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Application of Design Thinking in the Product Ideation Phase: Use of Agile Methodologies 1

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4th International Conference on Advanced Research in Technologies information Innovation and Sustainability-ARTIIS-Annual

作者： Noversa, Ricardo Tereso, Anabela Sousa, Paulo Teixeira, Senhorinha Univ Minho Masters Engn Project Management P-4804533 Guimaraes Portugal Univ Minho Dept Prod & Syst ALGORITMI Res Ctr LASI P-4710057 Guimaraes Portugal

ISBN: (数字)9783031832079

ISBN: (纸本)9783031832062;9783031832079

The transition to higher education presents challenges for incoming students. In a demanding academic environment, autonomy emphasizes fostering collaboration within the student community. This approach enhances interaction and integrates experienced students' knowledge to support peers, aiming to improve academic performance. The study is centered on developing software prototypes for a digital platform to facilitate the intermediation of contacts among students, primarily for scheduling tutoring services. An Action Research strategy was employed, using focus group techniques to actively involve participants in the project. This method, supported by Design Thinking, utilized iterative phases that generated valuable insights, leading to the creation of several prototypes tailored to the real needs of users. This iterative process not only highlights the significance of each phase but also explores how they collectively enhance product software development, focusing on ideating and refining concepts based on the perspective of future users. The testing of these prototypes met user expectations, demonstrating the effectiveness of the Design Thinking approach. This contributed to satisfying user needs and promoting collaboration through interaction with the focus group. Moreover, adopting the Kanban project management method allowed for practical and efficient workflow management. Consequently, this article not only promotes methodologies that facilitate the ideation of a digital product designed to address a real-world need but also underscores how project management can be an integral ally in development, ensuring effective integration.

关键词： Product Ideation Design Thinking Project Management

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Leveraging CPU-FPGA Co-design for Matrix Profile Computation 11th

Leveraging CPU-FPGA Co-design for Matrix Profile Computation

引用

11th Latin American Conference on High Performance Computing

作者： Huseynli, Fariz Raoofy, Amir Schulz, Martin Tech Univ Munich Chair Comp Architecture & Parallel Syst Munich Germany Bavarian Acad Sci & Human Leibniz Supercomp Ctr Garching Germany

ISBN: (纸本)9783031800832;9783031800849

Current technology trends in high-performance computing (HPC) are pushing us towards accelerated systems. While GPU-based systems are the most common option, not all applications work well on such architectures. Solutions, like programmable hardware in the form of FPGAs (Field Programmable Gate Arrays), can be a powerful alternative. However, the complexity of developing specialized computing units in FPGAs, which are optimized for a specific task, often limits their broad utilization. In this paper, we follow a co-design methodology to identify the key computational routines and to replace them by using user-friendly libraries that wrap complex FPGA access mechanisms. This simplifies the usage of specialized compute units in FPGAs. To demonstrate our approach, we focus on performance improvements for an HPC/BigData application called (MP)N, which is built around widely used data analytics algorithm computing the matrix profile for multidimensional time series. In this application, we identify a sorting kernel as one of the key time consumers and accelerate it designing a parallel sorting library and using it to offload sorting batches to the FPGA. At the same time, we enable efficient utilization of CPU resources through overlap and pipelining. We achieve a 2-fold run time improvement for computing a 128dimensional time series of 7 million records, with the performance gap increasing as the number of records grows, highlighting the potential of CPU-FPGA co-design in HPC.

关键词： CPU-FPGA Co-Design Time Series Mining HPC

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Semi-Quasi-Overlap Functions and Their Applications in Classifier Ensemble 4th

Semi-Quasi-Overlap Functions and Their Applications in Class...

引用

4th International Conference on Artificial Intelligence Logic and Applications

作者： Qiao, Junsheng Hu, Jia Northwest Normal Univ Coll Math & Stat Lanzhou 730070 Peoples R China Gansu Prov Res Ctr Basic Disciplines Math & Stat Lanzhou Peoples R China

ISBN: (纸本)9789819603534;9789819603541

This study is devoted to an investigation of a vital weak form of overlap functions (OFs) named with semi-quasi-overlap functions (SQOFs) and their applications in classifier ensemble. The main results are: (1) several construction ways for SQOFs via quasi-automorphisms (QAs), unary functions and strong fuzzy negations (SFNs) are proposed;(2) using 0,1-semi-quasi-overlap functions (0,1-SQOFs) and specific dualistic functions, two equivalent characterizations of SQOFs are obtained;(3) by introducing SQOFs into discrete Choquet integral, semi-quasi-overlap function based discrete Choquet integral (CSQOF-Integral) is proposed and used as a combination method of classifier ensemble.

