Search results for: artificial writers

Authors: Tsu-Wang Shen, Shan-Chun Chang, Chih-Hsien Wang, Te-Chao Fang

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For electrocardiogram (ECG) biometrics system, it is a tedious process to pre-install user’s high-intensity heart rate (HR) templates in ECG biometric systems. Based on only resting enrollment templates, it is a challenge to identify human by using ECG with the high-intensity HR caused from exercises and stress. This research provides a heartbeat segment method with slope-oriented neural networks against the ECG morphology changes due to high intensity HRs. The method has overall system accuracy at 97.73% which includes six levels of HR intensities. A cumulative match characteristic curve is also used to compare with other traditional ECG biometric methods.

Keywords: high-intensity heart rate, heart rate resistant, ECG human identification, decision based artificial neural network

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Authors: Aouiche Abdelaziz, Soudani Mouhamed Salah, Aouiche El Moundhe

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The present paper addresses the utilization of Artificial Neural Networks (ANNs) and Fuzzy Inference Systems (FISs) for the identification and control of dynamical systems with some degree of uncertainty. Because ANNs and FISs have an inherent ability to approximate functions and to adapt to changes in input and parameters, they can be used to control systems too complex for linear controllers. In this work, we show how ANNs and FISs can be put in order to form nets that can learn from external data. In sequence, it is presented structures of inputs that can be used along with ANNs and FISs to model non-linear systems. Four systems were used to test the identification and control of the structures proposed. The results show the ANNs and FISs (Back Propagation Algorithm) used were efficient in modeling and controlling the non-linear plants.

Keywords: non-linear systems, fuzzy set Models, neural network, control law

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Authors: Christopher Pullen

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This paper explores the significance of British cinema in the late 1950s and early 1960s as offering a renaissance of realist discourse, in the representation of everyday social issues. Offering a rejection of Hollywood cinema and the superficially of the middle classes, these ‘kitchen sink dramas’ often set within modest and sometimes squalid domestic and social environments, focused on the political struggle of the disenfranchised examining poverty, the oppressed and the outsider. While films like Look Back in Anger and Room at the Top looked primarily at male heterosexual subjectivity, films like A Taste of Honey and Victim focused on female and queer male narratives. Framing the urban landscape as a discursive architectural arena, representing basic living conditions and threatening social worlds, these iconic films established new storytelling processes for the outsider. This paper examines this historical context foregrounding the contemporary films Beautiful Thing (Hettie Macdonald, 1996), Weekend (Andrew Haigh, 2011) and Pride (Marcus Warchus, 2014), while employing the process of textual analysis in relation to theories of affect, defined by writers such as Lisa U. Marks and Sara Ahmed. Considering both romance narratives and public demonstrations of unity, where the queer ‘affective’ body is placed within architectural and social space, Beautiful Thing tells the story of gay male teenagers falling in love despite oppression from family and school, Weekend examines a one-night stand between young gay men and the unlikeliness of commitment, but the drive for sensitivity, and Pride foregrounds an historical relationship between queer youth activists and the miner’s union, who were on strike between 1984-5. These films frame the queer ‘affective’ body within politicized public space, evident in lower class men’s working clubs, tenement housing and brutal modernist tower blocks, focusing on architectural features such as windows, doorways and staircases, relating temporality, desire and change. Through such an examination a hidden history of gay male performativity is revealed, framing the potential of contemporary cinema to focus on the context of the outsider in encouraging social change.

Keywords: queer, affect, cinema, architecture, life chances

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Authors: Raja Omman Zafar, Yves Rybarczyk, Johan Borg

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This article proposes a conceptual framework for the application of digital twin technology in home care. The main goal is to bridge the gap between advanced digital twin concepts and their practical implementation in home care. This study uses a literature review and thematic analysis approach to synthesize existing knowledge and proposes a structured framework suitable for homecare applications. The proposed framework integrates key components such as IoT sensors, data-driven models, cloud computing, and user interface design, highlighting the importance of personalized and predictive homecare solutions. This framework can significantly improve the efficiency, accuracy, and reliability of homecare services. It paves the way for the implementation of digital twins in home care, promoting real-time monitoring, early intervention, and better outcomes.

