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检索条件"丛书名=Lecture Notes in Networks and Systems"

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Autonomous Emergency Landing of an Aircraft in Case of Total Engine-Out 1

引用

15th International Conference on Autonomous systems

作者： Flaemig, Steffen Schiffmann, Wolfram Fernuniv Unistr 1 D-58084 Hagen Germany

ISBN: (数字)9783031614187

ISBN: (纸本)9783031614170;9783031614187

An engine failure is the nightmare of every pilot. In order not to give away the best options for an emergency landing, a decision on the further flight route in gliding must be made as soon as possible. It is important to divide the remaining height available when deciding on an emergency landing in such a way that the runway threshold is still reached at a suitable flaring height despite the influence of wind. This route planning can be carried out with the help of smart emergency landing assistance systems in a very short time and with high accuracy. The present article describes the solutions developed so far by the SmartFly-Solutions team.

关键词： Engines

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Multiprocessor Task Scheduling with Probabilistic Task Duration 1

引用

19th International Conference on Dependability of Computer systems (DepCoS-RELCOMEX)

作者： Dorota, Dariusz Cracow Univ Technol St Warszawska 24 PL-31155 Krakow Poland

ISBN: (数字)9783031618574

ISBN: (纸本)9783031618567;9783031618574

Article concentrate on so-called multiprocessor task scheduling problem with uncertain (random) time of tasks duration. Multiprocessor scheduling can be perceived as a tool for improving dependability of the system by hardware and software redundancy. Our overall aim is develop more precise description of various configuration of embedded systems). Our aim is to evaluate the model of task duration distribution on the result of scheduling. We compare two models of the task: normal distribution and Erlang distribution. The latter model is considered as more suitable for multiprocessor scheduling, which reflects more accurately reality. We use MVA (Mean Value Analysis) methodology in the research with the application of modified Muntz-Coffman algorithm. The article is an extension of previous research of the author, considering uncertain task duration in different models. Computational experiments compared results obtained for both distributions in this stochastic model.

关键词： Multiprocessor tasks Uncertain task duration Scheduling

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Novel Statistical Glaucoma Prediction Algorithm Based on Spectral Analysis 1

引用

8th Smart Trends in Computing and Communications (SmartCom)

作者： Ghosh, Arkoprovo Bose, Soumalya Sen, Anindya Heritage Inst Technol Dept Elect & Commun Engn Kolkata India FAU Erlangen Nurnberg Dept Elect Engn Commun & Multimedia Engn Erlangen Bavaria Germany

ISBN: (数字)9789819713233

ISBN: (纸本)9789819713226;9789819713233

Glaucoma is a condition that causes damage to the eye's optic nerve and may result in the loss of vision. About 12 million people in India suffer from glaucoma. The ML models predicting Glaucoma are computationally complex, presence of infrastructure like GPU is of high importance, and sometimes they are also not eco-friendly due to carbon footprints. As a result, the authors of this paper proposed an algorithm which based on spectral analysis with fusion of advanced statistical approach of KL divergence for predicting the presence of Glaucoma. The algorithm has been evaluated on a total of 98 images: 70 images are used for training (glaucoma-49, normal-21) and 28 images (glaucoma-18, normal-10) are used for prediction. The accuracy obtained by the proposed novel algorithm is 76.4% with sensitivity of 86.7%, F1 Score of 82.5%, and precision 78.9%. In terms of computational efficiency, the training process takes approximately 51.116 s to complete, while the testing phase requires about 11.616 s to finish.

关键词： Glaucoma Prediction Non-local means FFT Disc segmentation KL divergence Spectral analysis

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AI Data Analysis and SOM for the Monitoring and Improvement of Quality in Rolled Steel Bars 1

引用

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

作者： Vannucci, Marco Colla, Valentina Giacomini, Alberto Scuola Super Sant Anna Ist TeCIP Pisa Italy Danieli Automat Udine Italy

ISBN: (数字)9783031456428

ISBN: (纸本)9783031456411;9783031456428

In the steel sector, within the production of high value hot rolled long products, assessment of components health and compliance with quality targets are fundamental aspects that need to be ensured. In this paper, an AI-based system for monitoring the conditions of the rolling process of bars with round section and estimating the final bars ovality is presented. The developed system, based on a Self Organising Map, is trained and evaluated by using data coming from a real plant and pre-processed by means of advanced AI techniques. The system allows monitoring a wide range of process variables affecting the ovality issue and actively supports plant operators in the task of avoiding quality-critical conditions and possible machine faults.

