Search results for: MR image
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2784

Search results for: MR image

594 Reconstruction of Visual Stimuli Using Stable Diffusion with Text Conditioning

Authors: ShyamKrishna Kirithivasan, Shreyas Battula, Aditi Soori, Richa Ramesh, Ramamoorthy Srinath

Abstract:

The human brain, among the most complex and mysterious aspects of the body, harbors vast potential for extensive exploration. Unraveling these enigmas, especially within neural perception and cognition, delves into the realm of neural decoding. Harnessing advancements in generative AI, particularly in Visual Computing, seeks to elucidate how the brain comprehends visual stimuli observed by humans. The paper endeavors to reconstruct human-perceived visual stimuli using Functional Magnetic Resonance Imaging (fMRI). This fMRI data is then processed through pre-trained deep-learning models to recreate the stimuli. Introducing a new architecture named LatentNeuroNet, the aim is to achieve the utmost semantic fidelity in stimuli reconstruction. The approach employs a Latent Diffusion Model (LDM) - Stable Diffusion v1.5, emphasizing semantic accuracy and generating superior quality outputs. This addresses the limitations of prior methods, such as GANs, known for poor semantic performance and inherent instability. Text conditioning within the LDM's denoising process is handled by extracting text from the brain's ventral visual cortex region. This extracted text undergoes processing through a Bootstrapping Language-Image Pre-training (BLIP) encoder before it is injected into the denoising process. In conclusion, a successful architecture is developed that reconstructs the visual stimuli perceived and finally, this research provides us with enough evidence to identify the most influential regions of the brain responsible for cognition and perception.

Keywords: BLIP, fMRI, latent diffusion model, neural perception.

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593 A U-Net Based Architecture for Fast and Accurate Diagram Extraction

Authors: Revoti Prasad Bora, Saurabh Yadav, Nikita Katyal

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In the context of educational data mining, the use case of extracting information from images containing both text and diagrams is of high importance. Hence, document analysis requires the extraction of diagrams from such images and processes the text and diagrams separately. To the author’s best knowledge, none among plenty of approaches for extracting tables, figures, etc., suffice the need for real-time processing with high accuracy as needed in multiple applications. In the education domain, diagrams can be of varied characteristics viz. line-based i.e. geometric diagrams, chemical bonds, mathematical formulas, etc. There are two broad categories of approaches that try to solve similar problems viz. traditional computer vision based approaches and deep learning approaches. The traditional computer vision based approaches mainly leverage connected components and distance transform based processing and hence perform well in very limited scenarios. The existing deep learning approaches either leverage YOLO or faster-RCNN architectures. These approaches suffer from a performance-accuracy tradeoff. This paper proposes a U-Net based architecture that formulates the diagram extraction as a segmentation problem. The proposed method provides similar accuracy with a much faster extraction time as compared to the mentioned state-of-the-art approaches. Further, the segmentation mask in this approach allows the extraction of diagrams of irregular shapes.

Keywords: computer vision, deep-learning, educational data mining, faster-RCNN, figure extraction, image segmentation, real-time document analysis, text extraction, U-Net, YOLO

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592 The Nursing Experience for an Intestinal Perforation Elderly with a Temporary Enterostomy

Authors: Hsiu-Chuan Hsueh, Kuei-Feng Shen Jr., Chia-Ling Chao, Hui-Chuan Pan

Abstract:

This article described a 75 years old woman who has suffered from intestinal perforation and accepted surgery with temporary enterostomy, the operation makes her depressed, refused relatives and friend's care, facing low willingness to participate in various activities due to fear of changing body appearance caused by surgery and leave enterostomy. The author collected information through observation talks, physical evaluation, and medical records during the period of care from November 14 to November 30, 2016, we used the four aspects of physiology, psychology, society and spirituality as a whole sexual assessment to establish the nursing problems of patient, included of acute pain, disturbance of body image,coping ineffective individual. For patient care issues, to encouraged case to express their inner feelings and take part in self-care programs through providing good therapeutic interpersonal relationships with their families. However, it provided clear information about the disease and follow-up treatment plan, give compliments in a timely manner, enhanced self-confidence of individual cases and their motivation to participate in self-care of stoma, further face the disease in a positive manner. At the same time, cross-section team care model and individual care measures were developed to enhance the care skills after returning home and at the same time assist the individual in facing the psychological impact caused by stoma. Hope to provide this experience, as a reference for the future care of the disease.

Keywords: enterostomy, intestinal perforation, nursing experience, ostomy

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591 Enhancement of Biomass and Bioactive Compounds in Kale Subjected to UV-A LED Lights

Authors: Jin-Hui Lee, Myung-Min Oh

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The application of temporary abiotic stresses before crop harvest is a potential strategy to enhance phytochemical content. The objective of this study was to determine the effect of various UV-A LED lights on the growth and content of bioactive compounds in kale (Brassica oleracea var. acephala). Fourteen-day-old kale seedlings were cultivated in a plant factory with artificial lighting (air temperature of 20℃, relative humidity of 60%, photosynthesis photon flux density (PPFD) of 125 µmol·m⁻²·s⁻¹) for 3 weeks. Kale plants were irradiated by four types of UV-A LEDs (peak wavelength; 365, 375, 385, and 395 nm) with 30 W/m² for 7 days. As a result, image chlorophyll fluorescence (Fv/Fm) value of kale leaves was lower as the UV-A LEDs peak wavelength was shorter. Fresh and dry weights of shoots and roots of kale plants were significantly higher in the plants under UV-A than the control at 7 days of treatment. In particular, the growth was significantly increased with a longer peak wavelength of the UV-A LEDs. The results of leaf area and specific leaf weight showed a similar pattern with those of growth characteristics. Chlorophyll content was highest in kale leaves subjected to UV-A LEDs with the peak wavelength of 395 nm at 3 days of treatment compared with the control. Total phenolic contents of UV-A LEDs with the peak wavelength of 395 nm at 5 and 6 days of treatment were 44% and 47% higher than those of the control, respectively. Antioxidant capacity showed almost the same pattern as the results of total phenol content. The activity of phenylalanine ammonia-lyase was approximately 11% and 8% higher in the UV-A LEDs with the peak wavelength of 395 nm compared to the control at 5 and 6 days of treatment, respectively. Our results imply that the UV-A LEDs with relative longer peak wavelength were effective to improve growth as well as the content of bioactive compounds of kale plants.

