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On near integrability of some impact systems

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arXiv 2018年

作者： Pnueli, M. Rom-Kedar, V. Department of Computer Science and Applied Mathematics Weizmann Institute of Science Rehovot Israel The Estrin Family Chair of Computer Science and Applied Mathematics

A class of Hamiltonian impact systems exhibiting smooth near integrable behavior is presented. The underlying unperturbed model investigated is an integrable, separable, 2 degrees of freedom mechanical impact system with effectively bounded energy level sets and a single straight wall which preserves the separable structure. Singularities in the system appear either as trajectories with tangent impacts or as singularities in the underlying Hamiltonian structure (e.g. separatrices). It is shown that away from these singularities, a small perturbation from the integrable structure results in smooth near integrable behavior. Such a perturbation may occur from a small deformation or tilt of the wall which breaks the separability upon impact, the addition of a small regular perturbation to the system, or the combination of both. In some simple cases explicit formulae to the leading order term in the near integrable return map are derived. Near integrability is also shown to persist when the hard billiard boundary is replaced by a singular, smooth, steep potential, thus extending the near-integrability results beyond the scope of regular perturbations. These systems constitute an additional class of examples of near integrable impact systems, beyond the traditional one dimensional oscillating billiards, nearly elliptic billiards, and the near-integrable behavior near the boundary of convex smooth billiards with or without magnetic field. Copyright © 2018, The Authors. All rights reserved.

关键词： Degrees of freedom (mechanics)

Weight stability intervals for multi-criteria decision analysis using the weighted sum model

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Expert Systems with Applications 2025年

作者： Richard O’Shea Peter Deeney Evangelos Triantaphyllou Luis Diaz-Balteiro S. Armagan Tarim Civil Structural and Environmental Engineering School of Engineering and Architecture University College Cork Cork Ireland MaREI – SFI Research Centre for Energy Climate and Marine Cork Ireland Cleaner Production Promotion Unit Environmental Research Institute University College Cork Ireland Division of Computer Science & Engineering College of Engineering Louisiana State University Baton Rouge LA 70803 USA Department of Medicine Section of Hematology & Med Oncology School of Medicine Tulane University New Orleans LA 70112 USA Forestry School Universidad Politécnica de Madrid Spain Cork University Business School University College Cork Ireland

Multi-criteria decision analysis (MCDA), or multi-criteria decision making (MCDM) encompasses a wide set of mathematical methods to compare alternatives whilst considering multiple criteria and the relative importance (weight) of each criterion or the allowable trade-off between criteria. MCDA/MCDM may be implemented in a decision support system to aid decision makers compare multiple alternatives. A key consideration in any MCDA is the sensitivity of the results obtained to alterations of the criteria weights used. Prior methods to determine the weight stability interval ( WSI , the range of values for individual weights for which the ranking of alternatives will not change) include the manual alteration of criteria weights, the use of different sets of criteria weights in a form of scenario analysis, or the process of iteratively searching for the maximum and minimum allowable alterations to individual criteria weights to determine the weight stability interval. The first contribution of this paper is the development of a novel method for determining precise weight stability intervals which does not rely on enumeration or simulation for use with the weighted sum model (WSM, based on the L 1 Minkowski norm), one of the most widely used aggregation methods within MCDA. The second contribution of this work is the use of these WSI s to identify the most sensitive weight(s) based on a Pareto dominance approach whilst considering both the allowable increase and decrease in criteria weights. The above points are demonstrated and applied in an analysis of several alternatives for renewable energy (biogas) production.