关键词： steel bars self organizing map variables selection

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Predicting and Explaining Variations in Software Effort Estimation Using Adaptive Fuzzy-Neural networks with Clustering

Predicting and Explaining Variations in Software Effort Esti...

引用

Intelligent systems Conference (IntelliSys)

作者： Mehdi, Riyadh A. K. Coll Engn & Informat Technol Artificial Intelligence Res Ctr Ajman U Arab Emirates

ISBN: (纸本)9783031477201;9783031477218

Software effort estimation is a significant and critical step in software development;an accurate estimate is vital to a software project's planning, scheduling, budgeting, and successful completion. This paper investigates the effect on prediction accuracy of introducing an initial clustering phase before applying an Adaptive Neuro-Fuzzy Inference System to estimate software efforts. Also, we explore the most significant determinants of variations in software efforts. The China dataset shows that dividing projects into groups using a clustering algorithm has reduced the root mean square error by 34%. Also, neural network sensitivity analysis has revealed that the resources required to complete the project are the most influential factor determining variations in software efforts for small-sized projects, followed by the product delivery rate. However, for medium and large-sized projects, the effect of resources is more significant than the delivery rate. Project duration comes third in importance for medium and large-sized projects;however, the number of function points is more important than project duration for small projects. Other metrics have little influence on software effort variations, with the number of deleted functional requirements having the slightest effect. These findings can significantly affect the accuracy of software effort estimation through proper analysis and computation of the factors that influence software efforts most. Future work will investigate model performance using different attributes, such as project type, for clustering large heterogeneous datasets.

关键词： Software cost estimation Fuzzy inference Clustering Neural networks And fuzzy-neural systems

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The Fast Health Interoperability Resources (FHIR) and Clinical Research, a Scoping Review 11th

The Fast Health Interoperability Resources (FHIR) and Clinic...

引用

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

作者： Pavao, Joao Bastardo, Rute Rocha, Nelson Pacheco Univ Tras Os Montes & Alto Douro Sci & Technol Sch INESC TEC Vila Real Portugal Univ Tras Os Montes & Alto Douro Sci & Technol Sch UNIDCOM Vila Real Portugal Univ Aveiro Dept Med Sci IEETA Aveiro Portugal

ISBN: (纸本)9783031456473;9783031456480

The focus of this scoping review was the application of Fast Health Interoperability Resources (FHIR) to support clinical research. After the search and selection processes 36 studies were identified and included in the review. Analysing these studies, it is possible to conclude that FHIR is being used in the implementation of information systems to support (i) clinical trials data management, (ii) data integration for clinical research, and (iii) secondary use of clinical information. Moreover, the results also show the interest on the development of novel FHIR profiles to answer specific data requirements of clinical research.

关键词： Clinical Research Fast Health Interoperability Resources FHIR Scoping Review

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A Comprehensive Survey and Future Standpoints on Big Data Analytics of Mobile Data 1

引用

8th Smart Trends in Computing and Communications (SmartCom)

作者： Mehta, Riya B. Patel, Dhruvkumar D. Vyas, Paulami D. Doshi, Kajal A. Undavia, Jaimin N. Solanki, Kamini H. Shukla, Abhilash M. Desai, Mittal Smt Chandaben Mohanbhai Patel Inst Comp Applicat Changa India Charotar Univ Sci & Technol Anand Gujarat India

ISBN: (数字)9789819713264

ISBN: (纸本)9789819713257;9789819713264

Data analytics word is mainly concerns with data of huge size, and finally it is termed as big data. The velocity, volume, variety, and variability are the characteristics of big data. These kinds of big data can be easily obtained through hand held mobile device where one can find data with high volume, versatility in nature, dynamic generation, and high complexity as well. Recent tools and technology in mobile device context encouraged high degree of analytics over the data generated through mobile device. Google analytics, Hadoop, Apple Analytics, Kobo Toolbox, etc. are the recent buzzwords in the area of mobile analytics. The article also depicts the survey and growth of mobile users so as the incremental volume of data through mobile device, which ultimately opens the door of research in mobile data. The future of mobile analytics is also shown how mobile analytics will be persisted in the market with growth in number and volume as well.