Keywords: digital twin, homecare, older adults, healthcare, IoT, artificial intelligence

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Authors: Maria Antonietta Marongiu

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Propositional information in discourse is made coherent, intelligible, and persuasive through metadiscourse. The linguistic and rhetorical choices that writers/speakers make to organize and negotiate content matter are intended to help relate a text to its context. Besides, they help the audience to connect to and interpret a text according to the values of a specific discourse community. Based on these assumptions, this work aims to analyse the use of metadiscourse in the spoken performance of teachers in online EFL, ESP, and subject-teacher courses taught in English to non-native learners in higher education. In point of fact, the global spread of Covid 19 has forced universities to transition their in-class courses to online delivery. This has inevitably placed on the instructor a heavier interactional responsibility compared to in-class courses. Accordingly, online delivery needs greater structuring as regards establishing the reader/listener’s resources for text understanding and negotiating. Indeed, in online as well as in in-class courses, lessons are social acts which take place in contexts where interlocutors, as members of a community, affect the ways ideas are presented and understood. Following Hyland’s Interactional Model of Metadiscourse (2005), this study intends to investigate Teacher Talk in online academic courses during the Covid 19 lock-down in Italy. The selected corpus includes the transcripts of online EFL and ESP courses and subject-teachers online courses taught in English. The objective of the investigation is, firstly, to ascertain the presence of metadiscourse in the form of interactive devices (to guide the listener through the text) and interactional features (to involve the listener in the subject). Previous research on metadiscourse in academic discourse, in college students' presentations in EAP (English for Academic Purposes) lessons, as well as in online teaching methodology courses and MOOC (Massive Open Online Courses) has shown that instructors use a vast array of metadiscoursal features intended to express the speakers’ intentions and standing with respect to discourse. Besides, they tend to use directions to orient their listeners and logical connectors referring to the structure of the text. Accordingly, the purpose of the investigation is also to find out whether metadiscourse is used as a rhetorical strategy by instructors to control, evaluate and negotiate the impact of the ongoing talk, and eventually to signal their attitudes towards the content and the audience. Thus, the use of metadiscourse can contribute to the informative and persuasive impact of discourse, and to the effectiveness of online communication, especially in learning contexts.

Keywords: discourse analysis, metadiscourse, online EFL and ESP teaching, rhetoric

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Authors: Hocine Terrab , Abdelhafid Bayadi, Adel Kara, Ayman El-Hag

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Insulator flashover under polluted conditions has been a serious threat on the reliability of power systems. It is known that the flashover process is mainly affected by the environmental conditions such as; the pollution level and humidity. Those are the essential parameters influencing the wetting process. This paper presents an investigation of the characteristics of leakage current (LC) developed on the surface of porcelain insulator at contaminated conditions under AC voltage. The study is done in an artificial fog chamber and the LC is characterized for different stages; dry, wetted and presence of discharge activities. Time-frequency and spectral analysis are adopted to calculate the evolution of LC characteristics with various stages prior to flashover occurrence. The preliminary results could be used in analysing the LC to develop more effective diagnosis of early signs of dry band arcing as an indication for insulation washing.

Keywords: flashover, harmonic components, leakage current, phase angle, statistical analysis

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Authors: P. Sankar, P. James Daniel Paul, Siddhant Sahu

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A brief review of the empirical studies on the methodology of the stock market decision support would indicate that they are at a threshold of validating the accuracy of the traditional and the fuzzy, artificial neural network and the decision trees. Many researchers have been attempting to compare these models using various data sets worldwide. However, the research community is on the way to the conclusive confidence in the emerged models. This paper attempts to use the automotive sector stock prices from National Stock Exchange (NSE), India and analyze them for the intra-sectorial support for stock market decisions. The study identifies the significant variables and their lags which affect the price of the stocks using OLS analysis and decision tree classifiers.

Keywords: Indian automotive sector, stock market decisions, equity portfolio analysis, decision tree classifiers, statistical data analysis

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Authors: Shola Abidemi Olabode

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The technological revolution over the years has impacted journalistic practice. As a matter of fact, journalistic practice has evolved alongside technologies of every generation transforming news and reporting, entertainment, and politics. Alongside these developments, the emergence of new kinds of risks and harms associated with generative AI has become rife with implications for media and journalism. Despite their numerous benefits for research and development, generative AI technologies like ChatGPT introduce new practical, ethical, and regulatory complexities in the practice of media and journalism. This paper presents a preliminary overview of the new kinds of challenges and issues for journalism and media practice in the era of generative AI, the implications for Nigeria, and invites a consideration of methods to mitigate the evolving complexity. It draws mainly on desk-based research underscoring the literature in both developed and developing non-western contexts as a contribution to knowledge.