关键词： Multiple criteria analysis Multi-criteria decision analysis Multi-criteria decision making sensitivity analysis Weight stability interval

Spinnaker 2: A 10 million core processor system for brain simulation and machine learning

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arXiv 2019年

作者： Mayr, Christian Hppner, Sebastian Furber, Steve Chair of Highly-Parallel VLSI-Systems and Neuromorphic Circuits Institute of Circuits and Systems Technische Universitt Dresden Dresden Germany Advanced Processor Technologies Group School of Computer Science University of Manchester Manchester United Kingdom

SpiNNaker is an ARM-based processor platform optimized for the simulation of spiking neural networks. This brief describes the roadmap in going from the current SPINNaker1 system, a 1 Million core machine in 130nm CMOS, to SpiNNaker2, a 10 Million core machine in 22nm FDSOI. Apart from pure scaling, we will take advantage of specific technology features, such as runtime adaptive body biasing, to deliver cutting-edge power consumption. Power management of the cores allows a wide range of workload adaptivity, i.e. processor power scales with the complexity and activity of the spiking network. Additional numerical accelerators will enhance the utility of SpiNNaker2 for simulation of spiking neural networks as well as for executing conventional deep neural networks. These measures should increase the simulation capacity of the machine by a factor >50. The interplay between the two domains, i.e. spiking and rate based, will provide an interesting field for algorithm exploration on SpiNNaker2. Apart from the platforms' traditional usage as a neuroscience exploration tool, the extended functionality opens up new application areas such as automotive AI, tactile internet, industry 4.0 and biomedical processing. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep neural networks

Retraction notice to "An efficient and magnetically recoverable g-C3N4/ZnS/CoFe2O4 nanocomposite for sustainable photodegradation of organic dye under UV-visible light illumination" [Environ. Res. 201 (2021) 111429]

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Environmental research 2025年 279卷 121909页

作者： G Palanisamy Nora Hamad Al-Shaalan K Bhuvaneswari G Bharathi G Bharath T Pazhanivel Sathishkumar V E Madan Kumar Arumugam S K Khadeer Pasha Mohamed A Habila Adel El-Marghany Department of Physics Periyar University Salem 636 011 Tamil Nadu India. Department of Chemistry College of Science Princess Nourah bint Abdulrahman University Riyadh 11671 Saudi Arabia. Key Laboratory of Optoelectronic Devices and Systems of Guangdong Province College of Optoelectronic Engineering Shenzhen University Shenzhen Guangdong Province 518060 PR China. Department of Chemical Engineering Khalifa University P.O. Box 127788 Abu Dhabi United Arab Emirates. Department of Computer Science and Engineering Kongu Engineering College Perundurai Erode 638101 Tamil Nadu India. Cancer Biology Lab Centre for Molecular and Nanomedical Sciences Sathyabama Institute of Science and Technology Chennai 600119 India. Department of Physics VIT-AP University Amaravati Guntur 522501 Andhra Pradesh India. Advanced Materials Research Chair Chemistry Department College of Science King Saud University Riyadh 11451 Saudi Arabia.

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Fungal electronics

arXiv 2021年

作者： Adamatzky, Andrew Ayres, Phil Beasley, Alexander E. Chiolerio, Alessandro Dehshibi, Mohammad M. Gandia, Antoni Albergati, Elena Mayne, Richard Nikolaidou, Anna Roberts, Nic Tegelaar, Martin Tsompanas, Michail-Antisthenis Phillips, Neil Wösten, Han A.B. Unconventional Computing Laboratory UWE Bristol United Kingdom The Centre for Information Technology and Architecture Royal Danish Academy Copenhagen Denmark Centre for Engineering Research University of Hertfordshire United Kingdom Center for Bioinspired Soft Robotics Istituto Italiano di Tecnologia Via Morego 30 Genova10163 Italy Department of Computer Science Multimedia and Telecommunications Universitat Oberta de Catalunya Barcelona Spain Institute for Plant Molecular and Cell Biology CSIC-UPV Valencia Spain Department of Design Politecnico di Milano Milan Italy MOGU S.r.l. Inarzo Italy Microbiology Department of Biology University of Utrecht Utrecht Netherlands

Fungal electronics is a family of living electronic devices made of mycelium bound composites or pure mycelium. Fungal electronic devices are capable of changing their impedance and generating spikes of electrical potential in response to external control parameters. Fungal electronics can be embedded into fungal materials and wearables or used as stand alone sensing and computing devices. Copyright © 2021, The Authors. All rights reserved.

