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作者： Tashu, Tsegaye Misikir Lenz, Marc Horváth, Tomáš ELTE – Eötvös Loránd University Faculty of Informatics Institute of Academia-Industry Cooperation Department of Data Science and Engineering Pázmány Péter sétány 1/C 1117 Budapest Hungary Pavol Jozef Šafárik University in Košice Faculty of Science Institute of Computer Science Jesenná 5 Košice040 01 Slovakia Department of Artificial Intelligence Bernoulli Institute of Mathematics Computer Science and Artificial Intelligence University of Groningen Groningen Netherlands Wollo University Kombolcha Institute of Technology College of Informatics Kombocha Ethiopia

In this work, we propose a novel method for generating inter-lingual document representations using neural network concept compression. The presented approach is intended to improve the quality of content-based multilingual document recommendation and information retrieval systems by creating a language-independent representation. The main idea is to use mappings to align monolingual representation spaces, using concept compression, to create inter-lingual representations. The proposed approach outperforms traditional cross-lingual retrieval and recommendations methods in experiments conducted on JRC-Acquis and EU bookshop multilingual corpora. Our dataset and code are publicly available at https://***/Tsegaye-misikir/NCC. © 2023

关键词： Information retrieval systems

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Enhancing Martian Mineral Identification Using an Artificial Neural Network With Extracted Spectral Features In CRISM MTRDR Data

Enhancing Martian Mineral Identification Using an Artificial...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Priyanka Kumari Sampriti Soor Amba Shetty B. S. Daya Sagar Department of Water Resources and Ocean Engineering NIT Karnataka Surathkal India School of Computer Engineering Kalinga Institute of Industrial Technology Bhubaneswar India Systems Science and Informatics Unit Indian Statistical Institute Bangalore India

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

Creating a supervised learning model for mineral identification is challenging due to the lack of ground-truth data. This study utilizes a method from existing literature that generates a training dataset by augmenting available spectra in the MICA spectral library. However, rather than using entire spectra for identification, this study extracts spectral features from each spectrum for model training. It employs the apparent continuum removal method, Segmented Curve Fitting, to identify the most informative or distinguishable parts in the spectral domain. Spectral features are then extracted based on band-centers and band-areas for each selected part. The model is evaluated against a Targeted Reduced Data Record (TRDR) dataset obtained using a hierarchical Bayesian model, demonstrating improved identification performance than the existing supervised models. Finally, using this model, dominant minerals are identified in MTRDR data from the Nilli Fossae region of Mars, and a corresponding mineral map is presented.

关键词： Training Absorption Supervised learning Artificial neural networks Feature extraction Data models Libraries

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WEIGHTED SUM OF SEGMENTED CORRELATION: AN EFFICIENT METHOD FOR SPECTra MATCHING IN HYPERSPECTraL IMAGES

arXiv

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arXiv 2024年

作者： Soor, Sampriti Kumari, Priyanka Sagar, B.S. Daya Shetty, Amba School of Computer Engineering Kalinga Institute of Industrial Technology Bhubaneswar India Department of Water Resources and Ocean Engineering NIT Karnataka Surathkal India Systems Science and Informatics Unit Indian Statistical Institute Bangalore India

Matching a target spectrum with known spectra in a spectral library is a common method for material identification in hyperspectral imaging research. Hyperspectral spectra exhibit precise absorption features across different wavelength segments, and the unique shapes and positions of these absorptions create distinct spectral signatures for each material, aiding in their identification. Therefore, only the specific positions can be considered for material identification. This study introduces the Weighted Sum of Segmented Correlation method, which calculates correlation indices between various segments of a library and a test spectrum, and derives a matching index, favoring positive correlations and penalizing negative correlations using assigned weights. The effectiveness of this approach is evaluated for mineral identification in hyperspectral images from both Earth and Martian surfaces. © 2024, CC BY-NC-ND.

