Search results for: noise shaping
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1616

Search results for: noise shaping

296 Solar-Blind Ni-Schottky Photodetector Based on MOCVD Grown ZnGa₂O₄

Authors: Taslim Khan, Ray Hua Horng, Rajendra Singh

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This study presents a comprehensive analysis of the design, fabrication, and performance evaluation of a solar-blind Schottky photodetector based on ZnGa₂O₄ grown via MOCVD, utilizing Ni/Au as the Schottky electrode. ZnGa₂O₄, with its wide bandgap of 5.2 eV, is well-suited for high-performance solar-blind photodetection applications. The photodetector demonstrates an impressive responsivity of 280 A/W, indicating its exceptional sensitivity within the solar-blind ultraviolet band. One of the device's notable attributes is its high rejection ratio of 10⁵, which effectively filters out unwanted background signals, enhancing its reliability in various environments. The photodetector also boasts a photodetector responsivity contrast ratio (PDCR) of 10⁷, showcasing its ability to detect even minor changes in incident UV light. Additionally, the device features an outstanding detective of 10¹⁸ Jones, underscoring its capability to precisely detect faint UV signals. It exhibits a fast response time of 80 ms and an ON/OFF ratio of 10⁵, making it suitable for real-time UV sensing applications. The noise-equivalent power (NEP) of 10^-17 W/Hz further highlights its efficiency in detecting low-intensity UV signals. The photodetector also achieves a high forward-to-backward current rejection ratio of 10⁶, ensuring high selectivity. Furthermore, the device maintains an extremely low dark current of approximately 0.1 pA. These findings position the ZnGa₂O₄-based Schottky photodetector as a leading candidate for solar-blind UV detection applications. It offers a compelling combination of sensitivity, selectivity, and operational efficiency, making it a highly promising tool for environments requiring precise and reliable UV detection.

Keywords: wideband gap, solar blind photodetector, MOCVD, zinc gallate

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295 Digital Value Co-Creation: The Case of Worthy a Virtual Collaborative Museum across Europe

Authors: Camilla Marini, Deborah Agostino

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Cultural institutions provide more than service-based offers; indeed, they are experience-based contexts. A cultural experience is a special event that encompasses a wide range of values which, for visitors, are primarily cultural rather than economic and financial. Cultural institutions have always been characterized by inclusivity and participatory practices, but the upcoming of digital technologies has put forward their interest in collaborative practices and the relationship with their audience. Indeed, digital technologies highly affected the cultural experience as it was conceived. Especially, museums, as traditional and authoritative cultural institutions, have been highly challenged by digital technologies. They shifted by a collection-oriented toward a visitor-centered approach, and digital technologies generated a highly interactive ecosystem in which visitors have an active role, shaping their own cultural experience. Most of the studies that investigate value co-creation in museums adopt a single perspective which is separately one of the museums or one of the users, but the analysis of the convergence/divergence of these perspectives is still emphasized. Additionally, many contributions focus on digital value co-creation as an outcome rather than as a process. The study aims to provide a joint perspective on digital value co-creation which include both museum and visitors. Also, it deepens the contribution of digital technologies in the value co-creation process, addressing the following research questions: (i) what are the convergence/divergence drivers on digital value co-creation and (ii) how digital technologies can be means of value co-creation? The study adopts an action research methodology that is based on the case of WORTHY, an educational project which involves cultural institutions and schools all around Europe, creating a virtual collaborative museum. It represents a valuable case for the aim of the study since it has digital technologies at its core, and the interaction through digital technologies is fundamental, all along with the experience. Action research has been identified as the most appropriate methodology for researchers to have direct contact with the field. Data have been collected through primary and secondary sources. Cultural mediators such as museums, teachers and students’ families have been interviewed, while a focus group has been designed to interact with students, investigating all the aspects of the cultural experience. Secondary sources encompassed project reports and website contents in order to deepen the perspective of cultural institutions. Preliminary findings highlight the dimensions of digital value co-creation in cultural institutions from a museum-visitor integrated perspective and the contribution of digital technologies in the value co-creation process. The study outlines a two-folded contribution that encompasses both an academic and a practitioner level. Indeed, it contributes to fulfilling the gap in cultural management literature about the convergence/divergence of service provider-user perspectives but it also provides cultural professionals with guidelines on how to evaluate the digital value co-creation process.

Keywords: co-creation, digital technologies, museum, value

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294 Structural Damage Detection Using Modal Data Employing Teaching Learning Based Optimization

Authors: Subhajit Das, Nirjhar Dhang

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Structural damage detection is a challenging work in the field of structural health monitoring (SHM). The damage detection methods mainly focused on the determination of the location and severity of the damage. Model updating is a well known method to locate and quantify the damage. In this method, an error function is defined in terms of difference between the signal measured from ‘experiment’ and signal obtained from undamaged finite element model. This error function is minimised with a proper algorithm, and the finite element model is updated accordingly to match the measured response. Thus, the damage location and severity can be identified from the updated model. In this paper, an error function is defined in terms of modal data viz. frequencies and modal assurance criteria (MAC). MAC is derived from Eigen vectors. This error function is minimized by teaching-learning-based optimization (TLBO) algorithm, and the finite element model is updated accordingly to locate and quantify the damage. Damage is introduced in the model by reduction of stiffness of the structural member. The ‘experimental’ data is simulated by the finite element modelling. The error due to experimental measurement is introduced in the synthetic ‘experimental’ data by adding random noise, which follows Gaussian distribution. The efficiency and robustness of this method are explained through three examples e.g., one truss, one beam and one frame problem. The result shows that TLBO algorithm is efficient to detect the damage location as well as the severity of damage using modal data.

Keywords: damage detection, finite element model updating, modal assurance criteria, structural health monitoring, teaching learning based optimization

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293 Nonlinear Aerodynamic Parameter Estimation of a Supersonic Air to Air Missile by Using Artificial Neural Networks

Authors: Tugba Bayoglu

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Aerodynamic parameter estimation is very crucial in missile design phase, since accurate high fidelity aerodynamic model is required for designing high performance and robust control system, developing high fidelity flight simulations and verification of computational and wind tunnel test results. However, in literature, there is not enough missile aerodynamic parameter identification study for three main reasons: (1) most air to air missiles cannot fly with constant speed, (2) missile flight test number and flight duration are much less than that of fixed wing aircraft, (3) variation of the missile aerodynamic parameters with respect to Mach number is higher than that of fixed wing aircraft. In addition to these challenges, identification of aerodynamic parameters for high wind angles by using classical estimation techniques brings another difficulty in the estimation process. The reason for this, most of the estimation techniques require employing polynomials or splines to model the behavior of the aerodynamics. However, for the missiles with a large variation of aerodynamic parameters with respect to flight variables, the order of the proposed model increases, which brings computational burden and complexity. Therefore, in this study, it is aimed to solve nonlinear aerodynamic parameter identification problem for a supersonic air to air missile by using Artificial Neural Networks. The method proposed will be tested by using simulated data which will be generated with a six degree of freedom missile model, involving a nonlinear aerodynamic database. The data will be corrupted by adding noise to the measurement model. Then, by using the flight variables and measurements, the parameters will be estimated. Finally, the prediction accuracy will be investigated.