Keywords: AI, journalism, media, online harms

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Authors: Diane Ghanem, Oscar Covarrubias, Michael Raad, Dawn LaPorte, Babar Shafiq

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Introduction: Standardized exams have long been considered a cornerstone in measuring cognitive competency and academic achievement. Their fixed nature and predetermined scoring methods offer a consistent yardstick for gauging intellectual acumen across diverse demographics. Consequently, the performance of artificial intelligence (AI) in this context presents a rich, yet unexplored terrain for quantifying AI's understanding of complex cognitive tasks and simulating human-like problem-solving skills. Publicly available AI language models such as ChatGPT have demonstrated utility in text generation and even problem-solving when provided with clear instructions. Amidst this transformative shift, the aim of this study is to assess ChatGPT’s performance on the orthopaedic surgery in-training examination (OITE). Methods: All 213 OITE 2021 web-based questions were retrieved from the AAOS-ResStudy website. Two independent reviewers copied and pasted the questions and response options into ChatGPT Plus (version 4.0) and recorded the generated answers. All media-containing questions were flagged and carefully examined. Twelve OITE media-containing questions that relied purely on images (clinical pictures, radiographs, MRIs, CT scans) and could not be rationalized from the clinical presentation were excluded. Cohen’s Kappa coefficient was used to examine the agreement of ChatGPT-generated responses between reviewers. Descriptive statistics were used to summarize the performance (% correct) of ChatGPT Plus. The 2021 norm table was used to compare ChatGPT Plus’ performance on the OITE to national orthopaedic surgery residents in that same year. Results: A total of 201 were evaluated by ChatGPT Plus. Excellent agreement was observed between raters for the 201 ChatGPT-generated responses, with a Cohen’s Kappa coefficient of 0.947. 45.8% (92/201) were media-containing questions. ChatGPT had an average overall score of 61.2% (123/201). Its score was 64.2% (70/109) on non-media questions. When compared to the performance of all national orthopaedic surgery residents in 2021, ChatGPT Plus performed at the level of an average PGY3. Discussion: ChatGPT Plus is able to pass the OITE with a satisfactory overall score of 61.2%, ranking at the level of third-year orthopaedic surgery residents. More importantly, it provided logical reasoning and justifications that may help residents grasp evidence-based information and improve their understanding of OITE cases and general orthopaedic principles. With further improvements, AI language models, such as ChatGPT, may become valuable interactive learning tools in resident education, although further studies are still needed to examine their efficacy and impact on long-term learning and OITE/ABOS performance.

Keywords: artificial intelligence, ChatGPT, orthopaedic in-training examination, OITE, orthopedic surgery, standardized testing

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Authors: L. Ramirez, E. Guillén, J. Sánchez

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Some of the main goals about telecare such as monitoring, treatment, telediagnostic are deployed with the integration of applications with specific appliances. In order to achieve a coherent model to integrate software, hardware, and healthcare systems, different telehealth models with Internet of Things (IoT), cloud computing, artificial intelligence, etc. have been implemented, and their advantages are still under analysis. In this paper, we propose an integrated model based on IoT architecture and cloud computing telehealth center. Analytics module is presented as a solution to control an ideal diagnostic about some diseases. Specific features are then compared with the recently deployed conventional models in telemedicine. The main advantage of this model is the availability of controlling the security and privacy about patient information and the optimization on processing and acquiring clinical parameters according to technical characteristics.

Keywords: analytics, telemedicine, internet of things, cloud computing

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Authors: Y. Kourd, D. Lefebvre, N. Guersi

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This paper presents a new idea for fault detection and isolation (FDI) technique which is applied to industrial system. This technique is based on Neural Networks fault-free and Faulty behaviors Models (NNFM's). NNFM's are used for residual generation, while decision tree architecture is used for residual evaluation. The decision tree is realized with data collected from the NNFM’s outputs and is used to isolate detectable faults depending on computed threshold. Each part of the tree corresponds to specific residual. With the decision tree, it becomes possible to take the appropriate decision regarding the actual process behavior by evaluating few numbers of residuals. In comparison to usual systematic evaluation of all residuals, the proposed technique requires less computational effort and can be used for on line diagnosis. An application example is presented to illustrate and confirm the effectiveness and the accuracy of the proposed approach.

