Authors: Willard Enrique R. Macaraan

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Filipino Catholics' historicized narrative in the Church of Japan is found to be marked by contestation and negotiation. This paper aims to uncover the nuances of this marginality by utilizing Loic Wacquant's theorization of urban ghettos as well as Pierre Bourdieu's field ideation. In an attempt to illustrate the dynamics of the power-play that is implicit in any situation of marginality, the paper proposes a 'diamond-quadrant' (DQ) plane that may serve as a heuristic device for analytical purposes. This study is drawn from data collected and gathered through ten-month field research in selected church communities in the Archdiocese of Tokyo, Japan employing qualitative methodologies like participant observation, interviews, and document reviews. Reconstructing their historicized struggle since the late 70s, it is discovered that the arena of contested space has shifted from the right plane of "ghettoization" tendencies in the early years towards the left plane of "deghettoization" strategies in recent years. Still, a highly negotiated space, several situational factors, and emerging trends in and outside the ecclesial grounds have led to this major shift.

Keywords: Wacquant, ghetto, migration, religion

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Authors: Xinchen Zhu

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The rapid fame of the renowned female film star Tang Wei has made her a typical subject (or object) entangled with sensitive issues involving the official ideology, sexuality, and patriarchal values of contemporary China. In 2008, Tang Wei’s official ban has triggered the wave of debates concerning state power and censorship, actor’s rights, sexual ethics, and feminism in the public sphere. Her ban implies that Chinese film censorship acts as a key factor in reconstructing Chinese film stardom. Following the ban, as sensational media texts are re-interpreting the official discourses, the texts also functioned as a crucial vehicle in reconstructing Tang's female image. Therefore, the case study of Tang's film stardom allows us to further explore how female stardom has been entangled with the issues involving official ideology, female sexual ethics, and patriarchal values in contemporary China. This paper argues that Chinese female film stars shoulder the responsibility of film acting which would conform to the official male-dominated values. However, with the development of the Internet, the state no longer remains an absolute control over the new venues. The netizens’ discussion about her ban reshaped Tang’s image as a victim and scapegoat under the unfair oppression of the official authority. Additionally, this paper argues that similar to State’s discourse, netizens’ discourse did not reject patriarchal values, and in turn emphasized Tang Wei’s female chastity.

Keywords: film censorship, Chinese female film stardom, party-state’s power, national discourses, Tang Wei

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Authors: Ahmed Elaksher

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Over the last few years, significant progresses have been made and new approaches have been proposed for efficient collection of 3D spatial data from Unmanned aerial vehicles (UAVs) with reduced costs compared to imagery from satellite or manned aircraft. In these systems, a low-cost GPS unit provides the position, velocity of the vehicle, a low-quality inertial measurement unit (IMU) determines its orientation, and off-the-shelf cameras capture the images. Structure from Motion (SfM) and photogrammetry are the main tools for 3D surface reconstruction from images collected by these systems. Unlike traditional techniques, SfM allows the computation of calibration parameters using point correspondences across images without performing a rigorous laboratory or field calibration process and it is more flexible in that it does not require consistent image overlap or same rotation angles between successive photos. These benefits make SfM ideal for UAVs aerial mapping. In this paper, a direct comparison between SfM Digital Elevation Models (DEM) and those generated through traditional photogrammetric techniques was performed. Data was collected by a 3DR IRIS+ Quadcopter with a Canon PowerShot S100 digital camera. Twenty ground control points were randomly distributed on the ground and surveyed with a total station in a local coordinate system. Images were collected from an altitude of 30 meters with a ground resolution of nine mm/pixel. Data was processed with PhotoScan, VisualSFM, Imagine Photogrammetry, and a photogrammetric algorithm developed by the author. The algorithm starts with performing a laboratory camera calibration then the acquired imagery undergoes an orientation procedure to determine the cameras’ positions and orientations. After the orientation is attained, correlation based image matching is conducted to automatically generate three-dimensional surface models followed by a refining step using sub-pixel image information for high matching accuracy. Tests with different number and configurations of the control points were conducted. Camera calibration parameters estimated from commercial software and those obtained with laboratory procedures were comparable. Exposure station positions were within less than few centimeters and insignificant differences, within less than three seconds, among orientation angles were found. DEM differencing was performed between generated DEMs and few centimeters vertical shifts were found.