Keywords: air to air missile, artificial neural networks, open loop simulation, parameter identification

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292 Developing Pedagogy for Argumentation and Teacher Agency: An Educational Design Study in the UK

Authors: Zeynep Guler

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Argumentation and the production of scientific arguments are essential components that are necessary for helping students become scientifically literate through engaging them in constructing and critiquing ideas. Incorporating argumentation into science classrooms is challenging and can be a long-term process for both students and teachers. Students have difficulty in engaging tasks that require them to craft arguments, evaluate them to seek weaknesses, and revise them. Teachers also struggle with facilitating argumentation when they have underdeveloped science practices, underdeveloped pedagogical knowledge for argumentation science teaching, or underdeveloped teaching practice with argumentation (or a combination of all three). Thus, there is a need to support teachers in developing pedagogy for science teaching as argumentation, planning and implementing teaching practice for facilitating argumentation and also in becoming more agentic in this regards. Looking specifically at the experience of agency within education, it is arguable that agency is necessary for teachers’ renegotiation of professional purposes and practices in the light of changing educational practices. This study investigated how science teachers develop pedagogy for argumentation both individually and with their colleagues and also how teachers become more agentic (or not) through the active engagement of their contexts-for-action that refer to this as an ecological understanding of agency in order to positively influence or change their practice and their students' engagement with argumentation over two academic years. Through educational design study, this study conducted with three secondary science teachers (key stage 3-year 7 students aged 11-12) in the UK to find out if similar or different patterns of developing pedagogy for argumentation and of becoming more agentic emerge as they engage in planning and implementing a cycle of activities during the practice of teaching science with argumentation. Data from video and audio-recording of classroom practice and open-ended interviews with the science teachers were analysed using content analysis. The findings indicated that all the science teachers perceived strong agency in their opportunities to develop and apply pedagogical practices within the classroom. The teachers were pro-actively shaping their practices and classroom contexts in ways that were over and above the amendments to their pedagogy. They demonstrated some outcomes in developing pedagogy for argumentation and becoming more agentic in their teaching in this regards as a result of the collaboration with their colleagues and researcher; some appeared more agentic than others. The role of the collaboration between their colleagues was seen crucial for the teachers’ practice in the schools: close collaboration and support from other teachers in planning and implementing new educational innovations were seen as crucial for the development of pedagogy and becoming more agentic in practice. They needed to understand the importance of scientific argumentation but also understand how it can be planned and integrated into classroom practice. They also perceived constraint emerged from their lack of competence and knowledge in posing appropriate questions to help the students engage in argumentation, providing support for the students' construction of oral and written arguments.

Keywords: argumentation, teacher professional development, teacher agency, students' construction of argument

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291 Similar Script Character Recognition on Kannada and Telugu

Authors: Gurukiran Veerapur, Nytik Birudavolu, Seetharam U. N., Chandravva Hebbi, R. Praneeth Reddy

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This work presents a robust approach for the recognition of characters in Telugu and Kannada, two South Indian scripts with structural similarities in characters. To recognize the characters exhaustive datasets are required, but there are only a few publicly available datasets. As a result, we decided to create a dataset for one language (source language),train the model with it, and then test it with the target language.Telugu is the target language in this work, whereas Kannada is the source language. The suggested method makes use of Canny edge features to increase character identification accuracy on pictures with noise and different lighting. A dataset of 45,150 images containing printed Kannada characters was created. The Nudi software was used to automatically generate printed Kannada characters with different writing styles and variations. Manual labelling was employed to ensure the accuracy of the character labels. The deep learning models like CNN (Convolutional Neural Network) and Visual Attention neural network (VAN) are used to experiment with the dataset. A Visual Attention neural network (VAN) architecture was adopted, incorporating additional channels for Canny edge features as the results obtained were good with this approach. The model's accuracy on the combined Telugu and Kannada test dataset was an outstanding 97.3%. Performance was better with Canny edge characteristics applied than with a model that solely used the original grayscale images. The accuracy of the model was found to be 80.11% for Telugu characters and 98.01% for Kannada words when it was tested with these languages. This model, which makes use of cutting-edge machine learning techniques, shows excellent accuracy when identifying and categorizing characters from these scripts.

Keywords: base characters, modifiers, guninthalu, aksharas, vattakshara, VAN

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290 A Deep Learning Model with Greedy Layer-Wise Pretraining Approach for Optimal Syngas Production by Dry Reforming of Methane

Authors: Maryam Zarabian, Hector Guzman, Pedro Pereira-Almao, Abraham Fapojuwo

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Dry reforming of methane (DRM) has sparked significant industrial and scientific interest not only as a viable alternative for addressing the environmental concerns of two main contributors of the greenhouse effect, i.e., carbon dioxide (CO₂) and methane (CH₄), but also produces syngas, i.e., a mixture of hydrogen (H₂) and carbon monoxide (CO) utilized by a wide range of downstream processes as a feedstock for other chemical productions. In this study, we develop an AI-enable syngas production model to tackle the problem of achieving an equivalent H₂/CO ratio [1:1] with respect to the most efficient conversion. Firstly, the unsupervised density-based spatial clustering of applications with noise (DBSAN) algorithm removes outlier data points from the original experimental dataset. Then, random forest (RF) and deep neural network (DNN) models employ the error-free dataset to predict the DRM results. DNN models inherently would not be able to obtain accurate predictions without a huge dataset. To cope with this limitation, we employ reusing pre-trained layers’ approaches such as transfer learning and greedy layer-wise pretraining. Compared to the other deep models (i.e., pure deep model and transferred deep model), the greedy layer-wise pre-trained deep model provides the most accurate prediction as well as similar accuracy to the RF model with R² values 1.00, 0.999, 0.999, 0.999, 0.999, and 0.999 for the total outlet flow, H₂/CO ratio, H₂ yield, CO yield, CH₄ conversion, and CO₂ conversion outputs, respectively.

Keywords: artificial intelligence, dry reforming of methane, artificial neural network, deep learning, machine learning, transfer learning, greedy layer-wise pretraining

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289 A Survey Study Exploring Principal Leadership and Teachers’ Expectations in the Social Working Life of Two Swedish Schools

Authors: Anette Forssten Seiser, Ulf Blossing, Mats Ekholm

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The expectation on principals to manage, lead and develop their schools and teachers are high. However, principals are not left alone without guidelines. Policy texts, curricula and syllabuses guide the orientation of their leadership. Moreover, principals’ traits and experience as well as professional norms, are decisive. However, in this study we argue for the importance to deepen the knowledge of how the practice of leadership is shaped in the daily social working life with the teachers at the school. Teachers’ experiences and expectations of leadership influence the principal’s actions, sometimes perhaps contrary to what is emphasized in official texts like the central guidelines. The expectations of teachers make up the norms of the school and thus constitute the local school culture. The aim of this study is to deepen the knowledge of teachers’ expectations on their principals to manage, lead and develop their schools. Two questions are used to guide the study: 1) How do teachers’ and principals’ expectations differ in realistic situations? 2) How do teachers’ experience-based expectations differ from more ideal expectations? To investigate teachers’ expectations of their principals, we use a social psychological perspective framed within an organisational development perspective. A social role is defined by the fact that, within the framework of the role, different people who fulfil the same role exhibit greater similarities than differences in their actions. The way a social role is exercised depends on the expectations placed on the role’s position but also on the expectations of the function of the role. The way in which the social role is embodied in practice also depends on how the person fulfilling the role perceives and understands those expectations. Based on interviews with school principals a questionnaire was constructed. Nine possible real-life and critical incidents were described that are important when it comes to role shaping in the dynamics between teachers and principals. Teachers were asked to make a choice between three, four, or five possible and realistic courses of action for the principal. The teachers were also asked to make two choices between these different options in real-life situations, one ideal as if they were working as a principal themselves, and one experience based – how they estimated that their own principal would act in such a situation. The sample consist of two elementary schools in Sweden. School A consists of two principals and 38 teachers and school B of two principals and 22 teachers. The response rate among the teachers is 95 percent in school A and 86 percent in school B. All four principals answered our questions. The results show that the expectations of teachers and principals can be understood as variations of being harmonic or disharmonic. The harmonic expectations can be interpreted to lead to an attuned leadership, while the disharmonic expectations lead to a more tensed leadership. Harmonious expectations and an attuned leadership are prominent. The results are compared to earlier research on leadership. Attuned and more tensed leadership are discussed in relation to school development and future research.

