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In this paper, we focus on ultra-dense network modelingwhere both the Base Stations (BSs) and Mobile Terminals(MTs) are UAVs. In this case, two communication nodes canbe very close to each other. However, existing cellular networkanalyses typically use the standard unbounded path loss modelwhere received power decays like r^beta over a distance r. Thisstandard model is a good approximation for the
Human complex-forming glycoprotein, heterogeneous in charge (protein HC) has previously been isolated from urine and immunochemically shown to be present in low and high molecular weight forms in blood plasma (Tejler, L., and Grubb, A. O. (1976) Biochim. Biophys. Acta 439, 82-94). In the present work, the major low and high molecular weight forms of the protein were isolated from plasma by immunos
Static checker frameworks support software developers by automatically discovering bugs that fit general-purpose bug patterns. These frameworks ship with hundreds of detectors for such patterns and allow developers to add custom detectors for their own projects. However, existing frameworks generally encode detectors in imperative specifications, with extensive details of not only what to detect b
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
Moving toward the open innovation (OI) model requires multifaceted transformations within companies. It often involves giving away the tools for product development or sharing future product directions with open tools ecosystems. Moving from the traditional closed innovation model toward an OI model for software development tools shows the potential to increase software development competence and
We propose an anti-windup scheme for a class of control problems. This class, includes networked systems, where each node contains a subsystem and each edge comprise a control action. The networked anti-windup control system is proposed to address the issues caused by integrator state saturation. We show that the suggested control scheme is input-output stable. Furthermore, we provide a numerical
This thesis explores the challenges and advancements in high-dimensional Bayesian optimization (HDBO), focusing on understanding, quantifying, and improving optimization techniques in high-dimensional spaces.Bayesian optimization (BO) is a powerful method for optimizing expensive black-box functions, but its effectiveness diminishes as the dimensionality of the search space increases due to the cu
Some common Christmas plants are presented with emphasis on Botany and their connection to Christmas. The plants dis- cussed are Picea abies, Euphorbia pulcherrima, Helleborus niger, Viscum album, Ilex aquifo- lium, Schlumbergera sp., Hippeastrum × hor- torum, Hyacinthus orientalis, Lycopodium s.l., and Cladonia stellaris.
High-pressure homogenizers are prone to cavitation, which causes wear and influences breakup efficiency. However, the inception point, as well as the extent and intensity, depends on geometry, operation, and fluid properties. While several methods have been previously suggested to characterize cavitation in homogenizer valves (including ultrasonic methods), they have required highly specialized, s
Recent advances have extended the scope of Bayesian optimization (BO) to expensive-to-evaluate black-box functions with dozens of dimensions, aspiring to unlock impactful applications, for example, in the life sciences, neural architecture search, and robotics. However, a closer examination reveals that the state-of-the-art methods for high-dimensional Bayesian optimization (HDBO) suffer from degr
Background: A novel data-driven classification of type 2 diabetes has been proposed to personalise anti-diabetic treatment according to phenotype. One subgroup, severe insulin-resistant diabetes (SIRD), is characterised by mild hyperglycaemia but marked hyperinsulinaemia, and presents an increased risk of diabetic nephropathy. We hypothesised that patients with SIRD could particularly benefit from
We present a unique comparative analysis, and evaluation of vision, radio, and audio based localization algorithms. We create the first baseline for the aforementioned sensors using the recently published Lund University Vision, Radio, and Audio (LuViRA) dataset, where all the sensors are synchronized and measured in the same environment. Some of the challenges of using each specific sensor for in
Future Internet-of-Things (IoT) systems need to combine heterogeneous IoT components and support weak connectivity. This paper introduces ComPOS, a domain-specific language for composing IoT services into systems. ComPOS is a small language but supports powerful message mediation, using stateful reactions with nested and parallel message sequences and anonymous futures. To deal with weak connectiv
Fat-soluble vitamin D is an essential bioactive compound important for human health. Insufficient vitamin D levels can result not only in bone disease but also in other disorders, such as cancer, metabolic disorders, and diseases related to poor immune function. The current methods commonly used for vitamin D analysis are often applied to determine the levels of the most abundant metabolite in pla
Uppenbarelseboken avtäcker med sina fasansfulla syner – sin Apokalyps – vad som ska ske på den yttersta dagen, då allt ont ska förgås och ett nytt rike ska upprättas. Men numera menas ofta med apokalyps enbart den skräckfyllda, mytologiska spådomen om en framtida katastrof. Kan man istället förstå Uppenbarelsebokens syner som en varning, för den katastrof vi själva är med om att skapa här och nu,
Bayesian Optimization has emerged as a crucial technique for optimizing costly, black-box functions where each evaluation comes at a high cost, such as in scientific experiments, and machine learning hyperparameter optimization. By combining probabilistic modeling with sequential decision-making, Bayesian Optimization achieves efficient exploration, guiding the search toward optimal parameters wit
Objective: To implement artificial neural network (ANN) algorithms for noninvasive lymph node staging (NILS) to a decision support tool and facilitate the option to omit surgical axillary staging in breast cancer patients with low-risk of nodal metastasis. Methods: The NILS tool is a further development of an ANN prototype for the prediction of nodal status. Training and internal validation of the
