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Analysis and Forecasting of Russell 2000 Stock Price Dynamics 13th

Analysis and Forecasting of Russell 2000 Stock Price Dynamic...

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13th Computer Science Online Conference

作者： Dzerjinsky, Roman Anosov, Timur Daeva, Sofia MIREA Russian Technol Univ Appl Math Dept 78 Vernadsky Pros Moscow 119454 Russia

ISBN: (纸本)9783031705175;9783031705182

The paper presents the results of the study of hidden periodicities in the dynamics of the Russell 2000 index stock using anamorphosis for Gompertz models. Boundaries of ranges of automodel growth are interconnected with local minima of functions and together with them determine the spectral composition of time series of world prices on the index fund "Russell 2000". It is shown that at the moment the price is between critical levels, when the next critical level is reached, the price of the index fund will go down to break through the value of the critical level in the future, continuing growth #CSOC1120.

关键词： Time Series Trend Exclusion Anamorphosis Near-Period

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Buildings and Vehicles Discrimination in Drone Images 1

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11st World Conference on Information systems and Technologies (WorldCIST)

作者： Neves, Antonio J. R. Amante, Rita Canedo, Daniel Silva, Jose Silvestre Univ Aveiro DETI Aveiro Portugal Univ Aveiro IEETA Aveiro Portugal Portuguese Mil Acad Lisbon Portugal CINAMIL Lisbon Portugal LIBPhys UC Lisbon Portugal

ISBN: (数字)9783031456459

ISBN: (纸本)9783031456442;9783031456459

The aim of this work is to analyze the performance of Deep Learning algorithms for detecting vehicles and buildings in aerial images. Two algorithms, Faster R-CNN and YOLO, are compared to identify the best performance. The results showed that there is a considerable discrepancy between the two algorithms, both in terms of performance and speed. Faster R-CNN only proved to be superior in terms of training speed, but YOLO achieved the best results.

关键词： Deep Learning Transfer Learning Computer Vision Object Detection

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Agricultural Sector and Digital Transformation: An Explorative Research of Consumers and Producers Views of Authenticity 4th

Agricultural Sector and Digital Transformation: An Explorati...

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4th International Conference on Digital Technologies and Applications (ICDTA)

作者： Ouboutaib, Fatima Ezzahra Ibn Zohr Univ Fac Law Econ & Social Sci AIT MELLOUL Aitmelloul Morocco

ISBN: (纸本)9783031686528;9783031686535

The landscape of the business world is switching to the new normal post Covid 19 era. Therefore, the pandemic has accelerated the digital transformation and it has been added to the deep health crises in human history. In turn, it has disrupted the consumer-health relationship and it has reshaped the digital transformation practices. This research contributes to knowledge by exploring how digital transformation affects the practices in the agricultural sector. Regarding the key determinants of authenticity's definition in post Covid 19, it considers the different and conflicting views from consumers and producers in the same time. This essay infers that the authenticity could represent a flexible, controversial and especially fluid concept. Findings underline that digital transformation of the agricultural sector needs to be shaped by a digital that emphasize the social reality of consumption. In this sense, a deep understanding of local environment provides a value for the technology and strategy for bridging the authenticity gap.

关键词： Authenticity Consumer Digital transformation Agricultural Sector Nvivo 12

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Revolutionizing Urban Mobility: YOLO D-NET-Based AIoT Solutions for Sustainable Traffic Management 2nd

Revolutionizing Urban Mobility: YOLO D-NET-Based AIoT Soluti...

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2nd International Conference on Forthcoming networks and Sustainability in the AIoT Era (FoNeS-AIoT)

作者： Islam, Md Ashraful Islam, Md Atiqul Sujana, Faiza Mollic Islam, Amirul Al Mamun, Abdulla Hasan, Abul Khaled, Emdad Ullah Alam, Md Sabbir Al Masum, Niaz Green Univ Bangladesh Dhaka Bangladesh Comilla Univ Kotbari 3506 Cumilla Bangladesh

ISBN: (纸本)9783031628801;9783031628818

This study presents an innovative approach for addressing the complex issues associated with urban traffic management in Dhaka, Bangladesh, by incorporating the YOLOv8 model into an AIoT-based system. A customized dataset, comprising 200 data points captured from Dhaka, was utilized for training and testing the model. The YOLOv8 model produced impressive results, identifying CNG with a high precision of 89%, cars, and buses with 84% accuracy, and people with 84% accuracy. The model demonstrated an 80% accuracy rate in identifying Lanes, demonstrating its effectiveness in managing road infrastructure. The precision-confidence graphs further validate the model's effectiveness, with discernible peaks aligning with accurately identified objects. Motorcycle detection exhibited a 60% accuracy rate, and an observed only 0.4 misclassification rate between Cars and Motorcycle suggests potential areas for refinement. These results emphasize how well the YOLOv8 model works for real-time object detection in Dhaka's dynamic and clogged traffic environment. The study lays a foundation for future improvements in object detection accuracy and overall urban mobility through the study's insightful contributions to developing an adaptive traffic management system. With the help of AIoT technologies, traffic management strategies in densely populated cities experiencing rapid urbanization could be revolutionized, as demonstrated by the YOLOv8 model.

