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arXiv 2024年

作者： Kirillov, Anatol Nenashev, Gleb Shapiro, Boris Vaintrob, Arkady Yanqi Lake Beijing Institute of Mathematical Sciences and Applications Huairou District Beijing China Department of Mathematics and Computer Science St. Petersburg State University St. Petersburg199178 Russia Department of Mathematics Stockholm University StockholmSE-106 91 Sweden Department of Mathematics University of Oregon EugeneOR97403 United States

Zonotopal algebras (external, central, and internal) of an undirected graph G introduced by Postnikov-Shapiro and Holtz-Ron, are finite-dimensional commutative graded algebras whose Hilbert series contain a wealth of combinatorial information about G. In this paper, we associate to G a new family of algebras, which we call bizonotopal, because their definition involves doubling the set of edges of G. These algebras are monomial and have intricate properties related, among other things, to the combinatorics of graphical parking functions and their polytopes. Unlike the case of usual zonotopal algebras, the Hilbert series of bizonotopal algebras are not specializations of the Tutte polynomial of G. Still, we show that in the external and central cases these Hilbert series satisfy a modified deletion-contraction relation. In addition, we prove that the external bizonotopal algebra is a complete graph *** Codes 05C31 Primary 13F55, Secondary 05C31 © 2024, CC BY.

关键词： Undirected graphs

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Self-supervised Contrastive Learning for Volcanic Unrest Detection

arXiv

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arXiv 2022年

作者： Ioannis, Bountos Nikolaos Papoutsis, Ioannis Michail, Dimitrios Anantrasirichai, Nantheera Institute of Astronomy Astrophysics Space Applications & Remote Sensing National Observatory of Athens Department of Informatics & Telematics Harokopio University of Athens Greece Department of Computer Science University of Bristol United Kingdom

Ground deformation measured from Interferometric Synthetic Aperture Radar (InSAR) data is considered a sign of volcanic unrest, statistically linked to a volcanic eruption. Recent studies have shown the potential of using Sentinel-1 InSAR data and supervised deep learning (DL) methods for the detection of volcanic deformation signals, towards global volcanic hazard mitigation. However, detection accuracy is compromised from the lack of labelled data and class imbalance. To overcome this, synthetic data are typically used for finetuning DL models pretrained on the ImageNet dataset. This approach suffers from poor generalisation on real InSAR data. This letter proposes the use of self-supervised contrastive learning to learn quality visual representations hidden in unlabeled InSAR data. Our approach, based on the SimCLR framework, provides a solution that does not require a specialized architecture nor a large labelled or synthetic dataset. We show that our self-supervised pipeline achieves higher accuracy with respect to the state-of-the-art methods, and shows excellent generalisation even for out-of-distribution test data. Finally, we showcase the effectiveness of our approach for detecting the unrest episodes preceding the recent Icelandic Fagradalsfjall volcanic eruption. © 2022, CC BY-SA.

关键词： Volcanoes

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Integration of allocentric and egocentric visual information in a convolutional/multilayer perceptron network model of goal-directed gaze shifts

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Cerebral Cortex 2022年第3期3卷 026-026页

作者： Abedi Khoozani, Parisa Bharmauria, Vishal Schutz, Adrian Wildes, Richard P Crawford, J. Douglas Centre for Vision Research and Vision: Science to Applications (VISTA) Program York University Toronto M3J 1P3 ON Canada Department of Neurophysics Phillips-University Marburg Marburg 35037 Germany Department of Electrical Engineering and Computer Science York University Toronto M3J 1P3 ON Canada Departments of Psychology Biology and Kinesiology & Health Sciences York University Toronto M3J 1P3 ON Canada

Allocentric (landmark-centered) and egocentric (eye-centered) visual codes are fundamental for spatial cognition, navigation, and goal-directed movement. Neuroimaging and neurophysiology suggest these codes are initially segregated, but then reintegrated in frontal cortex for movement control. We created and validated a theoretical framework for this process using physiologically constrained inputs and outputs. To implement a general framework, we integrated a convolutional neural network (CNN) of the visual system with a multilayer perceptron (MLP) model of the sensorimotor transformation. The network was trained on a task where a landmark shifted relative to the saccade target. These visual parameters were input to the CNN, the CNN output and initial gaze position to the MLP, and a decoder transformed MLP output into saccade vectors. Decoded saccade output replicated idealized training sets with various allocentric weightings and actual monkey data where the landmark shift had a partial influence (R2 = 0.8). Furthermore, MLP output units accurately simulated prefrontal response field shifts recorded from monkeys during the same paradigm. In summary, our model replicated both the general properties of the visuomotor transformations for gaze and specific experimental results obtained during allocentric-egocentric integration, suggesting it can provide a general framework for understanding these and other complex visuomotor behaviors. © 2022 The Author(s). Published by Oxford University Press.

