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4th ACM Workshop on Intelligent Cross-Data Analysis and Retrieval, ICDAR 2023

作者： Prokopiou, Ioannis Vikatos, Pantelis Chatzis, Christos Christodoulou, Christos Orfium Research Greece and Computer Engineering and Informatics Department Attiki Athens Greece Orfium Research Attiki Athens Greece

ISBN: (纸本)9798400701863

The movie industry is characterized by high levels of uncertainty due to the difficulties businesses have predicting sales and income since they depend on so many complex elements. Because of the significant movie industry's upfront costs, investors must make decisions based on accurate methodologies to estimate the success or returns of their investments. Due to social networks' widespread use in our daily lives, there is an unprecedented amount of publicly available posts containing emotional triggers that can be analyzed. In this paper, we showcase our movie trailers campaign surveillance system using social media analytics and public mood. The system provides an overall interactive dashboard to users and the capability for further process, analysis, and visualization of data in distinct customized reports. The proposed system also offers a configurable environment to gather metrics from heterogeneous social media platforms and extract advanced analytics through dedicated AI tools for sentiment and emotion extraction. This solution benefits the continuous surveillance of a movie trailer's popularity and supports the success of marketing campaigns. © 2023 ACM.

关键词： Light trailers

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Evaluating Deep Learning Models for Breast Cancer Classification: A Comparative Study

Evaluating Deep Learning Models for Breast Cancer Classifica...

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Medical Imaging 2025: Digital and Computational Pathology

作者： Eskandari, Sania Eslamian, Ali Cheng, Qiang Department of Electrical and Computer Engineering University of Kentucky Lexington United States Department of Computer Science University of Kentucky Lexington United States Institute for Biomedical Informatics University of Kentucky Lexington United States

ISBN: (纸本)9781510686045

The classification of histopathological images is crucial for the early and precise detection of breast cancer. This study investigates the efficiency of deep learning models in distinguishing between Invasive Ductal Carcinoma (IDC) and non-IDC in histopathology slides. We conducted a thorough comparison examination of eight sophisticated models: ResNet-50, DenseNet-121, ResNeXt-50, Vision Transformer (ViT), GoogLeNet (Inception v3), EfficientNet, MobileNet, and SqueezeNet. This analysis was carried out using a large dataset of 277,524 image patches. Our research makes a substantial contribution to the field by offering a comprehensive assessment of the performance of each model. We particularly highlight the exceptional efficacy of attention-based mechanisms in the ViT model, which achieved a remarkable validation accuracy of 94%, surpassing conventional convolutional networks. This study highlights the promise of advanced machine learning approaches in clinical settings, offering improved precision as well as efficiency in breast cancer diagnosis. © 2025 SPIE.

关键词： Breast cancer Deep learning Tumor growth modeling Medical imaging Pathology Alternate lighting of surfaces computer engineering computer science Health informatics

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Actively Learning Ontologies from LLMs: First Results (Extended Abstract) 37

Actively Learning Ontologies from LLMs: First Results (Exten...

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37th International Workshop on Description Logics, DL 2024

作者： Magnini, Matteo Ozaki, Ana Squarcialupi, Riccardo Department of Computer Science and Engineering University of Bologna Via dell’Università 50 Cesena Italy Department of Informatics University of Oslo Gaustadalléen 23B Oslo Norway Department of Informatics University of Bergen Thormøhlensgate 55 Bergen Norway

In active learning a learner attempts to acquire some kind of knowledge by posing questions to a teacher. Here we consider that the teacher is a language model and study the case in which the knowledge is expressed as an ontology. To evaluate the approach, we present first results testing logical consistency and the performance of GPT and other language models when answering whether concept inclusions from existing EL ontologies are ‘true’ or ‘false’. © 2024 Copyright for this paper by its authors.

关键词： Active learning

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Adaptive iterated local search algorithm for dynamic patient admission scheduling problems

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Soft Computing 2025年 1-11页

作者： Turky, Ayad Sabar, Nasser R. Song, Andy Hussain, Abir Liatsis, Panos Department of Computer Science College of Computing and Informatics University of Sharjah Sharjah United Arab Emirates Department of Computer Science and Information Technology La Trobe University MelbourneVIC3086 Australia School of Computing Technologies RMIT University Melbourne Australia Department of Electrical Engineering University of Sharjah Sharjah United Arab Emirates Department of Electrical Engineering and Computer Science Khalifa University Abu Dhabi United Arab Emirates

Healthcare resource management is essential for ensuring the quality of patient care. However, it can be a complex and costly task. This work addresses the patient admission scheduling (PAS) problem, a complex aspect of healthcare resource management. PAS aims to allocate patients to hospital beds within a planning horizon, subject to a variety of healthcare constraints. The goal is to maximize management efficiency and patient comfort to improve medical treatment. In this work, we consider a practical variant of PAS known as dynamic PAS (DPAS). DPAS considers several factors and constraints, such as the daily registration of new patients, urgent patients, uncertainties in stay lengths, operating theatre resources, and the surgery scheduling process. An effective and efficient adaptive iterated local search (AILS) algorithm is proposed to solve DPAS. To enable the search to explore the search space efficiently, the proposed AILS adaptively integrates a number of components. Two adaptive perturbation strategies are devised to locate unexplored areas in the search space. To exploit the newly discovered areas effectively, we propose an adaptive local search mechanism as an intensification strategy to find a high-quality solution. The proposed AILS algorithm is compared to benchmark problems used by existing algorithms. The experimental results demonstrate the effectiveness and efficiency of the proposed approach. Specifically, out of 30 tested instances, AILS obtains 17 of the best-known results using less computational time. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Resource allocation