Keywords: critical incidents, principal leadership, school culture, school development, teachers' expectations

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288 A Study of Bilingual Development of a Mandarin and English Bilingual Preschool Child from China to Australia

Authors: Qiang Guo, Ruying Qi

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This project aims to trace the developmental patterns of a child's Mandarin and English from China to Australia from age 3; 03 till 5; 06. In childhood bilingual studies, there is an assumption that age 3 is the dividing line between simultaneous bilinguals and sequential bilinguals. Determining similarities and differences between Bilingual First Language Acquisition, Early Second Language Acquisition, and Second Language Acquisition is of great theoretical significance. Studies on Bilingual First Language Acquisition, hereafter, BFLA in the past three decades have shown that the grammatical development of bilingual children progresses through the same developmental trajectories as their monolingual counterparts. Cross-linguistic interaction does not show changes of the basic grammatical knowledge, even in the weaker language. While BFLA studies show consistent results under the conditions of adequate input and meaningful interactional context, the research findings of Early Second Language Acquisition (ESLA) have demonstrated that this cohort proceeds their early English differently from both BFLA and SLA. The different development could be attributed to the age of migration, input pattern, and their Environmental Languages (Lε). In the meantime, the dynamic relationship between the two languages is an issue to invite further attention. The present study attempts to fill this gap. The child in this case study started acquiring L1 Mandarin from birth in China, where the environmental language (Lε) coincided with L1 Mandarin. When she migrated to Australia at 3;06, where the environmental language (Lε) was L2 English, her Mandarin exposure was reduced. On the other hand, she received limited English input starting from 1; 02 in China, where the environmental language (Lε) was L1 Mandarin, a non-English environment. When she relocated to Australia at 3; 06, where the environmental language (Lε) coincided with L2 English, her English exposure significantly increased. The child’s linguistic profile provides an opportunity to explore: (1) What does the child’s English developmental route look like? (2) What does the L1 Mandarin developmental pattern look like in different environmental languages? (3) How do input and environmental language interact in shaping the bilingual child’s linguistic repertoire? In order to answer these questions, two linguistic areas are selected as the focus of the investigation, namely, subject realization and wh-questions. The chosen areas are contrastive in structure but perform the same semantic functions in the two linguistically distant languages and can serve as an ideal testing ground for exploring the developmental path in the two languages. The longitudinal case study adopts a combined approach of qualitative and quantitative analysis. Two years’ Mandarin and English data are examined, and comparisons are made with age-matched monolinguals in each language in CHILDES. To the author’s best knowledge, this study is the first of this kind examining a Mandarin-English bilingual child's bilingual development at a critical age, in different input patterns, and in different environmental languages (Lε). It also expands the scope of the theory of Lε, adding empirical evidence on the relationship between input and Lε in bilingual acquisition.

Keywords: bilingual development, age, input, environmental language (Le)

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287 Recurrent Neural Networks for Complex Survival Models

Authors: Pius Marthin, Nihal Ata Tutkun

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Survival analysis has become one of the paramount procedures in the modeling of time-to-event data. When we encounter complex survival problems, the traditional approach remains limited in accounting for the complex correlational structure between the covariates and the outcome due to the strong assumptions that limit the inference and prediction ability of the resulting models. Several studies exist on the deep learning approach to survival modeling; moreover, the application for the case of complex survival problems still needs to be improved. In addition, the existing models need to address the data structure's complexity fully and are subject to noise and redundant information. In this study, we design a deep learning technique (CmpXRnnSurv_AE) that obliterates the limitations imposed by traditional approaches and addresses the above issues to jointly predict the risk-specific probabilities and survival function for recurrent events with competing risks. We introduce the component termed Risks Information Weights (RIW) as an attention mechanism to compute the weighted cumulative incidence function (WCIF) and an external auto-encoder (ExternalAE) as a feature selector to extract complex characteristics among the set of covariates responsible for the cause-specific events. We train our model using synthetic and real data sets and employ the appropriate metrics for complex survival models for evaluation. As benchmarks, we selected both traditional and machine learning models and our model demonstrates better performance across all datasets.

Keywords: cumulative incidence function (CIF), risk information weight (RIW), autoencoders (AE), survival analysis, recurrent events with competing risks, recurrent neural networks (RNN), long short-term memory (LSTM), self-attention, multilayers perceptrons (MLPs)

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286 Non-Destructive Static Damage Detection of Structures Using Genetic Algorithm

Authors: Amir Abbas Fatemi, Zahra Tabrizian, Kabir Sadeghi

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To find the location and severity of damage that occurs in a structure, characteristics changes in dynamic and static can be used. The non-destructive techniques are more common, economic, and reliable to detect the global or local damages in structures. This paper presents a non-destructive method in structural damage detection and assessment using GA and static data. Thus, a set of static forces is applied to some of degrees of freedom and the static responses (displacements) are measured at another set of DOFs. An analytical model of the truss structure is developed based on the available specification and the properties derived from static data. The damages in structure produce changes to its stiffness so this method used to determine damage based on change in the structural stiffness parameter. Changes in the static response which structural damage caused choose to produce some simultaneous equations. Genetic Algorithms are powerful tools for solving large optimization problems. Optimization is considered to minimize objective function involve difference between the static load vector of damaged and healthy structure. Several scenarios defined for damage detection (single scenario and multiple scenarios). The static damage identification methods have many advantages, but some difficulties still exist. So it is important to achieve the best damage identification and if the best result is obtained it means that the method is Reliable. This strategy is applied to a plane truss. This method is used for a plane truss. Numerical results demonstrate the ability of this method in detecting damage in given structures. Also figures show damage detections in multiple damage scenarios have really efficient answer. Even existence of noise in the measurements doesn’t reduce the accuracy of damage detections method in these structures.

