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The automotive and railway industries are rapidly transforming with a strong drive towards automation and digitalization, with the goal of increased convenience, safety, efficiency, and sustainability. Since assisted and fully automated automotive and train transport services increasingly rely on vehicle-to-everything communications, and high-accuracy real-time positioning, it is necessary to continuously maintain high-accuracy localization, even in occlusion scenes such as tunnels, urban canyons, or areas covered by dense foliage. In this paper, we review the 5G positioning framework of the 3rd Generation Partnership Project in terms of methods and architecture and propose enhancements to meet the stringent requirements imposed by the transport industry. In particular, we highlight the benefit of fusing cellular and sensor measurements and discuss required architecture and protocol support for achieving this at the network side. We also propose a positioning framework to fuse cellular network measurements with measurements by onboard sensors. We illustrate the viability of the proposed fusion-based positioning approach using a numerical example., 7 pages, 5 figures, accepted for publication in IEEE Communications Standards Magazine

Indoor positioning is currently recognized as one of the important features in emergency, commercial and industrial applications. The 5G network enhances mobility, flexibility, reliability, and security to new higher levels which greatly benefit the IoT and industrial applications. Industrial IoT (IIoT) use-cases are characterized by ambitious system requirements for positioning accuracy in many verticals. For example, on the factory floor, it is important to locate assets and moving objects such as forklifts. The deployment design for different IIoT environments has a significant impact on the positioning performance in terms of both accuracy and availability of the service. Indoor factory (InF) and indoor open office (IOO) are two available and standardized Third Generation Partnership Project (3GPP) scenarios for evaluation of indoor channel models and positioning performance in IIoT use cases. This paper aims to evaluate the positioning performance in terms of accuracy and availability while considering different deployment strategies. Our simulation-based evaluation shows that deployment plays a vital role when it comes to achieving high accuracy positioning performance. It is for example favorable to deploy the 5G Transmission and Reception Points (TRPs) on the walls of the factory halls than deploying them attached to the ceiling.

Future automated vehicles and advanced driver assistance systems are highly dependent on sensors to detect their environment as well as robust, accurate, and cost-effective sensor systems for positioning. Global Navigation Satellite systems (GNSS) provide a key technology that enables an absolute position estimate and Network-RTK (Real Time Kinematic) has the potential to meet the requirements of cost, accuracy, and availability. This technology is based on correction data being received from a fixed reference station via e.g. mobile communication. Current implementations have been driven by requirements from applications which operate within a limited region for lengthy periods of time, such as surveying and precision agriculture. These applications can tolerate relatively long initialization times and can afford expensive equipment. The mass market wants to benefit from infrastructure in place for these applications, but the requirements are somewhat different. Problems occur when the device moves from the coverage area of one reference station to another and reinitialization must be made. Consumer devices must also deliver similar performance with inexpensive components. In addition to this, the existing public-sector system for distribution of correction data, in Sweden governed by Lantmäteriet/ SWEPOS, is not designed for handling a large number of clients and efficiently distributing correction data to these clients based on their location.The telecom industry in 3GPP (Third generation partnership project) is currently addressing the need for a scalable provisioning of network RTK corrections. Based on the 3GPP specification, the project aimed to develop, implement, test and demonstrate an efficient distribution system for Network-RTK correction data in order to enable cm-level accuracy GNSS positioning for a large number of mobile platforms e.g. automated vehicles. The NPAD project has: Leveraged the existing Lantmäteriet/SWEPOS GNSS reference infrastructure to implement a virtual network of reference stations that provided coverage over selected test areas suitable for supporting a large number of simultaneous users. Implemented a scalable GNSS correction data provisioning based on the ongoing work in 3GPP that provides correction data from the reference network to mobile devices; Developed test cases for automated vehicle platforms related to positioning and implemented demonstrators; Investigated tools and methods for validating the accuracy of integrated GNSS positioning and navigation systems. The project was coordinated by RISE Research Institutes of Sweden and involved besides Lantmäteriet and AstaZero the following industrial partners: AB Volvo, Caliterra, Einride, Ericsson, Scania, and Waysure. NPAD