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Experiment on Multi-hop LoRa for Tracking Application

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International Journal of Sensors, Wireless Communications and Control 2023年第1期13卷 29-39页

作者： Sagala, Albert Lubis, Ramot Silalahi, Gomgom Ginting, Estika V. Simorangkir, Andreas J. D. Faculty of Informatics and Electrical Engineering Institut Teknologi Del Toba Samosir Indonesia Department of Computer Science Binus University West Jakarta Indonesia

Background: The Internet of Things (IoT) is an embryonic model that converts real-world things (objects) into smarter devices. IoT is applicable to a variety of application domains, including healthcare, smart grid, and agriculture. Low Power Wide Area Network (LPWAN) technology can transmit data over long distances with a low data rate without using the internet. There-fore, this technology is suitable for sending sensor measurement data in Internet of Things (IoT) applications. LPWANs, such as LoRa, use a star topology to reach their coverage to the maximum power that can be transmitted, considering the environmental conditions in the test area and the LoRa parameters used. Whereas for application development in rural areas, there is no internet connection, and often longer coverage is required from the sensor node to the gateway. Objective: This study aims to increase the transmission range from the end node to the gateway by adding an intermediate node. It is used as a relay from the end node to the gateway. Method: Static routing was applied so that any broadcast data from the end node would be for-warded first to the intermediate node and then to the gateway. Results: The LoRa transmission range expanded by changing the topology from peer-to-peer to multi-hop. An intermediate node between the transmitter (end node) and the gateway is available. In the experiment performed, a multi-hop with static routes successfully expanded the distance from 150 meters (single hop) to 250 meters (multi-hop), with a packet delivery ratio of 97%. In this experiment, GPS Ublox Neo was used for the sensor position and was successfully tested on the end node with an accuracy rate of 2.4% for latitude and 0.2% for longitude. Conclusion: The transmission range from the sensor node to the gateway can be extended using static routing by installing an intermediate node between the gateway and the sensor node. The data from the end node is successfully received by the gateway. © 2023 Be

关键词： energy efficiency GPS ublox neo internet of things LoRa tracking LPWAN multi-hop wireless sensor networks

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Ergodic Capacity Analysis of RIS-aided System Relying on User Grouping and Fixed Power Allocation 5th

Ergodic Capacity Analysis of RIS-aided System Relying on Use...

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5th International Conference on Communication, Device and Networking, ICCDN 2021

作者： Umamaheswari, Kaveti Fazal-E-Asim Do, Dinh-Thuan Department of Computer Science and Information Engineering College of Information and Electrical Engineering Asia University Taichung41354 Taiwan Department of Tele Informatics Engineering Federal University of Cear ´a Fortaleza Brazil

ISBN: (纸本)9789811920035

In this paper, we focus on the ergodic capacity of RIS-assisted NOMA in wireless communication systems. The closed upper bound of ergodic capacity analysis is obtained for the proposed technique by using both Rayleigh and Rician fading channel environments for multiple users. Compared to simulations, numerical results demonstrate the tightness and effectiveness of our closed-form expressions. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Rayleigh fading

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PToPI: A Comprehensive Review, Analysis, and Knowledge Representation of Binary Classification Performance Measures/Metrics

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SN computer Science 2023年第1期4卷 13页

作者： Canbek, Gürol Taskaya Temizel, Tugba Sagiroglu, Seref Pointr Ankara Turkey Informatics Institute Middle East Technical University Ankara Turkey Computer Engineering Department Gazi University Ankara Turkey

Although few performance evaluation instruments have been used conventionally in different machine learning-based classification problem domains, there are numerous ones defined in the literature. This study reviews and describes performance instruments via formally defined novel concepts and clarifies the terminology. The study first highlights the issues in performance evaluation via a survey of 78 mobile-malware classification studies and reviews terminology. Based on three research questions, it proposes novel concepts to identify characteristics, similarities, and differences of instruments that are categorized into ‘performance measures’ and ‘performance metrics’ in the classification context for the first time. The concepts reflecting the intrinsic properties of instruments such as canonical form, geometry, duality, complementation, dependency, and leveling, aim to reveal similarities and differences of numerous instruments, such as redundancy and ground-truth versus prediction focuses. As an application of knowledge representation, we introduced a new exploratory table called PToPI (Periodic Table of Performance Instruments) for 29 measures and 28 metrics (69 instruments including variant and parametric ones). Visualizing proposed concepts, PToPI provides a new relational structure for the instruments including graphical, probabilistic, and entropic ones to see their properties and dependencies all in one place. Applications of the exploratory table in six examples from different domains in the literature have shown that PToPI aids overall instrument analysis and selection of the proper performance metrics according to the specific requirements of a classification problem. We expect that the proposed concepts and PToPI will help researchers comprehend and use the instruments and follow a systematic approach to classification performance evaluation and publication. © 2022, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Classification Knowledge representation Machine learning Performance evaluation Performance measures Performance metrics Periodic table

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MobileDNN: Leveraging the Potential of Hybrid MobileNetV2-DNN for Advanced Image Analysis

MobileDNN: Leveraging the Potential of Hybrid MobileNetV2-DN...

