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<a href=/list/cs.ET/new?skip=0&show=1000 rel="nofollow"> fewer</a> | <span style="color: #454545">more</span> | <span style="color: #454545">all</span> </div> <dl id='articles'> <h3>New submissions (showing 1 of 1 entries)</h3> <dt> <a name='item1'>[1]</a> <a href ="/abs/2503.12709" title="Abstract" id="2503.12709"> arXiv:2503.12709 </a> [<a href="/pdf/2503.12709" title="Download PDF" id="pdf-2503.12709" aria-labelledby="pdf-2503.12709">pdf</a>, <a href="https://arxiv.org/html/2503.12709v1" title="View HTML" id="html-2503.12709" aria-labelledby="html-2503.12709" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.12709" title="Other formats" id="oth-2503.12709" aria-labelledby="oth-2503.12709">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Modular Mechanism Design Optimization in Large-Scale Systems with Manufacturing Cost Considerations </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Lee,+S">Sumin Lee</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kang,+N">Namwoo Kang</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Emerging Technologies (cs.ET)</span> </div> <p class='mathjax'> Modular design maximizes utility by using standardized components in large-scale systems. From a manufacturing perspective, it supports green technology by reducing material waste and improving reusability. Industrially, it offers economic benefits through economies of scale, making it a practical design strategy. Typically, modularization selects a representative design from predefined candidates to meet all performance requirements. However, achieving effective modularization in mechanical mechanisms presents challenges. First, mechanisms depend on geometric relationships for functional motion, and varying loads lead to different optimal parameters, complicating representative design selection. Second, the chosen design often exceeds optimal parameters, causing over-specification and performance deviations, which worsen as scale increases. To address this, we propose a modular mechanism design framework using surrogate-based optimization. This approach finds optimal designs for large-scale systems and partitions them into groups, each assigned an optimized design. This multi-objective optimization (MOO) problem balances economies of scale and performance consistency. Unlike conventional methods based on predefined candidates and simple grouping, our framework optimizes design variables flexibly for modularization. Additionally, we analyze manufacturing cost parameters to develop a decision support system for selecting optimal strategies in diverse design scenarios. This enhances maintainability, improves interchangeability, and fosters environmentally sustainable manufacturing. </p> </div> </dd> </dl> <dl id='articles'> <h3>Cross submissions (showing 8 of 8 entries)</h3> <dt> <a name='item2'>[2]</a> <a href ="/abs/2407.05178" title="Abstract" id="2407.05178"> arXiv:2407.05178 </a> (cross-list from quant-ph) [<a href="/pdf/2407.05178" title="Download PDF" id="pdf-2407.05178" aria-labelledby="pdf-2407.05178">pdf</a>, <a href="https://arxiv.org/html/2407.05178v1" title="View HTML" id="html-2407.05178" aria-labelledby="html-2407.05178" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2407.05178" title="Other formats" id="oth-2407.05178" aria-labelledby="oth-2407.05178">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A typology of quantum algorithms </div> <div class='list-authors'><a href="https://arxiv.org/search/quant-ph?searchtype=author&query=Arnault,+P">Pablo Arnault</a>, <a href="https://arxiv.org/search/quant-ph?searchtype=author&query=Arrighi,+P">Pablo Arrighi</a>, <a href="https://arxiv.org/search/quant-ph?searchtype=author&query=Herbert,+S">Steven Herbert</a>, <a href="https://arxiv.org/search/quant-ph?searchtype=author&query=Kasnetsi,+E">Evi Kasnetsi</a>, <a href="https://arxiv.org/search/quant-ph?searchtype=author&query=Li,+T">Tianyi Li</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 60 pages, 7 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Quantum Physics (quant-ph)</span>; Emerging Technologies (cs.ET) </div> <p class='mathjax'> We draw the current landscape of quantum algorithms, by classifying about 130 quantum algorithms, according to the fundamental mathematical problems they solve, their real-world applications, the main subroutines they employ, and several other relevant criteria. The primary objectives include revealing trends of algorithms, identifying promising fields for implementations in the NISQ era, and identifying the key algorithmic primitives that power quantum advantage. </p> </div> </dd> <dt> <a name='item3'>[3]</a> <a href ="/abs/2503.11665" title="Abstract" id="2503.11665"> arXiv:2503.11665 </a> (cross-list from cs.AR) [<a href="/pdf/2503.11665" title="Download PDF" id="pdf-2503.11665" aria-labelledby="pdf-2503.11665">pdf</a>, <a href="https://arxiv.org/html/2503.11665v1" title="View