Keywords: bioactive compounds, growth, Kale, UV-A LEDs

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590 A Study of Gender Awareness among College Students in Delhi

Authors: Shailly Kumar

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Gender is a social construction resulting in defining roles and responsibilities to carried out according to masculine and feminine traits. The main aim of the study was to explore gender awareness among college going students of Delhi. The objectives of studies were to find out (i) the understanding of term gender and roles and responsibilities associated with male and female as masculine and feminine traits in our society. (ii)Gender images representing the attributes and characteristics attached to particular gender. (iii) Gender discrimination prevailing among girls and boys in our society. (iv)Gender stereotypes resulting in gendering with respect to religion, culture, family and media. The sample of study consisted of 100 undergraduate college girl students. The findings of study stated that the students had this understanding that sex is a natural phenomenon and gender is socially constructed. Gender defines the roles and responsibilities among two sexes. On a gender image students concluded that males are represented as a powerful members of society showing physical strength and violence, force and society gave the power to men oppress and subjugate women in society that's why women are treated inferior and given secondary position in society. On gender discrimination, girl students stated that they faced discrimination at all level such as family, media ,education, workplace etc .There is strong prevailing gender stereotypes among girls and boys with respect to religious practices, choice of career ,preference of child etc. This study concluded that students were aware of gendered practices in various domains of life. The study helped to interpret the notions and perceptions of students towards gendering of social spaces and in their lives.

Keywords: gender, gender awareness, gender role, masculinity and feminity

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589 Neuroimaging Markers for Screening Former NFL Players at Risk for Developing Alzheimer's Disease / Dementia Later in Life

Authors: Vijaykumar M. Baragi, Ramtilak Gattu, Gabriela Trifan, John L. Woodard, K. Meyers, Tim S. Halstead, Eric Hipple, Ewart Mark Haacke, Randall R. Benson

Abstract:

NFL players, by virtue of their exposure to repetitive head injury, are at least twice as likely to develop Alzheimer's disease (AD) and dementia as the general population. Early recognition and intervention prior to onset of clinical symptoms could potentially avert/delay the long-term consequences of these diseases. Since AD is thought to have a long preclinical incubation period, the aim of the current research was to determine whether former NFL players, referred to a depression center, showed evidence of incipient dementia in their structural imaging prior to diagnosis of dementia. Thus, to identify neuroimaging markers of AD, against which former NFL players would be compared, we conducted a comprehensive volumetric analysis using a cohort of early stage AD patients (ADNI) to produce a set of brain regions demonstrating sensitivity to early AD pathology (i.e., the “AD fingerprint”). A cohort of 46 former NFL players’ brain MRIs were then interrogated using the AD fingerprint. Brain scans were done using a T1-weighted MPRAGE sequence. The Free Surfer image analysis suite (version 6.0) was used to obtain the volumetric and cortical thickness data. A total of 55 brain regions demonstrated significant atrophy or ex vacuo dilatation bilaterally in AD patients vs. healthy controls. Of the 46 former NFL players, 19 (41%) demonstrated a greater than expected number of atrophied/dilated AD regions when compared with age-matched controls, presumably reflecting AD pathology.

Keywords: alzheimers, neuroimaging biomarkers, traumatic brain injury, free surfer, ADNI

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588 Challenges of Management of Acute Pancreatitis in Low Resource Setting

Authors: Md. Shakhawat Hossain, Jimma Hossain, Md. Naushad Ali

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Acute pancreatitis is a dangerous medical emergency in the practice of gastroenterology. Management of acute pancreatitis needs multidisciplinary approach with support starts from emergency to ICU. So, there is a chance of mismanagement in every steps, especially in low resource settings. Other factors such as patient’s financial condition, education, social custom, transport facility, referral system from periphery may also challenge the current guidelines for management. The present study is intended to determine the clinico-pathological profile, severity assessment and challenges of management of acute pancreatitis in a government laid tertiary care hospital to image the real scenario of management in a low resource place. A total 100 patients of acute pancreatitis were studied in this prospective study, held in the Department of Gastroenterology, Rangpur medical college hospital, Bangladesh from July 2017 to July 2018 within one year. Regarding severity, 85 % of the patients were mild, whereas 13 were moderately severe, and 2 had severe acute pancreatitis according to the revised Atlanta criteria. The most common etiologies of acute pancreatitis in our study were gall stone (15%) and biliary sludge (15%), whereas 54% were idiopathic. The most common challenges we faced were delay in hospital admission (59%) and delay in hospital diagnosis (20%). Others are non-adherence of patient party, and lack of investigation facility, physician’s poor knowledge about current guidelines. We were able to give early aggressive fluid to only 18% of patients as per current guideline. Conclusion: Management of acute pancreatitis as per guideline is challenging when optimum facility is lacking. So, modified guidelines for assessment and management of acute pancreatitis should be prepared for low resource setting.