Keywords: UAV, photogrammetry, SfM, DEM

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Authors: Manssour Habbash, Srinivasa Rao Idapalapati

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Although writing is a multifaceted task, teaching writing is a demanding task basically for two reasons: Grammar and Syntax. This article provides a method of teaching writing that was found to be effective in improving students’ academic writing composition skill. The article explains the concepts of ‘guided-discovery’ and ‘guided-construction’ upon which a method of teaching writing is grounded and developed. Providing a brief commentary on what the core could mean primarily, the article presents an exposition of understanding and identifying the core and building upon the core that can demonstrate the way a teacher can make use of the concepts in teaching for improving the writing skills of their students. The method is an adaptation of grammar translation method that has been improvised to suit to a student-centered classroom environment. An intervention of teaching writing through this method was tried out with positive outcomes in formal classroom research setup, and in view of the content’s quality that relates more to the classroom practices and also in consideration of its usefulness to the practicing teachers the process and the findings are presented in a narrative form along with the results in tabular form.

Keywords: core of a text, guided construction, guided discovery, theme of a text

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Authors: Maryam Fallahpoor, Biswajeet Pradhan

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Background: Artificial intelligence (AI) serves as a valuable tool in mitigating the scarcity of human resources required for the evaluation and categorization of vast quantities of medical imaging data. When AI operates with optimal precision, it minimizes the demand for human interpretations and, thereby, reduces the burden on radiologists. Among various AI approaches, deep learning (DL) stands out as it obviates the need for feature extraction, a process that can impede classification, especially with intricate datasets. The advent of DL models has ushered in a new era in medical imaging, particularly in the context of COVID-19 detection. Traditional 2D imaging techniques exhibit limitations when applied to volumetric data, such as Computed Tomography (CT) scans. Medical images predominantly exist in one of two formats: neuroimaging informatics technology initiative (NIfTI) and digital imaging and communications in medicine (DICOM). Purpose: This study aims to employ DL for the classification of COVID-19-infected pulmonary patients and normal cases based on 3D CT scans while investigating the impact of image format. Material and Methods: The dataset used for model training and testing consisted of 1245 patients from IranMehr Hospital. All scans shared a matrix size of 512 × 512, although they exhibited varying slice numbers. Consequently, after loading the DICOM CT scans, image resampling and interpolation were performed to standardize the slice count. All images underwent cropping and resampling, resulting in uniform dimensions of 128 × 128 × 60. Resolution uniformity was achieved through resampling to 1 mm × 1 mm × 1 mm, and image intensities were confined to the range of (−1000, 400) Hounsfield units (HU). For classification purposes, positive pulmonary COVID-19 involvement was designated as 1, while normal images were assigned a value of 0. Subsequently, a U-net-based lung segmentation module was applied to obtain 3D segmented lung regions. The pre-processing stage included normalization, zero-centering, and shuffling. Four distinct 3D CNN models (ResNet152, ResNet50, DensNet169, and DensNet201) were employed in this study. Results: The findings revealed that the segmentation technique yielded superior results for DICOM images, which could be attributed to the potential loss of information during the conversion of original DICOM images to NIFTI format. Notably, ResNet152 and ResNet50 exhibited the highest accuracy at 90.0%, and the same models achieved the best F1 score at 87%. ResNet152 also secured the highest Area under the Curve (AUC) at 0.932. Regarding sensitivity and specificity, DensNet201 achieved the highest values at 93% and 96%, respectively. Conclusion: This study underscores the capacity of deep learning to classify COVID-19 pulmonary involvement using real 3D hospital data. The results underscore the significance of employing DICOM format 3D CT images alongside appropriate pre-processing techniques when training DL models for COVID-19 detection. This approach enhances the accuracy and reliability of diagnostic systems for COVID-19 detection.