Keywords: neural networks, decision trees, diagnosis, behaviors

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Authors: Jun-Yong Lee, Hyoung-Gook Kim

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In this paper, we propose a smart music player that combines the musical genre classification and the spatial audio processing. The musical genre is classified based on content analysis of the musical segment detected from the audio stream. In parallel with the classification, the spatial audio quality is achieved by adding an artificial reverberation in a virtual acoustic space to the input mono sound. Thereafter, the spatial sound is boosted with the given frequency gains based on the musical genre when played back. Experiments measured the accuracy of detecting the musical segment from the audio stream and its musical genre classification. A listening test was performed based on the virtual acoustic space based spatial audio processing.

Keywords: automatic equalization, genre classification, music segment detection, spatial audio processing

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Authors: Meruyert Serik, Nassipzhan Duisegaliyeva, Danara Tleumagambetova, Madina Ermaganbetova

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This research paper explores the process of creating a proctoring system by evaluating the implementation of practical face recognition algorithms. Students of educational programs reviewed the research work "6B01511-Computer Science", "7M01511-Computer Science", "7M01525- STEM Education," and "8D01511-Computer Science" of Eurasian National University named after L.N. Gumilyov. As an outcome, a proctoring system will be created, enabling the conduction of tests and ensuring academic integrity checks within the system. Due to the correct operation of the system, test works are carried out. The result of the creation of the proctoring system will be the basis for the automation of the informational, educational portal developed by machine learning.

Keywords: artificial intelligence, education portal, face recognition, machine learning, proctoring

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Authors: Harry B. Santoso, Lia Sadita, Firlia Sandyta, Musa Alfatih, Nove Spalo, Nu'man Naufal, Nuryahya P. Utomo, Putu A. Paramatha, Rezka Aufar Leonandya, Tommy Anugrah, Aulia Chairunisa, M. Fadly Uzzaki, Riandy D. Banimahendra

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The numbers of Internet active users in Indonesia reach out over 88.1 million, where 48% of them are daily active users. Seeing these numbers, it is the best opportunity for IT companies to grow their business, especially e-Commerce. In fact, the growth of e-Commerce companies in Indonesia is proportional with internet daily active users. This phenomenon shows that competition happening among the e-Commerce companies is raising high. It triggers many e-Commerce companies to improve their services. The authors hypothesized that one of the best ways to improve the services is by improving their usability. So, the authors had done a study to evaluate and find out ways to improve usability of those e-Commerce websites. The authors chose four e-Commerce websites which each of them has different business focus and profiles. Each company is labeled as A, B, C, and D. Company A is a fashion-based e-Commerce services with two-million desktop visits Indonesia. Company B is an international online shopping mall for everyday appliances with 48,3-million desktop visits in Indonesia. Company C is a localized online shopping mall with 3,2-million desktop visits in Indonesia. Company D is an online shopping mall with one-million desktop visits in Indonesia. Writers used popular web traffic analytics platform to gain the numbers. There are some approaches to evaluate the usability of e-Commerce websites. In this study, the authors used usability testing method supported by the User Experience Questionnaire. This method involved the user in interacting directly with the services provided by the e-Commerce company. This study was conducted within two months including preparation, data collection, data analysis, and reporting. We used a pair of computers, a screen-capture video application named Smartboard, and User Experience Questionnaire. A team was built to conduct this study. They consisted of one supervisor, two assistants, four facilitators and four observers. For each e-Commerce, three users aged 17-25 years old were invited to do five task scenarios. Data collected in this study included demographic information of the users, usability testing results, and users’ responses to the questionnaire. Some findings were revealed from the usability testing and the questionnaire. Compared to the other three companies, Company D had the least score for the experiences. One of the most painful issues figured out by the authors from the evaluation was most users claimed feeling confused by user interfaces in these e-Commerce websites. We believe that this study will help e-Commerce companies to improve their services and business in the future.

