Purpose – This paper aims to unveil how sustainability is integrated into the courses/programmes ofhigher education institutions. The research question addressed is: how do academics representing differentdisciplines cooperate and engage in the work of integrating sustainability into their teaching programmes.Design/methodology/approach – This paper draws upon the notions of practise variation andinstitutional work from institutional theory and empirically focusses on the case of Kristianstad University(Sweden). This case is based on an autoethnographic approach and illustrates the experiences shared by sixcolleagues, representing different disciplines, engaged in implementing sustainability in their courses/programmes.Findings – The findings highlight how academics representing different disciplines, with specific traditionsand characteristics, face the sustainability challenge. Despite being bound by similar sustainable developmentgoals, differences across disciplines need to be acknowledged and used as an asset if trans-disciplinarity is theultimate goal.Research limitations/implications – Although the intrinsic motivation of individuals to work withsustainability might be a strong driver, the implementation of sustainability within courses/programmes andacross disciplines requires joint efforts and collective institutional work.Practical implications – By highlighting how academics engage in the work of integratingsustainability, this study emphasizes that managers of higher education institutions need to account for thetime and additional resources needed to ensure that academics effectively cope with sustainability. Intrinsicmotivation may not last if organizational structures and leadership are not supportive on a practical level andin the long run.

The fast growth of Internet traffic, the growing importance of cellular accesses and the escalating competition between content providers and network operators result in a growing interest in improving network performance and user experience. In terms of network transport, different solutions ranging from tuning TCP to installing middleboxes are applied. It turns out, however, that the practical results sometimes are disappointing and we believe that poor testing is one of the reasons for this. Indeed, many cases in the literature limit testing to the simple and rare use case of a single file download, while common and complex use cases like web browsing often are ignored or modelled only by considering smaller files. To facilitate better testing, we present a broader view which includes domain counts, flow counts and different forms of concurrency to better characterise the complexity around web pages, and from which the potential for different optimisation techniques can be estimated. We also derive numerical values of these metrics for a small set of popular web pages and study similarities and differences between pages with the same kind of content (newspapers, e-commerce and video) and between pages designed for the same platform (computer and smartphone).

Streaming video continues to experience unprecedented growth. This underscores the need to identify user-centric performance measures and models that will allow operators to satisfy requirements for cost-effective network dimensioning delivered with an acceptable level of user experience. This paper presents an analysis of two novel metrics in the context of fixed capacity links: (i) the average proportion of a video’s playing time during which the quality is reduced and (ii) the average proportion of videos which experience reduced quality at least once during their playing time, based on an M/M/∞ system. Our analysis is shown to hold for the more general M/G/∞ system for metric (i), but not for (ii) and simulation studies show an unexpected form of sensitivity of metric (ii) to the flow duration distribution, contrary to the norm of increasing variance causing worse performance. At typical operational loads these new metrics provide a more sensitive and information rich guide for understanding how user experience degrades, than the widely used average throughput metric does. We further show that only the combined use of this existing and our new metrics can provide a holistic perspective on overall user performance.

We consider TCP performance for cloud servicesin 5G cellular networks and show that edge clouds offer the highest throughput, but that further improvements still arepossible. To this end we devise a concept where edge clouds connected directly to the radio access network can increase their transmission rates by relying on the built in re-transmissions (through quality of service features) and on the built in userfairness (through per-user buffers and scheduler policies). We use numerical examples from measurements in real networks to demonstrate that the concept is efficient and significantly improves the effective throughput beyond what placement alone can do, and we also outline possible further improvements.

We consider bottlenecks of TCP throughput in scenarios with edge clouds and 5G cellular networks. By numerical examples from measurements in real networks, we show that edge clouds indeed improve throughput but that several, nonnegligible bottlenecks remain. We therefore devise a concept where edge clouds connected directly to the radio access networkcan increase their transmission rates by relying on built in retransmissions (through quality of service features) and on the built in user fairness (through per-user buffers and scheduler policies). We then return to the numerical examples and show that our solution provides substantial gains and we concludeby identifying and discussing the remaining bottlenecks and the potential of an improved protocol.