Keywords: damage detection, finite element method, static data, non-destructive, genetic algorithm

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285 Geospatial Curve Fitting Methods for Disease Mapping of Tuberculosis in Eastern Cape Province, South Africa

Authors: Davies Obaromi, Qin Yongsong, James Ndege

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To interpolate scattered or regularly distributed data, there are imprecise or exact methods. However, there are some of these methods that could be used for interpolating data in a regular grid and others in an irregular grid. In spatial epidemiology, it is important to examine how a disease prevalence rates are distributed in space, and how they relate with each other within a defined distance and direction. In this study, for the geographic and graphic representation of the disease prevalence, linear and biharmonic spline methods were implemented in MATLAB, and used to identify, localize and compare for smoothing in the distribution patterns of tuberculosis (TB) in Eastern Cape Province. The aim of this study is to produce a more “smooth” graphical disease map for TB prevalence patterns by a 3-D curve fitting techniques, especially the biharmonic splines that can suppress noise easily, by seeking a least-squares fit rather than exact interpolation. The datasets are represented generally as a 3D or XYZ triplets, where X and Y are the spatial coordinates and Z is the variable of interest and in this case, TB counts in the province. This smoothing spline is a method of fitting a smooth curve to a set of noisy observations using a spline function, and it has also become the conventional method for its high precision, simplicity and flexibility. Surface and contour plots are produced for the TB prevalence at the provincial level for 2012 – 2015. From the results, the general outlook of all the fittings showed a systematic pattern in the distribution of TB cases in the province and this is consistent with some spatial statistical analyses carried out in the province. This new method is rarely used in disease mapping applications, but it has a superior advantage to be assessed at subjective locations rather than only on a rectangular grid as seen in most traditional GIS methods of geospatial analyses.

Keywords: linear, biharmonic splines, tuberculosis, South Africa

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284 Evaluation of Mechanical Behavior of Laser Cladding in Various Tilting Pad Bearing Materials

Authors: Si-Geun Choi, Hoon-Jae Park, Jung-Woo Cho, Jin-Ho Lim, Jin-Young Park, Joo-Young Oh, Jae-Il Jeong Seock-Sam Kim, Young Tae Cho, Chan Gyu Kim, Jong-Hyoung Kim

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The tilting pad bearing is a kind of the fluid film bearing and it can contribute to the high speed and the high load performance compared to other bearings including the rolling element bearing. Furthermore, the tilting bearing has many advantages such as high stability at high-speed performance, long life, high damping, high impact resistance and low noise. Therefore, it mostly used in mid to large size turbomachines, despite the high price disadvantage. Recently, manufacture and process employing laser techniques advancing at a fast-growing rate in mechanical industry, the dissimilar metal weld process employing laser techniques is actively studied. Moreover, also, Industry fields try to apply for welding the white metal and the back metal using laser cladding method for high durability. Furthermore, it has followed that laser cladding method has a lot better bond strength, toughness, anti-abrasion and environment-friendly than centrifugal casting method through preceding research. Therefore, the laser cladding method has a lot better quality, cost reduction, eco-friendliness and permanence of technology than the centrifugal casting method or the gravity casting method. In this study, we compare the mechanical properties of different bearing materials by evaluating the behavior of laser cladding layer with various materials (i.e. SS400, SCM440, S20C) under the same parameters. Furthermore, we analyze the porosity of various tilting pad bearing materials which white metal treated on samples. SEM, EDS analysis and hardness tests of three materials are shown to understand the mechanical properties and tribological behavior. W/D ratio, surface roughness results with various materials are performed in this study.

Keywords: laser cladding, tilting pad bearing, white metal, mechanical properties

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283 Beyond Geometry: The Importance of Surface Properties in Space Syntax Research

Authors: Christoph Opperer

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Space syntax is a theory and method for analyzing the spatial layout of buildings and urban environments to understand how they can influence patterns of human movement, social interaction, and behavior. While direct visibility is a key factor in space syntax research, important visual information such as light, color, texture, etc., are typically not considered, even though psychological studies have shown a strong correlation to the human perceptual experience within physical space – with light and color, for example, playing a crucial role in shaping the perception of spaciousness. Furthermore, these surface properties are often the visual features that are most salient and responsible for drawing attention to certain elements within the environment. This paper explores the potential of integrating these factors into general space syntax methods and visibility-based analysis of space, particularly for architectural spatial layouts. To this end, we use a combination of geometric (isovist) and topological (visibility graph) approaches together with image-based methods, allowing a comprehensive exploration of the relationship between spatial geometry, visual aesthetics, and human experience. Custom-coded ray-tracing techniques are employed to generate spherical panorama images, encoding three-dimensional spatial data in the form of two-dimensional images. These images are then processed through computer vision algorithms to generate saliency-maps, which serve as a visual representation of areas most likely to attract human attention based on their visual properties. The maps are subsequently used to weight the vertices of isovists and the visibility graph, placing greater emphasis on areas with high saliency. Compared to traditional methods, our weighted visibility analysis introduces an additional layer of information density by assigning different weights or importance levels to various aspects within the field of view. This extends general space syntax measures to provide a more nuanced understanding of visibility patterns that better reflect the dynamics of human attention and perception. Furthermore, by drawing parallels to traditional isovist and VGA analysis, our weighted approach emphasizes a crucial distinction, which has been pointed out by Ervin and Steinitz: the difference between what is possible to see and what is likely to be seen. Therefore, this paper emphasizes the importance of including surface properties in visibility-based analysis to gain deeper insights into how people interact with their surroundings and to establish a stronger connection with human attention and perception.

Keywords: space syntax, visibility analysis, isovist, visibility graph, visual features, human perception, saliency detection, raytracing, spherical images

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282 Provisional Settlements and Urban Resilience: The Transformation of Refugee Camps into Cities

Authors: Hind Alshoubaki

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The world is now confronting a widespread urban phenomenon: refugee camps, which have mostly been established in ‘rushing mode,’ pointing toward affording temporary settlements for refugees that provide them with minimum levels of safety, security and protection from harsh weather conditions within a very short time period. In fact, those emergency settlements are transforming into permanent ones since time is a decisive factor in terms of construction and camps’ age. These play an essential role in transforming their temporary character into a permanent one that generates deep modifications to the city’s territorial structure, shaping a new identity and creating a contentious change in the city’s form and history. To achieve a better understanding for the transformation of refugee camps, this study is based on a mixed-methods approach: the qualitative approach explores different refugee camps and analyzes their transformation process in terms of population density and the changes to the city’s territorial structure and urban features. The quantitative approach employs a statistical regression analysis as a reliable prediction of refugees’ satisfaction within the Zaatari camp in order to predict its future transformation. Obviously, refugees’ perceptions of their current conditions will affect their satisfaction, which plays an essential role in transforming emergency settlements into permanent cities over time. The test basically discusses five main themes: the access and readiness of schools, the dispersion of clinics and shopping centers; the camp infrastructure, the construction materials, and the street networks. The statistical analysis showed that Syrian refugees were not satisfied with their current conditions inside the Zaatari refugee camp and that they had started implementing changes according to their needs, desires, and aspirations because they are conscious about the fact of their prolonged stay in this settlement. Also, the case study analyses showed that neglecting the fact that construction takes time leads settlements being created with below-minimum standards that are deteriorating and creating ‘slums,’ which lead to increased crime rates, suicide, drug use and diseases and deeply affect cities’ urban tissues. For this reason, recognizing the ‘temporary-eternal’ character of those settlements is the fundamental concept to consider refugee camps from the beginning as definite permanent cities. This is the key factor to minimize the trauma of displacement on both refugees and the hosting countries. Since providing emergency settlements within a short time period does not mean using temporary materials, having a provisional character or creating ‘makeshift cities.’

