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31st International Conference on Automated Planning and Scheduling, ICAPS 2021

作者： Keren, Sarah Canal, Gerard Cashmore, Michael Harvard University School of Engineering and Applied Sciences Cambridge United States The Hebrew University of Jerusalem School of Computer Science and Engineering Israel Department of Informatics King’s College London United Kingdom University of Strathclyde Computer and Information Sciences Glasgow United Kingdom

ISBN: (纸本)9781713832317

To achieve a complex task, a robot often needs to navigate in a physical space in order to complete activities in different locations. For example, it may need to inspect several structures, making multiple observations of each structure from different perspectives. Typically, the positions from which these activities can be performed are represented as waypoints – discrete positions that are sampled from the continuous physical space and used to find a task plan. Existing approaches to waypoint selection either iteratively consider the entire space or use domain knowledge to consider each activity separately. This can lead to task planning problems that are more complex than is necessary or to plans of compromised quality. Moreover, all previous approaches only consider geometric constraints that can be imposed on the waypoint selection process. We present Task-Aware Waypoint Sampling (TAWS), which offers two key novelties. First, it is an anytime approach that combines the benefits of random sampling with the use of domain knowledge in waypoint selection by performing a onetime computation of the connectivity graph from which waypoints are sampled. In addition, TAWS is the first approach that accounts for performance preferences, which are preferences a system operator may have about the generated task plan. These can account, for example, for areas near doorways where it is preferable that the robot does not stop to perform activities. We demonstrate the performance benefits of our approach on simulated automated manufacturing tasks. Copyright © 2021, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Domain Knowledge

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An Adaptive Crack Identification Scheme Using Enhanced Segmentation and Feature Extraction for Electrical Discharge Machining of Inconel X750 1

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作者： Sabareesaan, K.J. Jaya, J. Al Ani, Habeeb Sivakumar, R. Alhadidi, Basim University of Technology and Applied Science Nizwa Oman Hindusthan College of Engineering and Technology Coimbatore India College of Engineering Taibah University Medina Saudi Arabia Vellore Institute of Technology Vellore India Department of Computer Information Systems Al-Balqa’ Applied University As-Salt Jordan

ISBN: (数字)9783030654078

ISBN: (纸本)9783030654061;9783030654092

Quick interchangeable search has more significance in a large-scale dataset while using for image indexing and retrieval in many applications. Mining of image presents special characteristics due to the superior quality of the data that an image can reflect. The change of gathering to pursuit in overall and flying make, particularly as a consequence of the snappy improvement in assessment of people going around the world brisk and wealthy using air course, the materials that are combined in that industries and its reasonable machining operations makes prominence. Before producing that for the use in business operation sectors and assembling industries, it should be assessed for flaws and necessity for a mechanized response for recognizing the parts in surface of the metals using computer Aided detection (CAD) system. The implementation of CAD framework has made a mammoth bounce in the powerful operations. It is proposed to find the applicable information for image examination and conclusion from the information base of picture depictions. This work center to actualize a viable division approach utilizing KFCM (Kernel Fuzzy C-Means) calculation. The solution consists of texture processing including feature extraction, segmentation with Content based image retrieval. The proposed solution achieves better performance compare to direct matching scheme in terms of number of segmented objects and extracted & matched feature. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Feature extraction

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A Covert Communication Method Using Special Bitcoin Addresses Generated by Vanitygen

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computers, Materials & Continua 2020年第10期65卷 597-616页

作者： Lejun Zhang Zhijie Zhang Weizheng Wang Rasheed Waqas Chunhui Zhao Seokhoon Kim Huiling Chen College of Information Engineering Yangzhou UniversityYangzhou225127China School Math&Computer Science Quanzhou Normal UniversityQuanzhou362000China University of Aizu Aizu Wakamatsu9658580Japan College of Information and Communication Engineering Harbin Engineering UniversityHarbin150001China Department of Computer Software Engineering Soonchunhyang UniversityAsanKorea Department of Computer Science and Artificial Intelligence Wenzhou UniversityWenzhou325035China