It has been well-known that the class of quasi-cyclic (QC) codes contain many good codes. In thispaper, a method to conduct a computer search for binary 2-generator QC codes is presented, anda large number of good 2-generator QC codes have been obtained. 5 new binary QC codes thatimprove the lower bounds on minimum distance are presented. Furthermore, with new 2-generatorQC codes and Construction X, 2 new improved binary linear codes are obtained. With the standardconstruction techniques, another 16 new binary linear codes that improve the lower bound on theminimum distance have also been obtained.

Error control codes have been widely used in data communications and storage systems. One centralproblem in coding theory is to optimize the parameters of a linear code and construct codes withbest possible parameters. There are tables of best-known linear codes over finite fields of sizes up to9. Recently, there has been a growing interest in codes over F13 and other fields of size greater than9. The main purpose of this work is to present a database of best-known linear codes over the fieldF13 together with upper bounds on the minimum distances. To find good linear codes to establishlower bounds on minimum distances, an iterative heuristic computer search algorithm is employed toconstruct quasi-twisted (QT) codes over the field F13 with high minimum distances. A large numberof new linear codes have been found, improving previously best-known results. Tables of [pm;m] QTcodes over F13 with best-known minimum distances as well as a table of lower and upper bounds onthe minimum distances for linear codes of length up to 150 and dimension up to 6 are presented.

This study presents an exploration of several machine learning and image processing theories, as well as a literature review of several previous works on concrete crack detection systems. Through the literature review a system is selected and implemented with the Öresund bridge photograph collection. The selected system is a Convolutional Neural Network (CNN) using cropped (256x256x) images for input. The CNN has a total of 13 layers that were implemented as described in the paper. All parts of the implementation such as cropping, code, and testing are described in detail. This study found a final accuracy rate of 77% for the trained net. This is combined with a sliding window technique for handling larger images. An exploration of reasons for this accuracy rate is done at the end of the paper.

These days, the Industrial Internet of Healthcare Things (IIT) enabled applications have been growing progressively in practice. These applications are ubiquitous and run onto the different computing nodes for healthcare goals. The applications have these tasks such as online healthcare monitoring, live heartbeat streaming, and blood pressure monitoring and need a lot of resources for execution. In IIoHT, remote procedure call (RPC) mechanism-based applications have been widely designed with the network and computational delay constraints to run healthcare applications. However, there are many requirements of IIoHT applications such as security, network and computation, and failure efficient RPC with optimizing the quality of services of applications. In this study, the work devised the lightweight RPC mechanism for IIoHT applications and considered the hybrid constraints in the system. The study suggests the secure hybrid delay scheme (SHDS), which schedules all healthcare workloads under their deadlines. For the scheduling problem, the study formulated this problem based on linear integer programming, where all constraints are integer, as shown in the mathematical model. Simulation results show that the proposed SHDS scheme and lightweight RPC outperformed the hybrid for IIoHT applications and minimized 50% delays compared to existing RPC and their schemes.

This contribution studies the new forms of work that arise as a consequence of the pandemic, and presents how students in education can be prepared for these forms of work. More and more discussions concern adjustments to remote work. This also applies to the academy, which then has a responsibility, not only to change work towards distance forms, but also train students in these for their future professional career. A survey was conducted during the autumn semester of 2020 when a course in Software Engineering, which normally is dependent on physical meetings, was forced to be given completely online. The outcome was documented by the teachers during the course through continuous discussions and investigations, and was later compiled into a conference contribution, which is currently in a peer-review process [1]. Among the discussions it was mentioned that we may experience a ‘game-changer’, and more precisely that in the future we may work globally and distributed, i.e., independently of a localized office. Globally, it is possible to see discussions regarding such a 'game-changer'. At the World Economic Forum's Davos Agenda 25-29 January, 2021, the possible future labor market was discussed via the article [2]. This as a reflection on the situation that has arisen that the pandemic has contributed to, and future possible consequences of this. Similar discussions on the expansion of remote work, are covered, e.g., in [3] and [4], which in turn demands for new responsibilities at academia, with respect to adjustments in courses to meet challenges of future remote work. The contribution presents changes in teaching so that this corresponds well with a shift in the IT-industry towards remote working. New teaching elements are implemented in larger project courses, where the focus is on online-based development with modern tools for testing and integration. Process models that were previously seen as flexible and efficient, but have been dependent on physical meetings, are adjusted to be able to be performed distributed and remote. Studies of corresponding changes in the regional IT-industry are reported, as well as psycho-social consequences of the new forms of working.