This research concerns the digitalisation of archaeology, with a focus on Swedish contract archaeology. The aim is to understand how the archaeological discipline relates to the change that digitalisation brings and human involvement in these processes. The thesis is a study of its impact on processes connected to archaeological knowledge production and communication. The work problematises how digital data might be understood within these contexts but also illustrates where the potential of the digitalisation lies and how archaeology can make use of it. The theoretical approach re-actualises the concept of reflexivity in a digital context, combining it with various communication theories aiming to challenge the archaeological workflow and connect it more closely to present-day society. The digitalisation of archaeology can be seen across the whole discipline withan emphasis on academia. This digital development has greater opportunities in larger research projects which have sufficient funding than in contract archaeology. In those projects leading the digital development, the reflexive approach has been re-discovered and the digital enabled for new processes of knowledge production to take place. In case studies of Swedish contract archaeology several observations are made where it becomes clear that the digitalisation already shows positive effects at a government level, in organisations and projects within the sector. But there are also issues regarding digital infrastructure, knowledge production, archiving, accessibility and transparency. The biggest challenge is not technical but in attitudes towards digitalisation. The research concludes that digital communication based on archaeological source material can be something more than mediation of results. With digital interactive storytelling there are ways to create emotional virtual connections with the user, relating to the present and the surrounding society. By interlinking the processes of interpretation and communication an archaeological knowledge production might become an archaeological knowledge development. Den här forskningen har studerat digitaliseringen av arkeologin med fokus på svensk uppdragsarkeologi. Målet har varit att öka förståelsen kring hur disciplinen förhåller sig till de förändringar som digitaliseringens innebär och människans roll i dessa processer. Avhandlingen är en studie av digitaliseringens betydelse för de arkeologiska processer som berör kunskapsproduktion och kommunikation. Arbetet problematiserar förståelsen av digitala data inom dessa kontexter men visar också på digitaliseringenspotential och hur arkeologin kan dra nytta av den. Forskningen aktualiserar på nytt det teoretiska angreppssättet reflexivitet i ett digitalt sammanhang och kombinerar detta med kommunikationsteorier i syfte att utmana det arkeologiska arbetsflödet och knyta det närmare dagens samhälle. Resultatet av denna forskning visar på att digital kommunikation baserad på arkeologiskt källmaterial kan vara något mer än förmedling av resultat. Med interaktivt historieberättande finns vägar att skapa emotionella virtuella kopplingar mellan användare och arkeologi som relaterar till nuet och detomgivande samhället. Genom att länka ihop den arkeologiska tolkningsprocessen med kommunikation, skapas möjligheten för kunskapsproduktion att bli kunskapsutveckling.

Kernel-based machine learning methods are gaining increasing interest in flow modeling and prediction in recent years. Gaussian process (GP) is one example of such kernelbased methods, which can provide very good performance for nonlinear problems. In this work, we apply GP regression to flow modeling and prediction of athletes in ski races, but the proposed framework can be generally applied to other use cases with device trajectories of positioned data. Some specific aspects can be addressed when the data is periodic, like in sports where the event is split up over multiple laps along a specific track. Flow models of both the individual skier and a cluster of skiers are derived and analyzed. Performance has been evaluated using data from the Falun Nordic World Ski Championships 2015, in particular the Men’s cross country 4 × 10 km relay. The results show that the flow models vary spatially for different skiers and clusters. We further demonstrate that GP regression provides powerful and accurate models for flow prediction.

