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arXiv 2022年

作者： Bayen, Alexandre M. Keimer, Alexander Müller, Nils Department of Electrical Engineering and Computer Sciences Department of Civil and Environmental Engineering University of California Berkeley United States Germany Max Planck Institute for Software Systems Saarland Informatics Campus Germany

Networks are essential models in many applications such as information technology, chemistry, power systems, transportation, neuroscience, and social sciences. In light of such broad applicability, a general theory of dynamical systems on networks may capture shared concepts, and provide a setting for deriving abstract properties. To this end, we develop a calculus for networks modeled as abstract metric spaces and derive an analog of Kirchhoff’s first law for hyperbolic conservation laws. In dynamical systems on networks, Kirchhoff’s first law connects the study of abstract global objects, and that of a computationally-beneficial edgewise-Euclidean perspective by stating its equivalence. In particular, our results show that hyperbolic conservation laws on networks can be stated without explicit Kirchhoff-type boundary *** Codes 35R02, 35C99 (Primary) 35L65, 00A71 (Secondary) © 2022, CC BY.

关键词： Dynamical systems

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A New Heuristic Algorithm for Balanced Deliberation Groups

arXiv

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arXiv 2024年

作者： Barrett, Jake Verpoort, Philipp C. Gal, Kobi School of Informatics University of Edinburgh 10 Crichton Street Edinburgh EdinburghEH8 9AB United Kingdom Sortition Foundation Cambridge United Kingdom Department of Software and Information Systems Engineering Ben-Gurion University Be’er Sheva Israel

We here present an improved version of the Sortition Foundation’s GROUPSELECT software package, which aims to repeatedly allocate participants of a deliberative process to discussion groups in a way that balances demographics in each group and maximises distinct meetings over time. Our result, DREAM, significantly outperforms the prior algorithmic approach LEGACY. We also add functionalities to the GROUPSELECT software to help the end user. The DREAM algorithm utilises random shuffles and Pareto swaps to find a locally optimal solution that maximises demographic balance and minimises the number of pairwise previous meetings, with the relative importance of these two metrics defined by the user. © 2024, CC BY.

关键词： software packages

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Work Engagement Recognition in Smart Office

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Procedia computer science 2022年 200卷 451-460页

作者： Congcong Ma Carman Ka Man Lee Juan Du Qimeng Li Raffaele Gravina Department of Industrial and Systems Engineering The Hong Kong Polytechnic University Hong Kong Special Administrative Region. School of Computer and Software Nanyang Institute of Technology Nanyang 473004 China. Department of Informatics Modeling Electronics and Systems University of Calabria Rende 87036 Italy.

The COVID-19 pandemic has forced a sudden change of traditional office works to smart working models, which however force many workers staying at home with a significant increase of sedentary lifestyle. Metabolic disorders, mental illnesses, and musculoskeletal injuries are also caused by the physical inactivity and chronic stress at work, threatening office workers' physical and physiological health. In the modern vision of smart workplaces, cyber-physical systems play a central role to augment objects, environments, and workers with integrated sensing, data processing, and communication capabilities. In this context, a work engagement system is proposed to monitor psycho-physical comfort and provide health suggestion to the office workers. Recognizing their activity, such as sitting postures and facial expressions, could help assessing the level of work engagement. In particular, head and body posture could reflects their state of engagement, boredom or neutral condition. In this paper we proposed a method to recognize such activities using an infrared sensor array by analyzing the sitting postures. The proposed approach can unobstructively sense their activities in a privacy-preserving way. To evaluate the performance of the system, a working scenario has been set up, and their activities were annotated by reviewing the video of the subjects. We carried out an experimental analysis and compared Decision Tree and k-NN classifiers, both of them showed high recognition rate for the eight postures. As to the work engagement assessment, we analyzed the sitting postures to give the users suggestions to take a break when the postures such as lean left/right with arm support, lean left/right without arm support happens very often.