关键词： Fungi

HYPA: Efficient detection of path anomalies in time series data on networks

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arXiv 2019年

作者： LaRock, Timothy Nanumyan, Vahan Scholtes, Ingo Casiraghi, Giona Eliassi-Rad, Tina Schweitzer, Frank Network Science Institute Northeastern University United States Chair of Systems Design ETH Zürich Switzerland Chair of Data Analytics University of Wuppertal Germany Data Analytics Group IfI University of Zürich Switzerland Khoury College of Computer Sciences Northeastern University United States

The unsupervised detection of anomalies in time series data has important applications in user behavioral modeling, fraud detection, and cybersecurity. Anomaly detection has, in fact, been extensively studied in categorical sequences. However, we often have access to time series data that represent paths through networks. Examples include transaction sequences in financial networks, click streams of users in networks of cross-referenced documents, or travel itineraries in transportation networks. To reliably detect anomalies, we must account for the fact that such data contain a large number of independent observations of paths constrained by a graph topology. Moreover, the heterogeneity of real systems rules out frequency-based anomaly detection techniques, which do not account for highly skewed edge and degree statistics. To address this problem, we introduce HYPA, a novel framework for the unsupervised detection of anomalies in large corpora of variable-length temporal paths in a graph. HYPA provides an efficient analytical method to detect paths with anomalous frequencies that result from nodes being traversed in unexpected chronological order. Copyright © 2019, The Authors. All rights reserved.

关键词： Anomaly detection

Multi-objective identification from fluorescence recovery after photobleaching experiments: Understanding morphogenetic regulation of epithelial polarity⁎

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IFAC-PapersOnLine 2018年第19期51卷 8-11页

作者： Vignoni, A. Bajur, A. Knust, E. Sbalzarini, I.F. Max Planck Institute of Molecular Cell Biology and Genetics Dresden01307 Germany MOSAIC Group Center for Systems Biology Dresden Dresden01397 Germany Chair of Scientific Computing for Systems Biology Faculty of Computer Science Technische Universität Dresden Dresden01187 Germany

Many of the processes related to morphogenesis depend critically on the maintenance of the spatial distribution of certain polarity proteins on the plasma membrane of the cell. Maintenance of this epithelial polarity depends on the localization and concentration of the polarity proteins. The transmembrane protein Crumbs (Crb) is vital for the dimensions and integrity of the apical membrane. However, there is a little knowledge on the molecular mechanism controlling Crumbs dynamics during morphogenesis. Fluorescence recovery after photobleaching (FRAP) is a live cell imaging technique allowing for the functional measurement of protein mobility in living cells. FRAP experiments we performed in different parts of the Drosophila melanogaster embryonic epithelium and in different developmental stages show significant differences in their characteristics. We analyze the relationship of the changes in the FRAP experiments with the different morphogenetic states of the embryo. To this end, we develop a reaction-diffusion spatiotemporal model involving processes in the membrane and in the cytosol. Moreover, we model the fluorescent tags of proteins and the bleaching process to get in silico FRAP experiments. These in silico FRAPs are then used together with the experimental data to perform parameter estimation based on a multi-objective optimization design procedure. The multi-objective optimization is suitable to understand how morphogenetic events result in different sets of model parameters. Our parameter identification can reveal the mechanisms involved in the regulation of the Crb protein in the different stages of embryonic development and how morphogenesis affects these mechanisms. © 2018

关键词： Multiobjective optimization Bioinformatics Cell membranes Cytology Fluorescence Molecular biology Morphology Parameter estimation Photobleaching Proteins Biological modeling Drosophila melanogaster Epithelial cells Fluorescence recovery after photobleaching Functional measurements Spatio temporal models Systems simulation Trans membrane proteins

TiCoNE 2: A composite clustering model for robust cluster analyses on noisy data

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arXiv 2019年

作者： Wiwie, Christian Röttger, Richard Baumbach, Jan Institute of Mathematics and Computer Science University of Southern Denmark Campusvej 55 OdenseDK-5230 Denmark Chair of Experimental Bioinformatics Technical University of Munich Maximus-von-Imhof-Forum 3 Freising-Weihenstephan85354 Germany

