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Applying LSTM for River's Water Level Forecasting as Potential Flood Indication: A Case Study in Greece 15

Applying LSTM for River's Water Level Forecasting as Potenti...

引用

15th International Conference on Information, Intelligence, systems and Applications, IISA 2024

作者： Tziolas, Theodoros Papageorgiou, Elpiniki Papageorgiou, Konstantinos Zardas, Georgios Lekidis, Alexios Panagiotis, Papazoglou University of Thessaly Dept. of Energy Systems Gaiopolis Campus Larisa41500 Greece University of Thessaly Dept. of Electrical and Computer Engineering Volos Greece National and Kapodistrian University of Athens Dept. of Architecture and Computer and Communication Simulation Systems Chalkida Greece

ISBN: (纸本)9798350368833

Floods can have significant life-threatening and economic impacts on human societies. Flood forecasting with data-driven methods is a crucial aspect of disaster risk management, providing valuable insights into potential flood events and allowing for timely mitigation measures. This work illustrates the application of a Long Short-Term Memory (LSTM) neural network for short-term forecasting of a river's water level. The water treatment data used for training the LSTM models were gathered from Sperchios river, located in central Greece. Historical time-series data in a half-hour interval of the river's water level, water velocity, and area precipitation were utilized for the development of the proposed scheme. The developed model is deployed in the backend of a web application for half-hour ahead predictions of the river's water level that are visualized in the frontend. The post-analysis of the deployed forecasting model indicates that it consistently delivers forecasts with minimal error and demonstrates high accuracy in recent flood events. © 2024 IEEE.

关键词： Rivers

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Development of an Ontology for Bulgarian Soil Types

Development of an Ontology for Bulgarian Soil Types

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2023 International Conference Automatics and Informatics, ICAI 2023

作者： Stoyanova-Doycheva, Asya Madanska, Sebiha Bilyanov, Sheban University of Plovdiv 'Paisii Hilendarski' Dept. of Computer Systems Plovdiv Bulgaria Iict Bulgarian Academy of Sciences Sofia Bulgaria University of Architecture Civil Engineering and Geodesy Dept. of Residential Buildings Sofia Bulgaria

ISBN: (纸本)9798350312911

The article presents the development of an ontology for the Taxonomic List of Soils in Bulgaria (according to the FAO World System). In addition to soil types, the ontology includes knowledge about the different agro-climatic regions in Bulgaria that are suitable for cultivating various agricultural crops. The ontology is part of the knowledge base of the ZEMELA platform for smart agriculture. © 2023 IEEE.

关键词： Soils

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BC4ECO - Using Visual Tools for a Shared Understanding and Pedagogical Approach across an Interdisciplinary Consortium 47

BC4ECO - Using Visual Tools for a Shared Understanding and P...

引用

47th IEEE Annual computers, Software, and Applications Conference, COMPSAC 2023

作者： Peruccon, Andy Lyons, Roisin De Gotzen, Amalia Margaria, Tiziana Simeone, Luca Design and Media Technology Aalborg University Dept. of Architecture Copenhagen Denmark Kemmy Business School University of Limerick Limerick Ireland University of Limerick Dept. of Computer Science and Information Systems Limerick Ireland

ISBN: (纸本)9798350326970

Effective communication is crucial when working on complex or wicked problems in interdisciplinary, international teams. Developing a shared understanding of critical concepts and aligning knowledge, focus, and resources can be problematic when stakeholders speak different languages, span several disciplines and work within different national or industry-based norms. Using visual tools to represent critical concepts and their relations, and map out our strategic goals has greatly helped combat such issues. This paper recounts the use and impact of adopting visual tools within the transnational and interdisciplinary collaborative environment in the BC4ECO project's international consortium. The Miro Board and the canvas approach greatly helped represent, visualise, and thus concretise the structure and contents of our collaboration, which takes place within a 3 years ERASMUS+ framework that builds and delivers Summer School, MOOCS as well as teacher and multiplier events about harnessing the potential of Distributed Ledger Technologies (DLTs) for environmental sustainability. As the materials and MOOCS are expected to become Open Education Resources and have a wide impact, it is particularly crucial to get the contents as well as the pedagogy right, in spite of the team's differences in almost any dimension of background and culture. © 2023 IEEE.

关键词： Blockchain

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Scalable Event-by-Event Processing of Neuromorphic Sensory Signals with Deep State-Space Models

Scalable Event-by-Event Processing of Neuromorphic Sensory S...