关键词： Aggregation function Overlap function Semi-quasi-overlap function Choquet integral Classifier ensemble

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Clustering Analysis for Forecasting Medicine Consumption 5th

Clustering Analysis for Forecasting Medicine Consumption

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5th International Conference on Innovative Intelligent Industrial Production and Logistics

作者： Machado, Douglas Mateus Yahouni, Zakaria Alpan, Gulgun Koala, Denis Univ Grenoble Alpes CNRS Grenoble INP G SCOP F-38000 Grenoble France KLS Grp F-38240 Meylan France

ISBN: (纸本)9783031807596;9783031807602

This study investigates machine learning for forecasting medicine consumption in hospitals to optimize resource allocation and logistics. We use two approaches: a unified approach that combines data from multiple hospitals and a separated approach that forecasts for individual hospitals. We explored both K-means clustering and manual pair clustering based on consumption trends. While K-means clustering did not yield improvements, manual clustering identified specific pairs of medicines with significantly enhanced forecast accuracy (e.g., Medicine 15 at Hospital 1: MAPE decreased from 19.70% to 3.30%). However, the unified approach did not consistently benefit all hospitals (e.g., Medicine 9). This underscores the need to balance accuracy gains in some hospitals against potential losses in others. Overall, manual clustering within the separated approach shows promise. Future work should explore advanced automated clustering techniques like Dynamic Time Warping (DTW) and leverage larger datasets for further validation.

关键词： Medicine consumption Forecasting demand Machine learning Clustering

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Satellite Data Analysis for the Observation and Monitoring of Cultural Heritage. The Case of the Archaeological Park of Metaponto, Italy

Satellite Data Analysis for the Observation and Monitoring o...

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4th International Conference on Advanced Research in Technologies information Innovation and Sustainability-ARTIIS-Annual

作者： Fattore, Carmen Priore, Arcangelo Porcari, Sara Porcari, Vito Univ Basilicata Dept European & Mediterranean Cultures Architectu Potenza Italy

ISBN: (纸本)9783031834318;9783031834325

Continuous monitoring is crucial for identifying potential threats to cultural heritage sites and implementing timely maintenance and preventive interventions. Scheduled inspections and proactive maintenance strategies are essential to prevent degradation and ensure long-term preservation. This study explores the use of satellite data and remote sensing technologies to monitor and preserve cultural heritage, with a focus on an archaeological park. The use of remote sensing techniques is essential for effective cultural heritage management. Satellite data provides high-resolution imagery that is instrumental in tracking environmental changes and assessing the impacts of human activities. This research utilizes Google Earth Engine (GEE) to process and analyze large datasets, employing spectral indices such as NDVI, NDMI, and NDSI to evaluate vegetation health, soil moisture, and soil characteristics. The methodology involves trend analysis and change detection, highlighting the temporal variations in the study area. The use of cloud-based platforms like GEE facilitates efficient data processing and enhances the scalability of the methodology, making it applicable to various environmental contexts.

关键词： Cultural Heritage Remote Sensing Spectral Index Monitoring

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Technologies and Systems for Monitoring the Onset of Accidents at Strategic Construction 2nd

Technologies and Systems for Monitoring the Onset of Acciden...

