Staffing & Scheduling

Robot-assisted gait training in a patient with hereditary spastic paraplegia.

Robot-assisted gait training has been investigated for restoring walking through activity-dependent neuroplasticity in persons with various neurologic disorders. This case report presents the outcome of robot-assisted gait training combined with physiotherapy in a 28-year-old man with pure hereditary spastic paraplegia. The patient participated in 25 training sessions over 6 weeks. Improvements we...

An Experimentation Platform for On-Chip Integration of Analog Neural Networks: A Pathway to Trusted and Robust Analog/RF ICs.

We discuss the design of an experimentation platform intended for prototyping low-cost analog neural networks for on-chip integration with analog/RF circuits. The objective of such integration is to support various tasks, such as self-test, self-tuning, and trust/aging monitoring, which require classification of analog measurements obtained from on-chip sensors. Particular emphasis is given to cos...

Robot-assisted gait training is not superior to balance training for improving postural instability in patients with mild to moderate Parkinson's disease: a single-blind randomized controlled trial.

OBJECTIVE: The main aim was to compare robotic gait training vs. balance training for reducing postural instability in patients with Parkinson's disea...

Development and validation of a stability-indicating RP-HPLC method for estimation of atazanavir sulfate in bulk.

A stability-indicating reverse phase-high performance liquid chromatography (RP-HPLC) method was developed and validated for the determination of ataz...

Evaluating performance bias in face-to-BMI vision transformer models across diverse human populations

Computer vision models that estimate body mass index (BMI) from facial features offer a non-invasive, low-cost alternative to physical measurement, wi...

Building Pretraining Data for World Models: An Unreal Engine-Based Pipeline for Action-Conditioned Video Generation

Action-conditioned video models require large-scale visual data paired with control signals that are temporally aligned with the resulting scene trans...

Tree-Structured Vector Quantization For Efficient And Progressive Image Compression

Vector-quantization based image compression has achieved strong rate--distortion performance, yet most of them still produce a separate compressed rep...

Disease Burden over Skin Tone: Decomposing the Dermatology-AI Generalization Gap

Dermatology artificial intelligence (AI) models are predominantly trained on light-skinned, cancer-focused image collections, yet they are increasingl...

Domain shift-robust object detection with GenAI image editing

Object detectors often degrade under domain shifts such as changes in lighting, weather, or occlusion. These shifts alter object appearance and expose...

Beyond Accuracy: Quantifying Pulmonary Attribution in Anatomy-Guided Chest X-Ray Classification Under Domain Shift

Deep-learning models can achieve strong chest X-ray (CXR) classification performance without establishing whether their predictions predominantly rely...

PixelIR: Fidelity-Perception Decoupling via Pixel-Space Image-Residual Flow Matching for Efficient One-Step Real-World Super-Resolution

Real-world image super-resolution (Real-ISR) aims to preserve structures supported by the degraded observation while reconstructing perceptually reali...

The Nearest Target Is the Wrong One: Target Separation in Arc2Face Identity Unlearning

Unlearning an identity from a face-conditioned generator by redirecting its conditioning embedding can silently fail if the redirected output is still...

From Perspective to Fisheye Depth Estimation and Open-Vocabulary Segmentation

Vision foundation models are capable of generalizing across 3-dimensional (3D) scenes with high-fidelity estimates; their empirical success can be att...

A Controlled Audit of Architectural Complexity in Uncertainty-Aware Multi-Organ Ultrasound Classification

Multi-organ ultrasound classifiers increasingly combine attention, mixture-of-experts routing, uncertainty gating, and evidential deep learning (EDL) ...

Image Augmentation as Test Generation for Deep Learning-Based Image Retrieval Systems

Ensuring the reliability of deep learning-based image retrieval systems is a software engineering challenge. This paper presents a dual contribution: ...

ShiftSplit-AD: Separating Domain Shift from Defects in Foundation-Feature Visual Anomaly Detection

Visual anomaly detectors based on frozen foundation-model features commonly score distances from test patches to a memory of normal features. Benign a...

MVC-Bench: Benchmarking Calibration of Medical Vision-Language Models

Reliable evaluation of vision-language models (VLMs) and medical vision-language models (Medical-VLMs) requires calibrated confidence, particularly un...

What Do Medical Vision-Language Models Learn in Radiology? Transfer, Alignment, and Source-Proxy Leakage Under Distribution Shift

Medical vision-language models (VLMs) can appear reliable in-domain while failing when acquisition domain, paired supervision, or evaluation protocol ...

Efficient Training with Foresight: Multi-Token Auxiliary Supervision for Autoregressive Image Generation

Autoregressive (AR) image generation has shown strong potential for scalable high-fidelity synthesis by modeling images as discrete token sequences. H...

Label-Free Foundational Model Selection for Medical Image Classification under Distribution Shift via Pseudo Label Discrepancy

Foundation models are increasingly deployed for medical image analysis. However, under the inter-institutional distribution shift typical of deploymen...