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arXiv 2025年

作者： Huang, Huishi Wang, Haozhe Fang, Chongyu Yan, Mingge Xu, Ruochen Zhang, Yiyuan Wang, Zhanchi Ying, Fengkang Liu, Jun Laschi, Cecilia Ang, Marcelo H. Advanced Robotics Centre National University of Singapore 117608 Singapore Integrative Sciences and Engineering Programme National University of Singapore Graduate School 119077 Singapore School of Computer Science and Technology University of Science and Technology of China Anhui Hefei230027 China 138632 Singapore

—The logarithmic spiral is observed as a common pattern in several living beings across kingdoms and species. Some examples include fern shoots, prehensile tails, and soft limbs like octopus arms and elephant trunks. In the latter cases, spiraling is also used for grasping. Motivated by how this strategy simplifies behavior into kinematic primitives and combines them to develop smart grasping movements, this work focuses on the elephant trunk, which is more deeply investigated in the literature. We present a soft arm combined with a rigid robotic system to replicate elephant grasping capabilities based on the combination of a soft trunk with a solid body. In our system, the rigid arm ensures positioning and orientation, mimicking the role of the elephant’s head, while the soft manipulator reproduces trunk motion primitives of bending and twisting under proper actuation patterns. This synergy replicates 9 distinct elephant grasping strategies reported in the literature, accommodating objects of varying shapes and sizes. The synergistic interaction between the rigid and soft components of the system minimizes the control complexity while maintaining a high degree of adaptability. Copyright © 2025, The Authors. All rights reserved.

关键词： Robotic arms

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Stimulating Critical Thinking in a Web Programming Module with Generative AI Tools

Stimulating Critical Thinking in a Web Programming Module wi...

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IEEE Education Engineering (EDUCON)

作者： Usman Naeem Arne Styve Outi T. Virkki School of Electronic Engineering and Computer Science Queen Mary University of London London UK Department of ICT and Natural Sciences Norwegian University of Science and Technology (NTNU) Alesund Norway Information Technology Degree Programme Haaga-Helia University of Applied Sciences Helsinki Finland

ISBN: (数字)9798331539498

ISBN: (纸本)9798331539504

Web frameworks have significantly changed how developers create web applications for the Internet. Thanks to pre-defined libraries, these frameworks not only accelerate development time but also reduce the amount of code developers need to write. However, to get the most out of the frameworks and libraries, developers need to have a deep understanding of core web programming languages. This allows them to write efficient code, troubleshoot effectively, and push the boundaries of what the frameworks can achieve. The same principle applies to Generative Artificial Intelligence (AI) tools, as they have the potential to enhance a developer's toolkit. However, they will only be useful if the developer has sound fundamental knowledge to verify the output from these tools. Educators in higher education face a similar predicament with the widespread use of Generative AI tools by learners. Many learners rely on these tools as a go-to solution without being able to verify or fully comprehend the output, leading to shallow understanding. The work in this paper outlines an approach used in a first-year web programming module within the School of Electronic Engineering and computer science at Queen Mary University of London, where learners were encouraged to use Generative AI tools to stimulate critical thinking when conducting assessments. Specifically, GitHub CoPilot was used as a pair programmer, and ChatGPT served as a peer reviewer. In this context, the peer reviewer's role was to help the learner reflect on the tool's output. The aim of this study was to explore the design of active learning activities that incorporate Generative AI tools for web programming to foster critical thinking practices among learners. To evaluate our approach, we employed a critical thinking self-evaluation questionnaire instrument, where learners' opinions and customs were surveyed before and after both of the assignments.

关键词： Codes Generative AI Instruments Active learning Chatbots Libraries Internet Programming profession Faces Software development management

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Pattern Discovery in an EEG Database of Depression Patients: Preliminary Results

Pattern Discovery in an EEG Database of Depression Patients:...