Keywords: deep learning, COVID-19 detection, NIFTI format, DICOM format

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Authors: Babatunde Olatujoye, Binbin Yang

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Microwave imaging is a portable, noninvasive, and non-ionizing imaging technique that employs low-power microwave signals to reveal objects in the microwave frequency range. This technique has immense potential for adoption in commercial and scientific applications such as security scanning, material characterization, and nondestructive testing. This work presents a monostatic microwave imaging setup using an Ultra-Wideband (UWB), low-cost, miniaturized Vivaldi antenna with a bandwidth of 1 – 6 GHz. The backscattered signals (S-parameters) of the Vivaldi antenna used for scanning targets were measured in the lab using a VNA. An automated two-dimensional (2-D) scanner was employed for the 2-D movement of the transceiver to collect the measured scattering data from different positions. The targets consist of four metallic objects, each with a distinct shape. Similar setup was also simulated in Ansys HFSS. A high-resolution Back Propagation Algorithm (BPA) was applied to both the simulated and experimental backscattered signals. The BPA utilizes the phase and amplitude information recorded over a two-dimensional aperture of 50 cm × 50 cm with a discreet step size of 2 cm to reconstruct a focused image of the targets. The adoption of BPA was demonstrated by coherently resolving and reconstructing reflection signals from conventional time-of-flight profiles. For both the simulation and experimental data, BPA accurately reconstructed a high resolution 2D image of the targets in terms of shape and location. An improvement of the BPA, in terms of target resolution, was achieved by applying the filtering method in frequency domain.

Keywords: back propagation, microwave imaging, monostatic, vivialdi antenna, ultra wideband

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Authors: C. Papapicco

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Motherhood is an existential human relationship that lasts for the whole life and is always interwoven with subjectivity and culture. As a result of the brain drain, the motherhood becomes motherhood at distance. Starting from the hypothesis that re-signification of the mother at distance practices is culturally relevant; the research aims to understand the experience of mother at a distance in order to extrapolate the strategies of management of the empty nest. Specifically, the research aims to evaluate the experience of a brain drain’s mother, who created a blog that intends to take care of other parents at a distance. Actually, the blog is the only artifact symbol of the Italian culture of motherhood at distance. In the research, a Netnographic Analysis of the blog mammedicervelliinfuga.com is offered with the aim of understanding if the online world becomes an opportunity to manage the role of mother at a distance. A narrative interview with the blog creator was conducted and then the texts were analyzed by means of a Diatextual Analysis approach. It emerged that the migration projects of talented children take on different meanings and representations for parents. Thus, it is shown that the blog becomes a new form of understanding and practicing motherhood at a distance.

Keywords: brain drain, diatextual analysis, distance motherhood blog, online and offline narrations

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Authors: Leone Sherman

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While the democratic rights of a citizen may be very clearly outlined in a country’s constitution, it’s not uncommon for political elite to undermine those rights and gain more power and control over a country than it is allowed by this constitution. Moreover, while such a change in some smaller states may not have a substantial impact on the international community, the same change in countries with vast resources and political influence, such as Russia, is always a considerable factor for the world policy. This article aims to research the weaknesses of the Russian democratic system and their effect on the international policy through the three key aspects: The Russian people’s ability to produce the required political will to control their government’s decisions, the current development of the Russian political environment, and the affection of this environment on the world community as a whole during the recent years. The used methodology is a narrative analysis of recent political events, official statistics, international investigations and media statements. As a result, the ever-widening gap between the people and the government becomes evidently seen, as well as the challenges it imposes on the political world arena, both current and those that still lie ahead of us.