HTML" id="html-2503.11665" aria-labelledby="html-2503.11665" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.11665" title="Other formats" id="oth-2503.11665" aria-labelledby="oth-2503.11665">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Towards Efficient Flash Caches with Emerging NVMe Flexible Data Placement SSDs </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Allison,+M">Michael Allison</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=George,+A">Arun George</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Gonzalez,+J">Javier Gonzalez</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Helmick,+D">Dan Helmick</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kumar,+V">Vikash Kumar</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Nair,+R">Roshan Nair</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Shah,+V">Vivek Shah</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> This is a pre-print version of the paper that will appear at Eurosys 2025 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Hardware Architecture (cs.AR)</span>; Databases (cs.DB); Emerging Technologies (cs.ET) </div> <p class='mathjax'> NVMe Flash-based SSDs are widely deployed in data centers to cache working sets of large-scale web services. As data centers face increasing sustainability demands, such as reduced carbon emissions, efficient management of Flash overprovisioning and endurance has become crucial. Our analysis demonstrates that mixing data with different lifetimes on Flash blocks results in high device garbage collection costs, which either reduce device lifetime or necessitate host overprovisioning. Targeted data placement on Flash to minimize data intermixing and thus device write amplification shows promise for addressing this issue. <br>The NVMe Flexible Data Placement (FDP) proposal is a newly ratified technical proposal aimed at addressing data placement needs while reducing the software engineering costs associated with past storage interfaces, such as ZNS and Open-Channel SSDs. In this study, we explore the feasibility, benefits, and limitations of leveraging NVMe FDP primitives for data placement on Flash media in CacheLib, a popular open-source Flash cache widely deployed and used in Meta's software ecosystem as a caching building block. We demonstrate that targeted data placement in CacheLib using NVMe FDP SSDs helps reduce device write amplification, embodied carbon emissions, and power consumption with almost no overhead to other metrics. Using multiple production traces and their configurations from Meta and Twitter, we show that an ideal device write amplification of ~1 can be achieved with FDP, leading to improved SSD utilization and sustainable Flash cache deployments. </p> </div> </dd> <dt> <a name='item4'>[4]</a> <a href ="/abs/2503.12044" title="Abstract" id="2503.12044"> arXiv:2503.12044 </a> (cross-list from stat.AP) [<a href="/pdf/2503.12044" title="Download PDF" id="pdf-2503.12044" aria-labelledby="pdf-2503.12044">pdf</a>, <a href="https://arxiv.org/html/2503.12044v1" title="View HTML" id="html-2503.12044" aria-labelledby="html-2503.12044" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.12044" title="Other formats" id="oth-2503.12044" aria-labelledby="oth-2503.12044">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A Simple and Explainable Model for Park-and-Ride Car Park Occupancy Prediction </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Kaltenbrunner,+A">Andreas Kaltenbrunner</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Ferrer,+J">Josep Ferrer</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Moreno,+D">David Moreno</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=G%C3%B3mez,+V">Vicen莽 G贸mez</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 25 pages, 16 figures, 1 table </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Applications (stat.AP)</span>; Emerging Technologies (cs.ET); Physics and Society (physics.soc-ph) </div> <p class='mathjax'> In a scenario of growing usage of park-and-ride facilities, understanding and predicting car park occupancy is becoming increasingly important. This study presents a model that effectively captures the occupancy patterns of park-and-ride car parks for commuters using truncated normal distributions for vehicle arrival and departure times. The objective is to develop a predictive model with minimal parameters corresponding to commuter behaviour, enabling the estimation of parking saturation and unfulfilled demand. The proposed model successfully identifies the regular, periodic nature of commuter parking behaviour, where vehicles arrive in the morning and depart in the afternoon. It operates using aggregate data, eliminating the need for individual tracking of arrivals and departures. The model's predictive and now-casting capabilities are demonstrated through real-world data from car parks in the Barcelona Metropolitan Area. A simple