Keywords: e-commerce, evaluation, usability testing, user experience

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Authors: Afshin Jahangirzadeh, Shatirah Akib, Keyvan Kimiaei, Hossein Basser

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Coastal defense structures were built to protect part of shore from beach erosion and flooding by sea water. Effects of coastal defense structures can be negative or positive. Some of the effects are beneficial in socioeconomic aspect, but environment matters should be given more concerns because it can bring bad consequences to the earth landscape and make the ecosystem be unbalanced. This study concerns on the negative impacts as they are dominant. Coastal structures can extremely impact the shoreline configuration. Artificial structures can influence sediment transport, split the coastal space, etc. This can result in habitats loss and lead to noise and visual disturbance of birds. There are two types of coastal defense structures, hard coastal structure and soft coastal structure. Both coastal structures have their own impacts. The impacts are induced during the construction, maintaining, and operation of the structures.

Keywords: ecosystem, environmental impact, hard coastal structures, soft coastal structures

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Authors: Varun Goel

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Solar energy is a good option among renewable energy resources due to its easy availability and abundance. The simplest and most efficient way to utilize solar energy is to convert it into thermal energy and this can be done with the help of solar collectors. The thermal performance of such collectors is poor due to less heat transfer from the collector surface to air. In this work, experimental investigations of single pass solar air heater having triangular duct and provided with roughness element on the underside of the absorber plate. V-shaped ribs are used for investigation having three different values of relative roughness pitch (p/e) ranges from 4-16 for a fixed value of angle of attack (α), relative roughness height (e/Dh) and a relative gap distance (d/x) values are 60°, 0.044 and 0.60 respectively. Result shows that considerable augmentation in heat transfer has been obtained by providing roughness.

Keywords: artificial roughness, solar air heater, triangular duct, V-shaped ribs

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Authors: Mohammad Abdullah-Al-Wadud

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In the current era of automation and artificial intelligence, different systems have been increasingly keeping on depending on decision-making capabilities of machines. Such systems/applications may range from simple classifiers to sophisticated surveillance systems based on traditional sensors and related equipment which are becoming more common in the internet of things (IoT) paradigm. However, the available data for such problems are usually imprecise and incomplete, which leads to uncertainty in decisions made based on traditional probability-based classifiers. This requires a robust fusion framework to combine the available information sources with some degree of certainty. The theory of evidence can provide with such a method for combining evidence from different (may be unreliable) sources/observers. This talk will address the employment of the Dempster-Shafer Theory of evidence in some practical applications.

Keywords: decision making, dempster-shafer theory, evidence fusion, incomplete data, uncertainty

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Authors: Pham Van Nha, Le Cam Binh

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Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO’s ideas are simple and easy to understand but PSO is only applied in simple model problems. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOs general mathematical model (MPSO) is analyzed as a universal optimization model. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes.

Keywords: analysis of optimization, artificial intelligence based optimization, optimization for learning and data analysis, global optimization

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Authors: Nguyen The Hoang Anh, Tran Huy Hoang, Vu Tat Thang, T. T. Quyen Bui

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Mental state classification is an important step for realizing a control system based on electroencephalography (EEG) signals which could benefit a lot of paralyzed people including the locked-in or Amyotrophic Lateral Sclerosis. Considering that EEG signals are nonstationary and often contaminated by various types of artifacts, classifying thoughts into correct mental states is not a trivial problem. In this work, our contribution is that we present and realize a novel model which integrates different techniques: Independent component analysis (ICA), relative wavelet energy, and support vector machine (SVM) for the same task. We applied our model to classify thoughts in two types of experiment whether with two or three mental states. The experimental results show that the presented model outperforms other models using Artificial Neural Network, K-Nearest Neighbors, etc.

Keywords: EEG, ICA, SVM, wavelet

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Authors: Chen Xi, Lao Xuerui, Li Junjie, Jiang Yike, Wang Hanwei, Zeng Zihao

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To further promote the development of smart cities, the microscopic "nerve endings" of the City Intelligent Model (CIM) are extended to be more sensitive. In this paper, we develop a pedestrian trajectory twin terminal based on the CIM and CNN technology. It also uses 5G networks, architectural and geoinformatics technologies, convolutional neural networks, combined with deep learning networks for human behaviour recognition models, to provide empirical data such as 'pedestrian flow data and human behavioural characteristics data', and ultimately form spatial performance evaluation criteria and spatial performance warning systems, to make the empirical data accurate and intelligent for prediction and decision making.

