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In this paper we propose a shared regression network to jointly estimate the pose of multiple objects, replacing multiple object-specific solutions. We demonstrate that this shared network can outperform other similar approaches that rely on multiple object-specific models by evaluating it on the TLESS dataset using the VSD (Visible Surface Discrepancy). Our approach offers a less complex solution
Brain-computer interfaces (BCIs) translate brain activity into digital commands for interaction with the physical world. The technology has great potential in several applied areas, ranging from medical applications to entertainment industry, and creates new conditions for basic research in cognitive neuroscience. The BCIs of today, however, offer only crude online classification of the user's cur
Support for Machine Learning (ML) applications in networking has significantly improved over the last decade. The availability of public datasets and programmable switching fabrics (including low-level languages to program them) presents a full-stack to the programmer for deploying in-network ML. However, the diversity of tools involved, coupled with complex optimization tasks of ML model design a
This article studies conceptualisations of social class in Swedish education research, c. 1945–1960. The article follows knowledge produced about talent and class in state commissions and in the newly expanded social sciences, and how it in turn was interpreted and used in political debates and in the media. I show that the taxonomy of the population in social groups (Socialgrupper) was key for co
Background: Low-cost particulate matter sensors have enabled new opportunities for exposure monitoring but require evaluation before application in epidemiological studies. This study assessed the performance of the SPS30 sensor integrated into the ARMIE portable monitoring sensor-node under controlled laboratory conditions. Methods: Sensors were co-located with two comparison instruments—the opti
Software analytics (SA) is often proposed as a tool to support software engineering (SE) tasks. Several secondary studies on SA have been published, some published within the same calendar year. This presents an opportunity to take a meta-perspective and examine how the field of SA has been conceptualized and synthesized so far. By analyzing how SA is defined, which topics are emphasized, what sea
Driven by the idea to use alarm data to explore machine learning across Industry 4.0 applications, the goal of this pilot study was to explore how to collect, store, manage and share data from the ESS Control System. Generally, we seek to make any control system data available for research and innovation but started with alarms as a feasible domain in which to explore machine learning. The goals w
Background: Hypoxic-ischaemic encephalopathy (HIE) is a leading cause of mortality and long-term neurological sequelae, affecting thousands of children worldwide. Current therapies to treat HIE are limited to cooling. Stem cell-based therapies offer a potential therapeutic approach to repair or regenerate injured brain tissue. These preclinical findings have now culminated in ongoing human neonata
This paper presents datasets that enable historical longitudinal studies of micro-level geographic factors in a rural setting. These types of datasets are new, as historical demography studies have generally failed to properly include the micro-level geographic factors. Our datasets describe the geography over five Swedish rural parishes, and by linking them to a longitudinal demographic database,
This paper presents an angular-domain massive MIMO detector which exploits sparsity in massive MIMO channel along with a reconfigurable systolic array architecture to achieve high area efficiency. The underlying idea is to perform signal detection in the angular domain, where the channel matrix can have much lower dimension due the limited number of dominant angles (of arrival and departure) of th
Prostate cancer is the most diagnosed cancer in men. The diagnosis is confirmed by pathologists based on ocular inspection of prostate biopsies in order to classify them according to Gleason score. The main goal of this paper is to automate the classification using convolutional neural networks (CNNs). The introduction of CNNs has broadened the field of pattern recognition. It replaces the classic
A low-latency and area-efficient FFT/IFFT scheme is presented. The main idea is to utilize OFDM guard bands to reduce the operation counts and processing time, which results in 42% latency reduction compared to the reported pipelined schemes. To realize this idea, a modified pipelined architecture and an efficient data scheduling scheme are proposed. Furthermore, the proposed architecture is scala
Geocoding longitudinal and individual-level historical demographic databases enables novel analyses of how micro-level geographic factors affected demographic outcomes over long periods. However, such detailed geocoding involves high costs. Additionally, the high spatial resolution cannot be properly utilized if inappropriate methods are used to quantify the geographic factors. We assess how diffe
Introduction: In palliative care, family caregivers are often faced with experiences of grief in anticipation of the loss of a close person. An instrument designed to measure this form of grief is the Anticipatory Grief Scale, which includes 27 items and has been used in several studies in various contexts. However, the instrument has not been validated. Aim: The aim was to evaluate the psychometr
Signal processing complexity and required memory become problematic in massive MIMO systems as the dimension of channel state information (CSI) matrix grows significantly with the large number of antennas and users. To address these challenges, we propose the first angular-domain massive MIMO detection scheme, which is based on three concepts: transferring the baseband processing from the spatial
A considerable part of latency in the baseband of massive multiple-input multiple-output (MIMO) systems is introduced by orthogonal frequency division multiplexing (OFDM) (de)modulation. To address the low-latency demand of massive MIMO systems, a fast Fourier transform (FFT) processor and corresponding reordering scheme are proposed, which reduce the processing latency and reordering latency of O
BACKGROUND: Contact allergy to oxidized (ox.) linalool and ox. limonene has been reported to have a high prevalence, raising the question of inclusion into the baseline series. However, several important issues should be clarified and further investigated before inclusion can be warranted.OBJECTIVES: To report the trends of ox. terpenes allergy in patients with dermatitis, features of the patch te