model extension furthermore enables the prediction of when a car park will reach its occupancy limit and estimates the additional spaces required to accommodate such excess demand. Thus, beyond forecasting, the model serves as a valuable tool for evaluating interventions, such as expanding parking capacity, to optimize park-and-ride facilities. </p> </div> </dd> <dt> <a name='item5'>[5]</a> <a href ="/abs/2503.12619" title="Abstract" id="2503.12619"> arXiv:2503.12619 </a> (cross-list from cs.HC) [<a href="/pdf/2503.12619" title="Download PDF" id="pdf-2503.12619" aria-labelledby="pdf-2503.12619">pdf</a>, <a href="https://arxiv.org/html/2503.12619v1" title="View HTML" id="html-2503.12619" aria-labelledby="html-2503.12619" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.12619" title="Other formats" id="oth-2503.12619" aria-labelledby="oth-2503.12619">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Rubikon: Intelligent Tutoring for Rubik's Cube Learning Through AR-enabled Physical Task Reconfiguration </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Wu,+M">Muzhe Wu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ren,+H">Haocheng Ren</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Croisdale,+G">Gregory Croisdale</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Guo,+A">Anhong Guo</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+X">Xu Wang</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Human-Computer Interaction (cs.HC)</span>; Emerging Technologies (cs.ET) </div> <p class='mathjax'> Learning to solve a Rubik's Cube requires the learners to repeatedly practice a skill component, e.g., identifying a misplaced square and putting it back. However, for 3D physical tasks such as this, generating sufficient repeated practice opportunities for learners can be challenging, in part because it is difficult for novices to reconfigure the physical object to specific states. We propose Rubikon, an intelligent tutoring system for learning to solve the Rubik's Cube. Rubikon reduces the necessity for repeated manual configurations of the Rubik's Cube without compromising the tactile experience of handling a physical cube. The foundational design of Rubikon is an AR setup, where learners manipulate a physical cube while seeing an AR-rendered cube on a display. Rubikon automatically generates configurations of the Rubik's Cube to target learners' weaknesses and help them exercise diverse knowledge components. In a between-subjects experiment, we showed that Rubikon learners scored 25% higher on a post-test compared to baselines. </p> </div> </dd> <dt> <a name='item6'>[6]</a> <a href ="/abs/2503.12705" title="Abstract" id="2503.12705"> arXiv:2503.12705 </a> (cross-list from cs.DB) [<a href="/pdf/2503.12705" title="Download PDF" id="pdf-2503.12705" aria-labelledby="pdf-2503.12705">pdf</a>, <a href="/format/2503.12705" title="Other formats" id="oth-2503.12705" aria-labelledby="oth-2503.12705">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A Brain-Computer Interface Data Persistence System for Multi-Scenario and Multi-Modal Data: NeuroStore </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+Y">Yang Chen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+H">Hongxin Zhang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Xiong,+G">Guanyu Xiong</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Li,+C">Chenxu Li</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Hong,+C">Chengcheng Hong</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yang,+C">Chen Yang</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Databases (cs.DB)</span>; Emerging Technologies (cs.ET) </div> <p class='mathjax'> With the rapid advancement of brain-computer interface (BCI) technology, the volume of physiological data generated in related research and applications has grown significantly. Data is a critical resource in BCI research and a key factor in the development of BCI technology, making efficient storage and management of this data increasingly vital. In the realm of research, ample data can facilitate the development of novel algorithms, which can be more accurately validated. In terms of applications, well-organized data can foster the emergence of new business opportunities, thereby maximizing the commercial value of the data. Currently, there are two major challenges in the storage and management of BCI data: providing different classification storage modes for multi-modal data, and adapting to varying application scenarios while improving storage strategies. To address these challenges, this study has developed the NeuroStore BCI data persistence system, which provides a general and easily scalable data model and can effectively handle multiple types of data storage. The system has a flexible distributed framework and can be widely applied to various scenarios. It has been utilized as the core support platform for efficient data storage and management services