Staffing & Scheduling

Staff Management with AI: Predicting the Nursing Workload.

The effective management of human resources in nursing fundamental to ensuring high-quality care. The necessary staffing levels can beis derived from the nursing-related health status. Our approach is based on the use of artificial intelligence (AI) and machine learning (ML) to recognize key workload-driving predictors from routine clinical data in the first step and derive recommendations for sta...

Assessing the Feasibility, and Efficacy of Virtual Reality Navigational Training for Older Adults

Objective. Evaluate the feasibility of Virtual Reality (VR) wayfinding training with aging adults, and examine the impact of the training on wayfinding performance. Design. Design involved wayfinding tasks in a study with three groups: active VR training, passive video training, and no training, assigned randomly. The training featured 5 tasks in a digital version of a real building. Post-traini...

User Behavior Analysis and Clustering in a MMO Mobile Game: Insights and Recommendations

This study presents a comprehensive analysis of user behavior and clustering in a popular mobile battle royale game, employing temporal and static d...

PICO-RAM: A PVT-Insensitive Analog Compute-In-Memory SRAM Macro with In-Situ Multi-Bit Charge Computing and 6T Thin-Cell-Compatible Layout

Analog compute-in-memory (CIM) in static random-access memory (SRAM) is promising for accelerating deep learning inference by circumventing the memo...

QSync: Quantization-Minimized Synchronous Distributed Training Across Hybrid Devices

A number of production deep learning clusters have attempted to explore inference hardware for DNN training, at the off-peak serving hours with many...

Deep Learning Prostate MRI Segmentation Accuracy and Robustness: A Systematic Review.

Purpose To investigate the accuracy and robustness of prostate segmentation using deep learning across various training data sizes, MRI vendors, prost...

Baseline Drift Tolerant Signal Encoding for ECG Classification with Deep Learning.

Common artefacts such as baseline drift, rescaling, and noise critically limit the performance of machine learning-based automated ECG analysis and in...

Scheduling with Obligatory Tests

Motivated by settings such as medical treatments or aircraft maintenance, we consider a scheduling problem with jobs that consist of two operations,...

Introducing Individuality into Students' High School Timetables

In a perfect world, each high school student could pursue their interests through a personalized timetable that supports their strengths, weaknesses...

Slice-Level Scheduling for High Throughput and Load Balanced LLM Serving

Large language models (LLMs) iteratively generate text token by token, with memory usage increasing with the length of generated token sequences. Si...

Transformative Influence of LLM and AI Tools in Student Social Media Engagement: Analyzing Personalization, Communication Efficiency, and Collaborative Learning

The advent of Large Language Models (LLMs) and Artificial Intelligence (AI) tools has revolutionized various facets of our lives, particularly in th...

A Symbolic Computing Perspective on Software Systems

Symbolic mathematical computing systems have served as a canary in the coal mine of software systems for more than sixty years. They have introduced...

Understanding Auditory Evoked Brain Signal via Physics-informed Embedding Network with Multi-Task Transformer

In the fields of brain-computer interaction and cognitive neuroscience, effective decoding of auditory signals from task-based functional magnetic r...

Mathematical Model-Driven Deep Learning Enables Personalized Adaptive Therapy.

UNLABELLED: Standard-of-care treatment regimens have long been designed for maximal cell killing, yet these strategies often fail when applied to meta...

Multi-word Term Embeddings Improve Lexical Product Retrieval

Product search is uniquely different from search for documents, Internet resources or vacancies, therefore it requires the development of specialize...

Artificial Intelligence: Reflections on Its Use to Promote DEIA Principles for Residency Recruitment.

Heterogeneous Forgetting Rates and Greedy Allocation in Slot-Based Memory Networks Promotes Signal Retention.

A key question in the neuroscience of memory encoding pertains to the mechanisms by which afferent stimuli are allocated within memory networks. This ...

Emulating biological synaptic characteristics of HfOx/AlN-based 3D vertical resistive memory for neuromorphic systems.

Here, we demonstrate double-layer 3D vertical resistive random-access memory with a hole-type structure embedding Pt/HfOx/AlN/TiN memory cells, conduc...

Imagine there is no paperwork… it's easy if you try.

Artificial Intelligence (AI) applied to radiology is so vast that it provides applications ranging from becoming a complete replacement for radiologis...

RT-Transformer: retention time prediction for metabolite annotation to assist in metabolite identification.

MOTIVATION: Liquid chromatography retention times prediction can assist in metabolite identification, which is a critical task and challenge in nontar...