关键词： Infrared Sensor Sitting Posture Recognition Smart Office Work Engagement

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Depth Based Region Proposal: Towards Robust Two-Stage Real-Time Object Detection

SSRN

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SSRN 2022年

作者： Ayman, Shehab Eldeen Hussein, Walid Karam, Omar H. Department of Software Engineering Faculty of Informatics and Computer Science The British University in Egypt Cairo Egypt Department of Computer Science Faculty of Informatics and Computer Science The British University in Egypt Cairo Egypt Department of Information Systems Faculty of Informatics and Computer Science The British University in Egypt Cairo Egypt

The majority of real-time object recognition systems operate on two-dimensional images, degrading the influence of the involved objects' third-dimensional (i.e., depth) information. The depth information of a captured scene provides a thorough understanding of an object in full-dimensional space. During the last decade, several region proposal techniques have been integrated into object detection. scenes’ objects are then localized and classified but only in a two-dimensional space. Such techniques exist under the umbrella of two-dimensional object detection models such as YOLO and SSD. However, these techniques have the issue of being uncertain that an object's boundaries are properly specified into the particular scene. This paper proposes a unique region proposal and object detection strategy based on retrieving depth information for localization and segmentation of the scenes’ objects in real-time manner. The obtained results on different datasets show superior accuracy in comparison to the commonly implemented techniques with regards to not only detection but also a pixel-by-pixel accurate localization of objects. © 2022, The Authors. All rights reserved.

关键词： Object recognition

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Depth Based Region Proposal: Multi-Stage Real- Time Object Detection

SSRN

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SSRN 2022年

The majority of real-time object recognition systems operate on two-dimensional images, degrading the influence of the involved objects' third-dimensional (i.e., depth) information. The depth information of a captured scene provides a thorough understanding of an object in full-dimensional space. During the last decade, several region proposal techniques have been integrated into object detection. scenes’ objects are then localized and classified but only in a twodimensional space. Such techniques exist under the umbrella of two-dimensional object detection models such as YOLO and SSD. However, these techniques have the issue of being uncertain that an object's boundaries are properly specified into the particular scene. This paper proposes a unique region proposal and object detection strategy based on retrieving depth information for localization and segmentation of the scenes’ objects in real-time manner. The obtained results on different datasets show superior accuracy in comparison to the commonly implemented techniques with regards to not only detection but also a pixel-bypixel accurate localization of objects. © 2022, The Authors. All rights reserved.

关键词： Object detection

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Segmentation and Multi-facet Classification of Individual Logs in Wooden Piles 18th

Segmentation and Multi-facet Classification of Individual Lo...

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18th International Conference on Computer Aided systems Theory, EUROCAST 2022

作者： Praschl, Christoph Auersperg-Castell, Philipp Forster-Heinlein, Brigitte Zwettler, Gerald Adam Research Group Advanced Information Systems and Technology Research and Development Department University of Applied Sciences Upper Austria Hagenberg Austria Department of Software Engineering School of Informatics Communications and Media University of Applied Sciences Upper Austria Hagenberg Austria Bluedynamics Auersperg-Castell KG Kritzing 31 Freinberg Austria Faculty of Computer Science and Mathematics University of Passau Passau Germany

ISBN: (纸本)9783031253119

The inspection of products and assessment of quality is connected with high costs and time effort in many industrial domains. This also applies to the forestry industry. Utilizing state-of-the-art deep learning models allows automizing the analysis of wooden piles in a vision-based manner. In this work, a parallel two-step approach is presented for the segmentation and multi-facet classification of individual logs, according to the wood type and quality. The present approach is based on a preliminary log localization step and like this allows determining the quality, volume and also the value of individual logs, respectively the whole wooden pile. Using a YOLOv4 model for wood species classification for douglas firs, pines and larches results in an accuracy of 74.53%, while a quality classification model for spruce logs reaches 86.58%. In addition to that, the trained U-NET segmentation model reaches an accuracy of 93%. In the future, the underlying data set and models will be further improved and integrated to a mobile application for the on site analysis of wooden piles by foresters. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Deep learning

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Cooperative Sensing Via Matrix Factorization of the Partially Received Sample Covariance Matrix

Cooperative Sensing Via Matrix Factorization of the Partiall...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Rui Zhou Wenqiang Pu Licheng Zhao Ming-Yi You Qingjiang Shi Sergios Theodoridis Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Shenzhen China National Key Laboratory of Electromagnetic Space Security Jiaxing China School of Software Engineering Tongji University Shanghai China Department of Electronics Systems Aalborg University Denmark Department of Informatics and Telecommunications National and Kapodistrian University of Athens Greece

A fundamental problem in cognitive radio is spectrum sensing, which detects the presence of the primary users in a licensed spectrum. To boost the detection performance and robustness, the multiantenna detector has been investigated and various related methods have been developed, e.g., the energy detector, the eigenvalue arithmetic-to-geometric mean detector, and the generalized likelihood ratio test detector. Cooperative sensing, which makes use of multiple receivers distributed in different locations, has the advantage of being able to make full use of the distributed antennas and enjoy a high spatial diversity gain. However, the successful employment of cooperative sensing depends on the reliable information exchange among the cooperating receivers over a long range, which may be impractical for real-world scenarios. In this paper, we consider the scenario where each receiving node can only broadcast its received raw data in a short-range communication fashion. We propose a novel cooperative sensing scheme by allowing each node to send to the fusion center only local correlation coefficients, computed within a neighborhood. A detection algorithm, based on matrix factorization of the partially received sample covariance matrix, i.e., with missing entries, is proposed. The performance of our proposed cooperative scheme is verified via numerical experiments.