Keywords: refugee, refugee camp, temporary, Zaatari

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281 Analysis of Real Time Seismic Signal Dataset Using Machine Learning

Authors: Sujata Kulkarni, Udhav Bhosle, Vijaykumar T.

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Due to the closeness between seismic signals and non-seismic signals, it is vital to detect earthquakes using conventional methods. In order to distinguish between seismic events and non-seismic events depending on their amplitude, our study processes the data that come from seismic sensors. The authors suggest a robust noise suppression technique that makes use of a bandpass filter, an IIR Wiener filter, recursive short-term average/long-term average (STA/LTA), and Carl short-term average (STA)/long-term average for event identification (LTA). The trigger ratio used in the proposed study to differentiate between seismic and non-seismic activity is determined. The proposed work focuses on significant feature extraction for machine learning-based seismic event detection. This serves as motivation for compiling a dataset of all features for the identification and forecasting of seismic signals. We place a focus on feature vector dimension reduction techniques due to the temporal complexity. The proposed notable features were experimentally tested using a machine learning model, and the results on unseen data are optimal. Finally, a presentation using a hybrid dataset (captured by different sensors) demonstrates how this model may also be employed in a real-time setting while lowering false alarm rates. The planned study is based on the examination of seismic signals obtained from both individual sensors and sensor networks (SN). A wideband seismic signal from BSVK and CUKG station sensors, respectively located near Basavakalyan, Karnataka, and the Central University of Karnataka, makes up the experimental dataset.

Keywords: Carl STA/LTA, features extraction, real time, dataset, machine learning, seismic detection

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280 Spatial and Time Variability of Ambient Vibration H/V Frequency Peak

Authors: N. Benkaci, E. Oubaiche, J.-L. Chatelain, R. Bensalem, K. Abbes

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The ambient vibration H/V technique is widely used nowadays in microzonation studies, because of its easy field handling and its low cost, compared to other geophysical methods. However, in presence of complex geology or lateral heterogeneity evidenced by more than one peak frequency in the H/V curve, it is difficult to interpret the results, especially when soil information is lacking. In this work, we focus on the construction site of the Baraki 40000=place stadium, located in the north-east side of the Mitidja basin (Algeria), to identify the seismic wave amplification zones. H/V curve analysis leads to the observation of spatial and time variability of the H/V frequency peaks. The spatial variability allows dividing the studied area into three main zones: (1) one with a predominant frequency around 1,5 Hz showing an important amplification level, (2) the second exhibits two peaks at 1,5 Hz and in the 4 Hz – 10 Hz range, and (3) the third zone is characterized by a plateau between 2 Hz and 3 Hz. These H/V curve categories reveal a consequent lateral heterogeneity dividing the stadium site roughly in the middle. Furthermore, a continuous ambient vibration recording during several weeks allows showing that the first peak at 1,5 Hz in the second zone, completely disappears between 2 am and 4 am, and reaching its maximum amplitude around 12 am. Consequently, the anthropogenic noise source generating these important variations could be the Algiers Rocade Sud highway, located in the maximum amplification azimuth direction of the H/V curves. This work points out that the H/V method is an important tool to perform nano-zonation studies prior to geotechnical and geophysical investigations, and that, in some cases, the H/V technique fails to reveal the resonance frequency in the absence of strong anthropogenic source.

Keywords: ambient vibrations, amplification, fundamental frequency, lateral heterogeneity, site effect

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279 Harsh Discipline and Later Disruptive Behavior Disorder in Two Contexts

Authors: Olga Santesteban, Glorisa Canino, Hector R. Bird, Cristiane S. Duarte

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Objective: To address whether harsh discipline is associated with disruptive behavior disorders (DBD) in Puerto Rican children over time. Background: Both cross-sectional and longitudinal studies report that rates of DBD vary by gender, age and other demographics, being more frequent among boys, later in life and among those who live in urban areas. Also, the literature supports the direct, positive association between harsh discipline and externalizing behaviors. Nevertheless, scholars have underscored the important role of race and ethnicity in understanding discipline effects on children. The impact of harsh discipline in a Puerto Rican population remains to be studied. Methods: Sample: This is a secondary analysis of the Boricua Youth Study which assessed yearly (3 times) Puerto Rican children aged 5-15 in two different sites: San Juan (Puerto Rico) and the South Bronx (NY), N=2951. Participants that did not have scores of harsh discipline in the 3 waves were excluded for this analysis (N=2091). Main Measures: a) Harsh Discipline (Parent report) was measured using 6 items from the “Parental Discipline Scale” that measures various forms of punishment, including physical and verbal abuse, and withholding affection; b) Disruptive Behavior Disorder (Parent report): Parent version of the Diagnostic Interview Schedule for Children-IV (DISC-IV) was used to asses children’s conduct disorders; c) Demographic factors: Child gender, child age, family income, marital status; d) Parental factors: parental psychopathology, parental monitoring, familism, parent support; e) Children characteristics: Controlling for any diagnostic at wave 1 (internalizing or externalizing). Data Analysis: Logistic regression was carried out relating the likelihood of DBD to harsh discipline along waves controlling for potential confounders as demographics, child and parent characteristics. Results: There were no significant differences in harsh discipline by site in wave 1 and wave 2 but there was a significant difference in wave 3. Also, there were no significant differences in DBD by site in wave 1 and wave 2 but there was a significant difference in wave 3. There was a significant difference of discipline by gender and age in all the waves. We calculated unadjusted (OR) and adjusted (AOD) and 95% confidence intervals (95%CI) showing the relation between harsh discipline at wave 1 and the presence of child disruptive behavior disorder at wave 3 for both South Bronx and Puerto Rico. There was an association between harsh discipline and the likelihood of having DBD in The Bronx (AOR=1.76; 95%CI=1.13-2.74, p.013) and in Puerto Rico (AOR=2.17; 95%CI=1.28-3.67, p.004) having controlled for demographic, parental and individual factors. Conclusions: Context may be an important differential factor shaping the potential risk of harsh discipline toward DBD for Puerto Rican children.

Keywords: disruptive behavior disorders, harsh discipline, puerto rican, psychological education

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278 Weight Estimation Using the K-Means Method in Steelmaking’s Overhead Cranes in Order to Reduce Swing Error

Authors: Seyedamir Makinejadsanij

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One of the most important factors in the production of quality steel is to know the exact weight of steel in the steelmaking area. In this study, a calculation method is presented to estimate the exact weight of the melt as well as the objects transported by the overhead crane. Iran Alloy Steel Company's steelmaking area has three 90-ton cranes, which are responsible for transferring the ladles and ladle caps between 34 areas in the melt shop. Each crane is equipped with a Disomat Tersus weighing system that calculates and displays real-time weight. The moving object has a variable weight due to swinging, and the weighing system has an error of about +-5%. This means that when the object is moving by a crane, which weighs about 80 tons, the device (Disomat Tersus system) calculates about 4 tons more or 4 tons less, and this is the biggest problem in calculating a real weight. The k-means algorithm is an unsupervised clustering method that was used here. The best result was obtained by considering 3 centers. Compared to the normal average(one) or two, four, five, and six centers, the best answer is with 3 centers, which is logically due to the elimination of noise above and below the real weight. Every day, the standard weight is moved with working cranes to test and calibrate cranes. The results are shown that the accuracy is about 40 kilos per 60 tons (standard weight). As a result, with this method, the accuracy of moving weight is calculated as 99.95%. K-means is used to calculate the exact mean of objects. The stopping criterion of the algorithm is also the number of 1000 repetitions or not moving the points between the clusters. As a result of the implementation of this system, the crane operator does not stop while moving objects and continues his activity regardless of weight calculations. Also, production speed increased, and human error decreased.

