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The global burden of neurological disorders is substantial and increasing, especially in low-resource settings. The current increased global interest in brain health and its impact on population wellbeing and economic growth, highlighted in the World Health Organization’s new Intersectoral Global Action Plan on Epilepsy and other Neurological Disorders 2022–2031, presents an opportunity to rethink

High-precision localization and machine learning (ML) are envisioned to be key technologies in future wireless systems. This paper presents an ML pipeline to solve localization tasks. It consists of multiple parallel processing chains, each trained using a different fingerprint to estimate the position of the user equipment. In this way, ensemble learning can be utilized to fuse all chains to impr

High-precision cellular-based localization is one of the key technologies for next-generation communication systems. In this paper, we investigate the potential of applying machine learning (ML) to a massive multiple-input multiple-output (MIMO) system to enhance localization accuracy. We analyze a new ML-based localization pipeline that has two parallel fully connected neural networks (FCNN). The

Most work implies the use of digital systems and tools, thus, digital technology plays a vital role in modern work environments. Even so, ergonomics and usability of IT systems and digital tools used at work are often weak, which causes work-related health problems including physical, visual, cognitive, and stress-related issues. We pose that one important reason for these types of issues is the l

To make glomerular filtration rate (GFR) estimating equations applicable across populations with different creatinine generation by using rescaled serum creatinine (sCr/Q) where sCr represents the individual creatinine level and Q the average creatinine value in healthy persons of the same population. GFR measurements (mGFR, plasma clearance of 51Cr-EDTA) were conducted in 964 adult Black European

In healthcare, data privacy of patients regulations prohibits data from being moved outside the hospital, preventing international medical datasets from being centralized for AI training. Federated learning (FL) is a data privacy-focused method that trains a global model by aggregating local models from hospitals. Existing FL techniques adopt a central server-based network topology, where the serv

TP53 is the most frequently mutated gene in human cancer. This gene shows not only loss-of-function mutations but also recurrent missense mutations with gain-of-function activity. We have studied the primary bone malignancy osteosarcoma, which harbours one of the most rearranged genomes of all cancers. This is odd since it primarily affects children and adolescents who have not lived the long life

Adapting several insights from the work of social theorists Michel de Certeau and Pierre Mayol on the concepts of “everyday life” and the “neighborhood,” as well as Cynthia Baker’s work on the architecture of gender in Late Antique Galilee, Cirafesi explores how the neighborhood architecture of the ancient Galilean village of Capernaum contributes to the way in which we imagine Jews and Christians

The Storage Location Assignment Problem (SLAP) has a significant impact on the efficiency of warehouse operations. We propose a multi-phase optimizer for the SLAP, where the quality of an assignment is based on distance estimates of future-forecasted order-picking. Candidate assignments are first sampled using a Markov Chain accept/reject method. Order-picking Traveling Salesman Problems (TSPs) ar

Massive multiple-input multiple-output (MIMO) plays an important role in beyond 5G systems to support high data rate and low latency, especially operating at millimeter-wave frequency bands. In traditional software-based simulators, the simulation time increases exponentially with the number of base station antennas and served users. We propose a hardware-in-loop simulator that combines the flexib

Massive multiple-input multiple-output (MIMO) technology will continue playing an important role in beyond 5G wireless systems. Fully digital beamforming at the millimeter wave (mmWave) spectrum enables applications that require high data rates and low latency. This paper investigates the development and deployment of mmWave massive MIMO systems in an in-flight cabin environment, from both system

The Storage Location Assignment Problem (SLAP) is of central importance in warehouse operations. An important research challenge lies in generalizing the SLAP such that it is not tied to certain order-picking methodologies, constraints, or warehouse layouts. We propose the OBP-based SLAP, where the quality of a location assignment is obtained by optimizing an Order Batching Problem (OBP). For the

Aims The European Unified Registries On Heart Care Evaluation and Randomized Trials (EuroHeart) aims to improve the quality of care and clinical outcomes for patients with cardiovascular disease. The collaboration of acute coronary syndrome/percutaneous coronary intervention (ACS/PCI) registries is operational in seven vanguard European Society of Cardiology member countries. Methods and Adults ad

The landscape of healthcare is experiencing a digitalization shift, transferring many medical activities to the patients’ homes, a phenomenon commonly referred to as Hospital-at-Home. While Internet of Things (IoT) devices facilitate the building of such systems, there is a need for powerful middleware that encapsulates device-to-device communication, and enables the construction of user-friendly,

We address the recognized person-to-person Brain–Computer Interface (BCI) calibration problem and tackle session-dependency through the use of unsupervised canonical polyadic (CP) tensor decomposition. For a motor imagery task, the approach reveals universal structures within EEG data, common between subjects and prominent for a certain task. Further, we develop a novel similarity measure that inc

Digital contact tracing substantially improves the identification of high-risk contacts during pandemics. Despite several attempts to encourage people to use digital contact-tracing applications by developing and rolling out decentralized privacy-preserving protocols (broadcasting pseudo-random IDs over Bluetooth Low Energy-BLE), the adoption of digital contact tracing mobile applications has been

In dynamic operational environments, particularly in collaborative robotics, the inevitability of failures necessitates robust and adaptable recovery strategies. Traditional automated recovery strategies, while effective for predefined scenarios, often lack the flexibility required for on-the-fly task management and adaptation to expected failures. Addressing this gap, we propose a novel approach

Robotic systems for manipulation tasks are increasingly expected to be easy to configure for new tasks. While in the past, robot programs were often written statically and tuned manually, the current, faster transition times call for robust, modular and interpretable solutions that also allow a robotic system to learn how to perform a task. We propose the method Behavior-based Bayesian Optimizatio

Near-field focusing (NFF) is a fundamental enabler for a broad spectrum of applications utilizing large intelligent surfaces (LIS) within sub-10 GHz frequency bands. This paper investigates the impact of element pattern on NFF properties, when the LIS array is a large planar array. The NFF properties of maximum received power, focal width, and focal depth are analyzed for three typical antenna pat