As an extension of the traditional encryption technology,information hiding has been increasingly used in the fields of communication and network media,and the covert communication technology has gradually *** blockchain technology that has emerged in recent years has the characteristics of decentralization and tamper resistance,which can effectively alleviate the disadvantages and problems of traditional covert ***,its combination with covert communication thus far has been mostly at the theoretical *** BLOCCE method,as an early result of the combination of blockchain and covert communication technology,has the problems of low information embedding efficiency,the use of too many Bitcoin addresses,low communication efficiency,and high *** present research improved on this method,designed the V-BLOCCE which uses base58 to encrypt the plaintext and reuses the addresses generated by Vanitygen multiple times to embed *** greatly improves the efficiency of information embedding and decreases the number of Bitcoin addresses *** the premise of ensuring the order,the Bitcoin transaction OP_RETURN field is used to store the information required to restore the plaintext and the transactions are issued at the same time to improve the information transmission ***,a more efficient and feasible method for the application of covert communication on the blockchain is *** addition,this paper also provides a more feasible scheme and theoretical support for covert communication in blockchain.

关键词： Covert communication blockchain Bitcoin address

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Explainable machine learning models for estimating daily dissolved oxygen concentration of the Tualatin River

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engineering Applications of Computational Fluid Mechanics 2024年第1期18卷

作者： Li, Shuguang Qasem, Sultan Noman Band, Shahab S. Ameri, Rasoul Pai, Hao-Ting Mehdizadeh, Saeid School of Computer Science and Technology Shandong Technology and Business University Yantai China Computer Science Department College of Computer and Information Sciences Imam Mohammad Ibn Saud Islamic University (IMSIU) Riyadh Saudi Arabia Computer Science Department Faculty of Applied Science Taiz University Taiz Yemen Future Technology Research Center National Yunlin University of Science and Technology Douliu Taiwan Department of Information Management International Graduate School of Artificial Intelligence National Yunlin University of Science and Technology Douliu Taiwan Department of Information Management National Yunlin University of Science and Technology Douliu Taiwan Bachelor Program of Big Data Applications in Business National Pingtung University Pingtung Taiwan Water Engineering Department Urmia University Urmia Iran

Monitoring the quality of river water is of fundamental importance and needs to be taken into consideration when it comes to the research into the hydrological field. In this context, the concentration of the dissolved oxygen (DO) is one of the most significant indicators of the quality of river water. The current study aimed to estimate the minimum, maximum, and mean DO concentrations (DO min, DO max, DO mean) at a gauging station located on Tualatin River, United States. To that end, four machine learning models, such as support vector regression (SVR), multi-layer perceptron (MLP), random forest (RF), and gradient boosting (GB) were established. Root mean square error (RMSE), mean absolute error (MAE), coefficient of correlation (R), and Nash-Sutcliffe efficiency (NSE) metrics were employed to better assess the accuracies of these models. The modeling results demonstrated that the SVR and MLP surpassed the RF and GB models. Despite this, the SVR was concluded to be the best-performing method when used to estimate the DO min, DO max, and DO mean. The best error statistics in the testing phase were related to the SVR model with full (four) inputs to estimate DO mean concentration (RMSE = 0.663 mg/l, MAE = 0.508 mg/l, R = 0.945, NSE = 0.875). Finally, the explainability of the superior models (i.e. SVR models) was conducted using SHapley Additive exPlanations (SHAP) for the first time to estimate DO concentration. In fact, evaluating the explainability of machine learning models can provide useful information about the impact of each of the input estimators used in the procedure of models development. It was concluded that the specific conductance (SC) and followed by water temperature (WT) could provide the most contributions for estimating the DO min, DO max, and DO mean concentrations. © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

关键词： dissolved oxygen concentration estimation Explainable machine learning SHapley additive explanations

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HISTORIAE, history of socio-cultural transformation as linguistic data science. A humanities use case 3

HISTORIAE, history of socio-cultural transformation as lingu...