in the "BCI Controlled Robot Contest in World Robot Contest." </p> </div> </dd> <dt> <a name='item7'>[7]</a> <a href ="/abs/2503.13128" title="Abstract" id="2503.13128"> arXiv:2503.13128 </a> (cross-list from quant-ph) [<a href="/pdf/2503.13128" title="Download PDF" id="pdf-2503.13128" aria-labelledby="pdf-2503.13128">pdf</a>, <a href="https://arxiv.org/html/2503.13128v1" title="View HTML" id="html-2503.13128" aria-labelledby="html-2503.13128" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.13128" title="Other formats" id="oth-2503.13128" aria-labelledby="oth-2503.13128">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Accelerating large-scale linear algebra using variational quantum imaginary time evolution </div> <div class='list-authors'><a href="https://arxiv.org/search/quant-ph?searchtype=author&query=Aboumrad,+W">Willie Aboumrad</a>, <a href="https://arxiv.org/search/quant-ph?searchtype=author&query=Zhu,+D">Daiwei Zhu</a>, <a href="https://arxiv.org/search/quant-ph?searchtype=author&query=Girotto,+C">Claudio Girotto</a>, <a href="https://arxiv.org/search/quant-ph?searchtype=author&query=Rouet,+F">Fran莽ois-Henry Rouet</a>, <a href="https://arxiv.org/search/quant-ph?searchtype=author&query=Jojo,+J">Jezer Jojo</a>, <a href="https://arxiv.org/search/quant-ph?searchtype=author&query=Lucas,+R">Robert Lucas</a>, <a href="https://arxiv.org/search/quant-ph?searchtype=author&query=Pathak,+J">Jay Pathak</a>, <a href="https://arxiv.org/search/quant-ph?searchtype=author&query=Kaushik,+A">Ananth Kaushik</a>, <a href="https://arxiv.org/search/quant-ph?searchtype=author&query=Roetteler,+M">Martin Roetteler</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 14 pages, 15 figures, 1 table </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Quantum Physics (quant-ph)</span>; Emerging Technologies (cs.ET) </div> <p class='mathjax'> Graph partitioning techniques enhance the efficiency of solving large-scale linear systems in the context of Finite Element Analysis (FEA). Even for systems of linear equations that are highly sparse, their direct solution via factorization methods, such as LU or Cholesky decomposition, is computationally expensive due to the introduction of non-zero elements, or ``fill-in.'' We introduce a quantum approach to the graph partitioning problem based on the variational quantum imaginary time evolution algorithm (VarQITE), allowing to solve the combinatorial optimization problem of reordering of sparse matrices to minimize the fill-in. We develop a hybrid quantum/classical pipeline to accelerate Finite Element solvers by integrating the VarQITE algorithm into the production workflow of Ansys' industrial software LS-DYNA. This allows to study multiple different types of FEA problems, ranging from mechanical engineering to computational fluid dynamics. <br>We prove out that VarQITE positively impacts LS-DYNA workflows by measuring the wall-clock time to solution of FEA problems when compared against the classical heuristic graph partitioning solver in LS-DYNA. The selected instances cover a range of FEA problems, including simulation of blood pumps, roof crushing of cars, and vibration analysis of cars. We report performance results for our hybrid quantum-accelerated workflow on FEA meshes of up to 5.9M vertices and 55 million edges. We find that the wall clock time of the heuristics solutions used in the industry-grade solver is improved by up to 12\%. We also execute the VarQITE algorithm on quantum hardware (IonQ Aria and IonQ Forte) and find that the results are comparable to noiseless and noisy simulations. Finally, we introduce a hybrid technique for post-processing the found solutions with classical refinement heuristics such as Fiduccia-Mattheyses. </p> </div> </dd> <dt> <a name='item8'>[8]</a> <a href ="/abs/2503.13310" title="Abstract" id="2503.13310"> arXiv:2503.13310 </a> (cross-list from cs.SE) [<a href="/pdf/2503.13310" title="Download PDF" id="pdf-2503.13310" aria-labelledby="pdf-2503.13310">pdf</a>, <a href="https://arxiv.org/html/2503.13310v1" title="View HTML" id="html-2503.13310" aria-labelledby="html-2503.13310" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.13310" title="Other formats" id="oth-2503.13310" aria-labelledby="oth-2503.13310">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Generative AI for Software Architecture. Applications, Trends, Challenges, and Future Directions </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Esposito,+M">Matteo Esposito</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Li,+X">Xiaozhou Li</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Moreschini,+S">Sergio Moreschini</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ahmad,+N">Noman Ahmad</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Cerny,+T">Tomas Cerny</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Vaidhyanathan,+K">Karthik Vaidhyanathan</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lenarduzzi,+V">Valentina