Keywords: acute pancreatitis, challenges of management, severity, prognosis

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587 Revisiting the Link between Corporate Social Performance and Corporate Financial Performance Post 2008 Global Economic Crisis

Authors: Anand Choudhary

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Following the global economic crisis in 2008, businesses and more especially the big multinational conglomerates were increasingly viewed by the people world over as one of the major causes of the economic problems faced by millions globally, in terms of job loss and lifetime savings being wiped out as banks and pension funds went bankrupt and people stared at an insecure financial future. This caused a lot of resentment in the public against big businesses and fueled several protest movements by the people such as “Occupy Wall Street” in different parts of the world. This forced the big businesses to respond to the challenge by adopting more people-centric policies and initiatives for local communities in societies where they operate as part of their corporate social responsibility (CSR), in order to regain their social acceptance among the people whilst earning their ‘social license to operate’. The current paper studies many of such large MNCs across the United States of America, India and South Africa, which changed the way they did business earlier, following the global economic crisis in 2008, by incorporating capacity building initiatives for local communities as part of their CSR strategy and explores whether it has contributed to improving their financial performance. It is a conceptual research paper using secondary source data. The findings reveal that there is a positive correlation between the companies’ corporate social performance and corporate financial performance. In addition, the findings also bring to light that the MNCs examined as part of the current paper have improved their image in the eyes of their stakeholders following the change in their CSR strategy and initiatives.

Keywords: corporate social responsibility (CSR), Corporate Social Performance (CSP), Corporate Financial Performance (CFP), local communities

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586 A Relative Entropy Regularization Approach for Fuzzy C-Means Clustering Problem

Authors: Ouafa Amira, Jiangshe Zhang

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Clustering is an unsupervised machine learning technique; its aim is to extract the data structures, in which similar data objects are grouped in the same cluster, whereas dissimilar objects are grouped in different clusters. Clustering methods are widely utilized in different fields, such as: image processing, computer vision , and pattern recognition, etc. Fuzzy c-means clustering (fcm) is one of the most well known fuzzy clustering methods. It is based on solving an optimization problem, in which a minimization of a given cost function has been studied. This minimization aims to decrease the dissimilarity inside clusters, where the dissimilarity here is measured by the distances between data objects and cluster centers. The degree of belonging of a data point in a cluster is measured by a membership function which is included in the interval [0, 1]. In fcm clustering, the membership degree is constrained with the condition that the sum of a data object’s memberships in all clusters must be equal to one. This constraint can cause several problems, specially when our data objects are included in a noisy space. Regularization approach took a part in fuzzy c-means clustering technique. This process introduces an additional information in order to solve an ill-posed optimization problem. In this study, we focus on regularization by relative entropy approach, where in our optimization problem we aim to minimize the dissimilarity inside clusters. Finding an appropriate membership degree to each data object is our objective, because an appropriate membership degree leads to an accurate clustering result. Our clustering results in synthetic data sets, gaussian based data sets, and real world data sets show that our proposed model achieves a good accuracy.

Keywords: clustering, fuzzy c-means, regularization, relative entropy

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585 The Importance of Visual Communication in Artificial Intelligence

Authors: Manjitsingh Rajput

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Visual communication plays an important role in artificial intelligence (AI) because it enables machines to understand and interpret visual information, similar to how humans do. This abstract explores the importance of visual communication in AI and emphasizes the importance of various applications such as computer vision, object emphasis recognition, image classification and autonomous systems. In going deeper, with deep learning techniques and neural networks that modify visual understanding, In addition to AI programming, the abstract discusses challenges facing visual interfaces for AI, such as data scarcity, domain optimization, and interpretability. Visual communication and other approaches, such as natural language processing and speech recognition, have also been explored. Overall, this abstract highlights the critical role that visual communication plays in advancing AI capabilities and enabling machines to perceive and understand the world around them. The abstract also explores the integration of visual communication with other modalities like natural language processing and speech recognition, emphasizing the critical role of visual communication in AI capabilities. This methodology explores the importance of visual communication in AI development and implementation, highlighting its potential to enhance the effectiveness and accessibility of AI systems. It provides a comprehensive approach to integrating visual elements into AI systems, making them more user-friendly and efficient. In conclusion, Visual communication is crucial in AI systems for object recognition, facial analysis, and augmented reality, but challenges like data quality, interpretability, and ethics must be addressed. Visual communication enhances user experience, decision-making, accessibility, and collaboration. Developers can integrate visual elements for efficient and accessible AI systems.

Keywords: visual communication AI, computer vision, visual aid in communication, essence of visual communication.

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584 LCA and Multi-Criteria Analysis of Fly Ash Concrete Pavements

Authors: Marcela Ondova, Adriana Estokova

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Rapid industrialization results in increased use of natural resources bring along serious ecological and environmental imbalance due to the dumping of industrial wastes. Principles of sustainable construction have to be accepted with regard to the consumption of natural resources and the production of harmful emissions. Cement is a great importance raw material in the building industry and today is its large amount used in the construction of concrete pavements. Concerning raw materials cost and producing CO2 emission the replacing of cement in concrete mixtures with more sustainable materials is necessary. To reduce this environmental impact people all over the world are looking for a solution. Over a period of last ten years, the image of fly ash has completely been changed from a polluting waste to resource material and it can solve the major problems of cement use. Fly ash concretes are proposed as a potential approach for achieving substantial reductions in cement. It is known that it improves the workability of concrete, extends the life cycle of concrete roads, and reduces energy use and greenhouse gas as well as amount of coal combustion products that must be disposed in landfills. Life cycle assessment also proved that a concrete pavement with fly ash cement replacement is considerably more environmentally friendly compared to standard concrete roads. In addition, fly ash is cheap raw material, and the costs saving are guaranteed. The strength properties, resistance to a frost or de-icing salts, which are important characteristics in the construction of concrete pavements, have reached the required standards as well. In terms of human health it can´t be stated that a concrete cover with fly ash could be dangerous compared with a cover without fly ash. Final Multi-criteria analysis also pointed that a concrete with fly ash is a clearly proper solution.