关键词： Hyperspectral imaging

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Implementation of Legendre Neural Network to Solve Time-Varying Singular Bilinear Systems

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computers, Materials & Continua 2021年第12期69卷 3685-3692页

作者： V.Murugesh B.Saravana Balaji Habib Sano Aliy J.Bhuvana P.Saranya Andino Maseleno K.Shankar A.Sasikala Department of Computer Science College of InformaticsBule Hora UniversityPO Box 144Ethiopia Department of Information Technology Lebanese French UniversityErbil44001Iraq Deptartment of Logistics and Supply Chain Management Arba Minch UniversitySawla CampusPO Box 13Ethiopia Department of MCA School of Computer Science and ITJain(Deemed to be)UniversityBangalore560069India Department of Computer Science and Engineering SRM Institute of Science and TechnologyChennai603203India Department of Information Systems STMIK PringsewuLampungIndonesia Department of Computer Applications Alagappa UniversityKaraikudi630003India Department of EEE Sri Sairam Institute of TechnologyChennai600044India

Bilinear singular systems can be used in the investigation of different types of engineering *** the past decade,considerable attention has been paid to analyzing and synthesizing singular bilinear *** importance lies in their real world application such as economic,ecological,and socioeconomic *** are also applied in several biological processes,such as population dynamics of biological species,water balance,temperature regulation in the human body,carbon dioxide control in lungs,blood pressure,immune system,cardiac regulation,*** singular systems naturally represent different physical processes such as the fundamental law of mass action,the DC motor,the induction motor drives,the mechanical brake systems,aerial combat between two aircraft,the missile intercept problem,modeling and control of small furnaces and hydraulic rotary multimotor *** current research work discusses the Legendre Neural Network’s implementation to evaluate time-varying singular bilinear systems for finding the exact *** results were obtained from two methods namely the RK-Butcher algorithm and the Runge Kutta Arithmetic Mean(RKAM)*** with the results attained from Legendre Neural Network Method for time-varying singular bilinear systems,the output proved to be *** such,this research article established that the proposed Legendre Neural Network could be easily implemented in *** can obtain the solution for any length of time from this method in time-varying singular bilinear systems.

关键词： Time-varying singular bilinear systems RK-butcher algorithm legendre neural network method

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Integrated fault-tolerant control of assembly and automated guided vehicle-based transportation layers

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International Journal of computer Integrated Manufacturing 2022年第4-5期35卷 409-426页

作者： Pawel Majdzik Marcin Witczak Bogdan Lipiec Zbigniew Banaszak a Department of Electronics and Computer Science Koszalin University of Technology Koszalin Polandb Institute of Control and Computation Engineering University of Zielona Góra Zielona Góra Poland

ABSTraCTABSTraCTThe paper concerns the digital twin design and fault-tolerant control of a production system. The real laboratory system under consideration consists of two subsystems: an assembly part and an automated guided vehicle transportation one. The proposed approach focuses, simultaneously, on both concurrency and synchronization problems as they are inevitable in such a kind of modern systems. The research contribution deals with the development of an analytical description of both an assembly system and a multiple automated guided vehicles transportation layer along with algorithms that are able to determine an optimum sequence of starting individual operations. Subsequently, diagnostics and fault-tolerant control schemes are elaborated and applied to the two-layer system being investigated. The core advantage of the proposed approach is that it can compensate or eliminate the impact of some faults, e.g. delays occurring in the assembly unit or reduced velocities of transportation means. This makes it possible to keep the desired schedule as far as possible. The paper concludes with a series of illustrative use cases and comparisons which exhibit the performance of the novel approach in both cases, i.e. faulty and fault-free.

关键词： Fault-tolerant control assembly system automated guided vehicles system digital twin concurrency synchronization predictive control

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How we can use text classification in the Back-Office environment of a bank as 'business as usual' solution 17

How we can use text classification in the Back-Office enviro...