引用

2024 International Conference on Neuromorphic systems, ICONS 2024

作者： Schone, Mark Sushma, Neeraj Mohan Zhuge, Jingyue Mayr, Christian Subramoney, Anand Kappel, David Ruhr University Bochum Institut für Neuroinformatik Germany Highly-Parallel VLSI-Systems and Neuro-Microelectronics TU Dresden Dresden Germany Dresden Germany with Human-in-the-Loop Dresden Germany University of London Royal Holloway Dept. of Computer Science Egham United Kingdom

ISBN: (纸本)9798350368659

Event-based sensors feature valuable properties for real-time processing such as fast response times and encoding of the sensory data as successive temporal differences. However, most current methods either collapse events into frames, therefore suppressing these properties, or cannot scale up when processing the event data directly event-by-event. In this work, we address the key challenges of scaling up event-by-event modeling of the long event streams emitted by such sensors, which is a particularly relevant problem for neuromorphic computing. While prior methods can process up to a few thousand time steps, our model, based on modern recurrent deep state-space models, scales to event streams of millions of events for both training and inference. We leverage their stable parameterization for learning long-range dependencies, parallelizability along the sequence dimension, and their ability to integrate asynchronous events effectively to scale them up to long event streams. We further augment these with novel event-centric techniques enabling our model to match or beat the state-of-the-art performance on several event stream benchmarks. In the Spiking Speech Commands task, we improve state-of-the-art by a large margin of 7.7 % to 88.4 %. On the DVS128-Gestures dataset, we achieve competitive results without using frames or convolutional neural networks. Our work demonstrates, for the first time, that it is possible to use fully event-based processing with purely recurrent networks to achieve state-of-the-art task performance in several event-based benchmarks. © 2024 IEEE.

关键词： Convolutional neural networks

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Triple-Node-Upset Recoverable Radiation-Hardened by Design Latch

Triple-Node-Upset Recoverable Radiation-Hardened by Design L...

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Panhellenic Conference on Electronics and Telecommunications (PACET)

作者： Evangelos Paparsenos Yiorgos Tsiatouhas Dept. of Computer Science and Engineering VLSI Systems and Computer Architecture (VCAS) Lab University of Ioannina Ioannina Greece

CMOS technology evolution enhances integrated circuits (ICs) performance characteristics at the cost of their increased susceptibility to radiation and thus to the occurrence of single-event upsets (SEUs) that may lead to soft errors generation. SEUs may affect multiple nodes in a circuit (multiple node upsets - MNUs). Fortunately, these disturbances do not cause permanent damage to the circuits. Various techniques have been proposed to deal with SEUs that concurrently affect one, two or three nodes. In this paper, we propose the design of a latch that offers tolerance up to the level of triple-node upsets (TNUs). This is achieved by using redundancy in the hardware which provides the ability to store a logic value in multiple nodes within the latch as well as by using multiple feedback paths which allow it to recover its correct state in the event of an SEU. Compared to other techniques dealing with the same problem, our proposed method provides faster recovery time (higher than 16.87%) after an SEU, and at the same time reduced power consumption and higher speed performance.

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Stealthy Attack Detection of controlled ramp meters in freeway networks 63

Stealthy Attack Detection of controlled ramp meters in freew...

引用

63rd IEEE Conference on Decision and Control, CDC 2024

作者： Menelaou, Charalambos Zhang, Kangkang Timotheou, Stelios Panayiotou, Christos G. Parisini, Thomas University of Cyprus Kios CoE Dept. of Electrical and Computer Engineering Cyprus Imperial College London Dept. of Electrical and Electronic Engineering LondonSW7 2AZ United Kingdom Aalborg University Department of Electronic Systems Denmark University of Trieste Department of Engineering and Architecture Italy

ISBN: (纸本)9798350316339

The increasing reliance on intelligent transportation systems (ITS) for traffic management has simultaneously heightened the potential for cybersecurity threats. Malicious cyber attacks on such systems can lead to operational inefficiencies, heightened congestion, and compromised safety. This work introduces a stealthy integrity attack tailored for ramp metered freeway systems. The attack model is conceptualized as a closed-loop dynamical system, formulated as an optimization problem based on the Cell Transmission Model. This work further proposes a distributed detection mechanism designed to identify attack residuals, which, by incorporating an adaptive threshold scheme, can detect the presence of an attack. To demonstrate the efficacy of our detection scheme, we present a scenario illustrating its application in freeway road networks. © 2024 IEEE.

关键词： Cyber attacks

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Applying LSTM for River's Water Level Forecasting as Potential Flood Indication: A Case Study in Greece

Applying LSTM for River's Water Level Forecasting as Potenti...

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International Conference on Information, Intelligence, systems and Applications (IISA)

作者： Theodoros Tziolas Elpiniki Papageorgiou Konstantinos Papageorgiou Georgios Zardas Alexios Lekidis Papazoglou Panagiotis Dept. of Energy Systems University of Thessaly Gaiopolis Campus Larisa Greece Dept. of Electrical and Computer Engineering University of Thessaly Volos Greece Dept. of Architecture and Computer and Communication Simulation Systems National and Kapodistrian University of Athens Chalkida Greece

ISBN: (数字)9798350368833

ISBN: (纸本)9798350368840

关键词： Training Precipitation Biological system modeling Prevention and mitigation Neural networks Predictive models Rivers Floods Forecasting Long short term memory

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Dynamic Adaptation Gain Design and Tuning for Threat Discrimination 63

Dynamic Adaptation Gain Design and Tuning for Threat Discrim...