Keywords: life cycle assessment, fly ash, waste, concrete pavements

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583 Laser Registration and Supervisory Control of neuroArm Robotic Surgical System

Authors: Hamidreza Hoshyarmanesh, Hosein Madieh, Sanju Lama, Yaser Maddahi, Garnette R. Sutherland, Kourosh Zareinia

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This paper illustrates the concept of an algorithm to register specified markers on the neuroArm surgical manipulators, an image-guided MR-compatible tele-operated robot for microsurgery and stereotaxy. Two range-finding algorithms, namely time-of-flight and phase-shift, are evaluated for registration and supervisory control. The time-of-flight approach is implemented in a semi-field experiment to determine the precise position of a tiny retro-reflective moving object. The moving object simulates a surgical tool tip. The tool is a target that would be connected to the neuroArm end-effector during surgery inside the magnet bore of the MR imaging system. In order to apply flight approach, a 905-nm pulsed laser diode and an avalanche photodiode are utilized as the transmitter and receiver, respectively. For the experiment, a high frequency time to digital converter was designed using a field-programmable gate arrays. In the phase-shift approach, a continuous green laser beam with a wavelength of 530 nm was used as the transmitter. Results showed that a positioning error of 0.1 mm occurred when the scanner-target point distance was set in the range of 2.5 to 3 meters. The effectiveness of this non-contact approach exhibited that the method could be employed as an alternative for conventional mechanical registration arm. Furthermore, the approach is not limited by physical contact and extension of joint angles.

Keywords: 3D laser scanner, intraoperative MR imaging, neuroArm, real time registration, robot-assisted surgery, supervisory control

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582 House Facades and Emotions: Exploring the Psychological Impact of Architectural Features

Authors: Nour Tawil, Sandra Weber, Kirsten K. Roessler, Martin Mau, Simone Kuhn

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The link between “quality” residential environments and human health and well-being has long been proposed. While the physical properties of a sound environment have been fairly defined, little focus has been given to the psychological impact of architectural elements. Recently, studies have investigated the response to architectural parameters, using measures of physiology, brain activity, and emotion. Results showed different aspects of interest: detailed and open versus blank and closed facades, patterns in perceiving different elements, and a visual bias for capturing faces in buildings. However, in the absence of a consensus on methodologies, the available studies remain unsystematic and face many limitations regarding the underpinning psychological mechanisms. To bridge some of these gaps, an online study was launched to investigate design features that influence the aesthetic judgement and emotional evaluation of house facades, using a well-controlled stimulus set of Canadian houses. A methodical modelling of design features will be performed to extract both high and low level image properties, in addition to segmentation of layout-related features. 300 participants from Canada, Denmark, and Germany will rate the images on twelve psychological dimensions representing appealing aspects of a house. Subjective ratings are expected to correlate with specific architectural elements while controlling for typicality and familiarity, and other individual differences. With the lack of relevant studies, this research aims to identify architectural elements of beneficial qualities that can inform design strategies for optimized residential spaces.

Keywords: architectural elements, emotions, psychological response, residential facades.

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581 On the Existence of Homotopic Mapping Between Knowledge Graphs and Graph Embeddings

Authors: Jude K. Safo

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Knowledge Graphs KG) and their relation to Graph Embeddings (GE) represent a unique data structure in the landscape of machine learning (relative to image, text and acoustic data). Unlike the latter, GEs are the only data structure sufficient for representing hierarchically dense, semantic information needed for use-cases like supply chain data and protein folding where the search space exceeds the limits traditional search methods (e.g. page-rank, Dijkstra, etc.). While GEs are effective for compressing low rank tensor data, at scale, they begin to introduce a new problem of ’data retreival’ which we observe in Large Language Models. Notable attempts by transE, TransR and other prominent industry standards have shown a peak performance just north of 57% on WN18 and FB15K benchmarks, insufficient practical industry applications. They’re also limited, in scope, to next node/link predictions. Traditional linear methods like Tucker, CP, PARAFAC and CANDECOMP quickly hit memory limits on tensors exceeding 6.4 million nodes. This paper outlines a topological framework for linear mapping between concepts in KG space and GE space that preserve cardinality. Most importantly we introduce a traceable framework for composing dense linguistic strcutures. We demonstrate performance on WN18 benchmark this model hits. This model does not rely on Large Langauge Models (LLM) though the applications are certainy relevant here as well.

Keywords: representation theory, large language models, graph embeddings, applied algebraic topology, applied knot theory, combinatorics

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580 Combining Diffusion Maps and Diffusion Models for Enhanced Data Analysis

Authors: Meng Su

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High-dimensional data analysis often presents challenges in capturing the complex, nonlinear relationships and manifold structures inherent to the data. This article presents a novel approach that leverages the strengths of two powerful techniques, Diffusion Maps and Diffusion Probabilistic Models (DPMs), to address these challenges. By integrating the dimensionality reduction capability of Diffusion Maps with the data modeling ability of DPMs, the proposed method aims to provide a comprehensive solution for analyzing and generating high-dimensional data. The Diffusion Map technique preserves the nonlinear relationships and manifold structure of the data by mapping it to a lower-dimensional space using the eigenvectors of the graph Laplacian matrix. Meanwhile, DPMs capture the dependencies within the data, enabling effective modeling and generation of new data points in the low-dimensional space. The generated data points can then be mapped back to the original high-dimensional space, ensuring consistency with the underlying manifold structure. Through a detailed example implementation, the article demonstrates the potential of the proposed hybrid approach to achieve more accurate and effective modeling and generation of complex, high-dimensional data. Furthermore, it discusses possible applications in various domains, such as image synthesis, time-series forecasting, and anomaly detection, and outlines future research directions for enhancing the scalability, performance, and integration with other machine learning techniques. By combining the strengths of Diffusion Maps and DPMs, this work paves the way for more advanced and robust data analysis methods.

