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IEEE Transactions on Artificial Intelligence 2023年第4期4卷 884-895页

作者： Yu, Haoxiang Raychoudhury, Vaskar Saha, Snehanshu Edinger, Janick Smith, Roger O. Gani, Md Osman The University of Texas at Austin Department of Electrical and Computer Engineering AustinTX78712 United States Miami University Department of Computer Science & Software Engineering OxfordOH45056 United States Bits Pilani K.K. Birla Goa Campus Department of Computer Science & Information Systems Appcair Zuarinagar403726 India University of Hamburg Department of Informatics & Distributed Operating Systems Hamburg20146 Germany University of Wisconsin-Milwaukee Department of Rehabilitation Sciences & Technology MilwaukeeWI53706 United States University of Maryland Baltimore County Department of Information Systems BaltimoreMD21250 United States

Finding a barrier-free accessible path through the built environment is necessary for wheelchair users. Researchers have identified the effect of surface vibration on the health of wheelchair users and proposed various solutions to identify and annotate mobility barriers. However, the effects of surface-induced vibration on accessibility are yet to be investigated. In order to address this problem, we present the WheelShare system, which uses machine learning to identify surfaces and curbs from vibration captured by accelerometer and gyroscope sensors (both smartphone and wearable device). WheelShare allows users to share their collected data via crowdsourcing. Based on this surface-specific vibration, we recognize 32 different surfaces found across the built environment (in Austria, China, France, Germany, India, and the USA for 32 human subjects) with an accuracy of 97.5%. The recognized surfaces are then grouped into different categories based on their characteristics. Our novel contributions in this article include the following. 1) We have developed a machine-learning-enabled surface recognition system that uses sensor data to capture surface-induced vibration patterns. 2) We have tested the robustness of the system for devices with only accelerometer data (such as low-end smartphones) and achieved an accuracy of 91.6%. 3) We have deployed our prototype WheelShare system for real-time surface classification in new sites that are unseen in training and testing and successfully recognized the surface characteristics. © 2020 IEEE.

关键词： Accelerometers

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One Flag to Rule Them All? On the Quest for Compiler Optimizations to Improve Fault Tolerance

One Flag to Rule Them All? On the Quest for Compiler Optimiz...

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European Dependable Computing Conference (EDCC)

作者： Robin Thunig Marcel Johannfunke Tianhao Wang Horst Schirmeier Chair of Operating Systems TU Dresden Germany Department of Computer Science 12 TU Dortmund Germany

ISBN: (数字)9798350360684

ISBN: (纸本)9798350360691

Soft errors pose a threat to all types of software-controlled electronic devices and can result in silent data corruptions (SDCs). Compiler optimizations usually target program execution time or memory footprint. They are oblivious of the fault tolerance of the resulting code, yet they might still be beneficial in this regard. However, it is non-trivial to pick a SDC-minimizing subset from the plethora of compiler flags for an individual program. Ideally, a developer could collectively enable reliability-improving optimizations with a single compiler *** this paper, we analyze the impact of compiler optimizations on the occurrence of SDCs. We consider nearly all GCC optimizations on x86 under CPU-register faults. We show that the same compiler optimizations can have a positive or negative effect depending on the target program. We search for a beneficial flag combination using a genetic algorithm, accelerated by a machine-learning based SDC predictor. Our findings suggest that while this leads to an improvement over -O0 of 7.1%, -O3 is a good default alternative.

关键词： Fault tolerance Program processors Codes Fault tolerant systems Europe Machine learning Optimization

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Analyzing the Effect of Taproot on Bitcoin Deanonymization

Analyzing the Effect of Taproot on Bitcoin Deanonymization

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International Conference on Distributed Computing systems Workshop

作者： Felix Kleinwort Wolf Posdorfer Janick Edinger Department of Computer Science Distributed Operating Systems University of Hamburg Hamburg Germany Department of Computer Science Computer Networks University of Hamburg Hamburg Germany

Bitcoin was released in 2008 as an electronic peer-to-peer payment system. The aim was to enable financial transactions in an anonymous manner between participating parties. However, Bitcoin is considered a pseudonymous network rather than anonymous, as the identity of the address owner is unknown, but every transaction is permanently stored on the Bitcoin blockchain and can be tracked by anyone. The structure of the blockchain, its transactions, and the Bitcoin network make it possible to deanonymize pseudonyms through various methods such as flow analysis, heuristics, and network traffic observations. Once a connection is established between pseudonyms used in the Bitcoin network and the real world, all previous transactions can be attributed to that identity. In 2021, Taproot was introduced to further increase privacy within the Bitcoin Network by introducing a new address format which will allow transactions to be more indistinguishable from one another. In this paper, we analyze current methods for deanonymizing Bitcoin transactions to understand which parts of the Bitcoin protocol they exploit. In addition, we look at the changes introduced by Taproot and determine the extent to which these changes affect the methods and what assumptions must be made for these methods to remain applicable.

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Development of an Interactive Map Within the Implementation of Actual State and Public Directions 12

Development of an Interactive Map Within the Implementation ...

