21 papers · ranked by Valyu relevance
Kathleen West, Vasilis Bountris, Philipp Thamm, Ulf Leser + 2 more
Scientific workflows are widely used to process large quantities of data, leading to significant energy consumption and carbon emissions. To reduce this environmental impact, energy and carbon-aware scheduling approaches could be employed. However, such methods require runtime and energy predictions, which are…
Jing Chen, Miquel Pericas
Energy efficiency has become a first-order concern in modern high-performance computing systems, as it directly determines achievable throughput under fixed power budgets. Although Dynamic Voltage and Frequency Scaling (DVFS) provides an effective mechanism for reducing GPU energy consumption, existing runtime systems…
Mohammad Pivezhandi, Mahdi Banisharif, Abusayeed Saifullah, Ali Jannesari
Dynamic voltage and frequency scaling (DVFS) and task-to-core allocation are critical for thermal management and balancing energy and performance in embedded systems. Existing approaches either rely on utilization-based heuristics that overlook stall times, or require extensive offline profiling for table generation…
Rick den Otter, Anna Dame, Sjoerd Stuit, Leendert van Maanen
Theories of dual-task interference assume that the same cognitive operations underlie multitasking regardless of stimulus timing, yet this core assumption has remained untested due to methodological limitations of behavioral averaging. Here, we combine hidden multivariate pattern (HMP) analysis with deep spatiotemporal…
Mao Lin, Hyeran Jeon, Keren Zhou
—The increasing complexity and diversity of hardware accelerators in modern computing systems demand flexible, lowoverhead program analysis tools. We present PASTA, a lowoverhead and modular Program AnalysiS Tool Framework for Accelerators. PASTA abstracts over low-level profiling APIs and diverse deep learning…
Maxence Lapatrie, Jason da Silva Castanheira, Idil Aydin, Sylvain Baillet
Human brain activity contains stable, individual-specific features that persist over months to years, forming neurophysiological profiles. Most model-based profiling approaches use participant labels or supervised objectives, making it difficult to determine whether successful differentiation reflects stable biology or…
Xuan Wen, Leo Malchin, Adam Neumann, Thilo Womelsdorf
Executive functions comprise at least four major subdomains: Inhibitory Control, Updating, Shifting, and Working Memory. Cognitive abilities in these subdomains are partially separable and partially unified in a common cognitive control factor in humans, but how these functions are organized in the nonhuman primate…
Joshua H. Davis, Klaudiusz Rydzy, Srinivasan Ramesh, Aadit Nilay + 4 more
Performance profiles of GPU kernels generated by tools such as Nsight Compute are rich in detail but are often challenging to interpret. To achieve the best performance possible on a given GPU architecture, kernel developers need to spend significant time analyzing and comparing profiles in the tool's graphical…
Christopher Draheim, Ciara Sibley, Nathan Herdener, Aaron Cochrane + 3 more
Aviation selection tests are high-stakes assessments designed to identify candidates capable of succeeding in demanding flight environments. Most branches of the US military incorporate both content-based and process-based assessments to evaluate prior knowledge and reasoning ability, respectively. A challenge with…
Jenna Tomkinson, Dave Bunten, Gregory P. Way
Over the past twenty years, high-content imaging has transformed our ability to measure cell phenotypes. The need to bioinformatically process these phenotypes led to the development of a research field called image-based profiling. However, because the standard image-based profiling approach involves averaging data…
Ali Darejeh, Nadine Marcus, Gelareh Mohammadi, John Sweller
Objective This systematic review evaluates the use of cognitive load measurement methods in usability testing across diverse software interfaces. It provides guidance for researchers and practitioners by proposing a framework for selecting appropriate cognitive load measurement techniques. Background Cognitive Load…
Yuqiu Yang, Kaiwen Wang, Yike Shen, Jon A Weidanz + 2 more
Extracting meaningful biological signals from Cytometry by time-of-flight (CyTOF) data remains challenging due to heterogeneity, data characteristics, and the presence of various technical artifacts. Current analysis workflows typically rely on task-specific tools assembled into pipelines, which often make inconsistent…
Adi Korisky, Eshsed Rabinovitch, Paz Har-Shai Yahav, Bruce D McCandliss + 1 more
Event-related potentials (ERPs) are among the most established tools for studying the neural mechanisms of perception and cognition. Advancing toward precision EEG, however, places new demands for a better understanding of how reliable neural markers are at the individual subject level. We conducted two complementary…
Farkhondeh Fakour Manavi, Paul D. Loprinzi, Rebekah E. Smith
Time-based prospective memory refers to the ability to remember activities at a specified future time. In our everyday lives, certain time-based tasks need to be completed within a short time period, while others are meant for a more distant future. We report the findings from two separate but related reviews regarding…
Abdul Rehman, Ilona Heldal, Jerry Chun-Wei Lin
Eye Tracking (ET) can help improve understanding of visual attention in computer-supported interactive environments. In attention tasks, distinguishing between relevant target objects and distractors is crucial for effective performance, yet the underlying gaze patterns that drive successful task completion remain…
Mingchong Xiao, Zhengwen Zhou, Han Peng, Zhe Lin + 5 more
Visual display terminal (VDT) tasks are common in safety-critical systems, where operators must continuously monitor dynamic information and maintain situation awareness (SA). This study examined whether EEG and eye-tracking technologies could support the assessment of SA and perceived mental workload in VDT tasks.…
Kai Xu, Diming Zhang, Xuguo Wang, Alessandra Rizzardi
To address the bottlenecks of missing decision-making closed loop, insufficient experience reuse, and decoupled resource scheduling in industrial LLM deployment, this paper proposes LLM-Conductor, a three-layer collaborative architecture that enables monitoring-feedback autonomous decision-making, structured policy…
Authors not listed
Incorporating prior domain knowledge into Bayesian optimization (BO) remains difficult for statistical methods, which also typically suffer from limited interpretability. Large language models (LLMs) offer complementary strengths in reasoning and knowledge integration, but it remains unclear when and how they improve…
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Alzheimer's disease (AD) is a neurodegenerative disorder caused by multiple factors that require the development of multi-target directed ligands (MTDL) to treat its pathophysiology. Using Hyperoside, a major Himalayan plant extract, this study will report on the potential use of this compound as a therapeutic agent…
Lihi Bar-El, Hila Chalutz-BenGal, Sivan Gazit, Tal Patalon + 1 more
In recent years, the growing amount of event-log data collected from websites and mobile applications has provided an opportunity to analyoc2vec to cluster physical ze user-behavior patterns in digital customer systems. However, a holistic data-driven approach for analyzing the digital customer journey is lacking. To…
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Quantitative Structure Activity Relationship (QSAR) remains an effective tool for early-stage chemical modelling and virtual screening in drug design. The advancements in this field are led by two core paradigms, 1) descriptor engineering, where complex fixed-length vectors of compounds are generated and conventional…