关键词： AIoT YOLO D-NET Computer Vision Traffic Management

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YOLO-Based Object Detection in Industry 4.0 Fischertechnik Model Environment 1

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Intelligent systems Conference (IntelliSys)

作者： Schneidereit, Slavomira Yarahmadi, Ashkan Mansouri Schneidereit, Toni Breuss, Michael Gebauer, Marc BTU Cottbus Senftenberg Chair Automat Technol Pl Deutsch Einheit 1 D-03046 Cottbus Germany BTU Cottbus Senftenberg Inst Math Pl Deutsch Einheit 1 D-03046 Cottbus Germany

ISBN: (数字)9783031477249

ISBN: (纸本)9783031477232;9783031477249

In this paper we extensively explore the suitability of YOLO architectures to monitor the process flow across a Fischertechnik Industry 4.0 application. Specifically, different YOLO architectures in terms of size and complexity design along with different prior-shapes assignment strategies are adopted. To simulate the real world factory environment, we prepared a rich dataset augmented with different distortions that highly enhance and in some cases degrade our image qualities. The degradation is performed to account for environmental variations and enhancements opt to compensate the color correlations that we face while preparing our dataset. The analysis of our conducted experiments shows the effectiveness of the presented approach evaluated using different measures along with the training and validation strategies that we tailored to tackle the unavoidable color correlations that the problem at hand inherits by nature.

关键词： Object detection Image augmentation Classification YOLO Fischertechnik industry Industry 4.0

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Learning Performance and the Influence of Individual Motivation Through Social networks 1

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11st World Conference on Information systems and Technologies (WorldCIST)

作者： Gutierrez-Aguilar, Olger Tomaylla-Quispe, Ygnacio Montesinos-Valencia, Lily Chicana-Huanca, Sandra Univ Catolica Santa Maria Arequipa Peru Univ Nacl San Agustin Arequipa Peru

ISBN: (数字)9783031456459

ISBN: (纸本)9783031456442;9783031456459

The research aims to find out how individual motivations, like altruism, affect how well people learn and how social networks help people form and share knowledge as one of their functions. The methodology used for the study corresponds to a non-experimental investigation. Reliability tests and a questionnaire were applied to a random sample of 130 university students (n = 24;alpha = 0.978 omega = 0.978). Through Partial Least Squares Structural Equation Modeling (PLS-SEM), the causal relationship between the exogenous and endogenous variables was used to design the model. This was done in addition to the exploratory and confirmatory factorial analyses. It has been shown that social networks are the best way for personal motivations like reputation and, significantly, altruism to affect the exchange of information and knowledge and the learning performance of college students in a way that supports the thesis. There is a statistically significant link between the altruistic sharing of knowledge, the formation of knowledge, and how well people learn.

关键词： Individual motivation social networks altruism learning performance knowledge exchange knowledge formation

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Food-Talks: Food Ordering and Delivering Application for Visually Challenged 1

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

作者： De Silva, D. I. Godapitiya, M. V. N. Peiris, M. M. A. E. Perakum, K. K. P. Mangchanayaka, M. V. V. Senevirathne, U. W. H. N. Sri Lanka Inst Informat Technol Malabe Sri Lanka

ISBN: (数字)9789819735594

ISBN: (纸本)9789819735587;9789819735594

In a digital age defined by rapid advancements, ensuring easy access to online services and fostering inclusivity is paramount. This paper introduces Food-Talk, a groundbreaking voice-based online food delivery system designed to meet the diverse needs of visually impaired and sighted users. It offers essential features, including voice-enabled registration and streamlined menu management, making it a transformative solution for the online food industry. Rigorous assessments, including usability, accessibility, and performance testing, confirm Food-Talk's remarkable performance, with shorter task times and minimal errors. Food-Talk's accessibility features, including compatibility with screen readers and clear audio output, empower visually impaired users for independent engagement in online food services. An intuitive user interface ensures a satisfying, efficient experience. Efficiency and effectiveness are the foundation of Food-Talk's design, providing prompt responses and multiuser support. The system prioritizes robust data security and privacy, adhering to stringent standards. Its scalability and compatibility with various devices underscore its transformative potential. As technology reshapes the digital landscape, Food-Talk exemplifies the fusion of accessibility and efficiency to bridge the digital divide. It sets a compelling precedent, emphasizing the vital combination of accessibility and efficiency to enhance the digital experiences of all users.

