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International Image Processing, Applications and Systems Conference (IPAS)

作者： Dat T. Chung Quan Nguyen Thanh-Minh Nguyen Quang-Vinh Dinh University of Technology and Education Ho Chi Minh City Vietnam Posts and Telecommunications Institute of Technology Hanoi Vietnam University of Medicine and Pharmacy Ho Chi Minh City Vietnam Vietnamese-German University Vietnam

ISBN: (数字)9798331506520

ISBN: (纸本)9798331506537

Breast ultrasound is a non-invasive, economical method that is essential for the diagnosis of cancer. With the advent of deep learning in recent years, numerous CNN-based methods have been thoroughly studied for tasks including tumor localization and cancer classification. While prior single models performed well in both challenges, these approaches had several drawbacks, including long inference times, a need for a GPU, and the need for individual model fine-tuning. Our goal in this work is to create a new end-to-end multi-task architecture that can be used for both segmentation and classification. We obtained exceptional performance and time efficiency with our suggested method, achieving 79.8% and 86.4% in the segmentation challenge in DeepLabV3+ architecture.

关键词： Location awareness Image segmentation Ultrasonic imaging Head Biological system modeling Graphics processing units Multitasking linear programming Cancer Tumors

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Distribution System State Estimation Using Automatic Differentiation with JAX

Distribution System State Estimation Using Automatic Differe...

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IEEE Texas Power and Energy Conference (TPEC)

作者： Rochisnu Dutta Ravi Teja Alla Amarsagar Reddy Ramapuram Matavalam K. Shanti Swarup Dept. of Electrical Engineering IIT Madras Chennai India School of ECEE Arizona State University Tempe USA Arizona State University Tempe USA

ISBN: (数字)9798331541125

ISBN: (纸本)9798331541132

With the growing integration of active control de-vices in distribution systems, Distribution System State Estimation (DSSE) is increasingly critical for ensuring effective operational control and preventing outages. This paper presents a novel DSSE approach that combines OpenDSS as a power flow solver with Python for state estimation, utilizing smart meter data accessed via the py-dss-interface. A significant contribution of this work is the application of JAX (Just After eXecution), a machine learning framework, to accelerate the gradient descent solution of the Weighted Least Squares (WLS) objective function, removing the need for explicitly computing the Jacobian matrix. The proposed method is validated on unbalanced IEEE 13, 37, and 123 radial bus distribution systems, showing substantial improvements in computational efficiency and accuracy.

关键词： Jacobian matrices Accuracy Machine learning linear programming Smart meters Computational efficiency State estimation Load flow

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Valued Neighborhood Search for Determination of Pareto-Optimal Solutions

Valued Neighborhood Search for Determination of Pareto-Optim...

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International Symposium on Applied Machine Intelligence and Informatics (SAMI)

作者： Marek Kvet Jaroslav Janácek Michal Kvet Faculty of Management Science and Informatics University of Zilina Zilina Slovakia

ISBN: (数字)9798350379365

ISBN: (纸本)9798350379372

Classical version of the neighborhood search based on exchange operation tests objective function of solution obtained by the exchange operation and depending on the objective function value decides on further progress. When a series of Pareto-optimal solutions of the p-location problem is determined, huge number of such operations must be tested and evaluated. As many of exchanges are repeated with the same consequence for the further progress, it is questionable whether the previously obtained information about their success can be taken into account in the decision process. In this contribution, we focus on answering this question. We perform the associated research of influence of information about previous success or failure on effectiveness of the neighborhood search application to determination of a set of Pareto-optimal solutions.

关键词： Costs Decision making Transportation Search problems linear programming Approximation algorithms Informatics System analysis and design Machine intelligence

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Optimization Study of Flexibility Scheduling Strategies for Independent and Interactive Operation of Regional Integrated Energy Systems

Optimization Study of Flexibility Scheduling Strategies for ...

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Smart Grid and Green Energy (ICSGGE), International Conference on

作者： Xusheng Wang Qifen Li Bangpeng Xie Yiming Yuan Shanghai University of Electric Power Energy and Environment Engineering Institute Shanghai China State Grid Shanghai Pudong Electric Power Supply Company Shanghai China

ISBN: (数字)9798331542139

ISBN: (纸本)9798331542146

In today’s increasingly severe energy crisis, integrated energy systems have become an important way to solve the above problems because they can realize multi-energy complementarity and improve energy efficiency. The mathematical model of the integrated energy subsystem and the regional integrated energy system is constructed, and its objective function and constraints are analyzed, and then, based on the example, the data analysis of the operating costs of the multiple systems under the interactive operation mode and the independent operation mode is carried out. The results show that the system can save $6.61 \%$ of the total cost compared with the independent operation, which has better economic efficiency and energy utilization. By considering the changes in the costs of independent and interactive operation of the integrated district energy system at different confidence levels, it is concluded that the interactive operation mode is superior to the individual operation mode at any confidence level.

