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Enhancing White Blood Cell Detection Using YOLOv8 Model

Enhancing White Blood Cell Detection Using YOLOv8 Model

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modeling, Simulation & Intelligent Computing (MoSICom), international conference on

作者： Piyu Kasundra Avani Khokhariya Amit Thakkar Rohan Vaghela Devanshi Dave Jigar Sarda Department of Computer Science & Engineering (CSPIT) Charotar University of Science & Technology Nadiad India

ISBN: (数字)9798331533311

ISBN: (纸本)9798331533328

White blood cells (WBCs) play a vital role in the immune system, defending the body against pathogens such as viruses, bacteria, parasites, and fungi, and are produced in bone marrow and lymphoid tissues. Traditional WBC analysis methods rely on manual counting, which is prone to human error and inefficiencies. Recent advancements in computeraided detection systems, powered by deep learning, have significantly improved the accuracy and speed of WBC diagnostics. These systems utilize convolutional neural networks (CNNs) to automatically extract important features from blood smear images, minimizing reliance on manual techniques and enhancing diagnostic reliability. This study employed various YOLO v8 model variants to detect specific WBC types, with evaluation metrics including precision, recall, and mean Average Precision (mAP). The results demonstrates that the YOLOv8 medium and nano variants achieved the highest mAP50 (IoU threshold of 50) value of $\mathbf{9 9 \%}$, while the small variant achieved an mAP50 of $98 \%$ over 25 epochs. When comparing mAP50-95 (IoU threshold of 95), the medium variant attained $91 \%$, while the nano variant achieved $90 \%$. Additionally, the nano and small variants reached the highest average precision of $99 \%$, while the medium and nano variants recorded the highest average recall at $\mathbf{9 8 \%}$.

关键词： White blood cells YOLO measurement Pathogens Accuracy Manuals Feature extraction Reliability Medical diagnosis Immune system

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Surrogate modeling assistant software 11

Surrogate modeling assistant software

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Workshop on Information Technology and Scientific Computing in the Framework of the 11th international conference Information and Telecommunication Technologies and Mathematical modeling of High-Tech systems, ITTMM 2021

作者： Demidova, Anastasia V. Velieva, Tatyana R. Korolkova, Anna V. Kulyabov, Dmitry S. 6 Miklukho-Maklaya St Moscow117198 Russia Plekhanov Russian University of Economics 36 Stremyanny lane Moscow117997 Russia Joint Institute for Nuclear Research Laboratory of Information Technologies 6 Joliot-Curie St. Dubna Moscow region141980 Russia

computer modeling is designed to predict the behavior of complex systems by solving the corresponding mathematical equations of the physical process. The simulation requires a huge number of parameters to be found, and they all require a large number of simulation runs, where each run takes a different combination of design parameters as input. computer simulations tend to be expensive. Research that requires a large number of computer calculations will lead to exorbitant computational costs, which will make them practically impracticable. This is what surrogate modeling is for. Surrogate modeling builds a statistical model to accurately approximate the simulation result. Subsequently, this trained model can replace the original computer simulation when performing system analysis. © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 international (CC BY 4.0).

关键词： computer software

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A Light-Weight Tool-Supported Method for Cyber Risk Assessment in the Planning of Cyber-Physical Smart Grids

A Light-Weight Tool-Supported Method for Cyber Risk Assessme...

