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Analysis of the Audiovisual Elements of the Episode "Face off" of the Series Breaking Bad, Season 4 9th

Analysis of the Audiovisual Elements of the Episode "Face of...

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9th International Congress on Information and Communication Technology (ICICT)

作者： Albarran, Aldo Manuel Seijas Reategui, Gabriel Alonso Sanchez Gayoso, Norma Ines Caldas Turriate-Guzman, Adriana Margarita Univ Privada Norte Lima Peru

ISBN: (纸本)9789819750344;9789819750351

The research work carried out answers the following question, how are the elements of audiovisual language presented in the scenes of the episode "Face Off" of the series Breaking Bad, season 4 (2022)? The objective is to analyze the audiovisual language of the series "Breaking Bad", the thirteenth episode "Face to Face" of the fourth season, created by Vince Gilligan in 2008. The methodology applied in this research is qualitative, with a phenomenological approach, making use of the method of content analysis and observation sheets to process the data, which resulted in the greater use of open shots and joint shots in almost half of the 63 scenes, where normal angles and the still camera predominate. In addition, the greatest use is made of artificial lights, intangible lights, side, filler and base lights. On the other hand, the images are saturated and with a nuance that leans toward warm, using interior and exterior scenery, both natural and artificial. On the other hand, the use of garments surpasses the use of makeup, performances by non-professional stars, actors and performers. In terms of sound, the use of voices is quite noticeable, while asynchronous, synchronous, spatial and studio sounds appear to a lesser extent. In conclusion, the Breaking Bad series makes correct use of image and sound, generating harmony and dynamism in them.

关键词： Audiovisual language Image Sound Breaking Bad

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Toward a Realistic Comparative Analysis of Recurrent Neural Network's Methods via Long-Term Memory Approaches 9th

Toward a Realistic Comparative Analysis of Recurrent Neural ...

引用

9th International Congress on Information and Communication Technology (ICICT)

作者： Nawej, Claude Mukatshung Owolawi, Pius Adewale Walingo, Tom Tshwane Univ Technol Dept Comp Syst Engn Pretoria South Africa Univ KwaZulu Natal Dept Elect Elect & Comp Engn Durban South Africa

ISBN: (纸本)9789819750344;9789819750351

Cellular networks face challenges in terms of real-time traffic forecasting;however, recurrent neural networks (RNNs) can be used for this effect. An RNN that has been trained rightfully may model any dynamic system;yet, learning longstanding dependencies remains the main challenge with RNN training. In this article, we present a comparative analysis of deep learning forecasting methods with focus on the two-protagonist RNN version, long short-term memory (LSTM), and gated recurrent units (GRU). We construct neural network patterns for GRU and LSTM, assess how well each model predicts the future quality of service (QoS), discuss, and compare them. These models were trained using a cellular network dataset. Based on the scenario and relevant experimental metrics results, loss, processing time, and number of parameters, there isn't a single top-notch RNN model suitable for all tasks and types of data.

关键词： 5G GRU LSTM RNN Prediction

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Artificial Intelligence in UX/UI Design: A Research Framework for Exploring the Impact of Artificial Intelligence Tools on Design Quality 9th

Artificial Intelligence in UX/UI Design: A Research Framewor...

引用

9th International Congress on Information and Communication Technology (ICICT)

作者： Schoenberger, Marius Univ Appl Sci Kaiserslautern Zweibrucken Germany

ISBN: (纸本)9789819750344;9789819750351

The integration of Artificial Intelligence (AI) tools into the User Experience/User Interface (UX/UI) design process poses challenges and opportunities. While AI can enhance efficiency and innovation, it raises questions about the changing role of designers and the potential risks associated with reduced human control. The rapid growth of AI technology in UX/UI design requires a comprehensive understanding of how AI can effectively complement human creativity and intuition, ensuring high-quality design outcomes while addressing concerns about job displacement and autonomy. This study develops a research framework that explores the interplay between AI applications and human skills in the context of modern UX/UI design. The framework aims to examine the impact of AI on design quality and how various factors moderate this influence. The hypotheses suggest that AI applications and user skills have a positive effect on design quality, but their impact is moderated by factors such as design complexity, user expectations, and collaboration. The research methodology combines literature review, data collection through surveys, data analysis, and expert evaluation to test these hypotheses rigorously. This research provides a foundation for further exploration of AI's role in UI/UX design, offering opportunities for examining its impact in diverse organizational contexts, user groups, and long-term UX effects. Ultimately, the study aims to enhance UI/UX design practices through informed AI integration.