Identifying groups of similar objects using clustering approaches is one of the most frequently employed first steps in exploratory biomedical data analysis. Many clustering methods have been developed that pursue different strategies to identify the optimal clustering for a data set. We previously published TiCoNE, an interactive clustering approach coupled with de-novo network enrichment of identified clusters. However, in this first version time-series and network analysis remained two separate steps in that only time-series data was clustered, and identified clusters mapped to and enriched within a network in a second separate step. In this work, we present TiCoNE 2: An extension that can now seamlessly incorporate multiple data types within its composite clustering model. Systematic evaluation on 50 random data sets, as well as on 2,400 data sets containing enriched cluster structure and varying levels of noise, shows that our approach is able to successfully recover cluster patterns embedded in random data and that it is more robust towards noise than non-composite models using only one data type, when applied to two data types simultaneously. Herein, each data set was clustered using five different similarity functions into k=10/30 clusters, resulting to ~5,000 clusterings in total. We evaluated the quality of each derived clustering with the Jaccard index and an internal validity score. We used TiCoNE to calculate empirical p-values for all generated clusters with different permutation functions, resulting in ~80,000 cluster p-values. We show, that derived p-values can be used to reliably distinguish between foreground and background clusters. TiCoNE 2 allows researchers to seamlessly analyze time-series data together with biological interaction networks in an intuitive way and thereby provides more robust results than single data type cluster analyses. Copyright © 2019, The Authors. All rights reserved.

关键词： Cluster analysis

Work in Progress – Establishing a Master Program in Cyber Physical Systems: Basic Findings and Future Perspectives

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Work in Progress – Establishing a Master Program in Cyber P...

International Conference on Promising Electronic Technologies (ICPET)

作者： Isam Ishaq Rashid Jayousi Salaheddin Odeh Ezzaldeen Edwan Asmaa Shaheen Mohamed Elnaggar Ahmed Elagha Samy Salamah Christian Weber Hasan Abu Rasheed Raimund Kirner Martina Doolan Hamidreza Ahmadian Roman Obermaisser Dhiah el Diehn I. Abou-Tair Ala Khalifeh Sahel Alouneh Zaid Alhalhouli Khalid Alemerien Faiez Gargouri Bassem Bouaziz Nadia Aloui Mohammad Saleh Computer Engineering and Science Departments Al-Quds University Jerusalem Palestine Engineering Program and Computer Department Palestine Technical College - Deir El-Balah Deir El-Balah Palestine Institute of Knowledge Based Systems & Knowledge Management University of Siegen Siegen Germany University of Siegen Siegen Germany School of Engineering and Computer Science University of Hertfordshire Hatfield UK Chair of Embedded Systems University of Siegen Siegen Germany German Jordanian University Amman Jordan School of Electrical Engineering and Information Technology German Jordanian University Amman Jordan Computer and Information Technology Department Tafila Technical University Tafila Jordan Higher Institute of Computer Science and Multimedia University of Sfax Sfax Tunisia Higher Institute of Applied Sciences and Technology of Mateur University of Carthage Mateure Tunisia KTH Royal Institute of Technology Stockholm Sweden

This paper reports on the basic findings and future perspectives of a capacity building project funded by the European Union. The International Master of science on Cyber Physical Systems (MS@CPS) is a collaborative project that aims to establish a master program in cyber physical systems (CPS). A consortium composed of nine partners proposed the project. Three partners are European and from Germany, UK and Sweden; while the other six partners are from the South Mediterranean region and include: Palestine, Jordan and Tunisia. The consortium is led by the University of Siegen in Germany who also manages the implementation of the work packages. CPS is an emerging engineering subject with significant economic and societal implications, which motivated the consortium to propose the establishment of a master program to offer educational and training opportunities at graduate level in the fields of CPS. In this paper, CPS as a field of study is presented with an emphasis on its importance, especially with regard to meeting local needs. A brief description of the project is presented in conjunction with the methodology for developing the courses and their learning outcomes.

关键词： computer science Internet of Things Industries Knowledge engineering Embedded systems Europe Collaboration