引用

63rd IEEE Conference on Decision and Control, CDC 2024

作者： Zhang, Kangkang Chen, Kaiwen Polycarpou, Marios M. Parisini, Thomas University of Cyprus Kios Research and Innovation Center of Excellence Dept. of Electrical and Computer Engineering Nicosia1678 Cyprus Imperial College London Dept. of Electrical and Electronic Engineering LondonSW7 2AZ United Kingdom Aalborg University Department of Electronic Systems Denmark University of Trieste Department of Engineering and Architecture Italy

ISBN: (纸本)9798350316339

Considering potential threats to cyber-physical systems such as component faults and stealthy cyber-attacks, an adaptive observer-based threat discrimination method is proposed for identifying the occurring threat type. Typically, stealthy attacks have only weak effects easily obscured by disturbances on the system outputs. To solve this problem, a parameter adaptation algorithm based on a newly designed dynamic adaptive gain generator is proposed, aiming at improving the sensitivity of the adaptive threat discrimination scheme to potential threats. Only the strictly positive real condition of the proposed gain generator sufficiently ensures the stability of the adaptive observer error system. A moment-matching method is then developed to determine the proper parameters of the gain generator, allowing for the improvement of the sensitivity of the threat discriminators. A numerical example to demonstrate the effectiveness of the proposed methodology is presented. © 2024 IEEE.

关键词： Cyber attacks

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Weight Sparsity Complements Activity Sparsity in Neuromorphic Language Models

Weight Sparsity Complements Activity Sparsity in Neuromorphi...

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2024 International Conference on Neuromorphic systems, ICONS 2024

作者： Mukherji, Rishav Schone, Mark Nazeer, Khaleelulla Khan Mayr, Christian Kappel, David Subramoney, Anand Birla Institute of Technology and Science Pilani Goa Campus Goa India TU Dresden Highly-Parallel VLSI-Systems and Neuro-Microelectronics Dresden Germany Dresden Germany with Human-in-the-Loop Dresden Germany Ruhr University Bochum Institut für Neuroinformatik Germany Royal Holloway University of London Dept. of Computer Science Egham United Kingdom

ISBN: (纸本)9798350368659

Activity and parameter sparsity are two standard methods of making neural networks computationally more efficient. Event-based architectures such as spiking neural networks (SNNs) naturally exhibit activity sparsity, and many methods exist to sparsify their connectivity by pruning weights. While the effect of weight pruning on feed-forward SNNs has been previously studied for computer vision tasks, the effects of pruning for complex sequence tasks like language modeling are less well studied since SNNs have traditionally struggled to achieve meaningful performance on these tasks. Using a recently published SNN-like architecture that works well on small-scale language modeling, we study the effects of weight pruning when combined with activity sparsity. Specifically, we study the tradeoff between the multiplicative efficiency gains the combination affords and its effect on task performance for language modeling. To dissect the effects of the two sparsities, we conduct a comparative analysis between densely activated models and sparsely activated event-based models across varying degrees of connectivity sparsity. We demonstrate that sparse activity and sparse connectivity complement each other without a proportional drop in task performance for an event-based neural network trained on the Penn Treebank and WikiText-2 language modeling datasets. Our results suggest sparsely connected event-based neural networks are promising candidates for effective and efficient sequence modeling. © 2024 IEEE.

关键词： Modeling languages

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Affine-NoC: Multi-ring NoCs exploiting long physical links

Affine-NoC: Multi-ring NoCs exploiting long physical links

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International Workshop on Network on Chip architectures, NoCArc

作者： Enrique Vallejo Evangelos Mageiropoulos Nikolaos Chrysos Manolis G.H. Katevenis Computer Science Dept. Universidad de Cantabria Spain Santander Spain Computer Architecture and VLSI Systems (CARV) Laboratory Foundation for Research and Technology – Hellas (FORTH) Heraklion Greece

ISBN: (数字)9798331506421

ISBN: (纸本)9798331506438

Routerless multi-ring proposals are low-cost NoCs that employ multiple independent rings, avoiding any crossbars or arbitration mechanisms. Their complexity lies on the selection of the set of rings to connect all the nodes. Previous proposals result in unbalanced designs with high hop *** work introduces Affine-NoC, a balanced routerless NoC based on a novel arrangement of rings derived from the Affine Plane. Affine-NoC exploits express channels to connect distant processing elements, allowing for a completely balanced layout of the set of rings and a reduction in average distance and diameter without sacrificing bisection *** shows that Affine-NoC presents a balanced design with a low number of rings per node and reduced complexity, similar cost to previous proposals in terms of aggregated link length, while it simplifies the multiplex units and reduces the hop count. Simulation results show that Affine-NoC reduces hop count and average latency by 76% and 20.5% respectively compared to previous designs, it reduces deflections by 27% and avoids unfairness, making it a feasible alternative for multi-ring routerless NoCs.

关键词： Multiplexing Network topology Flow production systems Simulation Layout computer architecture Complexity theory Topology Proposals Logic

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