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2024 International Conference on Science, engineering and Business for Driving Sustainable Development Goals, SEB4SDG 2024

作者： Ogundokun, Roseline Oluwaseun Maskeliunas, Rytis Damasevicius, Robertas Adebiyi, Marion Olubunmi Landmark University Department of Computer Science Omu Aran Nigeria Kaunas University of Technology Department of Multimedia Engineering Lithuania Kaunas University of Technology Faculty of Informatics Kaunas Lithuania

ISBN: (纸本)9798350358155

computer vision systems designed for posture recognition could offer valuable solutions in the healthcare sector, improving healthy ageing and supporting elderly individuals in their daily routines. One area of interest is the automatic detection of falls, which has garnered attention from computer vision and pattern recognition communities. While many existing methods rely on wearable sensors, which demonstrate high accuracy in fall detection, some individuals may be reluctant to wear such devices. Consequently, alternative approaches, such as vision-based techniques, have been developed. The proposed method utilizes a vision-based system that employs a convolutional neural network (CNN) to recognize and categorize various postures (e.g., sitting, lying, standing) in each frame, if available. This approach begins by detecting the person in the frame, applying background subtraction for human body shape extraction, and associating each daily activity with the extracted shape. The proposed model achieved an accuracy of 93.75%, which shows an outstanding performance over existing models. Subsequently, it estimates bounding boxes encompassing the predicted person's body shape. Overall, the proposed technique shows promising results for indoor monitoring systems. © 2024 IEEE.

关键词： Convolutional neural networks

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Roller Vibration Detection with Radar Sensor and Linear Discriminant Analysis 26

Roller Vibration Detection with Radar Sensor and Linear Disc...

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26th International Conference on Digital Signal Processing and its Applications, DSPA 2024

作者： Valuyskiy, Denis Vityazev, Sergey Vashkevich, Maxim Ryazan State Radio Engineering University Named after V.F. Utkin Ryazan Russia University of Informatics and Radioelectronics Computer Engineering Department of Belarussian State Minsk Belarus

ISBN: (纸本)9798350361728

This article is dedicated to research on the problems of quality control of rotation of industrial rollers using radar equipment. The radar signals reflected from roller are analyzed using short-time Fourier transform and classified using linear discriminant analysis technique. To evaluate the proposed approach an testbed has been implemented. To obtain a dataset a set of radar signals has been recorded. The results of experiments shown that the accuracy of the proposed approach of detecting roller condition is reach 98%. © 2024 IEEE.

关键词： Rollers (machine components)

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K-Banhatti Invariants Empowered Topological Investigation of Bridge Networks

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computers, Materials & Continua 2022年第12期73卷 5423-5440页

作者： Khalid Hamid Muhammad Waseem Iqbal Erssa Arif Yasir Mahmood Ahmad Salman Khan Nazri Kama Azri Azmi Atif Ikram Department of Computer Science Superior UniversityLahore54000Pakistan Department of Software Engineering Superior UniversityLahore54000Pakistan Department of Software Engineering Faculty of Information TechnologyThe University of Lahore54000Pakistan Advanced Informatics Department Razak Faculty of Technology and InformaticsUniversiti Teknologi MalaysiaKuala Lumpur54100Malaysia Faculty of Informatics and Applied Mathematics University Malaysia TerengganuMalaysia Department of Computer Science&Information Technology Faculty of Information TechnologyThe University of Lahore54000Pakistan

Any number that can be uniquely determined by a graph is called graph *** the most recent twenty years’innumerable numerical graph invariants have been described and used for correlation *** the fast and advanced environment of manufacturing of networks and other products which used different networks,no dependable assessment has been embraced to choose,how much these invariants are connected with a network graph or molecular *** this paper,it will talk about three distinct variations of bridge networks with great capability of expectation in the field of computer science,chemistry,physics,drug industry,informatics,and mathematics in setting with physical and synthetic constructions and networks,since K-Banhatti invariants are newly introduced and have various forecast characteristics for various variations of bridge graphs or *** review settled the topology of bridge graph/networks of three unique sorts with three types of K-Banhatti *** concluded outcomes can be utilized for the modeling of interconnection networks of Personal computers(PC),networks like Local area network(LAN),Metropolitan area network(MAN)and Wide area network(WAN),the spine of internet and different networks/designs of PCs,power generation interconnection,bio-informatics and chemical structures.

关键词： Bridge networks invariants k-banhatti indices maple network graph molecular graph

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