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International Conference on Measurement

作者： Kateřina Hlaváčková-Schindler Christina Pacher Claudia Plant Mykola Lazarenko Milan Paluš Jaroslav Hlinka Aditi Kathpalia Martin Brunovský Data Mining and Machine Learning Research Group Faculty of Computer Science University of Vienna Vienna Austria Department of Complex Systems Institute of Computer Science Czech Academy of Sciences Prague Czechia Clinical Research Programme National Institute of Mental Health Klecany Czechia

The ability to predict response to medication treatment of depressed patients, either early in the course of therapy or before treatment even begins can avoid trials of ineffective therapy and save patients from prolonged intervals of suffering. Symptom alleviation requires 4-6 weeks after starting current antidepressive medication. Based on the data basis of the patients and their EEG before and on the 7th day of treatment we apply data mining, causal discovery and machine learning approaches to discover interactive patterns between patient’s brain regions to separate the treatment responders from non-responders. In this paper we report the preliminary results of our international project "Learning Synchronization Patterns in Multivariate Neural Signals for Prediction of Response to Antidepressants" ongoing at the University of Vienna, the Czech Academy of sciences and the National Institute of Mental Health in the Czech Republic.

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Socio-Transactional Impact of Recency, Frequency, and Monetary Features oN Customers’ Behaviour in Telecoms’ Churn Prediction

Iraqi Journal for Computer Science and Mathematics

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Iraqi Journal for computer science and Mathematics 2022年第2期3卷 101-110页

作者： Ibitoye, Ayodeji O.J. Onime, Clement Zaki, Nashwan Dheyaa Onifade, Olufade F.W. Computer Science Programme Bowen University Iwo22021 Nigeria The Abdusalam ICTP Centre Trieste Italy University of information Technology and Communications College of Engineering Iraq Department of Computer Science University of Ibadan Ibadan20221 Nigeria

Due to the increasing competitiveness in telecom’s market, it has now become more necessary for operators to start building personal relationship with customers for targeted retention strategies. Achieving this goal requires the development of an effective churn prediction model that will solve the problem of churn misclassification, which is persistent in current churn prediction models. With several existing segment-oriented churn prediction models failing to harness the power of associative networking provided by telecoms users, churn prediction accuracy remains unguaranteed while targeted decision support is not enhanced. Here, the research introduced the Customer’s Influence Degree (I) to the existing Recency, Frequency, and Monetary (RFM) values as an additional predictive factor, towards determining the churn class of a customer. The essence is to utilise the socio-transactional affinities of customers’ direct dependent to targeted communication nodes through customers RFM analysis to determine the dominance of a customer in the community. The newly introduced predictive factor helped to minimise churn misclassification rate through appropriate reclassification of customers who were wrongly classified as churner or non-churner when using the existing RFM churn scores only. © 2022 Autoctonía. Revista de Ciencias Sociales e Historia. All rights reserved.

关键词： Forecasting

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Hybrid Global Flexible Power Point Tracking Algorithm for Photovoltaic Systems

Hybrid Global Flexible Power Point Tracking Algorithm for Ph...

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2024 Energy Conversion Congress and Expo Europe, ECCE Europe 2024

作者： Kumaresan, Anusha Tafti, Hossein Dehghani Farivar, Glen G. Pou, Josep Strunz, Kai Niyato, Dusit Nanyang Technological University Energy Research Institute at Ntu Interdisciplinary Graduate Programme Singapore Australia The University of Melbourne Department of Electrical and Electronic Engineering VIC3010 Australia Nanyang Technological University School of Electrical and Electronic Engineering Singapore Technische Universität Chair for Sustainable Electric Networks and Sources of Energy Berlin Germany Nanyang Technological University School of Computer Science and Engineering Singapore

ISBN: (纸本)9798350364446

Frequency support in grid-connected photovoltaic (PV) systems is achieved by employing flexible power point tracking (FPPT) algorithms. Subsequently, according to the grid frequency requirements, the PV power is curtailed to a power reference, unlike the traditional method of operating the PV at the maximum power point. In practical cases, the PV arrays are prone to partial shading, and hence, there is a requirement to formulate the FPPT algorithms that operates effectively during such cases. Moreover, fast transient response is a necessity, which implies that the algorithms proposed in this paper is desirable. This paper proposes a hybrid global FPPT (GFPPT) algorithm based on secant and Newton's method, to shift the PV operating point to the required power reference. The Newton's method offers quadratic convergence rate and the secant method guarantees convergence. Hence, a hybrid algorithm consisting of these two methods will provide both fast and guaranteed convergence. Validation through simulation is presented in this paper and the proposed method is compared with the recently presented perturb and observe (P&O) GFPPT algorithm in the literature. © 2024 IEEE.