Keywords: diffusion maps, diffusion probabilistic models (DPMs), manifold learning, high-dimensional data analysis

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579 Design of Two-Channel Quadrature Mirror Filter Banks Using a Transformation Approach

Authors: Ju-Hong Lee, Yi-Lin Shieh

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Two-dimensional (2-D) quadrature mirror filter (QMF) banks have been widely considered for high-quality coding of image and video data at low bit rates. Without implementing subband coding, a 2-D QMF bank is required to have an exactly linear-phase response without magnitude distortion, i.e., the perfect reconstruction (PR) characteristics. The design problem of 2-D QMF banks with the PR characteristics has been considered in the literature for many years. This paper presents a transformation approach for designing 2-D two-channel QMF banks. Under a suitable one-dimensional (1-D) to two-dimensional (2-D) transformation with a specified decimation/interpolation matrix, the analysis and synthesis filters of the QMF bank are composed of 1-D causal and stable digital allpass filters (DAFs) and possess the 2-D doubly complementary half-band (DC-HB) property. This facilitates the design problem of the two-channel QMF banks by finding the real coefficients of the 1-D recursive DAFs. The design problem is formulated based on the minimax phase approximation for the 1-D DAFs. A novel objective function is then derived to obtain an optimization for 1-D minimax phase approximation. As a result, the problem of minimizing the objective function can be simply solved by using the well-known weighted least-squares (WLS) algorithm in the minimax (L∞) optimal sense. The novelty of the proposed design method is that the design procedure is very simple and the designed 2-D QMF bank achieves perfect magnitude response and possesses satisfactory phase response. Simulation results show that the proposed design method provides much better design performance and much less design complexity as compared with the existing techniques.

Keywords: Quincunx QMF bank, doubly complementary filter, digital allpass filter, WLS algorithm

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578 The Perspectives of Preparing Psychology Practitioners in Armenian Universities

Authors: L. Petrosyan

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The problem of psychologist training remains a key priority in Armenia. During the Soviet period, the notion of a psychologist was obscure not only in Armenia but also in other Soviet republics. The breakup of the Soviet Union triggered a gradual change in this area activating the cooperation with specialists from other countries. The need for recovery from the psychological trauma caused by the 1988 earthquake pushed forward the development of practical psychology in Armenia. This phenomenon led to positive changes in perception of and interest to a psychologist profession.Armenian universities started designing special programs for psychologists’ preparation. Armenian psychologists combined their efforts in the field of training relevant specialists. During the recent years, the Bologna educational system was introduced in Armenia which led to implementation of education quality improvement programs. Nevertheless, even today the issue of psychologists’ training is not yet settled in Armenian universities. So far graduate psychologists haven’t got a clear idea of personal and professional qualities of a psychologist. Recently, as a result of educational reforms, the psychology curricula underwent changes, but so far they have not led to a desired outcome. Almost all curricula in certain specialties are aimed to form professional competencies and strengthen practical skills. A survey conducted in Armenia aimed to identify what are the ideas of young psychology specialists on the image of a psychologist. The survey respondents were 45 specialists holding bachelor’s degree as well as 30 master degree graduates, who have not been working yet. The research reveals that we need to change the approach of preparing psychology practitioners in the universities of Armenia. Such an approach to psychologist training will make it possible to train qualified specialists for enhancement of modern psychology theory and practice.

Keywords: practitioners, psychology degree, study, professional competencies

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577 The Yak of Thailand: Folk Icons Transcending Culture, Religion, and Media

Authors: David M. Lucas, Charles W. Jarrett

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In the culture of Thailand, the Yak serve as a mediated icon representing strength, power, and mystical protection not only for the Buddha, but for population of worshipers. Originating from the forests of China, the Yak continue to stand guard at the gates of Buddhist temples. The Yak represents Thai culture in the hearts of Thai people. This paper presents a qualitative study regarding the curious mix of media, culture, and religion that projects the Yak of Thailand as a larger than life message throughout the political, cultural, and religious spheres. The gate guardians, or gods as they are sometimes called, appear throughout the religious temples of Asian cultures. However, the Asian cultures demonstrate differences in artistic renditions (or presentations) of such sentinels. Thailand gate guards (the Yak) stand in front of many Buddhist temples, and these iconic figures display unique features with varied symbolic significance. The temple (or wat), plays a vital role in every community; and, for many people, Thailand’s temples are the country’s most endearing sights. The authors applied folk-nography as a methodology to illustrate the importance of the Thai Yak in serving as meaningful icons that transcend not only time, but the culture, religion, and mass media. The Yak represent mythical, religious, artistic, cultural, and militaristic significance for the Thai people. Data collection included interviews, focus groups, and natural observations. This paper summarizes the perceptions of the Thai people concerning their gate sentries and the relationship, communication, connection, and the enduring respect that Thai people hold for their guardians of the gates.

Keywords: communication, culture, folknography, icon, image, media, protection, religion, yak

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576 Aspects and Studies of Fractal Geometry in Automatic Breast Cancer Detection

Authors: Mrinal Kanti Bhowmik, Kakali Das Jr., Barin Kumar De, Debotosh Bhattacharjee

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Breast cancer is the most common cancer and a leading cause of death for women in the 35 to 55 age group. Early detection of breast cancer can decrease the mortality rate of breast cancer. Mammography is considered as a ‘Gold Standard’ for breast cancer detection and a very popular modality, presently used for breast cancer screening and detection. The screening of digital mammograms often leads to over diagnosis and a consequence to unnecessary traumatic & painful biopsies. For that reason recent studies involving the use of thermal imaging as a screening technique have generated a growing interest especially in cases where the mammography is limited, as in young patients who have dense breast tissue. Tumor is a significant sign of breast cancer in both mammography and thermography. The tumors are complex in structure and they also exhibit a different statistical and textural features compared to the breast background tissue. Fractal geometry is a geometry which is used to describe this type of complex structure as per their main characteristic, where traditional Euclidean geometry fails. Over the last few years, fractal geometrics have been applied mostly in many medical image (1D, 2D, or 3D) analysis applications. In breast cancer detection using digital mammogram images, also it plays a significant role. Fractal is also used in thermography for early detection of the masses using the thermal texture. This paper presents an overview of the recent aspects and initiatives of fractals in breast cancer detection in both mammography and thermography. The scope of fractal geometry in automatic breast cancer detection using digital mammogram and thermogram images are analysed, which forms a foundation for further study on application of fractal geometry in medical imaging for improving the efficiency of automatic detection.