Project-based educational forms are at the core of the CDIO concept, where students should be trained in contexts of complex enough tasks to prepare for the complexity of industry projects. Besides from fulfilling a project in itself, CDIO points out the importance of achieving integrated learning skills, including personal and interpersonal skills (CDIO Syllabus sections 2 and 3), where those are desired to meet the challenges of the working processes.

Projects in education moreover correspond to active learning, where students are encouraged to learn through solving the problems required to fulfill the goals of a project. Being active in the process of completing a project, does not only imply disciplinary training, but also training in achieving generic skills, such as experimentation, knowledge discovery, system thinking, teamwork, and communication. All in all, a conclusion is that student activities in project-based teaching and learning relate to all four sections of the CDIO Syllabus, and hence active learning will here contribute to integrated learning. Thus, activating students in project-based courses should have several positive values.

However, experiences show that one problem in project-based courses is that of activating a major part of a student group. Here, a common pattern is that some students are not contributing enough, resulting in other students covering up for them, or risking the whole project. Therefore, teaching efforts should be put on finding ways to widen the group of active students.

The project-based course Software Engineering 2, at Kristianstad University, Sweden, has undergone several years of improvements in order to, on one hand reduce the number of passive students, and on the other hand increase values of generic skills from the CDIO Syllabus. This paper will present development steps of that course. Methods, where some have been inspired from the Software Engineering industry, will be covered, and results of using those will be provided. A major result is that of increasing values of integrated learning, where this in itself contributes to the core of CDIO.

A purpose behind the United Nation’s Agenda 2030is that no one shall be left behind, which implies that supportfor vulnerable people shall be seen as clearly significant. Inthat context, assistive technologies serve purposes of improvingdisabled individuals’ inclusiveness and overall well-being. Thiscontribution covers ongoing experiments on techniquesdeveloped for Smart Homes, where the outcomes of suchdevelopments are targeted towards young people withfunctional disabilities, in order to provide them withindependence in their own living space.

The maturing of Artificial intelligence provides great opportunities for healthcare, but also comes with new challenges. For Artificial intelligence to be adequate a comprehensive analysis of the data is necessary along with testing the data in multiple algorithms to determine which algorithm is appropriate to use. In this study collection of data has been gathered that consists of patients who have either been readmitted or not readmitted to hospital within 30-days after being admitted. The data has then been analyzed and compared in different algorithms to determine the most appropriate algorithm to use.

The distribution of the Gamow–Teller (GT) β⁺ strength is estimated for both oblate and prolate Hartree–Fock (HF) local minima for even-even nuclei with 62 ≤ Z ≤ 70 near the proton drip line, using the quasiparticle Tamm–Dancoff approximation (TDA) based on a deformed HF + BCS calculation with Skyrme interaction. The prolate local minima and the oblate local minima lie energetically close for these nuclei. Almost all the GT strength lies below the ground state of the mother nuclei in this region. The GT strength distribution is not sensitive to deformation. For the isotones N = 74 and N = 76 close to the proton drip line the total GT strength is always larger for the prolate shape than the oblate shape. Approaching the proton drip line the total GT strength increases.

With the data logger DL141E it’s possible to continuously log measurement data from sensors up to 30k samples per second, and then transferring them to a mobile phone with Bluetooth technology. But this is by far too much sample data in a small time for a mobile phone with technical limitations to receive. That’s why only relevant measurement data should be mass logged to reduce the unnecessary data amount. Int his study a new approach is proposed where a specific and smaller amount of discrete pre-samples are logged in sequence. Every set of pre-samples is processed by comparing them to the user pre-defined trigger criterias. Met criterias will trigger logging of a massive set of samples on basis of only interesting signal deviations. The following trigger criterias are used: a specific signal level to cross, a specific signal direction, and both of these in combination with an amount of consecutive samples. The study provides an examination on how the signal processing method ”Lebesgue sampling” can be applied with the above criterias to achieve a god accuracy with reasonable processing time on mobile phones. This is observed using sensors with the most common signal types ramp and pulse in an environment where small noises and transients occur. The accuracy and the processing load are taken into account when estimating the efficiency of Lebesgue method and when estimating how many pre-samples per set might be sufficient. The implementation is written in Java Android platform and then integrated into a digital triggering module with Graphical User Interface (GUI).