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2nd International Conference on information Technologies and Their Applications

作者： Aliev, Telman Musaeva, Naila Rzayeva, Narmin Mammadova, Ana Azerbaijan Univ Architecture & Construct Ayna Sultanova 11 Baku Azerbaijan Inst Control Syst Minist Sci & Educ 68 B Vahabzade AZ-1141 Baku Azerbaijan Azerbaijan Tech Univ G Javid Ave 25 AZ-1148 Baku Azerbaijan

ISBN: (纸本)9783031734199;9783031734205

Currently, the beginning of transition to emergency states is not reflected in the readings of measurement equipment of control systems of many essential technical facilities. The signaling of the beginning of the latent period of an emergency state is not implemented either. There are no tools for monitoring malfunctions of the railroad bed, or for controlling the beginning of the emergence of various typical malfunctions in the equipment of urban water supply systems, which are operated in continuous rotary motion under high pressure. Control systems of said facilities detect malfunctions only when they already have a clearly pronounced form. Nevertheless, specialists and operating personnel use this information to take action and prevent various accidents. However, in some cases, it is too late and an accident becomes unavoidable. At the same time, the emergence of a malfunction at these facilities is accompanied with the emergence of noise in the vibration signals at the outputs of the vibration sensors in their control systems. This noise contains diagnostic information. In this study, we propose technologies for generating informative attributes that can be used to control the beginning of the latent period of accidents. We also show the possible applications of the proposed technologies in developing intelligent systems for controlling the onset of accidents at facilities under investigation and other strategic construction.

关键词： control signaling noise informative attribute construction facilities pumping stations malfunction seismic stability railroad track vibration signal

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Advancing Sensitive Health Data Recognition and Normalization Through Large Language Model Driven Data Augmentation

Advancing Sensitive Health Data Recognition and Normalizatio...

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2024 International Workshop on Deidentification of Electronic Medical Record Notes

作者： Chao, Chia-Yi Lin, Cheng-Wei Natl Kaohsiung Univ Sci & Technol Coll Elect Engn & Comp Sci Intelligent Syst Lab Kaohsiung Taiwan

ISBN: (纸本)9789819779659;9789819779666

Electronic Medical Record (EMR) text notes are a digital version of a patient's paper chart. It contains a comprehensive record of a patient's medical history. EMR text notes are designed to streamline healthcare processes, improve accuracy, and enhance patient care by providing easy access to up-to-date patient information for healthcare providers. The AI-cup 2023 competition for privacy protection and standardization of electronic medical records (EMR) has released a dataset annotated with sensitive health information (SHI) and temporal normalization values. This dataset aims to facilitate the development and evaluation of state-of-the-art natural language processing technologies for the task of privacy protection and standardization of EMR text notes. However, we observed that the annotation distribution for different SHI types is highly unbalanced. We, therefore, proposed a large language model (LLM)-powered data augmented approach to generate synthesized training instances to train anLLMbased on the Pythia-410m model released by EleutherAI. Combined with the pattern-based post-processing method, our team, TEAM_3917, achieved macro-F-scores of 0.8155 and 0.8065 for SHI recognition and temporal information normalization, respectively, which were officially ranked fourth during the competition.

关键词： Natural language processing de-identification sensitive health information temporal information normalization data augmentation pattern-based large language model

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Towards Optimal Leakage Assessment of TVLA 7th

Towards Optimal Leakage Assessment of TVLA

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8th Asia Pacific Web and Web-Age information Management Joint International Conference on Web and Big Data

作者： Bi, Yuanqiao Li, Weijian Xie, Guiyuan Jianghan Univ Engn Training Ctr Wuhan Peoples R China Guangdong Polytech Normal Univ Sch Comp Sci Guangzhou Peoples R China

ISBN: (纸本)9789819600540;9789819600557

Since side-channel attacks pose a very serious threat to cryptographic products, leakage assessment plays a key role in the evaluation of the physical security of cryptographic products before putting into the market. However, the widely used Common Criteria (CC) method is both costly and difficult to apply, while the Test Vector Leakage Assessment (TVLA) method fails to accurately detect key leakage points. In this paper, a feature selection technique in machine learning is introduced, with which the leakage points detected by TVLA are treated as features for supervised learning. According to their contribution to the classification, irrelevant features are removed, while the optimal features remained, which identify more important leakage points. We further extend the assessment from two groups to multiple groups, which achieves much better performance. Experimental results show that, compared with existing methods such as TVLA,chi(2)-test, TVLA-Bonferroni and ANOVA test, our methods detect leakage points more accurately and stably, and greatly improve the evaluation performance in term of accuracy, leakage hit rate and false positive rate. Besides, our methods require much fewer power traces and shorter time for evaluation than existing methods.