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17th IEEE International Symposium on Applied Computational Intelligence and informatics, SACI 2023

作者： Krutilla, Zsolt Kovari, Attila Óbuda University Doctoral School of Applied Informatics and Applied Mathematics Budapest Hungary Informatics Institution University of Dunaújváros Dunaújváros Hungary Institute of Engineering Alba Regia Technical Faculty buda University Budapest Hungary Institute of Digital Technology Faculty of Informatics Eszterházy Károly Catholic University Eger Hungary University of Dunaújváros Institute of Engineering Department of Natural Science Dunaújváros Hungary John von Neumann University Gamf Faculty of Engineering and Computer Science Kecskemét Hungary

ISBN: (纸本)9798350321104

Natural Language Processing nowadays provides scientists with many research areas and opportunities, but as with most applied sciences, our goal in Natural Language Processing is to refine the underlying science and technology until it can be used reliably for business purposes. Transformer models, such as GPT or BERT, are currently showing outstanding results in the field of natural-language processing, but they require huge computational power and data to teach, but these conditions can only be met by larger research centers and large companies, and their inaccuracy makes them unsuitable for use as a 'business as usual' (BAU) solution. In this paper, we present a solution that is able to overcome these problems by focusing on accuracy and usability, and that can also bring a new perspective to the process of teaching deep learning models. © 2023 IEEE.

关键词： Information retrieval systems

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FEASIBILITY OF ASSESSING COGNITIVE IMPAIRMENT VIA DISTRIBUTED CAMEra NETWORK AND PRIVACY-PRESERVING EDGE COMPUTING

arXiv

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arXiv 2024年

作者： Hegde, Chaitra Kiarashi, Yashar Levey, Allan I. Rodriguez, Amy D. Kwon, Hyeokhyen Clifford, Gari D. Department of Biomedical Informatics Emory University School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA United States Department of Biomedical Informatics Emory University AtlantaGA United States Department of Neurology Emory University AtlantaGA United States Department of Biomedical Informatics Emory University Department of Biomedical Engineering Georgia Institute of Technology AtlantaGA United States

INTRODUCTION: Mild cognitive impairment (MCI) is characterized by a decline in cognitive functions beyond typical age and education-related expectations. Since, MCI has been linked to reduced social interactions and increased aimless movements, we aimed to automate the capture of these behaviors to enhance longitudinal monitoring. METHODS: Using a privacy-preserving distributed camera network, we collected movement and social interaction data from groups of individuals with MCI undergoing therapy within a 1700m2 space. We developed movement and social interaction features, which were then used to train a series of machine learning algorithms to distinguish between higher and lower cognitive functioning MCI groups. RESULTS: A Wilcoxon rank-sum test revealed statistically significant differences between high and low-functioning cohorts in features such as linear path length, walking speed, change in direction while walking, entropy of velocity and direction change, and number of group formations in the indoor space. Despite lacking individual identifiers to associate with specific levels of MCI, a machine learning approach using the most significant features provided a 71% accuracy. DISCUSSION: We provide evidence to show that a privacy-preserving low-cost camera network using edge computing framework has the potential to distinguish between different levels of cognitive impairment from the movements and social interactions captured during group activities. © 2024, CC BY-NC-SA.

关键词： Differential privacy

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Understanding Older Adults' (Dis)Engagement with Design Materials 25

Understanding Older Adults' (Dis)Engagement with Design Mate...

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2025 CHI Conference on Human Factors in Computing Systems, CHI 2025

作者： Pradhan, Alisha Jelen, Ben Thangaraj, ramprabu Siek, Katie A. Jette, Shannon Lazar, Amanda Department of Informatics Ying Wu College of Computing New Jersey Institute of Technology NewarkNJ United States Computer Science and Software Engineering Rose-Hulman Institute of Technology Terre HauteIN United States Ying Wu College of Computing New Jersey Institute of Technology NewarkNJ United States Luddy School of Informatics Computing and Engineering Indiana University BloomingtonIN United States University of Maryland College ParkMD United States College of Information Studies University of Maryland College ParkMD United States

ISBN: (纸本)9798400713941

Design workshops are a popular approach to include older adults in the technology design process. However, formative design sessions with older adults have had unexpected outcomes such as the non-use of traditional design materials like craft-based prototyping supplies or disengagement from design activities. Analyzing the engagement of 32 older adults across two design workshops, this paper sheds insights on some of these outcomes. Contributing to a growing body of HCI research on understanding older adults' participation in design, we provide an understanding of how design materials can shape older adults' engagement in formative design activities. Our discussion furthers research on understanding who older adults design for and why, argues for a different understanding of creative expression, and offers considerations for choosing design materials. © 2025 Copyright held by the owner/author(s).