Lenarduzzi</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Taibi,+D">Davide Taibi</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Software Engineering (cs.SE)</span>; Artificial Intelligence (cs.AI); Distributed, Parallel, and Cluster Computing (cs.DC); Emerging Technologies (cs.ET) </div> <p class='mathjax'> Context: Generative Artificial Intelligence (GenAI) is transforming much of software development, yet its application in software architecture is still in its infancy, and no prior study has systematically addressed the topic. Aim: We aim to systematically synthesize the use, rationale, contexts, usability, and future challenges of GenAI in software architecture. Method: We performed a multivocal literature review (MLR), analyzing peer-reviewed and gray literature, identifying current practices, models, adoption contexts, and reported challenges, extracting themes via open coding. Results: Our review identified significant adoption of GenAI for architectural decision support and architectural reconstruction. OpenAI GPT models are predominantly applied, and there is consistent use of techniques such as few-shot prompting and retrieved-augmented generation (RAG). GenAI has been applied mostly to initial stages of the Software Development Life Cycle (SDLC), such as Requirements-to-Architecture and Architecture-to-Code. Monolithic and microservice architectures were the dominant targets. However, rigorous testing of GenAI outputs was typically missing from the studies. Among the most frequent challenges are model precision, hallucinations, ethical aspects, privacy issues, lack of architecture-specific datasets, and the absence of sound evaluation frameworks. Conclusions: GenAI shows significant potential in software design, but several challenges remain on its path to greater adoption. Research efforts should target designing general evaluation methodologies, handling ethics and precision, increasing transparency and explainability, and promoting architecture-specific datasets and benchmarks to bridge the gap between theoretical possibilities and practical use. </p> </div> </dd> <dt> <a name='item9'>[9]</a> <a href ="/abs/2503.13419" title="Abstract" id="2503.13419"> arXiv:2503.13419 </a> (cross-list from cs.CR) [<a href="/pdf/2503.13419" title="Download PDF" id="pdf-2503.13419" aria-labelledby="pdf-2503.13419">pdf</a>, <a href="https://arxiv.org/html/2503.13419v1" title="View HTML" id="html-2503.13419" aria-labelledby="html-2503.13419" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.13419" title="Other formats" id="oth-2503.13419" aria-labelledby="oth-2503.13419">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Securing Virtual Reality Experiences: Unveiling and Tackling Cybersickness Attacks with Explainable AI </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Kundu,+R+K">Ripan Kumar Kundu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Denton,+M">Matthew Denton</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Mongalo,+G">Genova Mongalo</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Calyam,+P">Prasad Calyam</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Hoque,+K+A">Khaza Anuarul Hoque</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> This work has been submitted to the IEEE for possible publication </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Cryptography and Security (cs.CR)</span>; Artificial Intelligence (cs.AI); Emerging Technologies (cs.ET); Human-Computer Interaction (cs.HC) </div> <p class='mathjax'> The synergy between virtual reality (VR) and artificial intelligence (AI), specifically deep learning (DL)-based cybersickness detection models, has ushered in unprecedented advancements in immersive experiences by automatically detecting cybersickness severity and adaptively various mitigation techniques, offering a smooth and comfortable VR experience. While this DL-enabled cybersickness detection method provides promising solutions for enhancing user experiences, it also introduces new risks since these models are vulnerable to adversarial attacks; a small perturbation of the input data that is visually undetectable to human observers can fool the cybersickness detection model and trigger unexpected mitigation, thus disrupting user immersive experiences (UIX) and even posing safety risks. In this paper, we present a new type of VR attack, i.e., a cybersickness attack, which successfully stops the triggering of cybersickness mitigation by fooling DL-based cybersickness detection models and dramatically hinders the UIX. Next, we propose a novel explainable artificial intelligence (XAI)-guided cybersickness attack detection framework to detect such attacks in VR to ensure UIX and a comfortable VR experience. We evaluate the proposed attack and the detection framework using two state-of-the-art open-source VR cybersickness datasets: Simulation 2021 and Gameplay dataset. Finally, to verify the effectiveness