Keywords: k-means, overhead crane, melt weight, weight estimation, swing problem

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277 Enhancing AI for Global Impact: Conversations on Improvement and Societal Benefits

Authors: C. P. Chukwuka, E. V. Chukwuka, F. Ukwadi

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This paper focuses on the advancement and societal impact of artificial intelligence (AI) systems. It explores the need for a theoretical framework in corporate governance, specifically in the context of 'hybrid' companies that have a mix of private and government ownership. The paper emphasizes the potential of AI to address challenges faced by these companies and highlights the importance of the less-explored state model in corporate governance. The aim of this research is to enhance AI systems for global impact and positive societal outcomes. It aims to explore the role of AI in refining corporate governance in hybrid companies and uncover nuanced insights into complex ownership structures. The methodology involves leveraging the capabilities of AI to address the challenges faced by hybrid companies in corporate governance. The researchers will analyze existing theoretical frameworks in corporate governance and integrate AI systems to improve problem-solving and understanding of intricate systems. The paper suggests that improved AI systems have the potential to shape a more informed and responsible corporate landscape. AI can uncover nuanced insights and navigate complex ownership structures in hybrid companies, leading to greater efficacy and positive societal outcomes. The theoretical importance of this research lies in the exploration of the role of AI in corporate governance, particularly in the context of hybrid companies. By integrating AI systems, the paper highlights the potential for improved problem-solving and understanding of intricate systems, contributing to a more informed and responsible corporate landscape. The data for this research will be collected from existing literature on corporate governance, specifically focusing on hybrid companies. Additionally, data on AI capabilities and their application in corporate governance will be collected. The collected data will be analyzed through a systematic review of existing theoretical frameworks in corporate governance. The researchers will also analyze the capabilities of AI systems and their potential application in addressing the challenges faced by hybrid companies. The findings will be synthesized and compared to identify patterns and potential improvements. The research concludes that AI systems have the potential to enhance corporate governance in hybrid companies, leading to greater efficacy and positive societal outcomes. By leveraging AI capabilities, nuanced insights can be uncovered, and complex ownership structures can be navigated, shaping a more informed and responsible corporate landscape. The findings highlight the importance of integrating AI in refining problem-solving and understanding intricate systems for global impact.

Keywords: advancement, artificial intelligence, challenges, societal impact

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276 Multi-Objective Optimal Design of a Cascade Control System for a Class of Underactuated Mechanical Systems

Authors: Yuekun Chen, Yousef Sardahi, Salam Hajjar, Christopher Greer

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This paper presents a multi-objective optimal design of a cascade control system for an underactuated mechanical system. Cascade control structures usually include two control algorithms (inner and outer). To design such a control system properly, the following conflicting objectives should be considered at the same time: 1) the inner closed-loop control must be faster than the outer one, 2) the inner loop should fast reject any disturbance and prevent it from propagating to the outer loop, 3) the controlled system should be insensitive to measurement noise, and 4) the controlled system should be driven by optimal energy. Such a control problem can be formulated as a multi-objective optimization problem such that the optimal trade-offs among these design goals are found. To authors best knowledge, such a problem has not been studied in multi-objective settings so far. In this work, an underactuated mechanical system consisting of a rotary servo motor and a ball and beam is used for the computer simulations, the setup parameters of the inner and outer control systems are tuned by NSGA-II (Non-dominated Sorting Genetic Algorithm), and the dominancy concept is used to find the optimal design points. The solution of this problem is not a single optimal cascade control, but rather a set of optimal cascade controllers (called Pareto set) which represent the optimal trade-offs among the selected design criteria. The function evaluation of the Pareto set is called the Pareto front. The solution set is introduced to the decision-maker who can choose any point to implement. The simulation results in terms of Pareto front and time responses to external signals show the competing nature among the design objectives. The presented study may become the basis for multi-objective optimal design of multi-loop control systems.

Keywords: cascade control, multi-Loop control systems, multiobjective optimization, optimal control

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275 Optimizing Super Resolution Generative Adversarial Networks for Resource-Efficient Single-Image Super-Resolution via Knowledge Distillation and Weight Pruning

Authors: Hussain Sajid, Jung-Hun Shin, Kum-Won Cho

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Image super-resolution is the most common computer vision problem with many important applications. Generative adversarial networks (GANs) have promoted remarkable advances in single-image super-resolution (SR) by recovering photo-realistic images. However, high memory requirements of GAN-based SR (mainly generators) lead to performance degradation and increased energy consumption, making it difficult to implement it onto resource-constricted devices. To relieve such a problem, In this paper, we introduce an optimized and highly efficient architecture for SR-GAN (generator) model by utilizing model compression techniques such as Knowledge Distillation and pruning, which work together to reduce the storage requirement of the model also increase in their performance. Our method begins with distilling the knowledge from a large pre-trained model to a lightweight model using different loss functions. Then, iterative weight pruning is applied to the distilled model to remove less significant weights based on their magnitude, resulting in a sparser network. Knowledge Distillation reduces the model size by 40%; pruning then reduces it further by 18%. To accelerate the learning process, we employ the Horovod framework for distributed training on a cluster of 2 nodes, each with 8 GPUs, resulting in improved training performance and faster convergence. Experimental results on various benchmarks demonstrate that the proposed compressed model significantly outperforms state-of-the-art methods in terms of peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and image quality for x4 super-resolution tasks.

Keywords: single-image super-resolution, generative adversarial networks, knowledge distillation, pruning

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274 A Compact Extended Laser Diode Cavity Centered at 780 nm for Use in High-Resolution Laser Spectroscopy

Authors: J. Alvarez, J. Pimienta, R. Sarmiento

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Diode lasers working in free mode present different shifting and broadening determined by external factors such as temperature, current or mechanical vibrations, and they are not more useful in applications such as spectroscopy, metrology, and cooling of atoms, among others. Different configurations can reduce the spectral width of a laser; one of the most effective is to extend the optical resonator of the laser diode and use optical feedback either with the help of a partially reflective mirror or with a diffraction grating; this latter configuration is not only allowed to reduce the spectral width of the laser line but also to coarsely adjust its working wavelength, within a wide range typically ~ 10nm by slightly varying the angle of the diffraction grating. Two settings are commonly used for this purpose, the Littrow configuration and the Littmann Metcalf. In this paper, we present the design, construction, and characterization of a compact extended laser cavity in Littrow configuration. The designed cavity is compact and was machined on an aluminum block using computer numerical control (CNC); it has a mass of only 380 g. The design was tested on laser diodes with different wavelengths, 650nm, 780nm, and 795 nm, but can be equally efficient at other wavelengths. This report details the results obtained from the extended cavity working at a wavelength of 780 nm, with an output power of around 35mW and a line width of less than 1Mhz. The cavity was used to observe the spectrum of the corresponding Rubidium D2 line. By modulating the current and with the help of phase detection techniques, a dispersion signal with an excellent signal-to-noise ratio was generated that allowed the stabilization of the laser to a transition of the hyperfine structure of Rubidium with an integral proportional controller (PI) circuit made with precision operational amplifiers.