Internet of Things facilitates interaction betweenhuman users and physical environment through the use ofelectronic sensors, wireless communication and cloudtechnology. In this paper, we demonstrate a scalableimplementation of Internet of Things in a lab environment. Aversatile set of sensors including cameras, power outlets andordinary temperature sensors are embedded in the physicalenvironment and connected to the cloud via local gateways. Datais processed locally and accessible via the cloud. A web servicehosted in the cloud enables remote two-way interaction betweenthe human users and the monitored physical environments.

To build student engagement and belonging early in the education is crucial for retention and student success. Since the COVID-19 outbreak, universities worldwide were forced to seek for alternative and complementary teaching approaches. In Sweden, universities adopted hybrid teaching since the end of the spring in 2020. The traditional face-to-face teaching facilitates immediate, real-time engagement with activities such as discussion and instant interaction between instructors and students and/or among students which encourages active learning, while an online teaching allows the students to watch videos and read requested materials many times, to complete the assignments at their suitable time and place, to enable good discussion and interaction via online forum and messaging. A hybrid approach combines the advantages of both face-to-face and online approaches. Research shows several challenges with online teaching, for examples, students´ engagement [1], communication between student(s) and teacher(s) [2], connection with/within the group, study groups, study buddies [3] as well as social engagement [4]. When a hybrid approach is applied to the First-Year courses due to the COVID-19, these challenges might have even more serious implications on the retention and success. This study explores two successful cases of how active learning, togetherness and engagement can be created among First-Year students. The study is based on two large introductory courses for the first-year students in Computer Science and in Business Administration at Kristianstad University, Sweden. Both programmes provide the Introduction courses for larger number of students (135 respective 195 students). Various methods and tools were used in the course design to engage students and create an active learning [5] environment using the hybrid approach. The results and experience were also presented. We experienced that students had actively participated in the arranged activities and the course passing rate was higher compared with the face-to-face teaching. The course evaluation also showed that the students were satisfied with course contents and various course activities.

This contribution addresses how two parallel courses during the last semester, where one is a final course for degree projects, have been synchronized. This is to give students a greater chance to complete the courses on time, and at the same time create a greater understanding of complicated problems.

The three-year Computer Engineering program at Kristianstad University, Sweden, has for several years suffered from difficulties during the third semester of the third year, where students most often tend to miss significant deadlines. This semester, which is the students' last, comprises a final degree project of 15 credits, which corresponds to half the work effort during the semester. Different approaches have been tested to give students the best possible conditions to complete the degree project on time. On the one hand, the degree project has been full-time during the latter part of the semester, with the first half consisting of other courses. On the other hand, the degree project has run in parallel with other courses throughout the semester. However, both approaches have resulted in situations where the students in many cases do not complete the degree project, and that other courses during the semester have also suffered.

A revision of the Computer Engineering program was made three years ago. The difficulties with the last semester have then also been considered. An effort has been made to develop synchronization opportunities between the courses during this semester. A new course, Systems Engineering, of 15 credits throughout the semester, has been developed, where the content of the course, as well as levels of learning objectives and examination forms have been considered to suit the parallel ongoing course for the degree project. Students have been offered opportunities to develop and analyze advanced systems where the course System Engineering has been based on the implementation of technical constructions, while the course for degree projects has been based on more theoretical and exploratory perspectives.

The students design the systems with both hardware and software. At the same time as they conduct literature studies, and investigate suitable analysis methods. Examples of systems include:

- Drones. Processors for these, as well as software to give these flying properties, are developed. Technical measurements are made, for analysis and evaluations. Measurements made are based, e.g., on the placement of sensors, and performance on technical protocols.

- Body Sensor Networks. Here, too, both hardware and software are designed to put the system into operation, and technical measurements are made to study at the usability of the system.

Synchronizing the courses has generally given good results, where the opportunity to complete the courses has increased drastically. A survey of the students' experiences has been made, and this has shown high satisfaction.