of our proposed method, we implement the attack and the XAI-based detection using a testbed with a custom-built VR roller coaster simulation with an HTC Vive Pro Eye headset and perform a user study. Our study shows that such an attack can dramatically hinder the UIX. However, our proposed XAI-guided cybersickness attack detection can successfully detect cybersickness attacks and trigger the proper mitigation, effectively reducing VR cybersickness. </p> </div> </dd> </dl> <dl id='articles'> <h3>Replacement submissions (showing 5 of 5 entries)</h3> <dt> <a name='item10'>[10]</a> <a href ="/abs/2401.16515" title="Abstract" id="2401.16515"> arXiv:2401.16515 </a> (replaced) [<a href="/pdf/2401.16515" title="Download PDF" id="pdf-2401.16515" aria-labelledby="pdf-2401.16515">pdf</a>, <a href="https://arxiv.org/html/2401.16515v3" title="View HTML" id="html-2401.16515" aria-labelledby="html-2401.16515" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2401.16515" title="Other formats" id="oth-2401.16515" aria-labelledby="oth-2401.16515">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Neuromorphic Photonic Computing with an Electro-Optic Analog Memory </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Lam,+S">Sean Lam</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Khaled,+A">Ahmed Khaled</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Bilodeau,+S">Simon Bilodeau</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Marquez,+B+A">Bicky A. Marquez</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Prucnal,+P+R">Paul R. Prucnal</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chrostowski,+L">Lukas Chrostowski</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Shastri,+B+J">Bhavin J. Shastri</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Shekhar,+S">Sudip Shekhar</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Emerging Technologies (cs.ET)</span>; Signal Processing (eess.SP); Systems and Control (eess.SY); Optics (physics.optics) </div> <p class='mathjax'> Artificial intelligence (AI) has seen remarkable advancements across various domains, including natural language processing, computer vision, autonomous vehicles, and biology. However, the rapid expansion of AI technologies has escalated the demand for more powerful computing resources. As digital computing approaches fundamental limits, neuromorphic photonics emerges as a promising platform to complement existing digital systems. In neuromorphic photonic computing, photonic devices are controlled using analog signals. This necessitates the use of digital-to-analog converters (DAC) and analog-to-digital converters (ADC) for interfacing with these devices during inference and training. However, data movement between memory and these converters in conventional von Neumann computing architectures consumes energy. To address this, analog memory co-located with photonic computing devices is proposed. This approach aims to reduce the reliance on DACs and minimize data movement to enhance compute efficiency. This paper demonstrates a monolithically integrated neuromorphic photonic circuit with co-located capacitive analog memory and analyzes analog memory specifications for neuromorphic photonic computing using the MNIST dataset as a benchmark. </p> </div> </dd> <dt> <a name='item11'>[11]</a> <a href ="/abs/2410.23517" title="Abstract" id="2410.23517"> arXiv:2410.23517 </a> (replaced) [<a href="/pdf/2410.23517" title="Download PDF" id="pdf-2410.23517" aria-labelledby="pdf-2410.23517">pdf</a>, <a href="https://arxiv.org/html/2410.23517v2" title="View HTML" id="html-2410.23517" aria-labelledby="html-2410.23517" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2410.23517" title="Other formats" id="oth-2410.23517" aria-labelledby="oth-2410.23517">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> HETRI: Heterogeneous Ising Multiprocessing </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=C%C4%B1lasun,+H">H眉srev C谋lasun</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kumar,+A">Abhimanyu Kumar</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zeng,+Z">Ziqing Zeng</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Prova,+N+S">Nafisa Sadaf Prova</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Sapatnekar,+S+S">Sachin S. Sapatnekar</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Karpuzcu,+U+R">Ulya R. Karpuzcu</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Emerging Technologies (cs.ET)</span>; Computational Physics (physics.comp-ph) </div> <p class='mathjax'> Ising machines are effective solvers for complex combinatorial optimization problems. The idea is mapping the optimal solution(s) to a combinatorial optimization problem to the minimum energy state(s) of a physical system, which naturally converges to a minimum energy state upon perturbance. The underlying mathematical abstraction, the Ising model, can capture the dynamic behavior of different physical systems