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Antenna bounds are a useful tool in assessing the feasibility or performance of an antenna design. Microstrip patch antennas are often limited by their relatively narrow bandwidth, and therefore Q-factor is an important design parameter, as it is related to the inverse of the fractional bandwidth. This article presents the first tight lower Q-factor bounds on microstrip patch antennas supported by
This exhibition of new sculptural works by the artist coincides with the launch of a new series of prints by Rosa Barba published by, and only available through Cahiers d’Art; featuring two distinct series of unique Monoprints and two Limited Edition print series. After spending time among the archives of Cahiers d’Art, Rosa Barba drew inspiration from the original copper printing plates featuring
Balcinrenone (AZD9977) is a selective mineralocorticoid receptor modulator in development in combination with dapagliflozin for treatment of heart failure with impaired kidney function and chronic kidney disease. A prespecified concentration–QT analysis was performed based on data from a phase I single ascending dose study prospectively designed as a thorough QT study substitute. Oral single doses
Grandparents’ involvement in their adult children’s families has increased in recent decades, especially in relation to care arrangements around grandchildren. This ‘new army of proxy parents’ calls for the need to critically analyse grandparental care. Drawing on a study on intergenerational care in Sweden, involving grandparents, adult children and grandchildren (63 interviewees including 28 gra
When it comes to innovation, economic growth, affluence and international attractiveness, there are currently few places in the world that can compare with the San Francisco Bay Area. However, new megatrends such as Sustainability, can challenge its attractiveness. Scholars talk about the “Nordic approach”.In the geographical area of Southern Scandinavia, ‘The Strait Area’, the focus is on Sustai
This paper describes a work in progress implementation of a programming tool that puts errors and their provenance at the forefront of the interaction between a developer and a compiler. We discuss the motivation for such a tool, it’s design and implementation, and reflect upon avenues for further research which it can facilitate.
Machine Learning (ML) is a fundamental part of modern perception systems. In the last decade, the performance of computer vision using trained deep neural networks has outperformed previous approaches based on careful feature engineering. However, the opaqueness of large ML models is a substantial impediment for critical applications such as in the automotive context. As a remedy, Gradient-weighte
Empirical software engineering research relies on good communication with industrial partners. Conducting joint research both requires and contributes to bridging the communication gap between industry and academia (IA) in software engineering. This study aims to explore communication between the two parties in such a setting. To better understand what facilitates good IA communication and what pr
Background: The literature concerning research methodologies and methods has increased in software engineering in the last decade. However, there is limited guidance on selecting an appropriate research methodology for a given research study or project.Objective: Based on a selection of research methodologies suitable for software engineering research in collaboration between industry and academia
Background: The socio-technical characteristic of software engineering is acknowledged by many, while the technical side still dominates research. As software engineering is a human-intensive activity, the cognitive side of software engineering needs more exploration when trying to improve its efficiency.Aim: The aim of this study is to increase the understanding of the impact of cognitive load in
In recent years the number of connected devices and the demand for high data-rates have been significantly increased. This enormous growth is more pronounced by the introduction of the Internet of things (IoT) in which several devices are interconnected to exchange data for various applications like smart homes and smart cities. Moreover, new applications such as eHealth, autonomous vehicles, and c
Software systems are increasingly depending on data, particularly with the rising use of machine learning, and developers are looking for new sources of data. Open Data Ecosystems (ODE) is an emerging concept for data sharing under public licenses in software ecosystems, similar to Open Source Software (OSS). It has certain similarities to Open Government Data (OGD), where public agencies share da
The notion of Cloud RAN is taking a prominent role in narrative for the next generation wireless infrastructure. It is also seen as a mean to industrial communication systems. In order to provide reliable wireless connectivity for industrial deployments, by conventional means, the cloud infrastructure needs to be reliable and incur little latency, which however, is contradictory to the stochastic
DevOps represent the tight connection between development and operations. To address challenges that arise on the bor- derline between development and operations, we conducted a study in collaboration with a Swedish company responsible for ticket management and sales in public transportation. The aim of our study was to explore and describe the existing DevOps environment, as well as to identify h
Large intelligent surface (LIS) is a technology that extends massive MIMO by considering an even greater number of antennas distributed throughout vast areas. In order to be able to implement this technology, it is crucial to consider decentralized architectures so as to make the whole system scalable. We consider a LIS divided into several LIS panels of smaller size, which can be located far away
While Bayesian Optimization (BO) is a very popular method for optimizing expensive black-box functions, it fails to leverage the experience of domain experts. This causes BO to waste function evaluations on bad design choices (e.g., machine learning hyperparameters) that the expert already knows to work poorly. To address this issue, we introduce Bayesian Optimization with a Prior for the Optimum
Security for outsourced control applications can be provided if the physical plant is enabled with a mechanism to verify the control signal received from the cloud. Recent developments in modern cryptography claim the applicability of verifiable computation techniques. Such techniques allow a client to check the correctness of a remote execution. This article delivers a proof of concept for applic
Order-batching is an important methodology in warehouse material handling. This paper addresses three identified shortcomings in the current literature on order-batching optimization. The first concerns the overly large dependence on conventional warehouse layouts. The second is a lack of proposed optimization methods capable of producing approximate solutions in minimal computational time. The th
In this paper, we study the effect of optimizing the per-antenna digital predistortion (DPD) sizes on the performance of the downlink massive MIMO system with residual hardware impairment. In particular, we first quantify the capacity after applying some per-antenna DPD with different numbers of coefficients at each antenna and then maximize the capacity by finding optimum values of the per-antenn