The program is clearly CDIO-oriented, which is also expressed in the education plan. The perception is that the synchronization of courses described in this contribution, and the effects of this, further increase the fundamental values ​​pointed out by the CDIO.

These days, healthcare applications on the Internet of Medical Things (IoMT) network have been growing to deal with different diseases via different sensors. These healthcare sensors are connecting to the various healthcare fog servers. The hospitals are geographically distributed and offer different services to the patients from any ubiquitous network. However, due to the full offloading of data to the insecure servers, two main challenges exist in the IoMT network. (i) Data security of workflows healthcare applications between different fog healthcare nodes. (ii) The cost-efficient and QoS efficient scheduling of healthcare applications in the IoMT system. This paper devises the Cost-Efficient Service Selection and Execution and Blockchain-Enabled Serverless Network for Internet of Medical Things system. The goal is to choose cost-efficient services and schedule all tasks based on their QoS and minimum execution cost. Simulation results show that the proposed outperform all existing schemes regarding data security, validation by 10%, and cost of application execution by 33% in IoMT.

Currently, the use of biosensor-enabled mobile healthcare workflow applications in mobile edge-cloud-enabled systems is increasing progressively. These applications are heavyweight and divided between a thin client mobile device and a thick server edge cloud for execution. Application partitioning is a mechanism in which applications are divided based on resource and energy parameters. However, existing application-partitioning schemes widely ignore security aspects for healthcare applications. This study devises a dynamic application-partitioning workload task-scheduling-secure (DAPWTS) algorithm framework that consists of different schemes, such as min-cut algorithm, searching node, energy-enabled scheduling, failure scheduling, and security schemes. The goal is to minimize the energy consumption of nodes and divide the application between local nodes and edge nodes by applying the secure min-cut algorithm. Furthermore, the study devises the secure-min-cut algorithm, which aims to migrate data between nodes in a secure form during application partitioning in the system. After partitioning the applications, the node-search algorithm searches optimally to run applications under their deadlines. The energy and failure schemes maintain the energy consumption of the nodes and the failure of the system. Simulation results show that DAPWTS outperforms existing baseline approaches by 30% in terms of energy consumption, deadline, and failure of applications in the system.

”Active Ageing – Personalised food and meal solutions for health and quality of life” (Aktivt åldrande – individuellt anpassade måltidslösningar för hälsa och livskvalitet hos äldre. Diarienr 2013-02780) is a project that aims to maintain the quality of life and autonomy of older persons, through individual and personalised meal solutions that fit their needs and requirements. The target group are primarily the age 75 or older. Five work packages are included in the project. This report describes the work package that had the scope of developing a concept for the ordering, distribution and delivery of meal to the elderly. Refrigeration technology and the cold-chain will play an important role in the concept by preserving the safety and quality of foods during its transportation to the elderly. Refrigeration technology and the cold-chain will also make it possible to prepare specific types of foods that meet the demand of the elderly. In particular for the elderly consumers that would like to eat at home and decrease their independency and overall quality of life. It is also important the value chain and concept for the business model must be flexible and taking into account needs from the elderly consumers at all stages, starting from ordering the meal, handling in the household and disposing of the packaging material. An interdisciplinary approach – combining knowledge of ICT (information and communications technology) – Technology, food quality, packaging, logistic, sensory, and waste/return systems for the food that is distributed is increasingly necessary. As the demand for food for the elderly is on the rise, the development of new products, models and services might be facilitated by collaborating with SMEs (micro, small and mediumsized enterprises) and other business partners interested in delivering solutions for the elderly consumers. The concept for the ordering, distribution and delivery of meal to the elderly developed in the project can be used by other end users and/or for other products and services.

This paper will discuss the future-ready university at the level of its future-ready teachers with regard to their teaching and learning practice for sustainable development. Academic institutions have both a role in promoting discussions of concern based on their specialized disciplines and a role in educating students to be future-ready to contribute to the society in a sustainable way. However, carrying out such roles with sufficient credibility may not be a matter of course for university teachers, who need sufficient insights into both sustainability per se and sustainable pedagogical teaching practice. This paper stresses the importance to the development of the future-ready university of cultivating sustainability, and provides an “educate the educators” project as an example.