关键词： Newton-Raphson method

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PREDICTING STOCK PRICES USING PERMUTATION DECISION TREES AND STRATEGIC TRAILING

arXiv

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arXiv 2025年

作者： Ramraj, Vishrut Nagaraj, Nithin Harikrishnan, N.B. Department of Computer Science and Information Systems BITS Pilani K K Birla Goa Campus Goa 403726 India Complex Systems Programme National Institute of Advanced Studies IISc Campus Karnataka Bengaluru560012 India

In this paper, we explore the application of Permutation Decision Trees (PDT) and strategic trailing for predicting stock market movements and executing profitable trades in the Indian stock market. We focus on high-frequency data using 5-minute candlesticks for the top 50 stocks listed in the NIFTY 50 index. We implement a trading strategy that aims to buy stocks at lower prices and sell them at higher prices, capitalizing on short-term market fluctuations. Due to regulatory constraints in India, short selling is not considered in our strategy. The model incorporates various technical indicators and employs hyperparameters such as the trailing stop-loss value and support thresholds to manage risk effectively. Our results indicate that the proposed trading bot has the potential to outperform the market average and yield returns higher than the risk-free rate offered by 10-year Indian government bonds. We trained and tested data on a 60 day dataset provided by Yahoo Finance. Specifically, 12 days for testing and 48 days for training. Our bot based on permutation decision tree achieved a profit of 1.3468% over a 12-day testing period, where as a bot based on LSTM gave a return of 0.1238% over a 12-day testing period and a bot based on RNN gave a return of 0.3096% over a 12-day testing period. All of the bots outperform the buy-and-hold strategy, which resulted in a loss of 2.2508%. Copyright © 2025, The Authors. All rights reserved.

关键词： Marketplaces

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Service Graphs Generation in Intent-Based Networks

Service Graphs Generation in Intent-Based Networks

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Consumer Communications and Networking Conference, CCNC IEEE

作者： Sasan Sabour Amin Ebrahimzadeh Fetahi Wuhib Mbarka Soualhia Roch. H. Glitho Telecommunication Service Engineering Research Lab Concordia University Montréal QC Canada Ericsson Research Montréal QC Canada Computer Science Programme University of Western Cape Capetown South Africa

Intent-Based Networking (IBN) has recently gained interest to realize intelligent cloud management systems. IBN makes cloud consumption user-friendly by allowing users to specify “what needs to be done” rather than “how it should be done”. In this paper, we address the problem of service graphs generation in IBN, while considering functional requirements derived from user intent. We propose a solution that uses a domain ontology to translate the intents into their functional requirements which are specified in terms of initial services. Then, we use a service catalog along with the initial services to generate all possible service graphs that can meet the functional requirements of the given intent. Our evaluations show that the proposed solution achieves up to 84% improvement of the execution time compared to the existing benchmarks.

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Microservices Upgrade in Clouds: Dynamic Management of Version Dependencies and User Load

Microservices Upgrade in Clouds: Dynamic Management of Versi...