关键词： Artificial Intelligence UX/UI design Design quality

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The GILL Platform: A Pan-European, Virtual, Learning, Sustainable and Collaborative Hub Built on the Living Lab Principles 21st

The GILL Platform: A Pan-European, Virtual, Learning, Sustai...

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21st International Symposium on Distributed Computing and Artificial Intelligence

作者： Plaza-Hernandez, Marta Liotopoulos, Fotis K. Tello-Alvarado, Carlos Mesonero-Ronco, Enrique Merchan-Benito, Javier Benito-Manzanas, Diego Rodrigo-Marcos, Mario Montero-Fernandez, Alberto Sanchez-Sanchez, David Rosa-Gonzalez, Alvaro Villoria-Torres, Carolina Prieto-Tejedor, Javier Univ Salamanca BISITE Res Grp Edificio Multiusos I D ICalle Espejo 2 Salamanca 37007 Spain SBOING K Karamanli 124 Thessaloniki 57008 Greece

ISBN: (纸本)9783031809453;9783031809460

The Gendered Innovation Living Labs (GILL) project consortium is developing a new IT platform that will be iteratively developed through a series of co-creation approaches to meet the needs of all gender innovation stakeholders. The platform will provide access to training, case studies, tools and methods, supporting gender-responsive innovation related to European challenges. It will facilitate collaborative work, knowledge sharing and creation between scientists, formal organisations and citizens engaged in open innovation cycles or gender innovation careers. Ultimately, it strives to become a sustainable open innovation resource driving cultural and systemic change through inclusive practices. Once the platform is populated, itwill integrate advanced digital technologies to support and enable GILL to reach an interested community of organisations, projects, and individuals across Europe.

关键词： IT platform Living Labs learning hub collaborative hub cloud

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Chatbots in Paradigm Shifting for Improving Gig Workers' Labor Conditions 9th

Chatbots in Paradigm Shifting for Improving Gig Workers' Lab...

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9th International Congress on Information and Communication Technology (ICICT)

作者： Arruda, Monique de Souza Catholic Univ Portugal Porto Fac Law Rua Diogo Botelho 1327 P-4169005 Porto Portugal

ISBN: (纸本)9789819750344;9789819750351

In the field of gig work and digital platforms, this article aims to investigate the improvement of workers' working conditions through the strategic implementation of chatbots. Using the resources of artificial intelligence, the study explores how chatbots could work in favor of platform workers, in the opposite direction to the current application of algorithmic management and its tools, such as recommendation algorithms, used for the unilateral purpose of potential increased profit by platforms. After problematizing the gaps that are harmful to platform workers when interacting with them in their daily work routine, an empirical typology of chatbots adjustable to the presupposed needs is suggested. These AI-driven chatbots, functioning as virtual advisors, not only tailor recommendations based on individual skills and preferences but also serve as immediate channels for answering queries. The expected results highlight a potential transformative impact on worker satisfaction, task efficiency and general well-being, portraying the integration of chatbot technology as a promising path to promoting a more humane and supportive work environment.

关键词： Conversational interface to gig workers Digital labor platforms Labor chatbot

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Effects of Strong Attribute Cooccurrence Influence Distance on Simple Linear Iterative Clustering Superpixel 9th

Effects of Strong Attribute Cooccurrence Influence Distance ...

