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Tool for Quantum-Classical Software Lifecycle 12th

Tool for Quantum-Classical Software Lifecycle

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12th Conference on Cloud Computing, Big Data and Emerging Topics

作者： Parraga Aranda, Jesus Perez del Castillo, Ricardo Piattini, Mario Univ Pontificia Salamanca Salamanca Spain Univ Castilla la Mancha Toledo Spain

ISBN: (纸本)9783031708060;9783031708077

With the growing diffusion of quantum computing technology and the increasingly promising applications derived from it, the relevance of developing specific software for these systems is gaining significant momentum. This surge is due to the need to design and produce quantum software that meets performance and functional requirements but also follows the well-known good practices and rigorous methodologies inherent in quantum software engineering. In this context, one of the main challenges facing the development of hybrid (quantum-classical) systems is the effective management of the lifecycle of this new type of software, whose nature differs from traditional systems. The proposed research attempts to comprehensively address the lifecycle management of hybrid software, through the design and development of a specific support tool. To achieve this goal, the ICSM (Integrated Software Cycle Management) model, which is a consolidated framework for the lifecycle management of traditional software, will be taken as a starting point. This model will be carefully adapted to meet the unique needs and challenges inherent in hybrid software, thus ensuring that the development, maintenance, and updating practices of this type of software are as robust and efficient as those applied in the realm of conventional software. Through this adaptation, the aim is not only to improve the quality of the developed hybrid software but also make developers easier to adopt the innovative and complex quantum software paradigm.

关键词： Quantum Computing Quantum Software Engineering Hybrid software Software Lifecycle ICSM

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Agile Audit Proposal for ISO IEC 27001 Standard Implementation in Higher Education Faculties 4th

Agile Audit Proposal for ISO IEC 27001 Standard Implementati...

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4th International Conference on Advanced Research in Technologies information Innovation and Sustainability-ARTIIS-Annual

作者： Ruete Zuniga, David Lopez Lira, Pilar Caroca Navarro, Alejandro Diaz Pena, Mailiu Caselli Benavente, Nicolas Leal Moraga, Danilo Reyes Rogget, Marcelo Maidana Gonzalez, Jean Paul Univ Andres Bello Vina Del Mar Chile

ISBN: (纸本)9783031840777;9783031840784

The information Security Management System (ISMS) is responsible for protecting information by implementing strategies to ensure its confidentiality, availability, and integrity. information for the ISMS is collected through a Statement of Applicability, allowing for an ISMS audit of the organization and demonstrating its condition. This work proposes an agile internal audit methodology based on ISO/IEC 27001, aimed at reducing the time required for internal audits and preparing the institution for formal certification.

关键词： ISMS information Security ISO27001 Cybersecurity

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Investigation of Observation Conditions and Detection Distance of Aircraft in the Thermal Range 2nd

Investigation of Observation Conditions and Detection Distan...

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2nd International Conference on information Technologies and Their Applications

作者： Rana, Huseynova Gunel, Aliyeva Azerbaijan Univ Architecture & Construct 11 A Sultanova AZ-1073 Baku Azerbaijan Natl Aerosp Agcy SS Akhundov St AZ-1115 Baku Azerbaijan

ISBN: (纸本)9783031734168;9783031734175

Frequent accidents of civil aircrafts that occur due to suddenly changing environmental conditions require their reliable tracking in real time. This circumstance dictates the need for further improvement of tracking systems of civil aircraft in flight. Flight control in the future can be carried out using unmanned carriers, as well as spacecrafts. The most important state of the aircraft's own thermal radiation, in which its infrared visibility is assessed, is the state of equilibrium self-radiation. Unlike civilian ships, in the military sphere it is important to hide aircraft flights from enemy observation equipment. The question of determining the detection distance of modern aircraft is considered, taking into account such factors as radiation contrast, the radiance of the object and background, radiation fluxes, the transmission coefficient of the optical part of the detector, the bandwidth of the atmosphere. The task of minimizing the detection distance of combat aircraft in the infrared range has been formulated. As a result of solving the problem in integral and non-integral formulations, design expressions for calculating the optimal values of the detection distance were obtained.

关键词： infrared range detection detector optimization functionality

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A Conceptual Framework for Digitalized Payment Systems in South Africa 4th

A Conceptual Framework for Digitalized Payment Systems in So...

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4th International Conference on Society 5.0

作者： Walaza, Mvelo Eybers, Sunet Univ South Africa Pretoria South Africa

ISBN: (纸本)9783031714115;9783031714122

SouthAfrica is regarded as a dual economy in which a significant financial and digital gap exists between people who live in rural, underdeveloped areas and those who live in urban, developed areas. The people who live in rural areas are often referred to as financially excluded because they do not fully participate in the country's economy. In such environments, the financially excluded frequently travel long distances to access financial products and services. A payment system is any system used to settle financial transactions by transferring monetary value. The digitalization of payment systems, in the context of this study, refers to the modernization and enhancement of payment systems using innovation and technology. This paper explores digitalizing South African payment systems so that the financially excluded can access basic banking. Financial inclusion refers to people and businesses accessing good banking resources, financial products, and services - resulting in improved economic growth. The study is underpinned by the Technology-Organization-Environment (TOE) framework as a lens to understand TOE elements relevant to the digitalization (technology) assisting the South African banking industry (organization) in its attempt to foster financial inclusivity of those living in the rural areas (environment). This study used a systematic review of the literature to propose a conceptual research framework that could be used to investigate the digitalization of payment systems in the South African banking industry for financial inclusion.