Driven by the promising beaconing techniques, this paper presents a general received-signal-strength (RSS) threshold optimization procedure for proximity reports to support networkbased indoor positioning. The desired RSS threshold is found through optimizing a metric function (for instance the localization root-mean-square-error) in terms of both the deployment information and the RSS modeling in consideration of an evaluation area. The resulting RSS threshold provides a trade-off between triggering many but less informative proximity reports with a low threshold, and triggering few but very informative proximity reports with a high threshold, and thus enables enhanced performance for some low-cost and low-complex proximity based positioning algorithms. The proposed framework is also validated with real RSS measurements collected in an office area with deployed bluetooth low-energy (BLE) beacons.

Bakgrund: Närstående kan uppleva återupplivning av en anhörig som traumatiskt och det har länge varit praxis att utesluta närstående ur rummet när återupplivning sker trots att det funnits en vilja hos närstående att närvara. Återupplivning kan framkalla stress hos närstående men att närvara har påvisats kunna ge fördelaktiga upplevelser. Sjuksköterskan har en viktig roll i att informera och hjälpa närstående i situationen men detta kompliceras av tidsbrist och kunskapsbrist samt en negativ inställning till att närstående närvarar. Syfte: Syftet var att belysa närståendes upplevelser i samband med återupplivning av en anhörig i sjukhusmiljö. Metod: En kvalitativ ansats användes i föreliggande litteraturstudie. Datainsamlingen resulterade i sex vetenskapliga artiklar med kvalitativ ansats och analyserades med Graneheim och Lundman (2004) tolkning av innehållsanalys. Resultat: Sex kategorier framkom och användes i resultatet. Dessa sex kategorier var: upplevde sig viktiga, kände sig väl omhändertagna, upplevde rädsla, upplevde maktlöshet, att inte störa samt ta svåra beslut. Slutsats: Det finns individuella skillnader i upplevelser där rädsla och en känsla av att vara omhändertagen är två av de mest förekommande beskrivna upplevelserna. Sjuksköterskan verkar ha en viktig roll i hur närståendes upplevelser gestaltar sig. Dock är mer empirisk forskning önskvärd då tillgången på denna är väldigt begränsad. Det kan vara önskvärt att implementera lokala sjukhusrutiner för omhändertagandet av närstående för att säkra en holistisk omvårdnad kring den anhörige.

Positioning in radio networks is a well establishedresearch area. The dominating approach has been that positioningalgorithms are implemented in the higher levels of the communicationsystem based on position related information derivedin the lowest (physical) layer. Examples of measurement includereceived signal strength (RSS), time of arrival (TOA), angleof arrival (AOA), and fusion and filtering is a straightforwardtask. The technical driver for positioning has been E911 andfor commercially driver comes from location based services andlogistics management. These demands are fundamental in thedevelopment of positioning in future radio networks standards.There is today a trend for accuracy demand that goes beyondwhat can be achieved with todays measurements. Another trendis that measurements and positioning algorithms are approachingeach other, so some parts of the positioning are performed on thechip-sets (lowest layer) and low-level measurements are availableto the operating system (highest level). The purpose of thissurvey is to describe this trend in more detail, with examples ofdevelopments in cellular networks as well as WiFi and Bluetooth. TRAX

The optimum multiuser detection problem can be formulated as a maximum likelihood problem, which yields a binary quadratic programming problem to be solved. Generally this problem is NP-hard and is therefore hard to solve in real time. In this paper, a preprocessing algorithm is presented which makes it possible to detect some or all users optimally for a low computational cost if signature sequences with low cross correlation, e.g., Gold sequences, are used. The algorithm can be interpreted as, e.g., an adaptive tradeoff between parallel interference cancellation and successive interference cancellation. Simulations show that the preprocessing algorithm is able to optimally compute more than 94,% of the bits in the problem when the users are time-synchronous, even though the system is heavily loaded and affected by noise. Any remaining bits, not computed by the preprocessing algorithm, can either be computed by a suboptimal detector or an optimal detector. Simulations of the time-synchronous case show that if a suboptimal detector is chosen, the bit error rate (BER) rate is significantly reduced compared with using the suboptimal detector alone.