关键词： allocentric convolutional network egocentric multilayer perceptron saccades

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A pragmatic cybersecurity strategies for combating IoT-cyberattacks

A pragmatic cybersecurity strategies for combating IoT-cyber...

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2020 International Symposium on Networks, computers and Communications, ISNCC 2020

作者： Djenna, Amir Saidouni, Djamel Eddine Abada, Wafia University Constantine2 Faculty of New Technologies of Information and Communication Department of Computer Science and Applications Constantine Algeria

ISBN: (纸本)9781728156286

Massive Cyberattacks, especially Distributed Denial of Service (DDoS), remain an overwhelming threat to new emerging computer paradigms such as Cloud Computing and Internet of Things, deployed within critical infrastructures (healthcare, aviation, energy, industrial control and military). Furthermore, conventional security approaches and strategies are no longer appropriate to deal with this kind of cyberattacks, for the reason that they have major limitations. Consequently, identification and efficient detection of anomalies in this context requires not only suitable mechanisms integrating correct detection, but also early detection with an autonomous operating mode. This paper focuses on DDoS cyberattack detection and mitigation method based on artificial intelligence model affecting IoT network infrastructure. © 2020 IEEE.

关键词： Cybersecurity

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An experimental study to recognize and mitigate the malevolent attack in wireless sensors networks

Global Transitions Proceedings

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Global Transitions Proceedings 2022年第1期3卷 55-59页

作者： Sankar Padmanabhan R. Maruthi R. Anitha Hindustan Institute of Technology and science Department of Electronics and Communication EngineeringOMR Padur Chennai Tamilnadu India Hindustan Institute of Technology and science Department of Computer Applications OMR Padur Chennai India Hindustan Institute of Technology and science Departmnet of Bio Technology OMR Padur Chennai Tamilnadu India

The Wireless Sensor Network (WSN)is applied in several networking situations. It suffers from dissimilar types of attack because of its meagre security mechanisms. The Sinkhole attack is the most destructive attack of WSN. A Reliable Self Reconfiguration (RSR) mechanism has been suggested in this work to eliminate the malicious sinkhole attack from the network. The proposed reliable reconfiguration (RSR)) system consists of two steps. The malicious node is detected and after detection it is corrected without resource loss by using the reconfiguration mechanism. In this paper, the reconfiguration mechanism for correcting sinkhole attack is applied using the C++ built simulator and factors such as Packet Delivery ratio and energy consumption are obtained for estimation The differences in the energy level have been calculated for the three scenarios i.e., Network without attack, Network with sinkhole attack and Network after Reconfiguration. The proposed Reliable Self-Reconfiguration (RSR) method outperforms the various detection mechanisms in finding and eliminating the sinkhole attack.

关键词： Attack Energy Reconfiguration mechanism Sinkhole Wireless sensor networks

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Enhanced Particle Swarm Optimization based Node Localization Scheme in Wireless Sensor Networks

Enhanced Particle Swarm Optimization based Node Localization...

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2022 International Conference on Augmented Intelligence and Sustainable Systems, ICAISS 2022

作者： Singh, Shashank Poonkuzhali, R. Nithya, G. Kumar, R. Anil Kartigeyan, J. Ramya, S. Department of Computer Science and Engineering Integral University Kurshi Road Uttar Pradesh Lucknow India Department of Information Technology K.S.Rangasamy College of Technology Tamilnadu Tiruchengode India Department of Electronics and Communication Engineering Malla Reddy Engineering College for Women Maisammaguda Telangana Secunderabad India Electronics and Communication Engineering Aditya College of Engineering and Technology Andhra Pradesh Surampalem India Department of Electrical and Electronics Engineering J.B.Institute of Engineering and Technology Telangana Hyderabad India Master of Computer Applications M.Kumarasamy College of Engineering Karur Tamilnadu Thalavapalayam India