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9th International Congress on Information and Communication Technology (ICICT)

作者： Moodley, Sadhasivan G. Olugbara, Oludayo O. Adeliyi, Timothy T. Durban Univ Technol MICTSETA 4IR Ctr Excellence Durban South Africa Univ Pretoria Dept Informat Pretoria South Africa

ISBN: (纸本)9789819750344;9789819750351

Digital image segmentation is a well-researched hard problem of highlighting each object in an image with a different shade. It increasingly relies on a superpixel approach to circumvent the computational sumptuousness inherent in a high number of image pixels. Superpixel clusters similar pixels in primitive features such as colors into semantically related groups of fewer pixels to accelerate computation. However, most of the existing superpixel methods rely heavily on Euclidean distance to measure color similarity between two image pixels. Unfortunately, Euclidean distance assumes that data samples are distributed about the mean in a spherical fashion and may not compactly measure color similarity to comply with human perception of object similarity. This study was aimed at experimentally comparing Euclidean distance with strong attribute concurrence influence distance (SAID) in simple linear iterative clustering (SLIC) superpixel segmentation algorithm to determine the effects of distance measures on the performance of SLIC. In addition, the density-based spatial clustering of applications with noise (DBSCAN) was used as a control superpixel algorithm to comprehend the efficiency, ability to adhere to image boundaries, and effects of distance measures on SLIC performance. Experimental results showed that DBSCAN achieved better results in terms of under-segmentation error for regular compactness in complex, multiple, and overlapping images. However, SLIC with SAID distance achieved better results in terms of achievable segmentation accuracy, and superpixel compactness for complex images. Moreover, SLIC superpixel algorithm achieved better results with Euclidean distance for normal images with less complex backgrounds when compared with SLIC with SAID distance and DBSCAN superpixel algorithm.

关键词： Distance metric Image segmentation Perceptual similarity Segmentation performance Superpixel clustering Superpixel compactness

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GaitSeries: Gait Recognition Using Unsynchronized Multi-variate Time Series 9th

GaitSeries: Gait Recognition Using Unsynchronized Multi-vari...

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9th International Congress on Information and Communication Technology (ICICT)

作者： Wang, Hongzhen Mahmoodi, Sasan Univ Southampton Southampton SO17 1BJ Hants England

ISBN: (纸本)9789819750344;9789819750351

The currently existing gait recognition methods mainly focus on detecting walking patterns based on synchronized data, especially the appearance-based methods using GEIs as original inputs. These methods need large amount of work to deal with data preprocessing to generate a fine-grained gait cycle for each subject, which is an obstacle to use gait recognition widely in real-word applications. To solve this problem, we propose a model-based gait recognition method that is able to generate gait representations from unsynchronized data and consider the dependencies between joints simultaneously. Firstly, we utilize simple joint-wise autoencoder groups to reconstruct unsynchronized joint sequences generated by pose estimation, where multi-scale time patches are employed to capture time-series patterns by capturing information from variable length windows. Then, to calculate the inter-joint dependencies, a feature fusion structure based on self-attention mechanism is used to generate final gait representations considering all joints' moving patterns. This pipeline gives out temporal-spatial gait representations from unsynchronized data. Experimental results demonstrate that the performance can be comparable to the state-of-the-art synchronized pose-based gait recognition methods. Moreover, extensive ablation studies also explain the effectiveness of the proposed method's structure design.

关键词： Biometrics Gait recognition Time series

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A Model of a Smart Waste Management System to Achieve Sustainable Development Goals in Saudi Arabia Supporting Industry 4.0 9th

A Model of a Smart Waste Management System to Achieve Sustai...