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3rd Conference on Language, Data and Knowledge, LDK 2021

作者： Armaselu, Florentina Apostol, Elena-Simona Khan, Anas Fahad Liebeskind, Chaya McGillivray, Barbara Truică, Ciprian-Octavian Oleškevičiene, Giedre Valūnaite University of Luxembourg Luxembourg Department of Computer Science and Engineering Faculty of Automatic Control and Computer University Politehnica of Bucharest Romania Institute for Computational Linguistics «A. Zampolli» National Research Council of Italy Pisa Italy Department of Computer Science Jerusalem College of Technology Israel Theoretical and Applied Linguistics Faculty of Modern and Medieval Languages and Linguistics University of Cambridge United Kingdom The Alan Turing Institute London United Kingdom Department of Computer Science and Engineering Faculty of Automatic Control and ComputerUniversity Politehnica of Bucharest Romania Institute of Humanities Mykolas Romeris University Vilnius Lithuania

ISBN: (纸本)9783959771993

The paper proposes an interdisciplinary approach including methods from disciplines such as history of concepts, linguistics, natural language processing (NLP) and Semantic Web, to create a comparative framework for detecting semantic change in multilingual historical corpora and generating diachronic ontologies as linguistic linked open data (LLOD). Initiated as a use case (UC4.2.1) within the COST Action Nexus Linguarum, European network for Web-centred linguistic data science, the study will explore emerging trends in knowledge extraction, analysis and representation from linguistic data science, and apply the devised methodology to datasets in the humanities to trace the evolution of concepts from the domain of socio-cultural transformation. The paper will describe the main elements of the methodological framework and preliminary planning of the intended workflow. © Florentina Armaselu, Elena-Simona Apostol, Anas Fahad Khan, Chaya Liebeskind, Barbara McGillivray, Ciprian-Octavian Truică, and Giedre Valūnaite Oleškevičien e;licensed under Creative Commons License CC-BY 4.0

关键词： Linguistics

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Optimal Polynomial Approximation to Rational Matrix Functions Using the Arnoldi Algorithm

arXiv

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arXiv 2023年

作者： Chen, Tyler Greenbaum, Anne Wellen, Natalie NYU Courant Department of Mathematics 251 Mercer St. New YorkNY10003 United States NYU Tandon Department of Computer Science and Engineering 370 Jay St. New YorkNY11201 United States University of Washington Applied Math Dept. Box 353925 SeattleWA98195 United States

Given an n by n matrix A and an n-vector b, along with a rational function R(z):= D(z)−1N (z), we show how to find the optimal approximation to R(A)b from the Krylov space, span(b, Ab, . . ., Ak−1b), using the basis vectors produced by the Arnoldi algorithm. To find this optimal approximation requires running max{deg(D), deg(N)} − 1 extra Arnoldi steps and solving a k + max{deg(D), deg(N)} by k least squares problem. Here optimal is taken to mean optimal in the D(A)∗D(A)-norm. Similar to the case for linear systems, we show that eigenvalues alone cannot provide information about the convergence behavior of this algorithm and we discuss other possible error bounds for highly nonnormal *** Codes 65F10 (Primary), 65F60, 47A12, 47A25 (Secondary) © 2023, CC BY.

关键词： Rational functions

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L2GNet: Optimal Local-to-Global Representation of Anatomical Structures for Generalized Medical Image Segmentation

arXiv

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arXiv 2025年

作者： Gorade, Vandan Mittal, Sparsh Dasu, Neethi Singhal, Rekha Santosh, K.C. Jha, Debesh Department of Biomedical Engineering Northwestern University IL United States Mehta School of Data Science and AI Indian Institute of Technology Roorkee India Beth Israel Lahey Health University of Massachusetts Chan School of Medicine United States TCS Research New York United States Applied AI Research Lab Department of Computer Science University of South Dakota United States

