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Integration of Clouds to Industrial Communication Networks

Cloud computing, owing to its ubiquitousness, scalability and on-demand ac- cess, has transformed into many traditional sectors, such as telecommunication and manufacturing production. As the Fifth Generation Wireless Specifica- tions (5G) emerges, the demand on ubiquitous and re-configurable computing resources for handling tremendous traffic from omnipresent mobile devices has been put forward.

Experimental Exploration of Unlicensed Sub-GHz Massive MIMO for Massive Internet-of-Things

IoT networks are getting overcrowded following the vast increase in number of Internet-of-Things (IoT) devices and connections. Networks can be extended with more gateways, increasing the number of supported devices. However, as investigated in this work, massive MIMO has the potential to increase the number of simultaneous connections and moreover lower the energy expenditure of these devices. We

Anomaly Detection Under Multiplicative Noise Model Uncertainty

State estimators are crucial components of anomaly detectors that are used to monitor cyber-physical systems. Many frequently-used state estimators are suscepti- ble to model risk as they rely critically on the availability of an accurate state-space model. Modeling errors make it more difficult to distinguish whether deviations from expected behavior are due to anomalies or simply a lack of knowl

Fair heat distribution under deficits in district heating networks

In order to improve the energy efficiency in district heating networks and the comfort of their customers, these networks need to overcome the problem of unfair heat distribution under heat deficits. This paper introduces a new strategy to achieve this thermal fairness objective: it is lowcost in terms of communication and computation. The proposed approach is illustrated on a simulation example.

Secondary ice production during the break-up of freezing water drops on impact with ice particles

We provide the first dedicated laboratory study of collisions of supercooled water drops with ice particles as a secondary ice production mechanism. We experimentally investigated collisions of supercooled water drops (∼5 mm in diameter) with ice particles of a similar size (∼6 mm in diameter) placed on a glass slide at temperatures >-12 °C. Our results showed that secondary drops were generated d

Triple collocation-based error estimation and data fusion of global gridded precipitation products over the Yangtze River basin

Error estimation and data fusion are critical to improving the accuracy of global model- and satellite-based precipitation products for practical applications. However, they face challenges over vast areas of the world due to limited ground observations. Triple collocation (TC) method can overcome this limitation and provide an efficient way for error estimation without the “ground truth” and thus

Improving generalisation capability of artificial intelligence-based solar radiation estimator models using a bio-inspired optimisation algorithm and multi-model approach

One way of reducing environmental pollution is to reduce our dependence on fossil fuels by replacing them with solar radiation (Rs), which is one of the main sources of clean and renewable energy. In this study, daily Rs values at seven meteorological stations in Iran (Ahvaz, Isfahan, Kermanshah, Mashhad, Bandar Abbas, Kerman and Tabriz) over 2010-2019 were estimated using empirical models, suppor

Collaborative Aspects of Open Data in Software Engineering

Engineers require high-quality data for the design and implementation of today’s software, especially in the context of machine learning (ML). This puts an emphasis on the need for the publication and sharing of data from and between organizations, public as well as private. Following the paradigm of open innovation, open data provide a mechanism to increase the availability of information, offeri

Self-Aware Anomaly-Detection for Epilepsy Monitoring on Low-Power Wearable Electrocardiographic Devices

Low-power wearable technologies offer a promising solution to pervasive epilepsy monitoring by removing the constraints concerning time and location, on one hand, and fulfilling long-term tracking, on the other hand. In the case of epileptic seizures, as the attacks infrequently occur, using an anomaly detection approach reduces the need to record long hours of data for each patient before detecti

Personalized Real-Time Federated Learning for Epileptic Seizure Detection

Epilepsy is one of the most prevalent paroxystic neurological disorders. It is characterized by the occurrence of spontaneous seizures. About 1 out of 3 patients have drug-resistant epilepsy, thus their seizures cannot be controlled by medication. Automatic detection of epileptic seizures can substantially improve the patient's quality of life. To achieve a high-quality model, we have to collect d

Assessing the effects of time interpolation of ndvi composites on phenology trend estimation

The accurate evaluation of shifts in vegetation phenology is essential for understanding of vegetation responses to climate change. Remote-sensing vegetation index (VI) products with multi-day scales have been widely used for phenology trend estimation. VI composites should be interpolated into a daily scale for extracting phenological metrics, which may not fully capture daily vegetation growth,

Developing eHealth in neonatal care to enhance parents' self-management

BackgroundDischarge from a neonatal care unit is often experienced as a vulnerable time for parents. By communicating through digital technology, it may be possible to improve the support for parents and thereby make the transition from hospital to home less stressful.AimTo develop an eHealth device supporting the transition from hospital to home for parents with a preterm‐born child in Sweden usi

Prototyping Practices in Software Startups : Initial Case Study Results

Software startups use prototyping to develop and test business ideas and to validate market viability. While prototyping is emphasized in agile methods, there is little research on how startups can best utilise scarce resources to effectively use prototypes in their dynamic business context. We performed a case study of four startups and investigated how startups currently use prototyping to elici

Distributed Neural-Network-Based Cooperation Control for Teleoperation of Multiple Mobile Manipulators Under Round-Robin Protocol

This article addresses the distributed cooperative control design for a class of sampled-data teleoperation systems with multiple slave mobile manipulators grasping an object in the presence of communication bandwidth limitation and time delays. Discrete-time information transmission with time-varying delays is assumed, and the Round-Robin (RR) scheduling protocol is used to regulate the data tran

NPI models explained and complained

Numerous modelling efforts have attempted to characterize the effects of different non-pharmaceutical interventions (NPIs) on the Covid-19 spread. Arguably the most famous is one published in Nature by an Imperial College group. A slight variation of it was later published in Science by a group of Oxford researchers. Both publications are based on hierarchical Bayesian modelling that aims to expla

Predicting Glycemia in Type 1 Diabetes Mellitus with Subspace-Based Linear Multistep Predictors

A major challenge for a person with diabetes is to adapt insulin dosage regimens and food intake to keep blood glucose within tolerable limits during daily life activities. The accurate prediction of blood glucose levels in response to inputs would support the patients with invaluable information for appropriate on-the-spot decision making concerning the management of the disease. Against this bac

A Low-Voltage 6T Dual-Port Configured SRAM with Wordline Boost in 28 nm FD-SOI

A 32 Kb dual-port low-voltage SRAM in 28 nm FD-SOI, featuring foundry supplied high-density 6T bitcells, is presented. Dual-port configurability is realized by a unique dual-rail architecture, utilizing boost techniques that guarantee reliable operation in low-voltage. The area cost of the array is 62% lower, compared to widely used 8T two-port or dual-port SRAM arrays. The SRAM reliably operates

Quantifying changes and drivers of runoff in the Kaidu River Basin associated with plausible climate scenarios

Study region: The Kaidu River Basin (KRB) is located on the central southern slope of the Tianshan Mountain in Northwest China. Study focus: This work aimed to assess changes and main drivers of snowmelt-driven runoff in KRB associated with three future climate scenarios. Six versions of the “Cemaneige” snowmelt module embedded in the hydrological model “GR4J” were calibrated and evaluated. The bi

ControlSystems.jl: A Control Toolbox in Julia

ControlSystems.jl enables the powerful features of the Julia language to be leveraged for control design and analysis.The toolbox provides types for state-space, transfer-function, and time-delay models, together with algorithms for design and analysis.Julia's mathematically-oriented syntax is convenient for implementing control algorithms, and its just-in-time compilation gives performance on par