引用

IEEE international conference on Smart Grid Communications (SmartGridComm)

作者： Gencer Erdogan Tesfaye Amare Zerihun Iver Bakken Sperstad Oddbjørn Gjerde Sustainable Communication Technologies SINTEF Digital Oslo Norway Energy Systems SINTEF Energi Trondheim Norway

ISBN: (数字)9798350318555

ISBN: (纸本)9798350318562

A major challenge during grid planning is the identification of cybersecurity threats potentially introduced by active digital measures. This challenge arises because grid planning occurs at an early, conceptual stage, typically years ahead of realization, and often lacks concrete information about the active digital measures at this early phase. This highlights the need for simple, user-friendly cyber risk assessment methods that grid planners can use, even without detailed information about the final solutions. To address this need, we propose a lightweight, tool-supported, six-step method. This method employs the Customer Journey modeling Language (CJML), which is comprehensible to various professional backgrounds, and which we have adapted to include the necessary cybersecurity concepts to help grid planners identify cybersecurity threats. The method is supported by our freely available, open-source risk modeling tool. Using a case based on a real-world electricity distribution grid, we demonstrate how our method supports grid planners in performing cyber-risk assessments with limited information about the final solutions and their vulnerabilities to cyber threats. Preliminary results indicate that our method is effective in enabling grid planners to assess potential cybersecurity risks during the planning phase, thereby enhancing the reliability and security of future electricity distribution systems.

关键词： computers Electric potential Adaptation models Phase measurement Planning Smart grids Risk management Reliability computer crime

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Enhanced Model for Automatic Tamil Text Summarization

Enhanced Model for Automatic Tamil Text Summarization

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Sustainable Computing and Data Communication systems (ICSCDS), international conference on

作者： Ignatious K Pious S Girirajan Computer Science and Engineering Vel Tech Rangarajan Dr Sagunthala R&D institute of Science and Technology Chennai India

Automatic Text Summarization (ATS) is a process of extracting few text portions from the given document. Such Text can also contain sentence that express the overall meaning of the document. Most of the research work in this field is carried out for Languages like English and Chinese with high accuracy. In this proposed work, hybrid model is used that combines Keyword-based score, sentiment score and Text Ranking-based score to perform Automatic text summarization on Tamil Language. To evaluate the performance of the proposed model, dataset that has been formulated from the scratch by using two reputed Tamil newspapers is considered. The Dataset have been categorized into four classes as Sports, Cinema, Astrology and Politics. The hybrid model increases the accuracy of Tamil text summarization when compared with previous research work. By using the proposed model average accuracy of around 0.81 as Recall score, 0.61 as Precision score and 0.67 as F score is achieved.

关键词： measurement Art Computational modeling Motion pictures Data mining Data communication Sports

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Performance Evaluation of Bifacial Photovoltaic Thermal systems in Environmental Condition

Performance Evaluation of Bifacial Photovoltaic Thermal Syst...

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Advanced Power Engineering and Energy (APEE), IEEE international conference on

作者： Ahmad Rajani Dalila Mat Said Zulkarnain Ahmad Noorden Nasarudin Ahmad Tinton Dwi Atmaja Ahmad Fudholi Faculty of Electrical Engineering Universiti Teknologi Malaysia (UTM) Johor Malaysia Centre of Electrical Energy System Institute of Future Energy Universiti Teknologi Malaysia Johor Bahru Malaysia Research Centre for Energy Conversion and Conservation Badan Riset dan Inovasi Nasional Bandung Indonesia Solar Energy Research Institute Universiti Kebangsaan Malaysia Bangi Selangor Malaysia

ISBN: (数字)9798350360936

ISBN: (纸本)9798350360943

This study aims to assess the performance of bifacial photovoltaic thermal (B-PVT) systems under real environmental conditions, considering factors such as solar radiation intensity and fluid mass flow rate. Testing was carried out in the city of Bandung, Indonesia. Sensors were to measure PV surface heat, inlet and outlet temperatures of air entering the system, as well as sensors to determine environmental conditions such as solar intensity. From the results of these measurements, the data was processed to obtain the efficiency of the bifacial PVT. From tests with different $\dot{m}$ , namely 0.15 and 0.25 kg/ $s$ , total efficiency values of the bifacial PVT system varying from 36.13% to 88.45%. This difference shows the importance of air flow rate regulation in maximizing system efficiency. To guide the development of more optimal designs and anticipate system performance under varying operating situations, mathematical modeling and computer simulations may be used in future research steps.