Keywords: Russia, political analysis, democratic weaknesses, international society

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Authors: Julius Brejohn Calvert

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This Study Aimed to Investigate the Ecological Nature of Extremism Online. The Construction of a Far-Right Ecosystem Was Successful Using a Sample of Posts, Each With Separate Narrative Domains. Most of the Content Expressed Anti-black Racism and Pro-white Sentiments. Many Posts Expressed an Overt Disdain for the Recent Progress Made Regarding the United States and the United Kingdom’s Expansion of Civil Liberties to People of Color (Poc). Of Special Note, Several Anti-lgbt Posts Targeted the Ongoing Political Grievances Expressed by the Transgender Community. Overall, the Current Study Is Able to Demonstrate That Direct Measures of User Engagement, Such as Shares and Reactions, Can Be Used to Predict the Effect of a Post’s Radicalization Capabilities, Although Single Posts Do Not Operate on the Cognitive Processes of Radicalization Alone. In This Analysis, the Data Supports a Theoretical Framework Where Individual Posts Have a Higher Radicalization Capability Based on the Amount of User Engagement (Both Indirect and Direct) It Receives.

Keywords: cognitive psychology, cognitive radicalization, extremism online, domestic extremism, political science, political psychology

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Authors: S. Teksin, S. Yayla

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The aim of the present study was to investigate details of flow structure in downstream of a circular cylinder base mounted on a flat surface in a rectangular duct with the dimensions of 8000 x 1000 x 750 mm in deep water flow for the Reynolds number 2500, 5000 and 7500. A flexible strip was attached to behind the cylinder and compared the bare body. Also, it was analyzed that how boundary layer affects the structure of flow around the cylinder. Diameter of the cylinder was 60 mm and the length of the flexible splitter plate which had a certain modulus of elasticity was 150 mm (L/D=2.5). Time-averaged velocity vectors, vortex contours, streamwise and transverse velocity components were investigated via Particle Image Velocimetry (PIV). Velocity vectors and vortex contours were displayed through the sections in which boundary layer effect was not present. On the other hand, streamwise and transverse velocity components were monitored for both cases, i.e. with and without boundary layer effect. Experiment results showed that the vortex formation occured in a larger area for L/D=2.5 and the point where the vortex was maximum from the base of the cylinder was shifted. Streamwise and transverse velocity component contours were symmetrical with reference to the center of the cylinder for all cases. All Froud numbers based on the Reynolds numbers were quite smaller than 1. The flow characteristics of velocity component values of attached circular cylinder arrangement decreased approximately twenty five percent comparing to bare cylinder case.

Keywords: partical image velocimetry, elastic plate, cylinder, flow structure

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Authors: Chadlia Ounissi, Maher Gzam, Tahani Hallek, Salah Mahmoudi, Mabrouk Montacer

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This work consists of a morphological study of the coastal domain at the central fringe of the Gulf of Gabes, Southeast of Tunisia, belonging to the structural domain of the maritime Jeffara. The diachronic study of tidal mouths in the study area and the observation of morphological markers revealed the existence of hydro-sedimentary processes leading to sedimentary accumulation and filling of the estuarine system. This filling process is materialized by the genesis of a sandy cord and the lateral migration of the tidal mouth. Moreover, we have been able to affirm, by the use of satellite images, that the dominant and responsible current at this particular coastal morphology is directed to the North, having constituted a controversy on the occurrence of what is previously mentioned in the literature. The speed of the lateral displacement of the channel varies as a function of the hydrodynamic forcing. Wave-dominated sites recorded the fastest speed (18 m/year) in the image of the mouth of Wadi el Melah. Tidal dominated sites in the Wadi Zerkine satellite image recorded a very low lateral migration (2 m / year). This variation in speed indicates that the intensity of the coastal current is uneven along the coast. This general pattern of hydrodynamic circulation, to the north, of the central fringe of the Gulf of Gabes, is disturbed by hydro-sedimentary cells.