Keywords: fractal, tumor, thermography, mammography

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575 Expounding the Evolution of the Proto-Femme Fatale and Its Correlation with the New Woman: A Close Study of David Mamet's Oleanna

Authors: Silvia Elias

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The 'Femme Fatale' figure has become synonymous with a mysterious and seductive woman whose charms captivate her lovers into bonds of irresistible desire, often leading them to compromise or downfall. Originally, a Femme Fatale typically uses her beauty to lead men to their destruction but in modern literature, she represents a direct attack on traditional womanhood and the nuclear family as she refuses to abide by the pillars of mainstream society creating an image of a strong independent woman who defies the control of men and rejects the institution of the family. This research aims at discussing the differences and similarities between the femme fatale and the New Woman and how they are perceived by the audience. There is often confusion between the characteristics that define a New Woman and a Femme Fatale since both women desire independence, challenge typical gender role casting, push against the limits of the patriarchal society and take control of their sexuality. The study of the femme fatale remains appealing in modern times because the fear of gender equality gives life to modern femme fatale versions and post-modern literary works introduce their readers to new versions of the deadly seductress. One that does not fully depend on her looks to destroy men. The idea behind writing this paper was born from reading David Mamet's two-character play Oleanna (1992) and tracing the main female protagonist/antagonist's transformation from a helpless inarticulate girl into a powerful controlling negotiator who knows how to lead a bargain and maintain the upper hand.

Keywords: Circe, David, Eve, evolution, feminist, femme fatale, gender, Mamet, new, Odysseus, Oleanna, power, Salome, schema, seduction, temptress, woman

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574 Experimental and Numerical Performance Analysis for Steam Jet Ejectors

Authors: Abdellah Hanafi, G. M. Mostafa, Mohamed Mortada, Ahmed Hamed

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The steam ejectors are the heart of most of the desalination systems that employ vacuum. The systems that employ low grade thermal energy sources like solar energy and geothermal energy use the ejector to drive the system instead of high grade electric energy. The jet-ejector is used to create vacuum employing the flow of steam or air and using the severe pressure drop at the outlet of the main nozzle. The present work involves developing a one dimensional mathematical model for designing jet-ejectors and transform it into computer code using Engineering Equation solver (EES) software. The model receives the required operating conditions at the inlets and outlet of the ejector as inputs and produces the corresponding dimensions required to reach these conditions. The one-dimensional model has been validated using an existed model working on Abu-Qir power station. A prototype has been designed according to the one-dimensional model and attached to a special test bench to be tested before using it in the solar desalination pilot plant. The tested ejector will be responsible for the startup evacuation of the system and adjusting the vacuum of the evaporating effects. The tested prototype has shown a good agreement with the results of the code. In addition a numerical analysis has been applied on one of the designed geometry to give an image of the pressure and velocity distribution inside the ejector from a side, and from other side, to show the difference in results between the two-dimensional ideal gas model and real prototype. The commercial edition of ANSYS Fluent v.14 software is used to solve the two-dimensional axisymmetric case.

Keywords: solar energy, jet ejector, vacuum, evaporating effects

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573 Review of Capitalization of Construction Industry on Sustainable Risk Management in Nigeria

Authors: Nnadi Ezekiel Ejiofor

Abstract:

The construction industry plays a decisive role in the healthy development of any nation. Not only large but even small construction projects contribute to a country’s economic growth. There is a need for good management to ensure successful delivery and sustainability because of the plethora of risks that have resulted in low-profit margins for contractors, cost and schedule overruns, poor quality delivery, and abandoned projects. This research reviewed Capitalization on Sustainable Risk Management. Questionnaires and oral interviews conducted were utilized as means of data collection. One hundred and ninety-eight (198) large construction firms in Nigeria form the population of this study. 15 (fifteen) companies that emanated from merger and acquisition were used for the study. The instruments used for data collection were a researcher-developed structured questionnaire based on a five-point rating scale, interviews, focus group discussion, and secondary sources (bill of quantities and stock and exchange commission). The instrument was validated by two experts in the field. The reliability of the instrument was established by applying the split-half method. Kendall’s coefficient of concordance was used to test the data, and a degree of agreement was obtained. Data were subjected to descriptive statistics and analyzed using analysis of variance, t-test, and SPSS. The identified impacts of capitalization were an increase in turnover (24.5%), improvement in the image (24.5%), risk reduction (20%), business expansion (17.3%), and geographical spread (13.6%). The study strongly advocates the inclusion of risk management evaluation as part of the construction procurement process.

Keywords: capitalization, project delivery, risks, risk management, sustainability

Procedia PDF Downloads 63
572 Technical Aspects of Closing the Loop in Depth-of-Anesthesia Control

Authors: Gorazd Karer

Abstract:

When performing a diagnostic procedure or surgery in general anesthesia (GA), a proper introduction and dosing of anesthetic agents are one of the main tasks of the anesthesiologist. However, depth of anesthesia (DoA) also seems to be a suitable process for closed-loop control implementation. To implement such a system, one must be able to acquire the relevant signals online and in real-time, as well as stream the calculated control signal to the infusion pump. However, during a procedure, patient monitors and infusion pumps are purposely unable to connect to an external (possibly medically unapproved) device for safety reasons, thus preventing closed-loop control. The paper proposes a conceptual solution to the aforementioned problem. First, it presents some important aspects of contemporary clinical practice. Next, it introduces the closed-loop-control-system structure and the relevant information flow. Focusing on transferring the data from the patient to the computer, it presents a non-invasive image-based system for signal acquisition from a patient monitor for online depth-of-anesthesia assessment. Furthermore, it introduces a UDP-based communication method that can be used for transmitting the calculated anesthetic inflow to the infusion pump. The proposed system is independent of a medical device manufacturer and is implemented in Matlab-Simulink, which can be conveniently used for DoA control implementation. The proposed scheme has been tested in a simulated GA setting and is ready to be evaluated in an operating theatre. However, the proposed system is only a step towards a proper closed-loop control system for DoA, which could routinely be used in clinical practice.