Continuous Latent Space (CLS) and Discrete Latent Space (DLS) models, like AttnUNet and VQUNet, have excelled in medical image segmentation. In contrast, Synergistic Continuous and Discrete Latent Space (CDLS) models show promise in handling fine and coarse-grained information. However, they struggle with modeling long-range dependencies. CLS or CDLS-based models, such as TransUNet or SynergyNet are adept at capturing long-range dependencies. Since they rely heavily on feature pooling or aggregation using self-attention, they may capture dependencies among redundant regions. This hinders comprehension of anatomical structure content, poses challenges in modeling intra-class and inter-class dependencies, increases false negatives and compromises generalization. Addressing these issues, we propose L2GNet, which learns global dependencies by relating discrete codes obtained from DLS using optimal transport and aligning codes on a trainable reference. L2GNet achieves discriminative on-the-fly representation learning without an additional weight matrix in self-attention models, making it computationally efficient for medical applications. Extensive experiments on multi-organ segmentation and cardiac datasets demonstrate L2GNet’s superiority over state-of-the-art methods, including the CDLS method SynergyNet, offering an novel approach to enhance deep learning models’ performance in medical image analysis. © 2025, CC BY.

关键词： Image segmentation

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Towards Optic Enlightenment: Future Free Space Optics Architecture & Dynamic Modeling

Towards Optic Enlightenment: Future Free Space Optics Archit...

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Intelligent Data Communication Technologies and Internet of Things (IDCIoT), International Conference on

作者： Ravi Gorli P Ashok Maharaja Kamatchi Mohsina Mirza G Kalanandhini Harishchander Anandaram Department of Computer Science and Engineering Gitam School of Technology Gitam University Visakhapatnam Andhra Pradesh India Symbiosis Institute of Digital and Telecom Management (SIDTM) Symbiosis International (Deemed University) (SIU) Lavale Pune Maharashtra India Department of Engineering University of Technology and Applied Sciences Al-Mussanah Sultanate of Oman Department of Electrical and Electronics Engineering Global College of Engineering and Technology Sultanate of Oman Department of Electronics and Communication Engineering Prince Shri Venkateshwara Padmavathy Engineering College Chennai Tamilnadu India Amrita School of Artificial Intelligence Amrita Vishwa Vidyapeetham Coimbatore India

Free space optics (FSO) is gradually being seen as a potential technique for supporting high-speed communication. Nonetheless, FSO meets challenges caused by the air medium through which the laser beam travels. This research overcomes these obstacles by utilizing spatial diversity tactics. In particular, a two-way relay (TWR) is used to build a two-way communication link between two remote places. The TWR extends the range of FSO gearbox and mitigates the effects of fading, which vary with distance. Extensive research is conducted on the many applications of TWR-supported FSO communication, and a mathematical methodology for analyzing performance indicators at the physical layer is introduced. Furthermore, various channel impediments such as route loss, pointing mistakes, and atmospheric turbulence are addressed in detail. To account for changing amounts of atmospheric turbulence, the use of log-normal, Gamma-Gamma, and M-distributions is done to replicate the fading effects caused by turbulence. There is an urgent need to broaden the application of TWR protocols into a multiuser scenario, especially in today's context when several pairs of users' demand data interchange among themselves. Thorough analysis on the use of a single TWR that serves many user-pairs via the implementation of a scheduleris explored.

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An Ensemble Models for the Prediction of Sickle Cell Disease from Erythrocytes Smears

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EAI Endorsed Transactions on Pervasive Health and Technology 2023年 9卷

作者： Ayoade, Oluwafisayo Babatope Oladele, Tinuke Omolewa Imoize, Agbotiname Lucky Adeloye, Jerome Adetoye Awotunde, Joseph Bamidele Olorunyomi, Segun Omotayo Faboya, Olusola Theophilus Idowu, Ayorinde Oladele Department of Computing and Information Science School of Pure and Applied Sciences College of Science Bamidele Olumilua University of Education Science & Technology Ekiti State Ikere-Ekiti Nigeria Department of Computer Science Faculty of Communication and Information Sciences University of Ilorin Kwara State Nigeria Department of Electrical and Electronics Faculty of Engineering University of Lagos Lagos State Akoka 100213 Nigeria Ekiti State Data Center Office Old Governor’s Office Ekiti State Ado-Ekiti Nigeria