Keywords: Littrow, Littman-Metcalf, line width, laser stabilization, hyperfine structure

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273 Civic E-Participation in Central and Eastern Europe: A Comparative Analysis

Authors: Izabela Kapsa

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Civic participation is an important aspect of democracy. The contemporary model of democracy is based on citizens' participation in political decision-making (deliberative democracy, participatory democracy). This participation takes many forms of activities like display of slogans and symbols, voting, social consultations, political demonstrations, membership in political parties or organizing civil disobedience. The countries of Central and Eastern Europe after 1989 are characterized by great social, economic and political diversity. Civil society is also part of the process of democratization. Civil society, funded by the rule of law, civil rights, such as freedom of speech and association and private ownership, was to play a central role in the development of liberal democracy. Among the many interpretations of concepts, defining the concept of contemporary democracy, one can assume that the terms civil society and democracy, although different in meaning, nowadays overlap. In the post-communist countries, the process of shaping and maturing societies took place in the context of a struggle with a state governed by undemocratic power. State fraud or repudiation of the institution is a representative state, which in the past was the only way to manifest and defend its identity, but after the breakthrough became one of the main obstacles to the development of civil society. In Central and Eastern Europe, there are many obstacles to the development of civil society, for example, the elimination of economic poverty, the implementation of educational campaigns, consciousness-related obstacles, the formation of social capital and the deficit of social activity. Obviously, civil society does not only entail an electoral turnout but a broader participation in the decision-making process, which is impossible without direct and participative democratic institutions. This article considers such broad forms of civic participation and their characteristics in Central and Eastern Europe. The paper is attempts to analyze the functioning of electronic forms of civic participation in Central and Eastern European states. This is not accompanied by a referendum or a referendum initiative, and other forms of political participation, such as public consultations, participative budgets, or e-Government. However, this paper will broadly present electronic administration tools, the application of which results from both legal regulations and increasingly common practice in state and city management. In the comparative analysis, the experiences of post-communist bloc countries will be summed up to indicate the challenges and possible goals for further development of this form of citizen participation in the political process. The author argues that for to function efficiently and effectively, states need to involve their citizens in the political decision-making process, especially with the use of electronic tools.

Keywords: Central and Eastern Europe, e-participation, e-government, post-communism

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272 Marker-Controlled Level-Set for Segmenting Breast Tumor from Thermal Images

Authors: Swathi Gopakumar, Sruthi Krishna, Shivasubramani Krishnamoorthy

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Contactless, painless and radiation-free thermal imaging technology is one of the preferred screening modalities for detection of breast cancer. However, poor signal to noise ratio and the inexorable need to preserve edges defining cancer cells and normal cells, make the segmentation process difficult and hence unsuitable for computer-aided diagnosis of breast cancer. This paper presents key findings from a research conducted on the appraisal of two promising techniques, for the detection of breast cancer: (I) marker-controlled, Level-set segmentation of anisotropic diffusion filtered preprocessed image versus (II) Segmentation using marker-controlled level-set on a Gaussian-filtered image. Gaussian-filtering processes the image uniformly, whereas anisotropic filtering processes only in specific areas of a thermographic image. The pre-processed (Gaussian-filtered and anisotropic-filtered) images of breast samples were then applied for segmentation. The segmentation of breast starts with initial level-set function. In this study, marker refers to the position of the image to which initial level-set function is applied. The markers are generally placed on the left and right side of the breast, which may vary with the breast size. The proposed method was carried out on images from an online database with samples collected from women of varying breast characteristics. It was observed that the breast was able to be segmented out from the background by adjustment of the markers. From the results, it was observed that as a pre-processing technique, anisotropic filtering with level-set segmentation, preserved the edges more effectively than Gaussian filtering. Segmented image, by application of anisotropic filtering was found to be more suitable for feature extraction, enabling automated computer-aided diagnosis of breast cancer.

Keywords: anisotropic diffusion, breast, Gaussian, level-set, thermograms

Procedia PDF Downloads 361
271 Newspaper Headlines as Tool for Political Propaganda in Nigeria: Trend Analysis of Implications on Four Presidential Elections

Authors: Muhammed Jamiu Mustapha, Jamiu Folarin, Stephen Obiri Agyei, Rasheed Ademola Adebiyi, Mutiu Iyanda Lasisi

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The role of the media in political discourse cannot be overemphasized as they form an important part of societal development. The media institution is considered the fourth estate of the realm because it serves as a check and balance to the arms of government (Executive, Legislature and Judiciary) especially in a democratic setup, and makes public office holders accountable to the people. They scrutinize the political candidates and conduct a holistic analysis of the achievement of the government in order to make the people’s representative accountable to the electorates. The media in Nigeria play a seminal role in shaping how people vote during elections. Newspaper headlines are catchy phrases that easily capture the attention of the audience and call them (audience) to action. Research conducted on newspaper headlines looks at the linguistic aspect and how the tenses used has a resultant effect on peoples’ attitude and behaviour. Communication scholars have also conducted studies that interrogate whether newspaper headlines influence peoples' voting patterns and decisions. Propaganda and negative stories about political opponents are stapling features in electioneering campaigns. Nigerian newspaper readers have the characteristic of scanning newspaper headlines. And the question is whether politicians effectively have played into this tendency to brand opponents negatively, based on half-truths and inadequate information. This study illustrates major trends in the Nigerian political landscape looking at the past four presidential elections and frames the progress of the research in the extant body of political propaganda research in Africa. The study will use the quantitative content analysis of newspaper headlines from 2007 to 2019 to be able to ascertain whether newspaper headlines had any effect on the election results of the presidential elections during these years. This will be supplemented by Key Informant Interviews of political scientists or experts to draw further inferences from the quantitative data. Drawing on newspaper headlines of selected newspapers in Nigeria that have a political propaganda angle for the presidential elections, the analysis will correspond to and complements extant descriptions of how the field of political propaganda has been developed in Nigeria, providing evidence of four presidential elections that have shaped Nigerian politics. Understanding the development of the behavioural change of the electorates provide useful context for trend analysis in political propaganda communication. The findings will contribute to how newspaper headlines are used partly or wholly to decide the outcome of presidential elections in Nigeria.

Keywords: newspaper headlines, political propaganda, presidential elections, trend analysis

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270 Improvement of Thermal Comfort Conditions in an Urban Space "Case Study: The Square of Independence, Setif, Algeria"

Authors: Ballout Amor, Yasmina Bouchahm, Lacheheb Dhia Eddine Zakaria

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Several studies all around the world were conducted on the phenomenon of the urban heat island, and referring to the results obtained, one of the most important factors that influence this phenomenon is the mineralization of the cities which means the reducing of evaporative urban surfaces, replacing vegetation and wetlands with concrete and asphalt. The use of vegetation and water can change the urban environment and improve comfort, thus reduce the heat island. The trees act as a mask to the sun, wind, and sound, and also as a source of humidity which reduces air temperature and surrounding surfaces. Water also acts as a buffer to noise; it is also a source of moisture and regulates temperature not to mention the psychological effect on humans. Our main objective in this paper is to determine the impact of vegetation, ponds and fountains on the urban micro climate in general and on the thermal comfort of people along the Independence square in the Algerian city of Sétif, which is a semi-arid climate, in particularly. In order to reach this objective, a comparative study between different scenarios has been done; the use of the Envi-met program enabled us to model the urban environment of the Independence Square and to study the possibility of improving the conditions of comfort by adding an amount of vegetation and water ponds. After studying the results obtained (temperature, relative humidity, wind speed, PMV and PPD indicators), the efficiency of the additions we've made on the square was confirmed and this is what helped us to confirm our assumptions regarding the terms of comfort in the studied site, and in the end we are trying to develop recommendations and solutions which may contribute to improve the conditions for greater comfort in the Independence square.