In nonuniform sampling (NUS), signal amplitudes and time stamps are delivered in pairs. Several methods to compute an approximate Fourier transform (AFT) have appeared in literature, and their posterior properties in terms of alias suppression and leakage have been addressed. In this paper, the sampling times are assumed to be generated by a stochastic process. The main result gives the prior distribution of several AFTs expressed in terms of the true Fourier transform and variants of the characteristic function of the sampling time distribution. The result extends leakage and alias suppression with bias and variance terms due to NUS. Specific sampling processes as described in literature are analyzed in detail. The results are illustrated on simulated signals, with particular focus to the implications for spectral estimation.

In this paper a preprocessing algorithm for binary quadratic programming problems is presented. For some types of binary quadratic programming problems, the algorithm can compute the optimal value for some or all integer variables without approximations in polynomial time. When the optimal multiuser detection problem is formulated as a maximum likelihood problem, a binary quadratic programming problem has to be solved. Fortunately, the low correlation between different users in the multiuser detection problem enables the use of the preprocessing algorithm. Simulations show that the preprocessing algorithm is able to compute almost all variables in the problem, even though the system is heavily loaded and affected by noise.

The limiting factor in the uplink of all CDMA cellular systems is the relation between uplink noise rise and intended coverage. In link budgets, noise rise is usually simply handled as a constant contribution to the background noise in logarithmic scale, often referred to as interference margin. In practice, however, it is not constant. We model the uplink noise rise as a lognormal distribution, and investigate the impact to link budgets. Simulations and numerical calculations show that the uplink noise rise variance does not critically affect the uplink capacity and coverage. System feasibility and its relation to the uplink load is also discussed. It is shown that approximative load expressions provides an upper bound on the uplink load and therefore they can be used to imply system feasibility. Furthermore, the uplink load expressions provide accurate approximations of the load given that the load is within the practical limits given by the link budgets.

In many real-time applications, sample values and time stamps are delivered in pairs, where sampling times are non-uniform. Frequency analysis using non-uniform data occurs in various real life problems and embedded systems, such as vibrational analysis in cars and control of packet network queue lengths. Our contribution is to first overview different ways to approximate the Fourier transform, and secondly to give analytical expressions for how non-uniform sampling affects these approximations. The results are expressed in terms of frequency windows describing how a single frequency in the continuous time signal is smeared out in the frequency domain, or, more precisely, in the expected value of the Fourier transform approximation.

Due to the rapid growth of the Internet and the use of packet data traffic, the communication world has to find ways of improving performance of this traffic. New areas of use include, e.g., radio transmissions and real time data. This work discusses some issues of performance when using TCP and also present some of the measures that are used today. Furthermore we discuss this matter from the perspective of a bottleneck queue and present a measure that can be used from that viewpoint in the network. This measure is illustrated by comparing two versions of TCP and form the basis for a discussion of what models will be needed to actually achieve the goals that we have. A control structure is presented and using simulations and a control interpretation we note that RED introduces an implicit wanted steady state value of the queue length. We use the dropping of packets as a control signal and the output signal is the queue length.

The economic value of the innovation robotic milking systems (AMS) is examined for Swedish dairy operations. A mixed integer mathematical programming model, considering crops, calving distribution, seasonality and capacity constraints of the AMS system, is developed. The marginal value of increasing the capacity of the AMS unit is found to amount to 40-60% of the milk revenues per cow.

The global communications systems critically relyon control algorithms of various kinds. In wireless communications systems, power control algorithms play an important role for efficient resource utilization. This survey article discusses relevant aspects of power control with emphasis on practical issues, using an automatic control framework. Generally, power control of each connection is distributedly implemented as cascade control, with an inner loop to compensate for fast variations and an outerloop focusing on longer term statistics. These control loops are interrelated via complex connections, which affect important issues such as capacity, load and stability. Therefore, both local and global properties are important. The concepts and algorithms are illustrated by simple examples and simulations.