Keywords: closed-loop control, depth of anesthesia (DoA), modeling, optical signal acquisition, patient state index (PSi), UDP communication protocol

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571 The Issue of Pedagogical Approaches in Higher Education: Public Universities as an Example

Authors: Majda El Moufarej

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Higher education plays a central role in socio-economic development. However, with the wave of change mainly due to the extensive use of technology in the workplace, the rate of unemployment among graduates rises because they lack the appropriate competencies and skills currently required in professional life. This situation has led higher education institutions worldwide to reconsider their missions, strategic planning, and curricula, among other elements to redress the image of the university as expected. When it comes to practice, there are many obstacles that hinder the achievement of the expected objectives, especially in public universities with free access, as in the case of Morocco. Nevertheless, huge efforts have been made by educational managers to improve the quality of education by focusing on the issue of pedagogical approaches, where university teachers assume more responsibility to save the situation. In this paper, the focus will be placed on the issue of pedagogical approaches to be adopted, depending on the nature of the subject, the size of the class, the available equipment, the students’ level and degree of motivation. Before elaborating on this idea, it may be more insightful to begin by addressing another variable, which concerns the new role of university teachers and their qualification in pedagogical competence. Then, the discussion will revolve around five pedagogical approaches currently adopted in western universities and the focus will be exclusively placed on the one which is called “the Systematic Approach to course Design”, due to its crucial relevance in the teaching of subjects in the schools of humanities, as it can guide the teacher in the development of an explicit program for purposeful teaching and learning. The study is based on a qualitative method, and the findings will be analyzed and followed by some recommendations about how to overcome difficulties in teaching large groups, while transmitting the relevant knowledge and skills on demand in the workplace.

Keywords: higher education, public universities, pedagogical approaches, pedagogical competence

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570 Designing Agricultural Irrigation Systems Using Drone Technology and Geospatial Analysis

Authors: Yongqin Zhang, John Lett

Abstract:

Geospatial technologies have been increasingly used in agriculture for various applications and purposes in recent years. Unmanned aerial vehicles (drones) fit the needs of farmers in farming operations, from field spraying to grow cycles and crop health. In this research, we conducted a practical research project that used drone technology to design and map optimal locations and layouts of irrigation systems for agriculture farms. We flew a DJI Mavic 2 Pro drone to acquire aerial remote sensing images over two agriculture fields in Forest, Mississippi, in 2022. Flight plans were first designed to capture multiple high-resolution images via a 20-megapixel RGB camera mounted on the drone over the agriculture fields. The Drone Deploy web application was then utilized to develop flight plans and subsequent image processing and measurements. The images were orthorectified and processed to estimate the area of the area and measure the locations of the water line and sprinkle heads. Field measurements were conducted to measure the ground targets and validate the aerial measurements. Geospatial analysis and photogrammetric measurements were performed for the study area to determine optimal layout and quantitative estimates for irrigation systems. We created maps and tabular estimates to demonstrate the locations, spacing, amount, and layout of sprinkler heads and water lines to cover the agricultural fields. This research project provides scientific guidance to Mississippi farmers for a precision agricultural irrigation practice.

Keywords: drone images, agriculture, irrigation, geospatial analysis, photogrammetric measurements

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569 Application of Remote Sensing for Monitoring the Impact of Lapindo Mud Sedimentation for Mangrove Ecosystem, Case Study in Sidoarjo, East Java

Authors: Akbar Cahyadhi Pratama Putra, Tantri Utami Widhaningtyas, M. Randy Aswin

Abstract:

Indonesia as an archipelagic nation have very long coastline which have large potential marine resources, one of that is the mangrove ecosystems. Lapindo mudflow disaster in Sidoarjo, East Java requires mudflow flowed into the sea through the river Brantas and Porong. Mud material that transported by river flow is feared dangerous because they contain harmful substances such as heavy metals. This study aims to map the mangrove ecosystem seen from its density and knowing how big the impact of a disaster on the Lapindo mud to mangrove ecosystem and accompanied by efforts to address the mangrove ecosystem that maintained continuity. Mapping coastal mangrove conditions of Sidoarjo was done using remote sensing products that Landsat 7 ETM + images with dry months of recording time in 2002, 2006, 2009, and 2014. The density of mangrove detected using NDVI that uses the band 3 that is the red channel and band 4 that is near IR channel. Image processing was used to produce NDVI using ENVI 5.1 software. NDVI results were used for the detection of mangrove density is 0-1. The development of mangrove ecosystems of both area and density from year to year experienced has a significant increase. Mangrove ecosystems growths are affected by material deposition area of Lapindo mud on Porong and Brantas river estuary, where the silt is growing medium suitable mangrove ecosystem and increasingly growing. Increasing the density caused support by public awareness to prevent heavy metals in the material so that the Lapindo mud mangrove breeding done around the farm.

