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arXiv 2023年

作者： Naor, Moni Pekel, Eugene Department of Computer Science and Applied Math Weizmann Institute of Science

An adjacency sketching or implicit labeling scheme for a family F of graphs is a method that defines for any n vertex G ∈ F an assignment of labels to each vertex in G, so that the labels of two vertices tell you whether or not they are adjacent. The goal is to come up with labeling schemes that use as few bits as possible to represent the labels. By using randomness when assigning labels, it is sometimes possible to produce adjacency sketches with much smaller label sizes, but this comes at the cost of introducing some probability of error. Both deterministic and randomized labeling schemes have been extensively studied, as they have applications for distributed data structures and deeper connections to universal graphs and communication complexity. The main question of interest is which graph families have schemes using short labels, usually O(log n) in the deterministic case or constant for randomized sketches. In this work we consider the resilience of probabilistic adjacency sketches against an adversary making adaptive queries to the labels. This differs from the previously analyzed probabilistic setting which is "one shot". We show that in the adaptive adversarial case the size of the labels is tightly related to the maximal degree of the graphs in F . This results in a stronger characterization compared to what is known in the non-adversarial setting. In more detail, we construct sketches that fail with probability Ε for graphs with maximal degree d using 2d log(1/Ε) bit labels and show that this is roughly the best that can be done for any specific graph of maximal degree d, e.g. a d-ary *** Codes 68W20, 68W40, 68Q87 Copyright © 2023, The Authors. All rights reserved.

关键词： Graphic methods

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Socioeconomic Changes Based Climate Training for Agricultural Application Using Deep Learning Model

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Remote Sensing in Earth Systems sciences 2024年第4期7卷 399-410页

作者： Sunitha, M. Durairaj, M. Rajalingam, A. Yusoff, Siti Khalidah Mohd Prasad, S. Hari Chandra Malluvalasa, S. N. Lakshmi Kiran, Ajmeera Department of CSE Vasavi College of Engineering Hyderabad India Department of ECE Saveetha School of Engineering SIMATS Chennai India Department of Engineering University of Technology and Applied Sciences-Shinas and Saveetha Institute of Medical and Technical Sciences Chennai India Management and Science University Selangor Shah Alam Malaysia Department of Electronics & amp Communication Engineering Aditya University Surampalem India Department of Artificial Intelligence & amp Data Science Koneru Lakshmaiah Education Foundation Guntur Dist. Andhra PradeshVaddeswaram 522302 India Department of Computer Science and Engineering MLR Institute of Technology Dundigal Telangana Hyderabad 500043 India

In socioeconomic factor studies, the use of the logit and probit models has the disadvantage of representing random variation in preference for unobserved components and time-linked errors. The agricultural sector in the coastal nations of South-East Asia is facing mounting strain due to the adverse effects of climate change. Anticipating and controlling climate variables is challenging and necessitates expensive fixes. Based on social and economic shifts and the use of a deep learning model to detect climate change, the two main facets of agricultural application have been examined in this study. The suggested model focusses on these two factors because the economics and climate are crucial components of agriculture. Initially, financial flow–based data analysis employing recurrent LSTM spatial neural networks for text data analysis was used to assess the social economic analysis for those countries with minimal agricultural development. The study of crop growth data based on climate change is then done using Boltzmann Markov quantile regression neural networks. In terms of training accuracy, sensitivity specificity, and ROC, a performance study is conducted for crop growth data based on climatic change and agricultural development based on economic data. The proposed approach in this instance produced training accuracy of 79%, specificity of 83%, ROC of 84%, and sensitivity of 80% for economic data–based agricultural development;the suggested method achieved 75% training accuracy, 73% specificity, 80% ROC, and 84% SENSITIVITY for climate change–based crop growth data. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Agricultural application Climate change detection Deep learning model Quantile regression Social economic changes

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JET FORMATION FOLLOWING DROPLET IMPACT ON AN INCLINED MICROHOLED HYDROPHILIC SUBSTRATE

JET FORMATION FOLLOWING DROPLET IMPACT ON AN INCLINED MICROH...