Keywords: comfort in outer space, urban environment, scenarisation, vegetation, water ponds, public square, simulation

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269 Building Transparent Supply Chains through Digital Tracing

Authors: Penina Orenstein

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In today’s world, particularly with COVID-19 a constant worldwide threat, organizations need greater visibility over their supply chains more than ever before, in order to find areas for improvement and greater efficiency, reduce the chances of disruption and stay competitive. The concept of supply chain mapping is one where every process and route is mapped in detail between each vendor and supplier. The simplest method of mapping involves sourcing publicly available data including news and financial information concerning relationships between suppliers. An additional layer of information would be disclosed by large, direct suppliers about their production and logistics sites. While this method has the advantage of not requiring any input from suppliers, it also doesn’t allow for much transparency beyond the first supplier tier and may generate irrelevant data—noise—that must be filtered out to find the actionable data. The primary goal of this research is to build data maps of supply chains by focusing on a layered approach. Using these maps, the secondary goal is to address the question as to whether the supply chain is re-engineered to make improvements, for example, to lower the carbon footprint. Using a drill-down approach, the end result is a comprehensive map detailing the linkages between tier-one, tier-two, and tier-three suppliers super-imposed on a geographical map. The driving force behind this idea is to be able to trace individual parts to the exact site where they’re manufactured. In this way, companies can ensure sustainability practices from the production of raw materials through the finished goods. The approach allows companies to identify and anticipate vulnerabilities in their supply chain. It unlocks predictive analytics capabilities and enables them to act proactively. The research is particularly compelling because it unites network science theory with empirical data and presents the results in a visual, intuitive manner.

Keywords: data mining, supply chain, empirical research, data mapping

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268 Oligarchic Transitions within the Tunisian Autocratic Authoritarian System and the Struggle for Democratic Transformation: Before and beyond the 2010 Jasmine Revolution

Authors: M. Moncef Khaddar

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This paper focuses mainly on a contextualized understanding of ‘autocratic authoritarianism’ in Tunisia without approaching its peculiarities in reference to the ideal type of capitalist-liberal democracy but rather analysing it as a Tunisian ‘civilian dictatorship’. This is reminiscent, to some extent, of the French ‘colonial authoritarianism’ in parallel with the legacy of the traditional formal monarchic absolutism. The Tunisian autocratic political system is here construed as a state manufactured nationalist-populist authoritarianism associated with a de facto presidential single party, two successive autocratic presidents and their subservient autocratic elites who ruled with an iron fist the de-colonialized ‘liberated nation’ that came to be subjected to a large scale oppression and domination under the new Tunisian Republic. The diachronic survey of Tunisia’s autocratic authoritarian system covers the early years of autocracy, under the first autocratic president Bourguiba, 1957-1987, as well as the different stages of its consolidation into a police-security state under the second autocratic president, Ben Ali, 1987-2011. Comparing the policies of authoritarian regimes, within what is identified synchronically as a bi-cephalous autocratic system, entails an in-depth study of the two autocrats, who ruled Tunisia for more than half a century, as modern adaptable autocrats. This is further supported by an exploration of the ruling authoritarian autocratic elites who played a decisive role in shaping the undemocratic state-society relations, under the 1st and 2nd President, and left an indelible mark, structurally and ideologically, on Tunisian polity. Emphasis is also put on the members of the governmental and state-party institutions and apparatuses that kept circulating and recycling from one authoritarian regime to another, and from the first ‘founding’ autocrat to his putschist successor who consolidated authoritarian stability, political continuity and autocratic governance. The reconfiguration of Tunisian political life, in the post-autocratic era, since 2011 will be analysed. This will be scrutinized, especially in light of the unexpected return of many high-profile figures and old guards of the autocratic authoritarian apparatchiks. How and why were, these public figures, from an autocratic era, able to return in a supposedly post-revolutionary moment? Finally, while some continue to celebrate the putative exceptional success of ‘democratic transition’ in Tunisia, within a context of ‘unfinished revolution’, others remain perplexed in the face of a creeping ‘oligarchic transition’ to a ‘hybrid regime’, characterized rather by elites’ reformist tradition than a bottom-up genuine democratic ‘change’. This latter is far from answering the 2010 ordinary people’s ‘uprisings’ and ‘aspirations, for ‘Dignity, Liberty and Social Justice’.

Keywords: authoritarianism, autocracy, democratization, democracy, populism, transition, Tunisia

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267 The Social Structuring of Mate Selection: Assortative Marriage Patterns in the Israeli Jewish Population

Authors: Naava Dihi, Jon Anson

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Love, so it appears, is not socially blind. We show that partner selection is socially constrained, and the freedom to choose is limited by at least two major factors or capitals: on the one hand, material resources and education, locating the partners on a scale of personal achievement and economic independence. On the other, the partners' ascriptive belonging to particular ethnic, or origin, groups, differentiated by the groups' social prestige, as well as by their culture, history and even physical characteristics. However, the relative importance of achievement and ascriptive factors, as well as the overlap between them, varies from society to society, depending on the society's structure and the factors shaping it. Israeli social structure has been shaped by the waves of new immigrants who arrived over the years. The timing of their arrival, their patterns of physical settlement and their occupational inclusion or exclusion have together created a mosaic of social groups whose principal common feature has been the country of origin from which they arrived. The analysis of marriage patterns helps illuminate the social meanings of the groups and their borders. To the extent that ethnic group membership has meaning for individuals and influences their life choices, the ascriptive factor will gain in importance relative to the achievement factor in their choice of marriage partner. In this research, we examine Jewish Israeli marriage patterns by looking at the marriage choices of 5,041 women aged 15 to 49 who were single at the census in 1983, and who were married at the time of the 1995 census, 12 years later. The database for this study was a file linking respondents from the 1983 and the 1995 censuses. In both cases, 5 percent of household were randomly chosen, so that our sample includes about 4 percent of women in Israel in 1983. We present three basic analyses: (1) Who was still single in 1983, using personal and household data from the 1983 census (binomial model), (2) Who married between 1983 and a1995, using personal and household data from the 1983 census (binomial model), (3) What were the personal characteristics of the womens’ partners in 1995, using data from the 1995 census (loglinear model). We show (i) that material and cultural capital both operate to delay marriage and to increase the probability of remaining single; and (ii) while there is a clear association between ethnic group membership and education, endogamy and homogamy both operate as separate forces which constraint (but do not determine) the choice of marriage partner, and thus both serve to reproduce the current pattern of relationships, as well as identifying patterns of proximity and distance between the different groups.

Keywords: Israel, nuptiality, ascription, achievement

Procedia PDF Downloads 100