Keywords: tidal mouth, direction of current, filling, sediment transport, Gulf of Gabes

Procedia PDF Downloads 284

Authors: Sophia Shi

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Acute kidney injury (AKI) is the sudden onset of kidney damage in which the kidneys cannot filter waste from the blood, requiring emergency hospitalization. AKI patient mortality rate is high in the ICU and is virtually impossible for doctors to predict because it is so unexpected. Currently, there is no hybrid model predicting AKI that takes advantage of two types of data. De-identified patient data from the MIMIC-III database and de-identified kidney images and corresponding patient records from the Beijing Hospital of the Ministry of Health were collected. Using data features including serum creatinine among others, two numeric models using MIMIC and Beijing Hospital data were built, and with the hospital ultrasounds, an image-only model was built. Convolutional neural networks (CNN) were used, VGG and Resnet for numeric data and Resnet for image data, and they were combined into a hybrid model by concatenating feature maps of both types of models to create a new input. This input enters another CNN block and then two fully connected layers, ending in a binary output after running through Softmax and additional code. The hybrid model successfully predicted AKI and the highest AUROC of the model was 0.953, achieving an accuracy of 90% and F1-score of 0.91. This model can be implemented into urgent clinical settings such as the ICU and aid doctors by assessing the risk of AKI shortly after the patient’s admission to the ICU, so that doctors can take preventative measures and diminish mortality risks and severe kidney damage.

Keywords: Acute kidney injury, Convolutional neural network, Hybrid deep learning, Patient record data, ResNet, Ultrasound kidney images, VGG

Procedia PDF Downloads 131

Authors: Adeoti Adebowale, Abduljaleel, Ejiogu Fidelis Onyekwo

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Form and image development are fundamental to creative expression in visual arts. The form is an element that distinguishes the difference between two-dimension and three-dimension among the branches of visual arts. Particularly, the sculpture is a three-dimensional form, while the textile design is a two-dimensional form of its visual appearance. The visual expression of each of them is embedded in the creative practice of the artist, which is easily understood and interpreted by the viewer. In this research, an attempt is made to explore and analyse sculptural forms adopted as a motif for wax print in textile design, aiming at breeding yet another pattern and motif suitable for various design uses. For instance, the dynamics of sculptural form adaptation into other areas of creativity, such as architecture, pictorial arts and pottery, as well as automobile bodies, is a discernible image everywhere. The research is studio exploratory, while a camera and descriptive analysis were used to process the data. Two sculptural forms were adopted from the Department of Fine and Applied Arts, Federal Capital Territory College of Education Zuba-Abuja, in this study due to the uniqueness of their technique of execution. The findings resulted in ten (10) paper designs showing the dexterity of studio practice in the development of design for various fashion and textile uses. However, the paper concludes that sculptural form is a source of inspiration for generating design concepts for a textile designer.

Keywords: exploration, design, motifs, sculptural forms, wax print

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Authors: Mawloud Mosbah, Bachir Boucheham

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Color Histogram is considered as the oldest method used by CBIR systems for indexing images. In turn, the global histograms do not include the spatial information; this is why the other techniques coming later have attempted to encounter this limitation by involving the segmentation task as a preprocessing step. The weak segmentation is employed by the local histograms while other methods as CCV (Color Coherent Vector) are based on strong segmentation. The indexation based on local histograms consists of splitting the image into N overlapping blocks or sub-regions, and then the histogram of each block is computed. The dissimilarity between two images is reduced, as consequence, to compute the distance between the N local histograms of the both images resulting then in N*N values; generally, the lowest value is taken into account to rank images, that means that the lowest value is that which helps to designate which sub-region utilized to index images of the collection being asked. In this paper, we make under light the local histogram indexation method in the hope to compare the results obtained against those given by the global histogram. We address also another noteworthy issue when Relying on local histograms namely which value, among N*N values, to trust on when comparing images, in other words, which sub-region among the N*N sub-regions on which we base to index images. Based on the results achieved here, it seems that relying on the local histograms, which needs to pose an extra overhead on the system by involving another preprocessing step naming segmentation, does not necessary mean that it produces better results. In addition to that, we have proposed here some ideas to select the local histogram on which we rely on to encode the image rather than relying on the local histogram having lowest distance with the query histograms.