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IEEE International Conference on Cloud Networking (CLOUDNET)

作者： Azadeh Azhdari Amin Ebrahimzadeh Carla Mouradian Róbert Szabó Roch. H. Glitho CIISE Concordia University Montréal QC Canada Ericsson Research Montréal QC Canada Ericsson Research Budapest Hungary Computer Science Programme University of Western Cape Capetown South Africa

ISBN: (数字)9798350376562

ISBN: (纸本)9798350376579

In today's cloud computing environments, where scalability, agility, and resiliency are paramount, microservices architecture stands out as a fundamental keystone of modern software development. While microservices are designed as independent components communicating through well-defined APIs, maintaining and upgrading them pose unique challenges, including version compatibility, dependency management, and service continuity. These challenges become intricate when multiple instances of a specific microservice are deployed, utilizing load balancing to distribute users and offering different functionalities simultaneously. This paper proposes a heuristic algorithm to address the microservices upgrading problem. The proposed algorithm migrates users gradually and effectively by managing version dependencies, user load, considering propagation impact, multiple instances, and resource constraints. The simulation results demonstrate the superiority of our algorithm over existing benchmarks in terms of resource usage cost and the number of new version instances.

关键词： Cloud computing Costs Heuristic algorithms Simulation Scalability Microservice architectures Load management Optimization Software development management Resilience

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Spin-UP: Spin Light for Natural Light Uncalibrated Photometric Stereo

Spin-UP: Spin Light for Natural Light Uncalibrated Photometr...

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Conference on computer Vision and Pattern Recognition (CVPR)

作者： Zongrui Li Zhan Lu Haojie Yan Boxin Shi Gang Pan Qian Zheng Xudong Jiang Rapid-Rich Object Search (ROSE) Lab Interdisciplinary Graduate Programme Nanyang Technological University School of Electrical and Electronic Engineering Nanyang Technological University The State Key Lab of Brain-Machine Intelligence Zhejiang University College of Computer Science and Technology Zhejiang University National Key Laboratory for Multimedia Information Processing School of Computer Science Peking University National Engineering Research Center of Visual Technology School of Computer Science Peking University

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

Natural Light Uncalibrated Photometric Stereo (NaUPS) relieves the strict environment and light assumptions in classical Uncalibrated Photometric Stereo (UPS) methods. However, due to the intrinsic ill-posedness and high-dimensional ambiguities, addressing NaUPS is still an open question. Existing works impose strong assumptions on the environment lights and objects' material, restricting the effectiveness in more general scenarios. Alternatively, some methods leverage supervised learning with intricate models while lacking interpretability, resulting in a biased estimation. In this work, we propose Spin Light Uncalibrated Photometric Stereo (Spin-UP), an unsupervised method to tackle NaUPS in various environment lights and objects. The proposed method uses a novel setup that captures the object's images on a rotatable platform, which mitigates NaUPS's ill-posedness by reducing unknowns and provides reliable priors to alleviate NaUPS's ambiguities. Leveraging neural inverse rendering and the proposed training strategies, Spin-UP recovers surface normals, environment light, and isotropic reflectance under complex natural light with low computational cost. Experiments have shown that Spin-UP outperforms other supervised / unsupervised NaUPS meth-ods and achieves state-of-the-art performance on synthetic and real-world datasets. Codes and data are available at https://***/LMozart/CVPR2024-SpinUP.

关键词： Reflectivity Training Shape Supervised learning Anisotropic Rendering (computer graphics) Structural engineering

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Phase Dynamics and Directed EEG Connectivity in Treatment of Major Depressive Disorder

Phase Dynamics and Directed EEG Connectivity in Treatment of...

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International Conference on Measurement

作者： Anupam Ghosh Madhurima Bhattacharjee Aditi Kathpalia Martin Brunovský Milan Paluš Department of Complex Systems Institute of Computer Science of the Czech Academy of Sciences Prague Czech Republic Clinical Research Programme National Institute of Mental Health Klecany Czech Republic

In this paper, we infer the direction of information transfer between interacting subsystems using a cross-dependence index derived from the phase dynamics of coupled subsystems. First, we apply this method to unidirectionally coupled Rössler oscillators. This index always has a higher value along the direction of coupling than that opposite to the coupling. Finally, we employ this method in analysis of EEG signals. The aim of this analysis is to identify the direction of information transfer in the brain in patients suffering from depression and quantify its changes during the treatment process.

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