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Extracting Relations between Organizational Patterns Using Association Mining 20

Extracting Relations between Organizational Patterns Using A...

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2020 European Conference on Pattern Languages of Programs, EuroPLoP 2020

作者： Waseeb, Shakirullah Khail, Waheedullah Sulaiman Wahaj, Haji Gul Vranić, Valentino Software Engineering Department Nangarhar University Afghanistan Institute of Informatics Information Systems and Software Engineering Slovak University of Technology in Bratislava Slovakia Database and Information System Department Nangarhar University Afghanistan

ISBN: (纸本)9781450377690

Patterns are powerful when used in combinations. Identifying relationships between patterns is challenging. The existing approaches and pattern formats reflect the relationships with other patterns in a very informal and traditional way. We are proposing an automatic approach which discover such relationships from the patterns descriptive text using text mining and natural language processing techniques. In this work, we demonstrate how it contributes in inference of relationships and its strength among patterns. © 2020 ACM.

关键词： Natural language processing systems

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Comparison of the Use of the DEMUCS Neural Network On Different Platforms for the Separation of Sources Of Musical Origin

Comparison of the Use of the DEMUCS Neural Network On Differ...

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International Conference on Computational Intelligence and Communication Networks (CICN)

作者： Raul Pérez Alarcón Luis Marcelo Pacheco Alvaro Ciro Rodriguez Favio Guevara Puente Ivan Petrlik Yuri Pomachagua Software Engineering Department Universidad Nacional Mayor de San MarcosUNMSM Lima Peru Department of Electronic Engineering and Informatics Universidad Nacional Federico Villarreal UNFV Lima Peru Systems Engineering Department Universidad Nacional Federico Villarreal UNFV Lima Peru

ISBN: (纸本)9781665487726

This paper makes a comparison between 3 systems deployed on different platforms (Web, Desktop, Mobile) which implement the DEMUCS neural network, responsible for separating sources of musical origin. The objective of this work is to determine on which platform the neural network can be executed more quickly for the use of the average user and from this to propose an optimal architecture for standard development. For this purpose, we selected 12 songs to be separated in the systems of the 3 platforms mentioned and we measured the time it takes for each system to execute the required separation and thus choose the best platform as a starting point. The results and conclusions of the work support the reason for choosing the platform, from which the development architecture was proposed.

关键词： Neural networks Music Computer architecture Time measurement Hardware Service-oriented architecture Delays

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Business Intelligence Architecture to Improve Decision Making

Business Intelligence Architecture to Improve Decision Makin...

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International Conference on Computational Intelligence and Communication Networks (CICN)

作者： Cristhian Villasante Moreno Ciro Rodriguez Favio Guevara Puente Ivan Petrlik Pedro Lezama Yuri Pomachagua Software Engineering Department Universidad Nacional Mayor de San MarcosUNMSM Lima Peru Department of Electronic Engineering and Informatics Universidad Nacional Federico Villarreal UNFV Lima Peru Systems Engineering Department Universidad Nacional Federico Villarreal UNFV Lima Peru

ISBN: (纸本)9781665487726

Summary - Currently in different organizations and public entities, have large amounts of data and many times the tools or technologies that achieve the analysis of such data are unknown. in this context, business intelligence emerged, which allows data to be analyzed and provided information to supports decision- making for senior executives of public entities. The objective of this research is to propose a business intelligence architecture that provides a solution to manage large amount of information. The methodology used was based on scrum as part of a good organization, structure and time control by the implementation of the proposed architecture in any system or tool of the public entities. as part of the review and part of the results, the research of various articles was carried out, and 20 were selected for sample and proof that the proposed architecture is the one indicated for decision making. in the results of part of the research, was found evidence that a business intelligence architecture is not only the most used, but it provides various response mechanisms for the large amount of information possessed and, in many cases, not used in the best way.

关键词： Decision making Data visualization Memory Computer architecture Organizations User experience software

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