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ASME 2024 International Mechanical engineering Congress and Exposition, IMECE 2024

作者： Nath, Tushar Shondhi, Sakib Sadat Tan, Hua Alam, Md Nur E. School of Engineering and Computer Science Washington State University VancouverWA98686 United States Department of Mechanical Engineering College of Engineering Computing and Applied Sciences Clemson University ClemsonSC29634 United States

ISBN: (纸本)9780791888667

Given its wide-ranging applications, the dynamics of liquid droplet impact on diverse surfaces has been extensively investigated. While much of the existing research focuses on droplet impacts on horizontal hydrophobic surfaces, it's worth noting that droplets often collide with inclined or moving surfaces in practical scenarios. Hence it is important to understand the physics related to such oblique impact of the droplet. Our present study focuses on the study of the oblique impacts. A microholed hydrophilic surface has been set at different inclination angles from 0o to 30o with an interval of 5o. Almost constant size droplets have been released through a micropipette tip using a syringe pump. The height of the release of the droplet was varied for every inclination angle to vary the impact velocity of the droplet. We focused on the normal impact velocity component and normal Weber number (WeN) in the study. We have found the time for maximum spread quite independent of the inclination angle for a certain normal Weber number (WeN). It is observed that the normalized maximum spreading dia. of the droplet remains almost constant for certain normal Weber number at different inclination angles and it follows a power law as βm ~ WeN0.27. Our power law model closely aligns with theoretical models discussed in the literature. The jet velocities at different inclinations have been found to vary linearly with the normal impact velocity and it has been found to increase at higher angles which can be described by the reduction in the effective area of the substrate hole at higher angles. The correlations between pinch-off time and maximum length of the jet before breakup have also been discussed. Copyright © 2024 by ASME.

关键词： Hydrophilicity

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Comparative Analysis of YOLOv9 and YOLOv10 Algorithms for Urban Safety Improvement 22

Comparative Analysis of YOLOv9 and YOLOv10 Algorithms for Ur...

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22nd IEEE International Symposium on Intelligent Systems and Informatics, SISY 2024

作者： Glucina, Matko Zigulic, Nikola Frank, Domagoj Lorencin, Ivan Matika, Dario Istrian University of Applied Sciences Department of Engineering Pula Croatia University of Rijeka Faculty of Engineering Rijeka Croatia University North Koprivnica Department of Computer Science and Informatics Croatia Juraj Dobrila University of Pula Faculty of Informatics Pula Croatia University North Department of Electrical Engineering Varazdin Croatia

ISBN: (纸本)9798350385601

Individual safety in urban and city centers is one of the fundamental rights of every person. Today's innovations open up various possibilities for improving the quality of life and safety, but if they are not applied, they carry the danger of an additional increase in crime or greater insecurity in urban centers. This investigation aims to apply insights into the anticipation of illegal actions by various criminal groups that use illegal means, such as weapons, to get property that does not belong to them. In this research, computer vision and advanced strategies such as YOLOv10 and YOLOv9 are used to compare their properties and performance for improving security in urban and populated areas. The best results were achieved by YOLOv9m with a high percentage of mean average precision in the amount of 0.923, while the worst performance was shown by YOLOv10n with a mean average precision of 0.902. Precision and recall for the YOLOv9 and YOLOv10 models were also taken into account and the results are as follows: 0.984.. 0.993.. 0.979.. and 0.996. © 2024 IEEE.

关键词： Neural networks

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Revolutionizing Neurological Diagnostics: Integrating 6G Technology with Deep Learning for Enhanced Detection of Multiple Sclerosis and Myelitis

Revolutionizing Neurological Diagnostics: Integrating 6G Tec...

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2024 International Telecommunications Conference, ITC-Egypt 2024

作者： Noureldeen, Rana M. Elshshtawy, Rahma A. Elgohary, Omnia A. Wahba, Fatma Alzahraa A. Attia, Marco K. Abo Elazm, Zeinab B. Khattap, Mohamed G. Galal Eldeen Mohamed Ali Hassan, Hend Mostafa, Mariam Ibrahim, Nayra Ramadan, Reem Refaat, Yomna Khaled, Mennatallah Maher, Ali Abd Elaziz, Mohamed Gamal Abdellatif Ibrahim, Ahmed Faculty of Applied Health Sciences Galala University Suez435611 Egypt Faculty of Computer Science and Engineering Galala University Suez435611 Egypt Artificial Intelligence Science Program Faculty of Computer Science and Engineering Galala University Suez435611 Egypt Air Defense College Department of Electronics and Electrical Communications Engineering Alexandria Egypt

ISBN: (纸本)9798350351408

This paper proposes an alternative detection frame-work for multiple sclerosis (MS) and idiopathic acute transverse myelitis (ATM) within the 6G-enabled Internet of Medical Things (IoMT) environment. The developed framework relies on the implementation of a deep learning technique known as Dense Convolutional Networks (DenseNets) in the 6G-enabled IoMT to enhance prediction performance. To validate the performance of DenseNets, we compared it with other deep learning techniques, including Convolutional Neural Networks (CNN) and MobileNet, using real-world datasets. The experimental results show the high performance of DenseNets in predicting MS and ATM compared to other methods, achieving an accuracy of nearly 90 %. © 2024 IEEE.