关键词： Costs Data analysis Power measurement Optimization models Size measurement linear programming Smart grids Power systems Thermal energy Optimization

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Towards Robust Subject Identification From EEG Segments With Data Augmentation Techniques

Towards Robust Subject Identification From EEG Segments With...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Meka Nani Supriyo Banerjea Raghavan R Speech Information Processing Lab Indian Institute of Technology Hyderabad India

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Electroencephalography (EEG) has a wide gamut of information, from subject identity to their emotional states encoded in it. Given a segment of the EEG signal, our study aims to identify the subject in a robust way using the EEGChannel-Net architecture. To achieve this goal, we add gaussian noise to the given 32-channel EEG signal, and minimize the ℓ 2 distance between embeddings of the original signal and that of the noisy signal in addition to the categorical cross entropy loss for classification of the 26 subjects in the dataset. Addition of noise to each channel at a fixed signal-to-noise ratio (SNR) of 15 dB gave the best balanced accuracy of 98.27% in the validation set. Our study concludes by justifying the optimality of the 15 dB SNR and highlights the superiority of our proposed objective function.

关键词： Accuracy Gaussian noise linear programming Brain modeling Electroencephalography Entropy Robustness Noise measurement Speech processing Signal to noise ratio

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Distributed Secretary Problem: A Case of Two Uneven Queues 25

Distributed Secretary Problem: A Case of Two Uneven Queues

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Companion Proceedings of the ACM on Web Conference 2025

作者： Ke Ding Bo Li Fangxiao Wang Department of Computing The Hong Kong Polytechnic University Hong Kong Hong Kong

ISBN: (纸本)9798400713316

Secretary problem is one of the most widely studied online stochastic models, in which an employer wants to hire the best candidate from n candidates who arrive in a random order. It is well-known that the optimal success probability is 1/e. However, in reality, things are more complex because employers often have interviewers in different cities, interviewing candidates in a distributed manner. This motivates us to study the secretary problem with multiple queues. Feldman and Tennenholtz [EC 2012] studied this assuming the candidates are distributed evenly. In particular, when there are two even queues, the optimal success probability is 1/4. In this work, we move to the general problem when the queues are arbitrary and design the optimal online algorithm for the case of two queues. Our results characterize the exact success probability curve, connecting the cases of a single queue and two equal queues. Our technique is grounded on the linear programming framework introduced by Buchbinder et al. [Math. Oper. Res. 2014] and a novel analysis.

关键词： linear programming

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Prescriptive Analytics for Logistics: Bridging Predictive Models and Actionable Decisions Through Advanced Optimization Techniques

Prescriptive Analytics for Logistics: Bridging Predictive Mo...

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Innovative Research in Applied Science, Engineering and Technology (IRASET),Conference on

作者： Oussama El Azzouzy Tarik Chanyour Said Jai Andaloussi Department of Mathematics and Computer Science Laboratory of Data Engineering and Intelligent Systems(LIDSI) Hassan II University Casablanca Morocco

ISBN: (数字)9798331532970

ISBN: (纸本)9798331532987

Modern logistics is facing increasing challenges due to the growing complexity of supply chains, high consumer expectations, and economic and environmental pressures. While predictive analytics, powered by artificial intelligence (AI) and massive data, has transformed the ability to forecast trends and risks, its application remains limited by the lack of effective mechanisms to convert these predictions into actionable decisions in dynamic and constrained environments. This paper proposes an innovative hybrid approach that combines advanced predictive models, notably the Temporal Fusion Transformer (TFT), with prescriptive algorithms, such as linear programming and deep reinforcement learning (DRL). The TFT demonstrated superior performance in terms of predictive accuracy (significant reduction in MAE, RMSE, and MAPE), while the prescriptive algorithms optimized complex logistics decisions in real time, even in uncertain environments. This integrated methodology was validated through use cases simulating critical logistics scenarios, such as delivery route optimization. Experimental results show a substantial improvement in operational efficiency, with reductions in costs, lead times and resource utilization. The prescriptive approach made it possible to automate complex decisions, while taking into account multiple constraints, such as costs, lead times and sustainability objectives. By integrating real-time data collected via IoT devices and logistics management systems, this architecture offers a robust, adaptable and scalable solution. It thus meets the requirements of modern logistics by enabling proactive, optimized and resilient decision-making. This research makes a significant contribution by bridging the gap between predictive and prescriptive analysis, while laying the foundations for new applications in the field of intelligent logistics.