ISBN: (纸本)9781665489621

Wireless sensor networks (WSNs) are widely examined recently because of their various applications in processes which has to scatter over a vast region. sensor's locations in WSNs generally must be known. WSN comprises great quantity of sensors thereby installing global position system devices in all of them does not accept. Some of the anchor nodes with well-known locations are generally utilized. Forecasting sensor node locations from radio strength signal index are regarded as a hard optimization issue. This article introduces an Enhanced Particle Swarm Optimization based Node Localization Scheme (EPSONLS) in WSN. The presented EPSONLS technique mainly aims to determine the location of the unknown nodes in the network. To do so, the presented EPSONLS model applies the PSO algorithm to identify the node position. In addition, the EPSONLS model determines the node location with the goal of minimizing localization error and time. An extensive-ranging experimental examination is performed and the outcomes are investigated under distinct prospects. The simulation outcome demonstrated the betterment of the EPSONLS model over recent approaches. © 2022 IEEE.

关键词： Sensor nodes

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Artificial Intelligence and Digital Media Industry Through Social Media Based on OpenAI Technology in the Indonesian Presidential Election 2024

Artificial Intelligence and Digital Media Industry Through S...

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International Conference on Smart Computing & Communications (ICSCC)

作者： I Gusti Ayu Agung Dewi Sucitawathi Pinatih Ni Putu Bayu Widhi Antari Kacung Marijan Gopal Sakarkar Public Administration Master's Study Program Universitas Pendidikan Nasional Denpasar Indonesia Public Administration Study Program Universitas Pendidikan Nasional Denpasar Indonesia Political Department Universitas Airlangga Surabaya Indonesia Department of Computer Science and Applications Dr. Vishwanath Karad MIT World Peace University Pune India

ISBN: (数字)9798350363104

ISBN: (纸本)9798350363111

This research aims to explain the use of social media based on OpenAI technology in the 2024 Presidential Election in Indonesia. The methodology used is based on a descriptive qualitative study with primary and secondary data analysis techniques. Primary data was obtained through interviews with academician in the fields of political marketing and academician in the fields of information technology. Secondary data was obtained through several journal literatures and official websites related to the research topic. The validity of the data is obtained through source triangulation based on interview data from different informants and documentation studies to obtain valid information. This study found that the use of AI-based social media is based on the advantages of OpenAI's more sophisticated technological features, fast and real-time data analysis capabilities, and content visualization capability of image rebranding.

关键词： Technological innovation Data analysis Social networking (online) Voting Data visualization Media Market research Real-time systems Interviews Information technology

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An Efficient Task Scheduling Strategy for DAG in Cloud Computing Environment 1

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International Conference on Recent Advancement in computer, Communication and Computational sciences, RACCCS 2019

作者： Rajak, Nidhi Shukla, Diwakar Department of Computer Science and Applications Dr. Harisingh Gour Central University SagarM.P. India

ISBN: (数字)9789811515187

ISBN: (纸本)9789811515170

Cloud computing is an active research topic in computer science and its popularity is increasing day-to-day due to the high demand of cloud in every field. Data center in cloud platform is having the number of computing resources which are interconnected with very high-speed network. These resources are accessed at the rapid speed so that minimum interaction with service provider. Task scheduling is a burning area of research in cloud environment. Here an application program is represented by directed acyclic graph (DAG). Major concerned of the task scheduling method is to reduce overall execution time. i.e., to minimize the makespan. This paper presents a new strategy for task scheduling in DAG which based on two well-known attributes critical path and static level. By using these attributes, we have developed new attributes CPS which is summation of critical path and static level. New strategy works on two phases such as task priority and resource selection. The proposed method is tested using two DAG models which shows outperformance as compared to heuristic algorithm HEFT. Comparisons have been done using some performance metrics which also gives good result of proposed method. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Cloud computing

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Hybrid Technology Based Smart Hostel Management System Using Artificial Intelligence and Internet of Things

Hybrid Technology Based Smart Hostel Management System Using...