关键词： Food ordering Visually impaired Voice commands

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Deep Reinforcement Learning for Mobile Robots: Overview and Issues 4th

Deep Reinforcement Learning for Mobile Robots: Overview and ...

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4th International Conference on Digital Technologies and Applications (ICDTA)

作者： Haja, Zakaria Aissi, Mohammed El Habchi, Ali Kelmoua, Leila Berrich, Jamal Bouchentouf, Toumi Rahmoune, Mohammed Univ Mohammed Premier Natl Sch Appl Sci Res Lab Appl Sci PB 669 Oujda 60000 Morocco

ISBN: (纸本)9783031686597;9783031686603

This study offers a comprehensive overview of the integration and impact of Deep Reinforcement Learning (DRL) in the field of mobile robotics. Focusing on the period from 2000 to 2023, The evolution and influence of DRL are analyzed through a detailed citation analysis, leveraging data from major scholarly databases. The core concepts of Reinforcement Learning (RL) are explored, emphasizing its application in mobile robotics for balancing exploration and exploitation, a critical aspect of autonomous decision-making processes. The paper delves into various applications of DRL in mobile robotics, including autonomous navigation, path planning, and target tracking, highlighting the advancements that have significantly enhanced robotic capabilities. A review of recent developments is also included in the analysis, such as Successor Representations and latent imagination learning strategies, illustrating their contribution to the exploration-exploitation trade-off. Additionally, the advantages of DRL, such as adaptability and learning from experience, alongside challenges like hardware limitations and dynamic environment adaptability. The paper concludes by identifying key future research directions, notably in generalization and transfer learning, robustness to uncertain environments, and the potential role of Graph Neural networks (GNNs) in further advancing RL for mobile robotics. This overview aims to provide a clear understanding of the current state and future potential of DRL in enhancing the efficiency and intelligence of mobile robotic systems.

关键词： Deep Reinforcement Learning Mobile Robots Robotic Learning Approaches

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Combining Distributed Ledger Technologies and Differentially Private Sketching Techniques for Securing Health Monitoring 1

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16th International Conference on Ubiquitous Computing and Ambient Intelligence

作者： Ramos-Cruz, Bruno Quesada-Real, Francisco J. Rodriguez-Garcia, Mercedes Andreu-Perez, Javier Martinez, Luis Univ Jaen Comp Sci Dept Jaen 23071 Spain Univ Cadiz Sch Engn Cadiz Spain Univ Essex Sch Comp Sci & Elect Engn Ctr Computat Intelligencer Colchester Essex England

ISBN: (数字)9783031775710

ISBN: (纸本)9783031775703;9783031775710

The integration of smart health environments has significantly enhanced patient care by enabling continuous monitoring of vital signs either at home or ubiquitously. However, this extensive data collection raises substantial privacy and security concerns. This contribution presents a novel solution that combines Differentially Private Sketching Techniques (DPS) and Distributed Ledger Technologies (DLT) to improve privacy, security, and efficiency in health data monitoring. By anonymising and compressing data before storage, DPS techniques preserve essential trends while preventing unauthorised access to precise patient information. DLT ensures data integrity and traceability through decentralised and immutable storage. Critical health parameters that exceed predefined normal values are anonymised and securely stored in the DLT, facilitating timely medical interventions. This approach allows patients to remain confidently in their homes, knowing their medical team is promptly informed of any deviation in his/her health parameters. Our proposal addresses the need for securing and managing health data efficiently, by offering a robust framework adaptable to various healthcare scenarios.

关键词： Smart Health Monitoring Data Privacy Distributed Ledger Technology

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The Dynamic Vehicle Routing Problem with Simultaneous Delivery and Pickup, Overtime and Inventory Restriction: Comparative Study of Three Resolution Methods 7th

The Dynamic Vehicle Routing Problem with Simultaneous Delive...

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7th International Conference on Logistics Operations Management (GOL)

作者： Berahhou, Amina Benadada, Youssef Mohammed V Univ Rabat Smart Syst Lab ENSIAS Rabat Morocco

ISBN: (纸本)9783031686337;9783031686344

The technological advancements and the development of more powerful computers and advanced optimization algorithms make Dynamic Vehicle Routing Problem a more practical and appealing area of research and application. This paper treat a bi-objective Dynamic Vehicle Routing Problem with Simultaneous Delivery and Pickup, Overtime and Inventory Restriction (DVRPSDP-OT-IR). The problem was solved by three methods;the first method is based on solving the mathematical model of each sub-problem by an iterative exact method, the second method is the memetic algorithm, and the third method is the golden ball algorithm. The three methods have been tested on instances from the literature, and the results show that golden ball algorithm is the most effective.

关键词： DVRP VRPSDP Overtime Inventory restriction GBA MA Exact method

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