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9th International Congress on Information and Communication Technology (ICICT)

作者： Alwadei, Hajer Almukadi, Wafa Hachicha, Hala Univ Jeddah Dept Comp Sci Coll Comp Sci & Engn Jeddah Saudi Arabia Univ Jeddah Dept Software Engn Coll Comp Sci & Engn Jeddah Saudi Arabia

ISBN: (纸本)9789819754403;9789819754410

Waste management has been given high priority in the Kingdom of Saudi Arabia, with the government implementing comprehensive strategies to reduce, recycle, and properly dispose of waste. The smart waste management system is crucial for addressing waste challenges. This paper suggests a sustainable smart management system model based on the principles of the circular economy. It incorporates Industry 4.0 technologies to achieve sustainable development goals. Our smart waste management model is based on machine learning algorithms and the Internet of Things. The proposed system includes a smart waste system equipped with sensors that record data in a database. Once the data are verified, an order for garbage collection is generated, and the completion of the process is confirmed. Additionally, a text messaging system is used to communicate with drivers. The model offers a new solution for sustainable smart waste management that benefits citizens, municipal workers, private organizations, local municipalities, and authorities.

关键词： Smart waste management Industry 4.0 Sensor Internet of Things Machine learning

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Decision System in a Building to Coordinate the Energy Forecasting Tasks 21st

Decision System in a Building to Coordinate the Energy Forec...

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21st International Symposium on Distributed Computing and Artificial Intelligence

作者： Ramos, Daniel Faria, Pedro Vale, Zita Polytech Porto LASI Intelligent Syst Associate Lab GECAD Res Grp Intelligent Engn & Comp Adv Innovat Porto Portugal

ISBN: (纸本)9783031820724;9783031820731

Nowadays, energy buildings have a huge impact in society regarding the active role in the management of energy consumption. Hence, building owners are required to avoid energy losses and improve energy efficiency as high as possible. Therefore, it is required to plan an optimization strategy to buy and sell energy in the market ahead of time. To formulate this optimization plan, building owners require the work of specialists responsible for processing, training, forecasting, and evaluation tasks regarding the prediction of energy consumption data from a building for a specific target of time. Therefore, a multiagent-system is needed to allow the cooperation of various agents including the building owner, forecast provider, data structurer and error analysis. Moreover, forecasting algorithms such as artificial neural networks should be taken into consideration in order to process large quantities of energy consumption data during the training and forecasting phases.

关键词： agents artificial neural networks building owner energy building

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Deep Learning-Based Diagnosis of Leukemia in Africa: Case of Acute Lymphoblastic and Acute Myeloid Leukemia in Senegal 9th

Deep Learning-Based Diagnosis of Leukemia in Africa: Case of...

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9th International Congress on Information and Communication Technology (ICICT)

作者： Diagne, Therese Daba Siga Ba, Mandicou Sall, Abibatou Toure, Fadel Fall, Ibrahima Diagne, Khadija Diouf, Assane Sene, Ibrahima Ngom, Charles Abdoulaye Diop, Idy Bah, Alassane Cheikh Anta Diop Univ Dakar UCAD Res Inst Dev IRD Unit Math Modeling & Comp Sci Complex Syst UMMISC Polytech Higher Sch ESP Dakar Senegal Univ Quebec Trois Rivieres Dept Math & Comp Sci Trois Rivieres PQ Canada Dalal Jamm Natl Hosp Ctr Hematol Dept Dakar Senegal

ISBN: (纸本)9789819754403;9789819754410

Early and accurate diagnosis of leukemia in Africa, particularly for children, remains a major public health challenge. In the current paper, we propose an application of deep learning (DL) and computer vision approaches in order to improve the diagnosis of acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML). We rely on two models, namely ViT and YOLOv8, that have been trained, evaluated on public open dataset (C-NMC dataset [1]) and designed for identifying acute lymphoblastic leukemia cell from microscopic images of immature blood cells. The results of this experimental evaluation reveal that YOLOv8 gives better performance in the context of limited data and resources. We then selected YOLOv8 pre-trained models and adopted a transfer learning approach on augmented data we collected from the Senegalese context of the Dalal Jamm Hospital. The results obtained present a precision of 96.6%, a recall of 92.9%, and an mAP50 of 98.6%. These encouraging performances demonstrate the ability of YOLOv8 to accurately identify ALL and AML cells.

关键词： Deep learning Computer vision Cancer blood cells Lymphoblasts Myeloblasts ViT YOLOv8 Data augmentation Transfer learning

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