关键词： Photovoltaic systems Temperature sensors Temperature measurement System performance Sensor systems Regulation Sensors Solar radiation Thermal energy Testing

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Scenario-Based Trajectory Generation and Density Estimation Towards Risk Analysis of Autonomous Vehicles

Scenario-Based Trajectory Generation and Density Estimation ...

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international conference on Intelligent Transportation

作者： Edvin Johansson Matilda Sönnergaard Selpi Sadegh Rahrovani Parsia Basimfar Department of Computer Science and Engineering Chalmers University of Technology Sweden Autonomous Drive Department in VolvoCars Sweden

A large amount of testing is needed to determine when autonomous vehicles are sufficiently safe. To achieve this goal, test cases should be representative of real-world driving but also designed to provide sufficient coverage of both frequent and rare events. This is a crucial step in finding potential high-consequence events, failure borders of the Autonomous Driving (AD) function and accurate estimation of the corresponding residual risks. In this paper, we propose a new method to adapt generative models to generate vehicle trajectories that are representative of the ones collected from the real world. The method uses Non-Uniform Rational B-Splines (NURBS) combined with normalizing flows to build a statistical scenario model. The method allows us to estimate a joint probability density that can be used to evaluate the likelihood of different trajectory occurrences. We demonstrate the method for statistical modeling on the (smooth and abrupt) cut-in traffic scenario and we give an example of how the estimated joint probability distribution can be used to assess the risk (trajectory occurrence probability and criticality) for different test cases. The results can be used for accelerated testing purposes, where the aim is to sample the rare tests more frequently, but can also be used to calculate the failure probability of AD functions.

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The Personalized Customized Framework Built with Implicit Feedback and Features

The Personalized Customized Framework Built with Implicit Fe...

引用

2021 international conference on Electronic Information Engineering and computer Science, EIECS 2021

作者： Luo, Haoran Normal University Xiongchu Avenue Wollongong Joint Institute Faculty of Artificial Intelligence in Education Central China Hongshan District6 China

ISBN: (纸本)9781665416740

With the advent of post-web, emerging large-scale IR systems began to be strictly differentiated from simple applications that favored the realization of 'Memorization' in the traditional sense, and transformed to predictive tools with the mission of 'Generalization'. [1] Feedback from users in the direction of personalized customization in the IR field is a far-reaching example under the influence of this idea. In particular, what this paper wants to focus on is implicit feedback.[2]In this paper, you will see how the development of some other prerequisites in the IR field has profoundly affected the shaping of personalized customized services. Besides, the paper will also show an improved relevance feedback framework for analyzing the personalized services. By constructing the feature table, two types of features are added to the representation process in this paper to improve the accuracy of BM25 algorithm. After DCG calculations., this will ultimately improve the accuracy of the rankings. © 2021 IEEE.

关键词： computer science Computational modeling Tools Mathematical models

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Evolutionary Interest Representation Network for Click-Through Rate Prediction

Evolutionary Interest Representation Network for Click-Throu...

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IEEE international conference on Web Services (ICWS)

作者： Renjie Zhou Zhenming Jin Jian Wan Jilin Zhang Xingyu Guo Qiang Liu Key Laboratory of Complex Systems Modeling and Simulation of the Ministry of Education School of Computer Science and Technology Hangzhou Dianzi University Hangzhou China Key Laboratory of Complex Systems Modeling and Simulation of the Ministry of Education ITMO Joint Institute Hangzhou Dianzi University Hangzhou China School of Information and Electronic Engineering Zhejiang University of Science and Technology Hangzhou China Dept. of Computer and Information Technology Zhejiang Police College Hangzhou China