Keywords: urban planning, urban governance, CIM, artificial intelligence, convolutional neural network

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Authors: Jamison Duckworth, Shankarachary Ragi

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Detection and segmentation of wildfire smoke plumes from remote sensing imagery are being pursued as a solution for early fire detection and response. Smoke plume detection can be automated and made robust by the application of artificial intelligence methods. Specifically, in this study, the deep learning approach Mask Region-based Convolutional Neural Network (RCNN) is being proposed to learn smoke patterns across different spectral bands. This method is proposed to separate the smoke regions from the background and return masks placed over the smoke plumes. Multispectral data was acquired using NASA’s Earthdata and WorldView and services and satellite imagery. Due to the use of multispectral bands along with the three visual bands, we show that Mask R-CNN can be applied to distinguish smoke plumes from clouds and other landscape features that resemble smoke.

Keywords: deep learning, mask-RCNN, smoke plumes, spectral bands

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Authors: Linette van der Merwe

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It is known that visual artists, performing artists, and literary artists have inspired each other since time immemorial. The enduring, symbiotic relationship between the various art genres is evident where words, colours, lines, and sounds act as metaphors, a physical separation of the transcendental reality of art. Simonides of Keos (c. 556-468 BC) confirmed this, stating that a poem is a talking picture, or, in a more modern expression, a picture is worth a thousand words. It can be seen as an ancient relationship, originating from the epigram (tombstone or artefact inscriptions), the carmen figuratum (figure poem), and the ekphrasis (a description in the form of a poem of a work of art). Visual artists, including Michelangelo, Leonardo da Vinci, and Goethe, wrote poems and songs. Goya, Degas, and Picasso are famous for their works of art and for trying their hands at poetry. Afrikaans writers whose fine art is often published together with their writing, as in the case of Andries Bezuidenhout, Breyten Breytenbach, Sheila Cussons, Hennie Meyer, Carina Stander, and Johan van Wyk, among others, are not a strange phenomenon either. Imitating one art form into another art form is a form of translation, transposition, contemplation, and discovery of artistic impressions, showing parallel interpretations rather than physical comparison. It is especially about the harmony that exists between the different art genres, i.e., a poem that describes a painting or a visual text that portrays a poem that becomes a translation, interpretation, and rediscovery of the verbal text, or rather, from the word text to the image text. Poetry-film, as a form of such a translation of the word text into an image text, can be considered a hybrid, transdisciplinary art form that connects poetry and film. Poetry-film is regarded as an intertwined entity of word, sound, and visual image. It is an attempt to transpose and transform a poem into a new artwork that makes the poem more accessible to people who are not necessarily open to the written word and will, in effect, attract a larger audience to a genre that usually has a limited market. Poetry-film is considered a creative expression of an inverted ekphrastic inspiration, a visual description, interpretation, and expression of a poem. Research also emphasises that animated poetry-film is not widely regarded as a genre of anything and is thus severely under-theorized. This paper will focus on Afrikaans animated poetry-films as a multimodal transposition of a poem text to an animated poetry film, with specific reference to animated poetry-films in Filmverse I (2014) and Filmverse II (2016).

Keywords: poetry film, animated poetry film, poetic metaphor, conceptual metaphor, monomodal metaphor, multimodal metaphor, semiotic metaphor, multimodality, metaphor analysis, target domain, source domain

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Authors: Tatiana A. Dolenko, Sergey A. Burikov, Alexander O. Efitorov, Sergey A. Dolenko

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In this study, a comparative analysis of the approaches associated with the use of neural network algorithms for effective solution of a complex inverse problem – the problem of identifying and determining the individual concentrations of inorganic salts in multicomponent aqueous solutions by the spectra of Raman scattering of light – is performed. It is shown that application of artificial neural networks provides the average accuracy of determination of concentration of each salt no worse than 0.025 M. The results of comparative analysis of input data compression methods are presented. It is demonstrated that use of uniform aggregation of input features allows decreasing the error of determination of individual concentrations of components by 16-18% on the average.

Keywords: inverse problems, multi-component solutions, neural networks, Raman spectroscopy

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Authors: Rauno Pääkkönen, Fabriziomaria Gobba, Leena Korpinen

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The objective of the study is to assess the implementation of LED lighting into forest machine work in the dark. In addition, the paper includes a wide variety of important and relevant safety and health parameters. In modern, computerized work in the cab of forest machines, artificial illumination is a demanding task when performing duties, such as the visual inspections of wood and computer calculations. We interviewed entrepreneurs and gathered the following as the most pertinent themes: (1) safety, (2) practical problems, and (3) work with LED lighting. The most important comments were in regards to the practical problems of LED lighting. We found indications of technical problems in implementing LED lighting, like snow and dirt on the surfaces of lamps that dim the emission of light. Moreover, service work in the dark forest is dangerous and increases the risks of on-site accidents. We also concluded that the amount of blue light to the eyes should be assessed, especially, when the drivers are working in a semi-dark cab.