INTRODUCTION: The human blood as a collection of tissues containing Red Blood Cells (RBCs), circular in shape and acting as an oxygen carrier, are frequently deformed by multiple blood diseases inherited from parents. These hereditary diseases of blood involve abnormal haemoglobin (Hb) or anemia which are major public health issues. Sickle Cell Disease (SCD) is one of the common non-communicable disease and genetic disorder due to changes in hematological conditions of the RBCs which often causes the inheritance of mutant Hb genes by the patient.. OBJECTIVES: The process of manual valuation, predictions and diagnosis of SCD necessitate for a passionate time spending and if not done properly can lead to wrong predictions and diagnosis. Machine Learning (ML), a branch of AI which emphases on building systems that improve performance based on the data they consume is appropriate. Despite previous research efforts in predicting with single ML algorithm, the existing systems still suffer from high false and wrong predictions. METHODS: Thus, this paper aimed at performing comparative analysis of individual ML algorithms and their ensemble models for effective predictions of SCD (elongated shapes) in erythrocytes blood cells. Three ML algorithms were selected, and ensemble models were developed to perform the predictions and metrics were used to evaluate the performance of the model using accuracy, sensitivity, Receiver Operating Characteristics-Area under Curve (ROC-AUC) and F1 score metrics. The results were compared with existing literature for model(s) with the best prediction metrics performance.. RESULTS: The analysis was carried out using Python programming language. Individual ML algorithms reveals that their accuracies show MLR=87%, XGBoost=90%, and RF=93%, while hybridized RF-MLR=92% and RF-XGBoost=99%. The accuracy of RF-XGBoost of 99% outperformed other individual ML algorithms and Hybrid models. CONCLUSION: Thus, the study concluded that involving hybridized M

关键词： Forecasting

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Spectral width of maximum deposition eigenchannels in diffusive media

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Physical Review B 2025年第14期111卷 144202-144202页

作者： Rohin E. McIntosh Arthur Goetschy Nicholas Bender Alexey Yamilov Chia Wei Hsu Hasan Yılmaz Hui Cao Department of Physics Yale University New Haven Connecticut 06511 USA Institut Langevin ESPCI Paris PSL University CNRS F-75005 Paris France School of Applied and Engineering Physics Cornell University Ithaca New York 14850 USA Physics Department Missouri University of Science & Technology Rolla Missouri 65409 USA Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los Angeles California 90089 USA Institute of Materials Science and Nanotechnology National Nanotechnology Research Center (UNAM) Bilkent University 06800 Ankara Turkey

The maximum deposition eigenchannel provides the largest possible power delivery to a target region inside a diffusive medium by optimizing the incident wavefront of a monochromatic beam. It originates from constructive interference of scattered waves, which is frequency sensitive. We investigate the spectral width of the maximum deposition eigenchannels over a range of target depths using numerical simulations of a 2D diffusive system. Compared to tight focusing into the system, power deposition to an extended region is more sensitive to frequency detuning. The spectral width of enhanced delivery to a large target displays a rather weak, nonmonotonic variation with target depth, in contrast to a sharp drop of focusing bandwidth with depth. While the maximum enhancement of power deposited within a diffusive system can exceed that of power transmitted through it, this comes at the cost of a narrower spectral width. We investigate the narrower deposition width in terms of the constructive interference of transmission eigenchannels within the target. We further observe that the spatial field distribution inside the target region decorrelates more slowly with spectral detuning than the power decay of the maximum deposition eigenchannel. Additionally, absorption increases the spectral width of deposition eigenchannels, but the depth dependence remains qualitatively identical to that without absorption. These findings hold for any diffusive waves, including electromagnetic waves, acoustic waves, pressure waves, mesoscopic electrons, and cold atoms.

关键词： Wavefronts

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