关键词： digitalized payment systems financial inclusivity Technology-Organization-Environment framework

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Convolutional Neural Networks for the Classification of Comet Assay Cells 5th

Convolutional Neural Networks for the Classification of Come...

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5th International Symposium on Intelligent Computing Systems

作者： Rizo-Blanco, Ismel Martin-Gonzalez, Anabel Brito-Loeza, Carlos Legarda-Saenz, Ricardo Espinosa-Romero, Arturo Lafon-Hughes, Laura Univ Autonoma Yucatan Fac Matemat Computat Learning & Imaging Res Merida 97119 Mexico Univ Republ Ctr Univ Reg Litoral Norte CENUR Salto Uruguay

ISBN: (纸本)9783031829307;9783031829314

The comet assay is a versatile method used to determine the DNA damage in individual cells. The cells processed by this technique preserve the stable genetic material in the head of the comet and the unstable portion of DNA in the tail. The analysis of the resulting microscopic images from this test must be carried out by an expert, who must precisely determine the extent of DNA liberated from the head of the comet, since it is related to the level of damage. Since this is a time-consuming and very specialized task, the objective of this research is to develop a computational system, based on the use of a convolutional neural network, for the automatic classification of cells processed by comet assay according to the level of DNA damage they present.

关键词： Comet Assay Convolutional Neural Network Cell Classification Deep Learning

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Optimizing Vehicle Emissions: Identifying High-Impact Vehicles and Exploring Sustainable Fuel Options 4th

Optimizing Vehicle Emissions: Identifying High-Impact Vehicl...

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4th International Conference on Advanced Network Technologies and Intelligent Computing-ANTIC-Annual

作者： Muttal, Channabasappa Sujatha, C. Pandekamat, Manoj Hiremath, Veeresh Pujari, Rahul KLE Technol Univ Hubli 580031 India

ISBN: (纸本)9783031837920;9783031837937

This study presents an extensive examination of emissions from passenger vehicles, particularly focusing on the benefits of hybrid vehicles over conventional vehicles powered by fossil fuels. Although hybrid vehicles have a more favorable environmental impact, their production is hindered by higher costs and production challenges. By utilizing a Linear Regression Model, this study confirms the positive correlation between fuel consumption and CO2 emissions, emphasizing that increased fuel consumption results in increased CO2 emissions. These findings highlight the need for policies that encourage the adoption and production of hybrid vehicles to mitigate vehicular pollution effectively. In addition, the study analyzed real-time vehicle emission data and employed predictive modeling to assess the influence of factors, including fuel type, driving habits, vehicle maintenance, and environmental conditions, on emissions. In addition, it compares laboratory-based emission tests with real-world measurements, revealing significant disparities and highlighting the importance of real-world emission monitoring. This study offers critical insights for policymaker and stakeholders working to develop sustainable transportation solution, and serves as a foundation for future strategies to address the environmental and health impacts of urban transportation. This study presents a linear regression model to predict vehicle CO2 emissions (g/km) from fuel consumption (L/100km) and vice versa, achieving 92.44% of accuracy for cars and 86.68% for vans. This tool facilitates comparisons of fuel consumption or CO2 emissions between cars and vans, helping policymakers and stakeholders craft sustainable transportation strategies.

关键词： Vehicular emissions Hybrid vehicles Fuel consumption CO2 emissions Predictive modeling Sustainable transportation

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Multi-agent Path Planning for Logistics Cargo Environment Using LSTM Based Reinforcement Learning 5th

Multi-agent Path Planning for Logistics Cargo Environment Us...

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5th International Conference on Innovative Intelligent Industrial Production and Logistics

作者： Cho, Gun Rae Park, Sungho Jung, Eui-Jung Shin, Hyunseok Son, So Eun Choi, Yong Korea Inst Robot & Technol Convergence Pohang 37666 South Korea

ISBN: (纸本)9783031807596;9783031807602

In the operation of logistics cargo, temporal efficiency in handling logistics is a critical issue. One solution to enhance this efficiency is the deployment of multiple autonomous ground vehicles (AGVs). This paper proposes a reinforcement learning approach based on Long Short-Term Memory (LSTM) for multi-agent path planning in the logistics cargo environment. When AGVs are treated as moving obstacles to each other, the application of LSTM allows for path planning that aptly addresses changes over time within the environment. Additionally, to solve the well-known problem of the sparse reward in pathfinding, we propose a reinforcement learning architecture for multi-agent path planning that uses the path planning results of a single agent, guided by Q-learning, as the guide path. Furthermore, we have established state variables independent of the number of agents by setting interest window-based state variables, and introduced revisit rewards, effectively resolving the issue of local minima caused by repetitive movement-avoidance behavior between agents. Simulation results, emulating a real-world logistics warehouse environment, demonstrate the proposed technique's capability for effective multi-agent path planning in such settings.