关键词： Side-channel Attacks Leakage Evaluation Feature Selection

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Optimizing Internal Logistics Using Automated Guided Vehicles: An Evaluation of Heuristic Approaches 5th

Optimizing Internal Logistics Using Automated Guided Vehicle...

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5th International Conference on Innovative Intelligent Industrial Production and Logistics

作者： Oliveira, Jose Fernandes, Bernardo Henriques, Marcelo Univ Minho Algoritmi Res Ctr P-4710057 Braga Portugal Univ Minho Dept Prod & Syst P-4710057 Braga Portugal

ISBN: (纸本)9783031807749;9783031807756

Future factories, underpinned by Industry 4.0 and Industry 5.0 frameworks, increasingly depend on Automated Guided Vehicles (AGVs) and Intelligent Autonomous Vehicles to enhance internal logistics efficiency. These vehicles are integral to achieving greater efficiency, safety, and adaptability in modern manufacturing environments. AGVs are transformative technologies that significantly enhance internal logistics operations in modern manufacturing. Despite their numerous advantages, overcoming key challenges is crucial for their successful integration and sustainable operation. This paper evaluates the operational efficiencies of AGVs in industrial settings, with a focus on optimising the sequencing of AGV movements. Traditionally, the First In, First Out (FIFO) method has been employed to decide the next job for the AGV. However, through computational experiments, we analyse various heuristic methods to enhance the throughput and reduce idle times or 'empty' movements of AGVs, thereby optimising internal logistics and supporting robust production processes. The FIFO approach, while straightforward, often leads to suboptimal scheduling outcomes, especially in complex and dynamic manufacturing environments where job priorities frequently shift. It is increasingly evident that FIFO is inadequate for the nuanced demands of modern AGV operations, which benefit significantly from the adaptability and efficiency provided by heuristic solutions. This study suggests that advanced heuristics, particularly those designed for solving Travelling Salesman Problem (TSP) or Vehicle Routing Problem (VRP) are better suited to these tasks. These methods not only offer more flexible and efficient route planning but also significantly improve the overall utility of AGVs in high-demand scenarios.

关键词： Logistics AGV planning Constructive heuristic

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Edge AI to Edge Robotics: Enhancing Human Pose Estimation with High-Performance TPU Computing 4th

Edge AI to Edge Robotics: Enhancing Human Pose Estimation wi...

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4th International Conference on Advanced Network Technologies and Intelligent Computing-ANTIC-Annual

作者： Sharma, Vijeta Mupenda, Didier Numbi Thorvik, Lars Mishra, Deepti NTNU Norwegian Univ Sci & Technol Educ Technol Lab Dept Comp Sci IDI N-2815 Gjovik Norway

ISBN: (纸本)9783031837821;9783031837838

The convergence of Edge AI and high-performance computing (HPC) is revolutionising intelligent systems by enabling real-time data processing and decision-making at the network's edge. The demand for high-performance computing in resource-constrained environments opens opportunities for applications such as autonomous vehicles, smart cities, and industrial automation. This study presents the terminology that evidences the evolution of edge AI to the edge Robotics landscape, and then we present the novel approach to leveraging Tensor Processing Units (TPUs) to enhance the inference capabilities of robotic systems at the edge. Using a Reachy robot as a case study, we demonstrate real-time human pose estimation powered by TPUs. The research investigates the intersection of robotics, Edge AI, and HPC, focusing on accelerating inference tasks with TPUs. We implemented deep learning-based human pose estimation models-PoseNet-ResNet50, PoseNet-MobileNet V1, MoveNet Lightning, and MoveNet Thunder-on the Robot Operating System (ROS) and benchmarked their performance. Results show that MoveNet Thunder achieved the fastest inference time (48 ms) with a pose score of 98%, while PoseNet-ResNet50 was the slowest (701 ms) with a score of 93%. Our findings highlight the significant improvements in inference speed and accuracy using TPUs over CPUs. We discuss the implications of TPU-accelerated AI in robotics and explore future research directions in this evolving field.

关键词： High-Performance Computing Edge AI Tensor Processing Unit (TPU) Inferencing Human pose estimation Robotics

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