The recent shift in machine learning towards the edge offers a new opportunity to realize intelligent applications on resource constrained Internet of Things (IoT) hardware. This paper presents a pre-trained Recurrent Neural Network (RNN) model optimized for an IoT device running on 8-bit microcontrollers. The device is used for data acquisition in a research on the impact of prolonged sedentary work on health. Our prediction model facilitates smart data transfer operations to reduce the energy consumption of the device. Application specific optimizations were applied to deploy and execute the pre-trained model on a device which has only 8 KB RAM size. Experiments show that the resulting edge intelligence can reduce the communication cost significantly, achieving subs-tantial saving in energy used by the IoT device.

Recycling is an important aspect of a sustainable society and depends to a large extent on consumers' willingness to provide the voluntary work needed to take the first critical step in many recycling systems. Based on a systematic review of articles on recycling behavior, this paper presents and discusses the findings in relation to Fogg's Beha vioral Model (FBM). Through the analysis of a corpus of 72 articles, the most important research contributions on recycling behavior are summarized and discussed. The choice of using FBM as a framework provides a new way of viewing previous research findings, and facilitates the identification of knowledge gaps. Based on the review, this work identifies and discusses four areas of potential interest for future research: the development of a comprehensive conceptual model for recycling behavior, the inclusion of triggers, the influence of persuasive technology, and the effect of different waste fractions. 

Context. Changes in drinking water treatment can affect the biofilm in the drinking water distribution system (DWDS) and enhanced monitoring is recommended to guarantee drinking water safety after substantial process modifications. Ultrafiltration was introduced in 2016 to the drinking water treatment plant Kvarnagården in Varberg, Sweden, achieving total removal of bacteria cells. This improved treatment led to the decision to remove the disinfectant monochloramine in 2020. 

Gap. Several studies compare the bacteria in different DWDS with and without disinfectants. To minimize complicating variables, this study examined the effects of the removal of the disinfectant in a single full scale DWDS.

Aim. This study describes flow cytometry (FCM) monitoring initiated to follow bacteria in the water of the DWDS during removal of monochloramine. 

Methods. Water samples from 15 points in the DWDS were analysed by standard FCM, with data analysis using custom scripts in R for data analysis.

Findings. By comparing FCM data to baselines, distinct changes in the bacterial community were observed following removal of monochloramine. Percentages of high nucleic acid bacteria (HNA) decreased at all sampling points, from 55 – 90 % to 45 – 60 %. Total cell counts (TCC) increased only in parts of the DWDS that had been exposed to monochloramine before the removal. Principal component analysis visualized the changes (Figure 1). The bacterial community at DWDS locations that used to differ largely regarding TCC and %HNA started to become more homogenous, emphasizing the value of FCM monitoring, as these same changes were not observed with traditional heterotrophic plate counts. The bacterial communities stabilized in summer 2020 and began to follow previously observed seasonal trends.

Utilization. This study demonstrated the application of FCM monitoring of the impact of monochloramine removal on bacterial water quality, and the importance of having robust baselines for multiple locations within a DWDS for comparison. 

This thesis uses one of Brain Computer Interface (BCI) products, NeuroSky headset, to design a prototype model to control window blind by using headset’s single channel electrode. Seven volunteers performed eight different exercises while the signal from the headset was recorded. The dataset was analyzed, and exercises with strongest power spectral density (PSD) were chosen to continue to work with. Matlabs spectrogram function was used to divide the signal in time segments, which were 0.25 seconds. One segment from each of these eight exercises was taken to form different combinations which were later classified.The classification result, while using two of proposed exercises (tasks) was successful with 97.0% accuracy computed by Nearest Neighbor classifier. Still, we continued to investigate if we could use three or four thoughts to create three or four commands. The result presented lower classification accuracy when using either 3 or 4 command thoughts with performance accuracy of 92% and 76% respectively.Thus, two or three exercises can be used for constructing two or three different commands.