Keywords: forest machines, health, LED, safety

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Authors: Ayanda P. Deliwe, Storm B. Watson

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The COVID-19 pandemic has disrupted the established practices of higher education institutions (HEIs). Most higher education institutions worldwide had to shift from traditional face-to-face to online learning. The online environment and new online tools are disrupting the way in which higher education is presented. Furthermore, the structures of higher education institutions have been impacted by rapid advancements in information and communication technologies. Emerging technologies should not be viewed in a negative light because, as opposed to the traditional curriculum that worked to create productive and efficient researchers, emerging technologies encourage creativity and innovation. Therefore, using technology together with traditional means will enhance teaching and learning. Emerging technologies in higher education not only change the experience of students, lecturers, and the content, but it is also influencing the attraction and retention of students. Higher education institutions are under immense pressure because not only are they competing locally and nationally, but emerging technologies also expand the competition internationally. Emerging technologies have eliminated border barriers, allowing students to study in the country of their choice regardless of where they are in the world. Higher education institutions are becoming indifferent as technology is finding its way into the lecture room day by day. Academics need to utilise technology at their disposal if they want to get through to their students. Academics are now competing for students' attention with social media platforms such as WhatsApp, Snapchat, Instagram, Facebook, TikTok, and others. This is posing a significant challenge to higher education institutions. It is, therefore, critical to pay attention to emerging technologies in order to see how they can be incorporated into the classroom in order to improve educational quality while remaining relevant in the work industry. This study aims to understand how emerging technologies have been utilised at Nelson Mandela University in presenting teaching and learning activities since April 2020. The primary objective of this study is to analyse how academics are incorporating emerging technologies in their teaching and learning activities. This primary objective was achieved by conducting a literature review on clarifying and conceptualising the emerging technologies being utilised by higher education institutions, reviewing and analysing the use of emerging technologies, and will further be investigated through an empirical analysis of the use of emerging technologies at Nelson Mandela University. Findings from the literature review revealed that emerging technology is impacting several key areas in higher education institutions, such as the attraction and retention of students, enhancement of teaching and learning, increase in global competition, elimination of border barriers, and highlighting the digital divide. The literature review further identified that learning management systems, open educational resources, learning analytics, and artificial intelligence are the most prevalent emerging technologies being used in higher education institutions. The identified emerging technologies will be further analysed through an empirical analysis to identify how they are being utilised at Nelson Mandela University.

Keywords: artificial intelligence, emerging technologies, learning analytics, learner management systems, open educational resources

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Authors: Jekaterina Novikova, Leon Watts

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In the emerging world of human-robot interaction, people and robots will interact socially in real-world situations. This paper presents the results of an experimental study probing the interaction between situational context and emotional body language in robots. 34 people rated video clips of robots performing expressive behaviours in different situational contexts both for emotional expressivity on Valence-Arousal-Dominance dimensions and by selecting a specific emotional term from a list of suggestions. Results showed that a contextual information enhanced a recognition of emotional body language of a robot, although it did not override emotional signals provided by robot expressions. Results are discussed in terms of design guidelines on how an emotional body language of a robot can be used by roboticists developing social robots.

Keywords: social robotics, non-verbal communication, situational context, artificial emotions, body language

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Authors: Sezer Kefeli, Sertaç Arslan

Abstract:

Supercavitation is a pressure dependent process which gives opportunity to eliminate the wetted surface effects on the underwater vehicle due to the differences of viscosity and velocity effects between liquid (freestream) and gas phase. Cavitation process occurs depending on rapid pressure drop or temperature rising in liquid phase. In this paper, pressure based cavitation is investigated due to the fact that is encountered in the underwater world, generally. Basically, this vapor-filled pressure based cavities are unstable and harmful for any underwater vehicle because these cavities (bubbles or voids) lead to intense shock waves while collapsing. On the other hand, supercavitation is a desired and stabilized phenomena than general pressure based cavitation. Supercavitation phenomena offers the idea of minimizing form drag, and thus supercavitating vehicles are revived. When proper circumstances are set up, which are either increasing the operating speed of the underwater vehicle or decreasing the pressure difference between free stream and artificial pressure, the continuity of the supercavitation is obtainable. There are 2 types of supercavitation to obtain stable and continuous supercavitation, and these are called as natural and artificial supercavitation. In order to generate natural supercavitation, various mechanical structures are discovered, which are called as cavitators. In literature, a lot of cavitator types are studied either experimentally or numerically on a CFD platforms with intent to observe natural supercavitation since the 1900s. In this paper, firstly, experimental results are obtained, and trend lines are generated based on supercavitation parameters in terms of cavitation number (), form drag coefficientC_D, dimensionless cavity diameter (d_m/d_c), and length (L_c/d_c). After that, natural cavitation verification studies are carried out for disk and cone shape cavitators. In addition, supercavitation parameters are numerically analyzed at different operating conditions, and CFD results are fitted into trend lines of experimental results. The aims of this paper are to generate one generally accepted drag coefficient equation for disk and cone cavitators at different cavitator half angle and investigation of the supercavitation parameters with respect to cavitation number. Moreover, 165 CFD analysis are performed at different cavitation numbers on FLUENT version 21R2. Five different cavitator types are modeled on SCDM with respect tocavitator’s half angles. After that, CFD database is generated depending on numerical results, and new trend lines are generated based on supercavitation parameters. These trend lines are compared with experimental results. Finally, the generally accepted drag coefficient equation and equations of supercavitation parameters are generated.

Keywords: cavity envelope, CFD, high speed underwater vehicles, supercavitation, supercavitating flows, supercavitation parameters, drag reduction, viscous force elimination, natural cavitation verification

Procedia PDF Downloads 118

Authors: Huy Q. Tran, Bac V. Nguyen, Choonghyun Kang, Jungwon Huh

Abstract:

Jumbo container crane is an important part of port structures that needs to be designed properly, even when the port locates in low seismicity zone such as in Korea. In this paper, 30 artificial ground motions derived from the elastic response spectra of Korean Building Code (2005) are used for time history analysis. It is found that the uplift might not occur in this analysis when the crane locates in the low seismic zone. Therefore, a selection of a pinned or a gap element for base supporting has not much effect on the determination of the total base shear. The relationships between the total base shear and peak ground acceleration (PGA) and the relationships between the portal drift and the PGA are proposed in this study.

Keywords: jumbo container crane, portal drift, time history analysis, total base shear

Procedia PDF Downloads 173

Authors: Noura Al-Ajmi, Mohammed A. Almulla

Abstract:

With the increased utilization of technology devices around the world, healthcare and medical diagnosis are critical issues that people worry about these days. Doctors are doing their best to avoid any medical errors while diagnosing diseases and prescribing the wrong medication. Subsequently, artificial intelligence applications that can be installed on mobile devices such as rule-based expert systems facilitate the task of assisting doctors in several ways. Due to their many advantages, the usage of expert systems has increased recently in health sciences. This work presents a backward rule-based expert system that can be used for a headache diagnosis and medication recommendation system. The structure of the system consists of three main modules, namely the input unit, the processing unit, and the output unit.

Keywords: headache diagnosis system, prescription recommender system, expert system, backward rule-based system

Procedia PDF Downloads 188

Authors: Saad Al-Baddai, Karema Al-Subari, Elmar Lang, Bernd Ludwig

Abstract:

Empirical mode decomposition (EMD), a new data-driven of time-series decomposition, has the advantage of supposing that a time series is non-linear or non-stationary, as is implicitly achieved in Fourier decomposition. However, the EMD suffers of mode mixing problem in some cases. The aim of this paper is to present a solution for a common type of signals causing of EMD mode mixing problem, in case a signal suffers of an intermittency. By an artificial example, the solution shows superior performance in terms of cope EMD mode mixing problem comparing with the conventional EMD and Ensemble Empirical Mode decomposition (EEMD). Furthermore, the over-sifting problem is also completely avoided; and computation load is reduced roughly six times compared with EEMD, an ensemble number of 50.

Keywords: empirical mode decomposition (EMD), mode mixing, sifting process, over-sifting

Procedia PDF Downloads 375