Keywords: CBIR, color global histogram, color local histogram, weak segmentation, Euclidean distance

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Authors: Sven Weidner

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In the last two decades, US-American Independent Cinema has been faced with numerous metamorphoses. With regard to style, content, film aesthetics and themes a large array is offered. And as a consequence of the increasing influence of the world wide web and absolutely new ways of production opportunities alter the indie-film scene fundamentally. While in the 90s many independent films were situated in urban spaces -for instance, films of Jim Jarmusch, Abel Ferrara or Quentin Tarantino- there is a tendency from the 2000s years on to go to rural America. Jeff Nichols, Debra Granik or Matthew Porterfield can be named. Suburbia the symbol of the American Dream and in particular of an emerging prosperity after the Second World War is an essential theme with some independent directors; among them indie icons Todd Solondz and Todd Haynes. Based on selected films of both of them the paper explores the formal and aesthetic structures (narrative, drama, montage, lighting, sound, color) of the pictures and how suburbia, its people, and its "perfect" families are shown and unmasked in all facets. Films are: "Happiness" (1998), "Life During Wartime" (2009) and "Far From Heaven" (2002).

Keywords: US-independent cinema, Suburbia, film history, film analysis

Procedia PDF Downloads 267

Authors: Shariful Islam, Sharun Akter Khushbu, S. M. Shaqib, Shahriar Sultan Ramit

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In the construction sector, ensuring worker safety is of the utmost significance. In this study, a deep learning-based technique is presented for identifying safety gear worn by construction workers, such as helmets, goggles, jackets, gloves, and footwear. The suggested method precisely locates these safety items by using the YOLO v7 (You Only Look Once) object detection algorithm. The dataset utilized in this work consists of labeled images split into training, testing and validation sets. Each image has bounding box labels that indicate where the safety equipment is located within the image. The model is trained to identify and categorize the safety equipment based on the labeled dataset through an iterative training approach. We used custom dataset to train this model. Our trained model performed admirably well, with good precision, recall, and F1-score for safety equipment recognition. Also, the model's evaluation produced encouraging results, with a [email protected] score of 87.7%. The model performs effectively, making it possible to quickly identify safety equipment violations on building sites. A thorough evaluation of the outcomes reveals the model's advantages and points up potential areas for development. By offering an automatic and trustworthy method for safety equipment detection, this research contributes to the fields of computer vision and workplace safety. The proposed deep learning-based approach will increase safety compliance and reduce the risk of accidents in the construction industry.

Keywords: deep learning, safety equipment detection, YOLOv7, computer vision, workplace safety

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Authors: Obidimma Ezezika

Abstract:

In light of the increasing importance of trust in development programs, the purpose of this study, was to identify how trust functions as an essential key determinant in successful innovation and technology development programs. Using projects in the agricultural sector as case studies, we determined how the concept of trust is understood. Our data collection relied on semi-structured, face-to-face interviews conducted as part of a larger study investigating the role of trust in development programs. Interview transcripts were analyzed to create a narrative on how trust is understood by the study’s participants and how trust functions in fostering innovation. We identified six themes and showed how trust plays an important factor in innovation. These themes included the practice of integrity and honesty; delivery of results in an accountable manner; capability and competency; sharing of the same objectives and interests; transparency about actions and intentions through clear communication; and the targeting of services toward the interests of the public. The results of this study can provide guidance on how to enhance implementation mechanisms and provide impetus for organizations to implement trust building activities in fostering effective innovation.

Keywords: trust, research, innovation, technology

Procedia PDF Downloads 482