关键词： Convolutional neural networks

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Automated Detection of Alzheimer's Disease Using EfficientNet-B3 Architecture with Transfer Learning 25

Automated Detection of Alzheimer's Disease Using EfficientNe...

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25th International Arab Conference on Information Technology, ACIT 2024

作者： Aburomman, Ahmad Abuowaida, Suhaila Al-Momani, Adai Al Henawi, Esraa Elsoud, Esraa Abu Salah, Zaher Alzoubi, Haneen Chan, Huah Yong Khouj, Mohammed Zarqa University Department of Data Science and Ai Zarqa Jordan Al-Bayt University Department of Computer Science Ai Mafraq Jordan Zarqa University Department of Computer Science Zarqa Jordan The Hashemite University Department of Information Technology Zarqa Jordan Applied Science Private University Faculty of Information Technology Amman Jordan Universiti Sains Malaysia School of Computer Sciences Pulau Pinang Gelugor11800 Malaysia University of Business and Technology Department of Electrical Engineering Jeddah21432 Saudi Arabia

ISBN: (纸本)9798331540012

In order to bring forward expansion in both the accuracy and the processing speed of the detection of Alzheimer's disease, an automated approach for Alzheimer's disease diagnosis with passable EfficientNet-B3 neural network and transfer learning techniques is provided in this work. After direct fitness on a large number of annotated brain images, the model of EfficientNet-B3 is further trained, in an effort to obtain worse depicted quality connected with Alzheimer's Disease. To hasten the process of training and to make the model fit for this specific task, transfer learning was employed. The results of these experiments prove the efficiency of our approach to the diagnostic Alzheimer's disease compared to the most advanced and regular deep learning methods. Thus, the model may also withstand the test amidst diverse clinical populations by performing well in dementia classification with precision and recall performance coupled with over 99% accuracy. These findings demonstrate how the EfficientNet-B3 architecture and transfer learning enhance generalization across. © 2024 IEEE.

关键词： Image annotation

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Processing in Memory for mathematics of Arrays Operations

Processing in Memory for Mathematics of Arrays Operations

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2022 International Conference on Power, Energy and Innovations, ICPEI 2022

作者： Grout, Ian Mullin, Lenore Department of Electronic and Computer Engineering Faculty of Science and Engineering University of Limerick Limerick Ireland Department of Computer Science College of Engineering and Applied Sciences University at Albany SUNY Albany United States

ISBN: (数字)9781665460194

ISBN: (纸本)9781665460194

Processing In Memory (PIM), also referred to as Processor in Memory, is the integration of a processor with RAM (Random Access Memory) on a single Integrated Circuit (IC). In this paper, the concept of PIM is developed to support memory read/write requirements for mathematics of Arrays (MoA) operations that implement tensor inner and outer products. The concept for MoA in PIM supports the integration of the processing operations and data storage memory, allowing for increases in processing speed and memory data transfer rate, and can support decreases in memory access latency and power usage. © 2022 IEEE.

关键词： Data transfer

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Remote Sensing Based Crop Monitoring Techniques: A Case Study for the Navajo Nation

Remote Sensing Based Crop Monitoring Techniques: A Case Stud...

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2024 Annual Conference, ASPRS 2024

作者： Thangavel, Varatharajaperumal Nagarajan, Sudhagar Arockiasamy, Madasamy Khan, Md. Tarique Sklivanitis, George Department of Civil Environmental and Geomatics Engineering Florida Atlantic University FL United States School of Engineering Math & Technology Faculty Navajo Technical University CrownpointNM United States Department of Electrical Engineering and Computer Science Florida Atlantic University FL United States