关键词： Costs Supply chains Predictive models Prediction algorithms linear programming Transformers Real-time systems Thin film transistors Resource management Optimization

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Generating Cardiovascular Data by Integration of Physiological Information

Generating Cardiovascular Data by Integration of Physiologic...

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Computational Intelligence in Health and Medicine (CIHM), IEEE Symposium on

作者： Johannes Kummert Alexander Schulz Moriz Habigt Maike Stemmler Christina Kohler Dirk Abel Rolf Rossaint Barbara Hammer Machine Learning Group Bielefeld University Bielefeld Germany Anaesthesiology Clinic RWTH Aachen University Aachen Germany Institute of Automatic Control RWTH Aachen University Aachen Germany

ISBN: (数字)9798331508333

ISBN: (纸本)9798331508340

Medical data is a valuable resource that is under privacy constraints and often requires a substantial effort and cost to obtain. This is the case for physiological cardiovascular data that is among others utilized to develop assistive heart devices. In the present work, we aim to improve a GAN based generative approach from the literature by integrating physiological knowledge in form of pressure-value curves together with a dynamic time warping cost function into the model. We demonstrate that our adapted model generates more realistic cardiovascular signals as measured by targeted physiological markers and showcase that such generated signals can be used to improve a downstream task on real data.

关键词： Heart Adaptation models Visualization Data privacy Time series analysis Focusing Inspection linear programming Physiology Data models

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Lightweight Image Quality Prediction Guided by Perceptual Ranking Feedback

Lightweight Image Quality Prediction Guided by Perceptual Ra...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Aymen Sekhri Mohamed-Chaker Larabi Seyed Ali Amirshahi CNRS Université de Poitiers XLIM Poitiers France Norwegian University of Science and Technology Gjøvik Norway

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Automatic Image Quality Assessment (IQA) remains a difficult challenge due to the complexity of mimicking the Human Visual System (HVS) and the limitations of traditional objective Image Quality Metrics (IQM). Existing learnable methods often involve high computational costs and fail to adequately capture the nuanced perceptual characteristics of the HVS, including the human ability to rank image quality and human sensitivity to differences in areas with high-frequency. In this study, we propose an effective approach that addresses these challenges by incorporating the characteristics of HVS and the perceptual classification into a lightweight IQM framework based on the transformer architecture. This allows our method to capture long-range dependencies effectively. Our approach leverages Objective Error Maps (OEMs) to enhance sensitivity to visual errors and employs a ranking module as an objective function, providing feedback on the perceptual quality at the feature level. Experimental results demonstrate that our approach not only achieves competitive performance compared to state-of-the-art IQMs but also significantly reduces computational complexity.

关键词： Image quality Visualization Sensitivity Computer architecture Visual systems Signal processing Transformers linear programming Computational efficiency Speech processing

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Animal welfare and economic optimisation of farrowing systems

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Animal Welfare 2023年第1期20卷 57-67页

In many countries, including the UK, the majority of domestic sows are housed in farrowing crates during the farrowing and lactation periods. Such systems raise welfare problems due to the close confinement of the sow. Despite the fact that many alternative housing systems have been developed, no commercially viable/feasible option has emerged for large scale units. Current scientific and practical knowledge of farrowing systems were reviewed in this study to identify alternative systems, their welfare and production potential. The aim was to establish acceptable trade-offs between profit and welfare within alternative farrowing systems. linear programming (LP) was used to examine possible trade-offs and to support the design of welfare-friendly yet commercially viable alternatives. The objective of the LP was to optimise the economic performance of conventional crates, simple pens and designed pens subject to both managerial and animal welfare constraints. Quantitative values for constraints were derived from the literature. The potential effects of each welfare component on productivity were assessed by a group of animal welfare scientists and used in the model. The modelled welfare components (inputs) were extra space, substrate and temperature. Results showed that, when using piglet survival rate in the LP based on data drawn from the literature and incorporating costs of extra inputs in the model, the crates obtained the highest annual net margin and the designed pens and the pens were in second and third place, respectively. The designed pens and the pens were able to improve their annual net margin once alternative reference points, following expert-derived production functions, were used to adjust piglet survival rates in response to extra space, extra substrate and modified pen heating. The non-crate systems then provided higher welfare and higher net margin for sows and piglets than crates, implying the possibility of a win-win situation.

关键词： alternative housing systems animal welfare economic optimisation farrowing systems linear programming pig

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