关键词： Design for manufacturability

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Urban Pluvial Flood Prediction Using Machine Learning Models

Urban Pluvial Flood Prediction Using Machine Learning Models

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Innovations in computer Science & Software engineering (ICONICS), International Conference on

作者： Waseemullah Tahir Hassan Sajid Majeed Muhammad Qasim Memon Department of Computer Science & Information Technology NED University of Engineering and Technology Karachi Pakistan Department of Remote Sensing & Geo-Informatics Institute of Space Technology Karachi Pakistan Department of Information and Computing University of Sufism and Modern Sciences Bhitshah Pakistan

ISBN: (数字)9798331504342

ISBN: (纸本)9798331504359

Urban pluvial flooding causes threats to human lives, economy, infrastructure, and ecosystems around the world, particularly in developing countries. Pakistan is among those developing countries that have become vulnerable to urban flooding due to global warming, climate change risks, rapid urbanization, and the occurrence of extreme and unusual rainfall events in the monsoon season. To effectively mitigate the adverse effects of pluvial flooding, there is a pressing need for an advanced and accurate predictive model that is capable of predicting urban pluvial flooding. The aim of this research is to utilize the potential of machine learning (ML) techniques and algorithms to accurately predict the occurrence of urban pluvial flooding, for this study we have worked on the monsoon rainfall data of multiple cities of Sindh province in Pakistan. We made an attempt to use multiple ML models especially logistic regression (LR), random forest (RF), k nearest neighbor (KNN), and support vector machine (SVM) to propose the best and accurate predictive model. The developed models were evaluated and assessed using various performance evaluation metrics which includes accuracy, recall, precision and F1 score. The best among proposed models was created using LR which achieved an accuracy of 97%, while the accuracy of other models which were created using SVM, KNN and RF were 96%, 93%, and 92% respectively.

关键词： Support vector machines radio frequency Accuracy rain Machine learning algorithms Computational modeling Biological system modeling Predictive models Nearest neighbor methods Floods

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Ant Colony Optimization for Service Composition in Multi-cloud Environments

Ant Colony Optimization for Service Composition in Multi-clo...

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International Conference on Computing and Networking technology (ICCNT)

作者： Mahesh Maurya G Vidhya Faiz Akram M Saravanan K Venkata ramana S rajakumari Department of Computer Engineering K.C. College of Engineering Mith Bunder road Kopri Thane East Maharashtra India Department of Computer Science and Engineering Sona College of Technology Salem Tamilnadu India Department of Computer Science Faculty of Computing and Informatics Jimma Institute of Technology Jimma University Jimma Oromia Region Ethiopia Department of ECE Sri Eshwar College of Engineering Coimbatore Tamilnadu India Department of CSE QIS College of Engineering and Technology Ongole Andrapradesh India Department of Mathematics R.M.D. Engineering College

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

the Ant Colony Optimization (ACO) algorithm is a famous metaheuristic technique that has been successfully applied in various optimization issues. It mimics the foraging conduct of ants to locate the shortest path among meals assets and their colony. Recently, ACO has been increasingly more applied for provider composition in multi-cloud environments. This involves the composition of offerings from different cloud carriers to satisfy the service necessities of a person. By way of using ACO, services can be correctly selected and composed from a couple of carriers, considering elements including cost, excellent, and availability. ACO has proven promising outcomes in enhancing the overall performance and reliability of carrier composition in multi-cloud environments, making it a precious technique in todays tremendously distributed computing landscape.

关键词： Measurement Ant colony optimization Costs Shape Metaheuristics MIMICs Quality of service Reliability Distributed computing

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