by mapping each problem variable to a spin which can interact with other spins. Ising model as a mathematical abstraction can be mapped to hardware using traditional devices. In this paper we instead focus on Ising machines which represent a network of physical spins directly implemented in hardware using, e.g., quantum bits or electronic oscillators. To eliminate the scalability bottleneck due to the mismatch in problem vs. Ising machine size and connectivity, in this paper we make the case for HETRI: Heterogeneous Ising Multiprocessing. HETRI organizes the maximum number of physical spins that the underlying technology supports in Ising cores; and multiple independent Ising cores, in Ising chips. Ising cores in a chip feature different inter-spin connectivity or spin counts to match the problem characteristics. We provide a detailed design space exploration and quantify the performance in terms of time or energy to solution and solution accuracy with respect to homogeneous alternatives under the very same hardware budget and considering the very same spin technology. </p> </div> </dd> <dt> <a name='item12'>[12]</a> <a href ="/abs/2101.08939" title="Abstract" id="2101.08939"> arXiv:2101.08939 </a> (replaced) [<a href="/pdf/2101.08939" title="Download PDF" id="pdf-2101.08939" aria-labelledby="pdf-2101.08939">pdf</a>, <a href="https://arxiv.org/html/2101.08939v4" title="View HTML" id="html-2101.08939" aria-labelledby="html-2101.08939" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2101.08939" title="Other formats" id="oth-2101.08939" aria-labelledby="oth-2101.08939">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Hoare meets Heisenberg: A Lightweight Logic for Quantum Programs </div> <div class='list-authors'><a href="https://arxiv.org/search/quant-ph?searchtype=author&query=Sundaram,+A">Aarthi Sundaram</a>, <a href="https://arxiv.org/search/quant-ph?searchtype=author&query=Rand,+R">Robert Rand</a>, <a href="https://arxiv.org/search/quant-ph?searchtype=author&query=Singhal,+K">Kartik Singhal</a>, <a href="https://arxiv.org/search/quant-ph?searchtype=author&query=Lackey,+B">Brad Lackey</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 52 pages, 3 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Quantum Physics (quant-ph)</span>; Emerging Technologies (cs.ET); Logic in Computer Science (cs.LO); Programming Languages (cs.PL) </div> <p class='mathjax'> We show that Gottesman's (1998) semantics for Clifford circuits based on the Heisenberg representation gives rise to a lightweight Hoare-like logic for efficiently characterizing a common subset of quantum programs. Our applications include (i) certifying whether auxiliary qubits can be safely disposed of, (ii) determining if a system is separable across a given bipartition, (iii) checking the transversality of a gate with respect to a given stabilizer code, and (iv) computing post-measurement states for computational basis measurements. Further, this logic is extended to accommodate universal quantum computing by deriving Hoare triples for the $T$-gate, multiply-controlled unitaries such as the Toffoli gate, and some gate injection circuits that use associated magic states. A number of interesting results emerge from this logic, including a lower bound on the number of $T$ gates necessary to perform a multiply-controlled $Z$ gate. </p> </div> </dd> <dt> <a name='item13'>[13]</a> <a href ="/abs/2409.05217" title="Abstract" id="2409.05217"> arXiv:2409.05217 </a> (replaced) [<a href="/pdf/2409.05217" title="Download PDF" id="pdf-2409.05217" aria-labelledby="pdf-2409.05217">pdf</a>, <a href="https://arxiv.org/html/2409.05217v3" title="View HTML" id="html-2409.05217" aria-labelledby="html-2409.05217" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2409.05217" title="Other formats" id="oth-2409.05217" aria-labelledby="oth-2409.05217">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> From Concept to Reality: 5G Positioning with Open-Source Implementation of UL-TDoA in OpenAirInterface </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Malik,+A">Adeel Malik</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ahadi,+M">Mohsen Ahadi</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kaltenberger,+F">Florian Kaltenberger</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Warnke,+K">Klaus Warnke</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Thinh,+N+T">Nguyen Tien Thinh</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Bouknana,+N">Nada Bouknana</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Thienot,+C">Cedric Thienot</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Onche,+G">Godswill Onche</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Arora,+S">Sagar Arora</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Information Theory (cs.IT)</span>; Emerging Technologies (cs.ET); Performance (cs.PF) </div> <p class='mathjax'> This paper presents, for the first time, an open-source