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12th International Conference on Advanced computer Information Technologies, ACIT 2022

作者： Lupei, Maksym Shlahta, Myroslav Mitsa, Oleksandr Horoshko, Yurii Tsybko, Hanna Gorbachuk, Vasyl Institute of Cybernetics of National Academy of Sciences of Ukraine Department of Intellectual Information Technologies Kyiv Ukraine Lviv National University Department of Ukrainian Geographics Lviv Ukraine Uzhhorod National University Department of Informative and Operating Systems and Technologies Uzhhorod Ukraine Taras Shevchenko National University 'Chernihiv Colehium' Department of Computer Science and Computer Engineering Chernihiv Ukraine

ISBN: (数字)9781665410502

ISBN: (纸本)9781665466479

The problem of developing an effective way to display selected dynamic information of geographical content on an interactive map is being investigated. Various approaches to solving this problem are analyzed, including the use of Python programming language. Pointing out their advantages and disadvantages, the paper proposes an approach that allows one to complete the task in full with high efficiency and low cost of time and human resources. It is based on a model that uses a Data science methodology of five stages: obtaining primary data, data processing, necessary calculations, visualization creating and visualization disseminating. As a source of data there were used open data from the web portal 'Diia', developed by the Ministry of Digital Transformation of Ukraine, and data from the Institute of National Memory. The processing of the data was as follows: each toponym was assigned a localization binding and it was determined whether it falls under the law on decommunization or not. The processed data were visualized using the Google Maps web mapping service. Each non-decommunized object was marked on the map. The interactive map is integrated into the Analitycs-UA web portal. © 2022 IEEE.

关键词： Geographic information systems

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Evaluation of Wireless Technologies for an Embedded Camera-based Pest Monitoring System

Evaluation of Wireless Technologies for an Embedded Camera-b...

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IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)

作者： Leonard J. Zurek Amin Kargar Brendan O’Flynn David Niederprüm Lars Wolf Dimitrios Zorbas Tyndall National Institute University College Cork Ireland Institute of Operating Systems and Computer Networks Technische Universität Braunschweig Germany Department of Computer Science Nazarbayev University Astana Kazakhstan

Thorough pest monitoring is essential for sustainable farming. Wide monitoring coverage can support farmers in maintaining abundant harvests while pesticides are reduced and used more efficiently. Various research projects studied the use of Internet of Things (IoT) devices to establish smart farming. These devices can gather a vast amount of data to assist the detection of pests. However, when working on remote fields many constraints such as limited cellular coverage and absence of power supply are present. Thus, high computational tasks cannot natively be performed on the fields. To overcome some of these constraints, an embedded camera-based trap system has been developed to detect one particular type of pest: Brown Marmorated Stink Bug (BMSB). To leverage the usage of this system, this paper presents an evaluation of commercially available radio modules for the wireless technologies: Bluetooth Low Energy (BLE), LoRa, and IEEE 802.15.4. In order to place this system anywhere on the orchard, we analyze the transmission range and reliability for image transmission. The preliminary experiments show that although commercially available radio modules are often easier to integrate due to an additional Microcontroller Unit (MCU) managing the communication, additional power consumption can have great affect on the systems’ battery lifetime.

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Optimizing Emergency department Staff Configurations Through Simulation and Montecarlo Clustering Search Algorithm (Mcsa)

SSRN

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SSRN 2025年

作者： Harita, Maria Wong, Alvaro Rexachs, Dolores Bruballa, Eva Epelde, Francisco Luque, Emilio Department of Computer Architecture and Operating Systems Carrer de les Sitges Cerdanyola del Valles Barcelona08193 Spain Computer Science School Avinguda de la Generalitat 202 Sant Cugat del Valles Barcelona08174 Spain Department of Medicine Hospital Universitari Parc Taulí Parc Tauli 1 Sabadell Barcelona08208 Spain

The Hospital Emergency department (ED) provides critical care for acute and urgent conditions, making it one of the most complex areas in healthcare. Optimizing staff configurations to reduce patient waiting times and improve efficiency is a significant challenge. This study introduces a methodology that integrates an agent-based simulation model with the Montecarlo Clustering Search Algorithm (MCSA). Designed to handle multidimensional and combinatorial challenges, the approach identifies optimal staff configurations to manage large patient volumes with varying acuity levels within a ED. Key Performance Indicators (KPIs), such as Length of Stay (LoS), guide the optimization process by aligning medical staff allocation—doctors, nurses, and technicians—with patient arrival patterns. The proposed framework ensures practical, real-world solutions without reallocating personnel from other hospital areas, maintaining operational balance while scaling resources to meet ED demands. A key advantage of MCSA is its ability to reduce computational time compared to exhaustive search methods, enabling efficient exploration of complex search spaces. Results validate this methodology, demonstrating significant reductions in LoS compared to a baseline configuration. By identifying effective staff arrangements, this approach provides decision- makers with a robust and scalable tool to optimize ED operations. It enhances system performance and improves KPIs while avoiding the impracticality of exhaustive computational methods, ensuring applicability in healthcare environments. © 2025, The Authors. All rights reserved.