关键词： Multi-agent path planning Reinforcement learning Long-short term memory Autonomous ground vehicles Logistics cargo

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A Continuous Structural Intervention Distance to Compare Causal Graphs 6th

A Continuous Structural Intervention Distance to Compare Cau...

引用

6th Pacific Causal Inference Conference

作者： Dhanakshirur, Mihir Laumann, Felix Park, Junhyung Barahona, Mauricio Indian Inst Sci Bengaluru Dept Math Bangalore Karnataka India Imperial Coll London Dept Math London England MPI Intelligent Syst Tubingen Germany

ISBN: (纸本)9789819778119;9789819778126

Causal inference under interventions requires accurate assessment of differences between true and learned causal graphs. We introduce a new continuous metric that extends beyond graph-based measures like Structural Hamming Distance and Structural Intervention Distance by incorporating underlying data alongside graph structures. Our approach embeds intervention distributions for each node pair as conditional mean embeddings in reproducing kernel Hilbert spaces, then quantifies their disparity using maximum (conditional) mean discrepancy. We present theoretical findings supported by synthetic data experiments.

关键词： Directed acyclic graphs graph distance conditional mean embeddings kernel methods

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Adaptation Dynamics of Galapagos Finches: Evolutionary Responses to Climate Variation Explored through Machine Learning 12th

Adaptation Dynamics of Galapagos Finches: Evolutionary Respo...

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12th Ecuadorian Conference on information and Communication Technologies

作者： Jimenez Narvaez, Ariana Deyaneira Sanchez Vera, Danely Leonor Reyes, Ivan Vizcaino-Imacana, Paulina Morocho-Cayamcela, Manuel Eugenio Yachay Tech Univ Sch Math & Computat Sci Urcuqui 100119 Ecuador Univ Internac Ecuador Sch Comp Sci Fac Tech Sci Quito 170411 Ecuador

ISBN: (纸本)9783031754302;9783031754319

Climate change is accelerating the evolution of species as global warming intensifies and natural environments undergo significant alterations. This study addresses the urgent need to understand how these environmental changes impact avian populations, specifically focusing on the physiological adaptation of finch beaks on the Galapagos Islands. By employing multiple models-logistic regression, XGBOOST, and Random Forest Classifier-using the most recent data, the study investigates how changes in climate conditions correlate with variations in beak dimensions. The analysis reveals significant relationships between temperature, precipitation, and finch beak characteristics, indicating that climatic factors have a notable impact on beak morphology. The study aims to clarify the evolutionary dynamics at play and to predict future adaptations based on projected climate scenarios. The results highlight the robust correlation between climatic variables and finch physiology, providing deeper insights into the complex interplay between climate change and evolutionary biology. These findings are crucial for developing targeted conservation and adaptation strategies, helping to safeguard biodiversity in the face of ongoing climate shifts. The insights gained from this study are essential for guiding policymakers and stakeholders in implementing effective measures to mitigate the impacts of climate change on ecosystems and species survival.

关键词： Evolutionary adaptation Predictive modeling Data analysis Climate change Artificial intelligence Biodiversity Conservation

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Forecasting Multivariate Time Series with Trend and Seasonality: A Random Forest Approach 5th

Forecasting Multivariate Time Series with Trend and Seasonal...

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5th International Conference on Innovative Intelligent Industrial Production and Logistics

作者： Marzak, Zahira Benabbou, Rajaa Mouatassim, Salma Benhra, Jamal Hassan II Univ Casablanca Dept Ind & Logist Engn GIL ENSEM Lab Adv Res Ind & Logist Engn LARILE OSIL TeamENSEM Casablanca Morocco

ISBN: (纸本)9783031807749;9783031807756

Random Forest algorithm, a powerful machine learning technique recognized for its flexibility and high predictive accuracy has been used in different applications across various domains. This paper presents a comparative analysis of the performance of Random Forest in forecasting multivariate time series data exhibiting trend and seasonality, a task that poses a significant challenge since the traditional methods often used to forecast time series can fail to accurately model these complex characteristics, leading to poor forecasting performance and unreliable prediction. In this study, different optimization techniques are used to enhance the performance of the RF models, such as feature engineering, using various features (temporal, lagged, rolling window, and interaction features), and parameter tuning (Manual, Random Search, and Grid Search). The models are evaluated using three accuracy metrics: Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE) with lower values indicating better performances, the results are then compared to traditional forecasting methods. The proposed forecasting framework demonstrated the capability of the RF model to capture trends and seasonality in multivariate time series and provide competitive results.

关键词： Multivariate time series Forecasting Trend Seasonality Random forest

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