Keywords: archipelagic nation, mangrove, Lapindo mudflow disaster, NDVI

Procedia PDF Downloads 440
568 The Image of Victim and Criminal in Love Crimes on Social Media in Egypt: Facebook Discourse Analysis

Authors: Sherehan Hamdalla

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Egypt has experienced a series of terrifying love crimes in the last few months. This ‘trend’ of love crimes started with a young man caught on video slaughtering his ex-girlfriend in the street in the city of El Mansoura. The crime shocked all Egyptian citizens at all levels; unfortunately, not less than three similar crimes took place in other different Egyptian cities with the same killing trigger. The characteristics and easy access and reach of social media consider the reason why it is one of the most crucial online communication channels; users utilize social media platforms for sharing and exchanging ideas, news, and many other activities; they can freely share posts that reflect their mindset or personal views regarding any issues, these posts are going viral in all social media account by reposting or numbers of shares for these posts to support the content included, or even to attack. The repetition of sharing certain posts could mobilize other supporters with the same point of view, especially when that crowd’s online participation is confronting a public opinion case’s consequences. The death of that young woman was followed by similar crimes in other cities, such as El Sharkia and Port Said. These love crimes provoked a massive wave of contention among all social classes in Egypt. Strangely, some were supporting the criminal and defending his side for several reasons, which the study will uncover. Facebook, the most popular social media platform for Egyptians, reflects the debate between supporters of the victim and supporters of the criminal. Facebook pages were created specifically to disseminate certain viewpoints online, for example, asking for the maximum penalty to be given to criminals. These pages aimed to mobilize the maximum number of supporters and to affect the outcome of the trials.

Keywords: love crimes, victim, criminal, social media

Procedia PDF Downloads 77
567 Final Account Closing in Construction Project: The Use of Supply Chain Management to Reduce the Delays

Authors: Zarabizan Zakaria, Syuhaida Ismail, Aminah Md. Yusof

Abstract:

Project management process starts from the planning stage up to the stage of completion (handover of buildings, preparation of the final accounts and the closing balance). This process is not easy to implement efficiently and effectively. The issue of delays in construction is a major problem for construction projects. These delays have been blamed mainly on inefficient traditional construction practices that continue to dominate the current industry. This is due to several factors, such as environments of construction technology, sophisticated design and customer demands that are constantly changing and influencing, either directly or indirectly, the practice of management. Among the identified influences are physical environment, social environment, information environment, political and moral atmosphere. Therefore, this paper is emerged to determine the problem and issues in the final account closing in construction projects, and it establishes the need to embrace Supply Chain Management (SCM) and then elucidates the need and strategies for the development of a delay reduction framework. At the same time, this paper provides effective measures to avoid or at least reduce the delay to the optimum level. Allowing problems in the closure declaration to occur without proper monitoring and control can leave negative impact on the cost and time of delivery to the end user. Besides, it can also affect the reputation or image of the agency/department that manages the implementation of a contract and consequently may reduce customer's trust towards the agencies/departments. It is anticipated that the findings reported in this paper could address root delay contributors and apply SCM tools for their mitigation for the better development of construction project.

Keywords: final account closing, construction project, construction delay, supply chain management

Procedia PDF Downloads 370
566 A Real-Time Moving Object Detection and Tracking Scheme and Its Implementation for Video Surveillance System

Authors: Mulugeta K. Tefera, Xiaolong Yang, Jian Liu

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Detection and tracking of moving objects are very important in many application contexts such as detection and recognition of people, visual surveillance and automatic generation of video effect and so on. However, the task of detecting a real shape of an object in motion becomes tricky due to various challenges like dynamic scene changes, presence of shadow, and illumination variations due to light switch. For such systems, once the moving object is detected, tracking is also a crucial step for those applications that used in military defense, video surveillance, human computer interaction, and medical diagnostics as well as in commercial fields such as video games. In this paper, an object presents in dynamic background is detected using adaptive mixture of Gaussian based analysis of the video sequences. Then the detected moving object is tracked using the region based moving object tracking and inter-frame differential mechanisms to address the partial overlapping and occlusion problems. Firstly, the detection algorithm effectively detects and extracts the moving object target by enhancing and post processing morphological operations. Secondly, the extracted object uses region based moving object tracking and inter-frame difference to improve the tracking speed of real-time moving objects in different video frames. Finally, the plotting method was applied to detect the moving objects effectively and describes the object’s motion being tracked. The experiment has been performed on image sequences acquired both indoor and outdoor environments and one stationary and web camera has been used.

Keywords: background modeling, Gaussian mixture model, inter-frame difference, object detection and tracking, video surveillance

Procedia PDF Downloads 479
565 Prediction of Remaining Life of Industrial Cutting Tools with Deep Learning-Assisted Image Processing Techniques

Authors: Gizem Eser Erdek

Abstract:

This study is research on predicting the remaining life of industrial cutting tools used in the industrial production process with deep learning methods. When the life of cutting tools decreases, they cause destruction to the raw material they are processing. This study it is aimed to predict the remaining life of the cutting tool based on the damage caused by the cutting tools to the raw material. For this, hole photos were collected from the hole-drilling machine for 8 months. Photos were labeled in 5 classes according to hole quality. In this way, the problem was transformed into a classification problem. Using the prepared data set, a model was created with convolutional neural networks, which is a deep learning method. In addition, VGGNet and ResNet architectures, which have been successful in the literature, have been tested on the data set. A hybrid model using convolutional neural networks and support vector machines is also used for comparison. When all models are compared, it has been determined that the model in which convolutional neural networks are used gives successful results of a %74 accuracy rate. In the preliminary studies, the data set was arranged to include only the best and worst classes, and the study gave ~93% accuracy when the binary classification model was applied. The results of this study showed that the remaining life of the cutting tools could be predicted by deep learning methods based on the damage to the raw material. Experiments have proven that deep learning methods can be used as an alternative for cutting tool life estimation.

Keywords: classification, convolutional neural network, deep learning, remaining life of industrial cutting tools, ResNet, support vector machine, VggNet

Procedia PDF Downloads 80