The explosive growth of the Internet has fundamentally changed the global society. The emergence of concepts like service-oriented architecture (SOA), Software as a Service (SaaS), Platform as a Service (PaaS), Infrastructure as a Service (IaaS), Network as a Service (NaaS) and Cloud Computing in general has catalyzed the migration from the information-oriented Internet into an Internet of Services (IoS). This has opened up virtually unbounded possibilities for the creation of new and innovative services that facilitate business processes and improve the quality of life. However, this also calls for new approaches to ensuring quality and reliability of these services. The goal of this book chapter is to first analyze the state-of-the-art in the area of autonomous control for a reliable IoS and then to identify the main research challenges within it. A general background and high-level description of the current state of knowledge is presented. Then, for each of the three subareas, namely the autonomous management and real-time control, methods and tools for monitoring and service prediction, and smart pricing and competition in multi-domain systems, a brief general introduction and background are presented, and a list of key research challenges is formulated.

The broadcast nature of wireless communication makes it intrinsically vulnerable to eavesdropping attacks. This article suggests the using of secret spreading codes (i.e. only a legitimate receiver knows the spreading sequence) and artificial interference (i.e. by intentionally adding noise to the broadcast channel) on countering eavesdropping attacks. We have made a theoretical analysis on the potential performance degradation at the eavesdropper and at the legitimate receiver for a point-to-point wireless communication system using direct-sequence spread spectrum (DSSS) with coherent phase-shift keying (PSK) modulation. We have also proposed a lightweight non-cryptographic secret code generation scheme which leads to low correlation between the spreading codes used at the transmitter and at the eavesdropper. Simulation results confirms the good anti-eavesdropping performance on using the proposed non-cryptographic secret code generation scheme. Simulation results also conform with the theoretical analysis and motivate the using of artificial interference on countering eavesdropping attacks.

Internet of Things is evolving from the theory into reality. It is increasingly embedded into our daily lives to provide critical services such as pervasive healthcare and intelligent transportation systems, for which our privacy and security highly rely on the proper functioning of the products. This paper proposes a lightweight session-key establishment protocol that provides fundamental protection for the sensitive information flow in the Internet of Things. The new session-key establishment scheme utilizes the fact that time synchronization is a standard service in most of the Internet of Things products, and relies on loose time synchronization information to achieve secure and fast key agreement. Compared to traditional session-key establishment methods such as the one used by Wi-Fi, the new scheme is more lightweight and also allows a faster session establishment which can be critical for real-time services.

There is currently an ongoing digital transformation for sewage and wastewater management. By automating data collection and enabling remote monitoring, we will not only be able to save abundant human resources but also enabling predictive maintenance which is based on big data analytics. This paper presents a smart sewage water management system which is currently under development in southern Sweden. Real-time data can be collected from over 500 sensors which have already been partially deployed. Preliminary data analysis shows that we can build statistical data models for ground water, rainfall, and sewage water flows, and use those models for data forecast and anomaly detection.

This thesis fouces on Machine Learning predition techniques when calculating pedicatric drug dosing. The selected study drug used in this thesis is Cefaclor, an antibiotic prescribed to both children and adults.It compares the results of traditional dosing and ML prediction dosing. Then do anlysis of the result and get conclusion of ML performance.

Sigfox is one of the newly-emerging LPWAN (Low Power Wide Area Network) technologies aiming to provide power-efficient solutions to the world of IoT. This study presents a comparison between Sigfox Geolocation and GPS (Global Positioning System) in terms of power consumption and performance which includes three metrics: accuracy and precision, response rate and response time. This study includes for the first part a series of lab tests where Sigfox Geolocation and GPS were studied in a single Sleep, Wake up, Idle, Tx/Rx cycle. For the second part, field tests with different geographical parameters (altitude, population, mobility) were conducted. Results of lab tests show that power consumption difference between Sigfox and GPS is a linear function of Idle time. In field tests, GPS presents a far superior performance than Sigfox in all metrics and marginally better power efficiency for relatively short Idle interval. For both GPS and Sigfox, a correlation between power efficiency and performance was observed. Results show that GPS operates best in rural environments while Sigfox stands out in urban ones. Payload size was observed to affect Sigfox in both power consumption and performance while different transmission rates only affect power consumption but do not seem to impact the other metrics. A solution based on the outcome of this study is suggested for a freight-monitoring system where geolocation is handled by GPS and the coordinates transmitted via Sigfox. As an emerging technology under constant development, Sigfox Geolocation is expected to have improved performance in the near future.