Agriculture plays a major role in eradicating poverty, promoting prosperity, and nourishing a projected 10 billion people by 2050 globally. In a changing climate, achieving optimal agricultural yields requires a deeper understanding of available natural resources and crops. This is especially important for places like the Navajo Nation, which faces significant challenges in food supply chain management due to various factors such as water demand, water quality, and insufficient information about land fertility and crops timings/seasons. Additionally, it is the largest Native American reservation in the U.S. It covers 27,425 square miles across Arizona, Utah, and New Mexico and has a population of 165,158 people, according to the 2020 census. Agriculture has been a key part of life in the Navajo Nation since the late 19th and early 20th centuries, playing a big role in the region’s development and stability. However, the lack of knowledge about decisions and actions during the crop growing season has resulted in lower crop productivity, as evidenced by the USDA statistical report for the Navajo Nation in 2012 and 2017. To support farmers by providing better decision-making and actionable insights, high-resolution, open-source Sentinel-2 satellite images are being used to develop advanced crop mapping techniques for identifying the spatial extent of various agricultural crops in the Navajo Nation. To address this, a collection of research papers was reviewed, leading to the development of a new methodology for analysing Sentinel-2 data from the 2017 and 2023 growing seasons within the Navajo Nation. The collected data was pre-processed by creating monthly median composites of surface reflectance to remove noise and enhance the results more accurately. After preprocessing, spectral indices were calculated from the spectral bands, including NDVI (Normalized Difference Vegetation Index), EVI (Enhanced Vegetation Index), GCVI (Green Chlorophyll Vegetation Index), and LSWI

关键词： Surface waters

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Paradoxical roles of inhibitory autapse and excitatory synapse in formation of counterintuitive anticipated synchronization

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Chinese Physics B 2023年第8期32卷 499-509页

作者：丁学利古华光李玉叶贾雁兵 Department of Public Basic Education Fuyang Institute of TechnologyFuyang 236031China School of Aerospace Engineering and Applied Mechanics Tongji UniversityShanghai 200092China College of Mathematics and Computer Science Chifeng UniversityChifeng 024000China School of Mathematics and Statistics Henan University of Science and TechnologyLuoyang 471000China

Different from the common delayed synchronization(DS)in which response appears after stimulation,anticipated synchronization(AS)in unidirectionally coupled neurons denotes a counterintuitive phenomenon in which response of the receiver neuron appears before stimulation of the sender neuron,showing an interesting function of brain to anticipate the *** dynamical mechanism for the AS remains unclear due to complex dynamics of inhibitory and excitatory *** this article,the paradoxical roles of excitatory synapse and inhibitory autapse in the formation of AS are ***,in addition to the common roles such that inhibitory modulation delays and excitatory modulation advances spike,paradoxical roles of excitatory stimulation to delay spike via type-II phase response and of inhibitory autapse to advance spike are obtained in suitable parameter regions,extending the dynamics and functions of the excitatory and inhibitory ***,AS is related to the paradoxical roles of the excitatory and inhibitory modulations,presenting deep understandings to the *** autapse induces spike of the receiver neuron advanced to appear before that of the sender neuron at first,and then excitatory synapse plays a delay role to prevent the spike further advanced,resulting in the AS as the advance and delay effects realize a dynamic ***,inhibitory autapse with strong advance,middle advance,and weak advance and delay effects induce phase drift(spike of the receiver neuron advances continuously),AS,and DS,respectively,presenting comprehensive relationships between AS and other *** results present potential measures to modulate AS related to brain function.

关键词： anticipated synchronization inhibitory autapse excitatory synapse paradoxical firing

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Efficiently Reconfiguring a Connected Swarm of Labeled Robots 33

Efficiently Reconfiguring a Connected Swarm of Labeled Robot...

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33rd International Symposium on Algorithms and Computation, ISAAC 2022

作者： Fekete, Sándor P. Kramer, Peter Rieck, Christian Scheffer, Christian Schmidt, Arne Department of Computer Science TU Braunschweig Germany Faculty of Electrical Engineering and Computer Science Bochum University of Applied Sciences Germany

ISBN: (纸本)9783959772587

When considering motion planning for a swarm of n labeled robots, we need to rearrange a given start configuration into a desired target configuration via a sequence of parallel, continuous, collision-free robot motions. The objective is to reach the new configuration in a minimum amount of time;an important constraint is to keep the swarm connected at all times. Problems of this type have been considered before, with recent notable results achieving constant stretch for not necessarily connected reconfiguration: If mapping the start configuration to the target configuration requires a maximum Manhattan distance of d, the total duration of an overall schedule can be bounded to O(d), which is optimal up to constant factors. However, constant stretch could only be achieved if disconnected reconfiguration is allowed, or for scaled configurations (which arise by increasing all dimensions of a given object by the same multiplicative factor) of unlabeled robots. We resolve these major open problems by (1) establishing a lower bound of Ω(√n) for connected, labeled reconfiguration and, most importantly, by (2) proving that for scaled arrangements, constant stretch for connected reconfiguration can be achieved. In addition, we show that (3) it is NP-hard to decide whether a makespan of 2 can be achieved, while it is possible to check in polynomial time whether a makespan of 1 can be achieved. © Sándor P. Fekete, Peter Kramer, Christian Rieck, Christian Scheffer, and Arne Schmidt.

关键词： Motion planning

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