implementation of the 3GPP Uplink Time Difference of Arrival (UL-TDoA) positioning method using the OpenAirInterface (OAI) framework. UL-TDoA is a critical positioning technique in 5G networks, leveraging the time differences of signal arrival at multiple base stations to determine the precise location of User Equipment (UE). This implementation aims to democratize access to advanced positioning technology by integrating UL-TDoA capabilities into both the Radio Access Network (RAN) and Core Network (CN) components of OAI, providing a comprehensive and 3GPP-compliant solution. The development includes the incorporation of essential protocol procedures, message flows, and interfaces as defined by 3GPP standards. Validation is conducted using two distinct methods: an OAI-RF simulator-based setup for controlled testing and an O-RAN-based Localization Testbed at EURECOM in real-world conditions. The results demonstrate the viability of this open-source UL-TDoA implementation, enabling precise positioning in various environments. By making this implementation publicly available, the study paves the way for widespread research, development, and innovation in the field of 5G positioning technologies, fostering collaboration and accelerating the advancement of cellular network positioning. </p> </div> </dd> <dt> <a name='item14'>[14]</a> <a href ="/abs/2501.12470" title="Abstract" id="2501.12470"> arXiv:2501.12470 </a> (replaced) [<a href="/pdf/2501.12470" title="Download PDF" id="pdf-2501.12470" aria-labelledby="pdf-2501.12470">pdf</a>, <a href="https://arxiv.org/html/2501.12470v2" title="View HTML" id="html-2501.12470" aria-labelledby="html-2501.12470" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2501.12470" title="Other formats" id="oth-2501.12470" aria-labelledby="oth-2501.12470">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Efficient Compilation for Shuttling Trapped-Ion Machines via the Position Graph Architectural Abstraction </div> <div class='list-authors'><a href="https://arxiv.org/search/quant-ph?searchtype=author&query=Bach,+B">Bao Bach</a>, <a href="https://arxiv.org/search/quant-ph?searchtype=author&query=Safro,+I">Ilya Safro</a>, <a href="https://arxiv.org/search/quant-ph?searchtype=author&query=Younis,+E">Ed Younis</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 15 pages, 7 figures, 2 tables </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Quantum Physics (quant-ph)</span>; Emerging Technologies (cs.ET) </div> <p class='mathjax'> With the growth of quantum platforms for gate-based quantum computation, compilation holds a crucial factor in deciding the success of the implementation. There has been rich research and development in compilation techniques for the superconducting-qubit regime. In contrast, the trapped-ion architectures, currently leading in robust quantum computations due to their reliable operations, do not have many competitive compilation strategies. This work presents a novel unifying abstraction, called the position graph, for different types of hardware architectures. Using this abstraction, we model trapped-ion Quantum Charge-Coupled Device (QCCD) architectures and enable high-quality, scalable superconducting compilation methods. In particular, we devise a scheduling algorithm called SHuttling-Aware PERmutative heuristic search algorithm (SHAPER) to tackle the complex constraints and dynamics of trapped-ion QCCD with the cooperation of state-of-the-art permutation-aware mapping. This approach generates native, executable circuits and ion instructions on the hardware that adheres to the physical constraints of shuttling-based quantum computers. Using the position graph abstraction, we evaluate our algorithm on theorized and actual architectures. Our algorithm can successfully compile programs for these architectures where other state-of-the-art algorithms fail. In the cases when other algorithms complete, our algorithm produces a schedule that is $14\%$ faster on average, up to $69\%$ in the best case.\\ {\bf Reproducibility:} source code and computational results are available at $[$will be added upon acceptance$]$ </p> </div> </dd> </dl> <div class='paging'>Total of 14 entries </div> <div class='morefewer'>Showing up to 2000 entries per page: <a href=/list/cs.ET/new?skip=0&show=1000 rel="nofollow"> fewer</a> | <span style="color: #454545">more</span> | <span style="color: #454545">all</span> </div> </div> </div> </div> </main> <footer style="clear: both;"> <div class="columns is-desktop" role="navigation" aria-label="Secondary" style="margin: -0.75em -0.75em 0.75em -0.75em">  <div class="column" style="padding: 0;"> <div class="columns"> <div class="column"> <ul style="list-style: none; line-height: 2;"> <li><a href="https://info.arxiv.org/about">About</a></li> <li><a href="https://info.arxiv.org/help">Help</a></li> </ul> </div> <div class="column"> <ul style="list-style: none; 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