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International Conference on Emerging Research in Electronics, computer science and Technology (ICERECT)

作者： Shashank Bhardwaj Venkadeshwaran K Meraj Farheen Ansari Bibhu Prasad Dash Pawankumar Sharma Devesh Pratap Singh Department of Computer Applications Dr. A.P.J. Abdul Kalam Technical University Lucknow India Department of Mechanical Engineering JAIN University Bangalore India Department of Information Technology University of the Cumberlands Williamsburg USA School of computer and information sciences University of the Cumberlands Williamsburg USA Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun India

Notably in the last ten years, the number of learning organizations throughout the globe has grown at an unmatched pace. Teaching has now reached homesteads thanks to the growth. As a consequence, worldwide literacy levels have increased significantly in recent decades. As per reports, just 12% of the populace knew comprehend and write in 1820; nevertheless, data currently show a dramatic shift in or reversal of this trend: Figures prove that amongst 1820 and 2016, the high school graduation rate rose by 72%. If the pace of growth is considered, it is around 4% per five years, rising from 42percentage points in 1970 to 86% in 2015. Proper training has benefited in the development of intelligent people who can easily embrace and establish regulations for a civilized country, improving it and making an important contribution. However, the majority of recently built academic system, particularly dormitory amenities, still manage their possessions and property using outdated traditional methods. After the dotcom boom, digital services and products have advanced significantly. The cost of using the net is also decreasing, and its growth has been facilitated by faster internet. It is simple to assert that contemporary civilization now includes this digital age. The need for a growing percentage of world wide web gadgets has grown due to this change in social cognition from citizenry to bloggers. The popularity of smart homes or other Cellular solutions is rising. Nowadays, using the Internet as a resource to address problems is common. We've been staying in hostels nearly five years, we've discovered a number of major issues that impact every person with the help of the survey and our own findings. We've developed a solid and intelligent conceptual model as part of the technological study that promises to solve these problems by leveraging snipping innovations, notably AI (Artificial Intelligence) and IOT (Internet of Things), with sufficient evidence and verification. We

关键词： Training Visualization Technological innovation Solid modeling Smart homes User interfaces Solids

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Complex Event Processing in Web Streams with Ontology-Based Abstraction Layers for Smart City Frameworks

Complex Event Processing in Web Streams with Ontology-Based ...

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Trends in Quantum Computing and Emerging Business Technologies (TQCEBT), International Conference on

作者： M Hari KrishnA Manjunatha Rakesh Kumar Navdeep Singh Ashwani Kumar Adnan Allawi Ftaiet Institute of Aeronautical Engineering Hyderabad Department of Mechanical Engineering New Horizon College of Engineering Bangalore Department of Computer Engineering & Applications GLA University Mathura Lovely Professional University Phagwara Lloyd Institute of Engineering & Technology Greater Noida Uttar Pradesh College of Technical Engineering National University of Science and Technology Dhi Qar Iraq

ISBN: (数字)9798350384277

ISBN: (纸本)9798350384284

Smart cities embody the integration of information technology, urban infrastructure, and citizen engagement to optimize city functions and drive economic growth. A critical component in achieving this integration is the ability to process complex events in real-time, particularly from diverse web streams. This paper introduces a novel framework for Complex Event Processing (CEP) in web streams by employing ontology-based abstraction layers, aiming to enhance the interpretability and interoperability of heterogeneous data sources within smart city frameworks. The proposed approach uses a layered architecture where the bottom layer deals with raw data streams from various sources, including IoT devices, social media, and sensor networks. The middle layer employs an ontology-based model to abstract and enrich the raw data, providing a unified and semantic representation. This representation facilitates the identification and correlation of complex events, which are pertinent to city management and planning. The top layer involves the application of advanced data mining techniques to predict, detect, and respond to urban events in a timely and efficient manner. Through this methodology, the framework addresses the challenges of scalability, semantic heterogeneity, and real-time processing needs inherent in smart city applications. Empirical evaluations demonstrate the efficacy of the approach in various urban scenarios, showing promising improvements over existing methods. This work lays a foundational architecture for future research and development in smart city technologies, aiming to make urban areas more livable, sustainable, and efficient.

关键词： Smart cities Social networking (online) Scalability Soft sensors Ontologies Real-time systems Service-oriented architecture

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