关键词： Mobile application Mobile analytics Web analytics Google analytics Hadoop Kobo toolbox Apple analytics

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Determining the Physiological Cost of a Military Serviceman's Activity in the Field Using Innovative Miniature Devices and Advance ECG Analysis: Different Scenarios of Use 1

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

作者： Chaikovsky, Illya Bocharov, Mykhailo Stasiuk, Vasyl Ryzhenko, Tetyana Frolov, Iurii Parovska, Sofia Sharypanov, Anton Malanin, Vladyslav Osyodlo, Vasyl Glushkov Inst Cybernet Natl Acad Sci Acad Glushkov Ave 40 UA-03187 Kyiv Ukraine Natl Def Univ Ukraine Kyiv Ukraine Natl Guard Ukraine Presidential Brigade Operat Assignment 1 Kyiv Ukraine Natl Acad Sci Ukraine Inst Math Machines & Syst Kyiv Ukraine

ISBN: (数字)9789819735594

ISBN: (纸本)9789819735587;9789819735594

In the context of military operations in developed countries, the assessment of combat readiness among defense personnel holds significant importance. This evaluation serves the dual purpose of optimizing combat potential while minimizing personnel casualties. This study aims to estimate the physiological cost incurred by soldiers' duties in the Armed Forces of Ukraine (AFU), utilizing miniature ECG systems. Our research employed ultra-miniature ECG devices designed for prolonged on-body use, referred to as wearable "on-body" ECG patches, along with miniature ECG devices equipped with finger electrodes, across various combat scenarios. Data analysis was conducted through a comprehensive approach to ECG analysis, encompassing four key aspects: heart rate variability (HRV), amplitude and time ECG parameters, heart arrhythmia, psychological and mental state assessment. Within this study, we devised a complex functional state index based on established metrics and original parameters of heart rhythm variability, ECG waveforms and intervals. Additionally, we developed a psychoemotional state index using a modified McCraty algorithm (USA) for heart rhythm variability analysis. Our monitoring system exhibited a noteworthy sensitivity to detect changes in the functional state under different field conditions and permanent deployment settings. These methods and tools offer valuable support for commanders in their decision-making process, enabling them to assess personnel readiness to execute combat tasks based on their functional state.

关键词： Electrocardiogram Heart rate variability Physiological cost of activity Military officers Monitoring

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Contribution of Artificial Intelligence in Entrepreneurship: A Systematic Literature Review 4th

Contribution of Artificial Intelligence in Entrepreneurship:...

引用

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

作者： Mnajli, Fatima Ezzahra Chroqui, Razane Hassan First Univ Settat Lab Management Mkt & Commun ENCG Settat Morocco Hassan First Univ Settat Natl Sch Appl Sci Berrechid LISA Settat Morocco

ISBN: (纸本)9783031686597;9783031686603

Increasing digitization and advances in artificial intelligence (AI) are bringing new jobs or business models. There is a gap in current research on the impact of digitalization on performance. This systematic literature review (SLR) seeks to enhance our understanding of this field and provides a logical evaluation of existing contributions. It aims to review research on the way artificial intelligence impacts performance. The findings show that artificial intelligence has a significant impact on business, especially a positive impact on entrepreneurs. The present study provides policy signal makers and entrepreneurs with a comprehensive view of key concepts, enabling them to understand the current state of artificial intelligence in the industry.

关键词： Entrepreneurship Artificial Intelligence Entrepreneur SLR

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An Automated and Goal-Oriented Clustering Procedure 9th

An Automated and Goal-Oriented Clustering Procedure

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

作者： Koren, Oded Koren, Michal Peretz, Or Shenkar Engn Design Art Sch Ind Engn & Management Anne Frank 12 Ramat Gan Israel

ISBN: (纸本)9789819745807;9789819745814

Clustering techniques are convenient tools for preparing and organizing unstructured and unclassified data. Depending on the data, they can be used to prepare for an analysis or to gain insight. However, choosing a clustering technique can be challenging when dealing with high-dimensional datasets. Most often, application requirements and data distribution need to be considered. Since clustering is defined as a complex problem to calculate, different algorithms may produce different results that meet the application's needs. This study presents an automated threshold-based and goal-oriented clustering procedure. It is based on the AutoML mechanism to estimate the most suitable hyperparameters according to predefined needs and can learn four clustering performance metrics thresholds for a given dataset. The significant advantages of this method are the automatic selection of clustering technique (i.e., partitional, hierarchical, density-based, or graph-based) and the ability to determine the output dynamically, according to predefined goals. We tested our method over four datasets and analyzed the results according to different goals. The results show that our method improved the silhouette score by 549.5% (from 0.105 to 0.682) compared to popular and commonly used K-means. Furthermore, clustering based on multiple metrics yielded more information than clustering by a single metric.

关键词： Clustering AutoML Threshold learning Decision-making

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