关键词： Decision making

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Analysis of the Resilience of an Emergency department: The Case of Accident with Multiple Victims

Analysis of the Resilience of an Emergency Department: The C...

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2023 Winter Simulation Conference, WSC 2023

作者： Rodriguez, Mariela Boixader, Francesc Bruballa, Eva Epelde, Francisco De Giusti, Armando Wong, Alvaro Rexach, Dolores Luque, Emilio National University of Jujuy Faculty of Engineering 10 Italo Palanca Jujuy4600 Argentina Computer Science School Universitat Autonoma de Barcelona Barcelona Sant Cugat del Vallès08174 Spain University Hospital Parc Tauli Universitat Autonoma de Barcelona Internal Medicine Sadabell Barcelona08208 Spain National University of la Plata Faculty of Informatics Calles 50 y 120 Buenos Aires La Plata1900 Argentina Universitat Autonoma de Barcelona Computer Architecture and Operating Systems Department Barcelona Edific Q Campus UAB Bellaterra08193 Spain

ISBN: (纸本)9798350369663

The care of multiple victims such as in natural disasters in an Emergency department is critical. This differs from ordinary care by the number of patients that arrive, their severity and insufficient staff for these events. Designing and simulating this real life scenario will be useful for disaster management decision makers. The objective of this simulation is to model a system with resilience to critical situations. To model the input of this research, we worked with the percentage of patients received by Cauquenes Hospital during the Chilean Earthquake on February 27th, 2010. A comparison of two situations has been carried out: the admission of patients before an earthquake with normal daily attention versus the admission of patients before an earthquake and the activation of the relief chain. The latter situation allows the system to be resilient and adapt quickly to its new reality. © 2023 IEEE.

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Analysis of the Resilience of an Emergency department: The Case of Accident with Multiple Victims 23

Analysis of the Resilience of an Emergency Department: The C...

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Proceedings of the Winter Simulation Conference

作者： Mariela Rodriguez Francesc Boixader Eva Bruballa Francisco Epelde Armando De Giusti Alvaro Wong Dolores Rexach Emilio Luque Faculty of Engineering National University of Jujuy Jujuy ARGENTINA Escoles Universitaries Gimbernat (EUG) Computer Science School Universitat Autonoma de Barcelona Sant Cugat del Vallès Barcelona SPAIN Consultant Internal Medicine University Hospital Parc Tauli Universitat Autonoma de Barcelona Sadabell Barcelona SPAIN Faculty of Informatics National University of La Plata Buenos Aires ARGENTINA Computer Architecture and Operating Systems Department Universitat Autonoma de Barcelona Bellaterra Barcelona SPAIN

ISBN: (纸本)9798350369663

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Analysis of the Resilience of an Emergency department: The Case of Accident with Multiple Victims

Analysis of the Resilience of an Emergency Department: The C...

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Simulation Winter Conference

作者： Mariela Rodriguez Francesc Boixader Eva Bruballa Francisco Epelde Armando De Giusti Alvaro Wong Dolores Rexach Emilio Luque Faculty of Engineering National University of Jujuy Jujuy Argentina Escoles Universitaries Gimbernat (EUG) Computer Science School Universitat Autonoma de Barcelona Barcelona Spain Consultant Internal Medicine University Hospital Parc Tauli Universitat Autonoma de Barcelona Sadabell Barcelona Spain Faculty of Informatics National University of La Plata Buenos Aires Argentina Computer Architecture and Operating Systems Department Universitat Autonoma de Barcelona Bellaterra Barcelona Spain

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Polyjuice: High-performance transactions via learned concurrency control

arXiv

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arXiv 2021年

作者： Wang, Jiachen Ding, Ding Wang, Huan Christensen, Conrad Wang, Zhaoguo Chen, Haibo Li, Jinyang Institute of Parallel and Distributed Systems Shanghai Jiao Tong University China Shanghai AI Laboratory China Engineering Research Center for Domain-specific Operating Systems Ministry of Education China Department of Computer Science New York University

Concurrency control algorithms are key determinants of the performance of in-memory databases. Existing algorithms are designed to work well for certain workloads. For example, optimistic concurrency control (OCC) is better than twophase- locking (2PL) under low contention, while the converse is true under high contention. To adapt to different workloads, prior works mix or switch between a few known algorithms using manual insights or simple heuristics. We propose a learning-based framework that instead explicitly optimizes concurrency control via offline training to maximize performance. Instead of choosing among a small number of known algorithms, our approach searches in a "policy space" of fine-grained actions, resulting in novel algorithms that can outperform existing algorithms by specializing to a given workload. We build Polyjuice based on our learning framework and evaluate it against several existing algorithms. Under different configurations of TPC-C and TPC-E, Polyjuice can achieve throughput numbers higher than the best of existing algorithms by 15% to 56%. Copyright © 2021, The Authors. All rights reserved.

关键词： Concurrency control

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