The rapid development of the Internet has revo-lutionized our lives, providing us with an array of convenient services. However, this revolution has also led to the problem of data overload. Personalized recommendation services have been widely recognized as an effective solution to this problem by both the industrial and academic communities. Accurate prediction of click-through rate (CTR) is a critical task in personalized recommendation systems since it can improve the user’s shopping experience, ultimately increasing revenue for the platform. To achieve accurate CTR prediction, it is crucial to capture user interests. While several methods for interest modeling exist, challenges related to user interest evolution and user behavior noise need further attention. This paper proposes a novel CTR prediction model named the Evolutionary Interest Representation Network (EIRN), which learns the evolving interest representation of users from their behaviors, profiles, and environmental attributes. In the model, we introduce an advertisement correlation graph decomposition layer and a noise filter layer to enhance and purify the user behavior representation. An interest extraction layer is designed to capture sequential correlations and common characteristics between user behaviors, representing their interests. Additionally, as user interests evolve over time and their importance changes, an attention-based interest evolution layer is designed to track the evolution of user interests. Our proposed method is validated using four public datasets and an industrial dataset, showing its superiority over existing CTR prediction methods.

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User Experience Evaluation of AR Assisted Industrial Maintenance and Support Applications

User Experience Evaluation of AR Assisted Industrial Mainten...

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Virtual Reality (ICVR), IEEE international conference on

作者： Akos Nagy Yannis Spyridis Gregory J Mills Vasileios Argyriou Department of Networks & Digital Media School of Computer Science & Maths ECE Kingston University Kingston Upon Thames UK

ISBN: (数字)9798350364231

ISBN: (纸本)9798350364248

The paper introduces an innovative approach to industrial maintenance leveraging augmented reality (AR) technology, focusing on enhancing the user experience and efficiency. The shift from traditional to proactive maintenance strategies underscores the significance of maintenance in industrial systems. The proposed solution integrates AR interfaces, particularly through Head-Mounted Display (HMD) devices, to provide expert personnel-aided decision support for maintenance technicians, with the association of Artificial Intelligence (AI) solutions. The study explores the user experience aspect of AR interfaces in a simulated industrial environment, aiming to improve the maintenance processes’ intuitiveness and effectiveness. Evaluation metrics such as the NASA Task Load Index (NASA-TLX) and the System Usability Scale (SUS) are employed to assess the usability, performance, and workload implications of the AR maintenance system. Additionally, the paper discusses the technical implementation, methodology, and results of experiments conducted to evaluate the effectiveness of the proposed solution.

关键词： measurement Productivity Solid modeling Three-dimensional displays Resists User experience Maintenance Safety Usability Artificial intelligence

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Stochastic Workflow modeling in a Surgical Ward: Towards Simulating and Predicting Patient Flow 13th

Stochastic Workflow Modeling in a Surgical Ward: Towards Sim...

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13th international joint conference on Biomedical Engineering systems and Technologies, BIOSTEC 2020

作者： Back, Christoffer O. Manataki, Areti Papanastasiou, Angelos Harrison, Ewen Department of Computer Science University of Copenhagen Copenhagen Denmark Usher Institute University of Edinburgh Edinburgh United Kingdom Department of Mathematics and Statistics University of Cyprus Nicosia Cyprus School of Computer Science University of St Andrews St Andrews United Kingdom

ISBN: (纸本)9783030723781

Intelligent systems play an increasingly central role in healthcare systems worldwide. Nonetheless, operational friction represents an obstacle to full utilization of scarce resources and improvement of service standards. In this paper we address the challenge of developing data-driven models of complex workflow systems - a prerequisite for harnessing intelligent technologies for workflow improvement. We present a proof-of-concept model parametrized using real-world data and constructed based on domain knowledge from the Royal Infirmary of Edinburgh, demonstrating how off-the-shelf process mining, machine learning and stochastic process modeling tools can be combined to build predictive models that capture complex control flow, constraints, policies and guidelines. © 2021, Springer Nature Switzerland AG.

关键词： Petri nets

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