https://www.mdu.se/

Study design: Triangulated mixed-methods validation study.

Objectives: To validate the Danish version of the Spinal Cord Lesion-related Coping Strategies Questionnaire (SCL-CSQ).

Setting: Community in Denmark.

Methods: Participants were invited via a patient organization and its specialized hospital. Eligibility criteria were having a spinal cord injury (SCI), being 18 years or older, and able to understand and respond in Danish. Quantitative data were collected to determine internal consistency and criterion validity of the three subscales of SCL-CSQ, i.e., acceptance, fighting spirit, and social reliance. The Three-Step Test-Interview approach was employed to determine whether items measured what they were intended to measure (i.e., construct validity based on response processes).

Results: The quantitative sample consisted of 107 participants, and the interview sample comprised 11 participants. The acceptance and fighting spirit subscales showed adequate internal consistency (Cronbach's alpha of 0.72 and 0.76 respectively) and satisfactory criterion validity (expected correlations with quality of life and depression). The social reliance subscale showed inadequate internal consistency (Cronbach's alpha of 0.58) and criterion validity. All fighting spirit items and all but one acceptance items were interpreted congruently by most participants. Conversely, two social reliance items were only interpreted congruently by 9 and 27%.

Conclusion: The acceptance and fighting spirit subscales of the Danish version of the SCL-CSQ showed good psychometric properties, while the social reliance subscale showed serious issues and should be revised. Researchers and clinicians are urged to reflect on these findings when revising the SCL-CSQ or adapting it to other languages, cultural contexts, and rehabilitation settings.

Bakgrund: Tidigare forskning visar att trycksår är smärtsamt och orsakar ett stort lidande för patienterna. Trycksår ger en ökad risk för infektioner och förlängd vårdtid vilket även leder till ökade kostnader för samhället. Trycksår som drabbar patienter inom vården räknas som en vårdskada och en av sjuksköterskans arbetsuppgifter är att förhindra vårdskador. Syfte: Var att beskriva sjuksköterskors erfarenheter av att vårda trycksårsförebyggande.Metod: En allmän litteraturöversikt enligt Friberg med totalt tio artiklar fördelat på fyra kvantitativa artiklar och sex kvalitativa artiklar. Samtliga artiklar analyserades utifrån likheter och skillnader i syfte, metod och resultat. Resultat: Det framträdde tre olika teman “Betydelsen av kunskap och kompetens”, ”Betydelsen av delaktighet och kommunikation”och “Betydelsen av arbetsmiljön och resursbrist”. Sjuksköterskorna hade även erfarenheter av att trycksårförebyggande åtgärder var prioriterat men att det var svårt att genomföra på grund av en hög arbetsbelastning och brist på vårdpersonalresurser. Sjuksköterskorna erfor även att brister i kommunikationen kunde leda till en ökad risk för trycksår. När sjuksköterskorna involverade patient och anhöriga i omvårdnaden ökades förståelsen för sjuksköterskans åtgärder och samarbetet underlättades. Slutsats: Sjuksköterskorna behöver mer kunskap och kompetens för att bli mer effektiva i det trycksårförebyggande arbetet. Tid-och resursbrist gjorde att sjuksköterskorna inte kunde prioritera trycksårsförebyggande åtgärder. Risken för trycksår minskade när sjuksköterskorna involverade patienten och anhöriga i omvårdnaden.

The purpose of this study is to gain an understanding of social workers intervention programs and how they approach perpetrators of intimate partner violence. The study is based on a qualitative methodology using semi-structured interviews to answer the studies aim. The data gathered through interviews were thematically analysed where the following themes emerged; perpetrators prerequisites for change, intervention programs development areas, mapping the treatment, networking and the perpetrators risk factors. The results were analyzed by scientific articles and theoretical frameworks: power, room for maneuver, mentalization and stigma. Our findings from the data indicate that perpetrators have a lack of insight and emotional management to violence where the social workers approach becomes essential for perpetrators progress. The interventions programs foundation is based on the perpetrators individual problem areas where the social worker adapts the treatment utilizing their own knowledge and expertise. Intervention treatment places a large emphasis on partner contact to motivate and support them during the perpetrators treatment. There is a cooperation with other authorities that needs further development to enable an increased exchange of knowledge and extended reach of perpetrators. The results also show that previous exposure in childhood is a predominant pattern to perpetrators alongside other problems.

Assessing the effectiveness of inflation targeting in promoting economic growth is crucial for policymakers in determining appropriate monetary policy measures. Given the lack of consensus regarding the impact of inflation targeting on economic growth, it prompts the question of whether inflation targeting indeed exerts a significant effect on economic growth.  This bachelor's thesis investigates the impact of inflation targeting on economic growth in developed countries over a 29-year period from 1991 to 2019. Using a methodology that accounts for both static and dynamic economic growth relationships, we analyze data from 45 developed countries, some employing inflation targeting and others not. Our findings suggest a positive effect of inflation targeting on economic growth in the static model, but autocorrelation issues necessitate the use of a dynamic model. The utilization of two distinct types of dummy variables yielded disparate outcomes compared to those obtained from the static model. Results from dynamic modeling indicate a slight negative effect of inflation targeting on economic growth. Together these results point to an inconclusive effect of inflation targeting on economic growth.

Objective: International collaboration in science has received increasing attention given emphases on relevance, generalizability, and impact of research. Implementation science (IS) is a growing discipline that aims to translate clinical research findings into health services. Research is needed to identify efficient and effective ways to foster international collaboration in IS. Concept-mapping (CM) was utilized with a targeted sample for preliminary exploration of fostering international collaboration. Concept-mapping is a mixed-method approach (qualitative/quantitative) particularly suited for identifying essential themes and action items to facilitate planning among diverse stakeholders. We sought to identify key factors likely to facilitate productive and rewarding international collaborations in implementation research. Results: We identified eleven dimensions: Strategic Planning; Practicality; Define Common Principles; Technological Tools for Collaboration; Funding; Disseminate Importance of Fostering International Collaboration in IS; Knowledge Sharing; Innovative & Adaptive Research; Training IS Researchers; Networking & Shared Identity; Facilitate Meetings. Strategic Planning and Funding were highest rated for importance and Strategic Planning and Networking and Shared Identity were rated most feasible to institute. Fostering international collaboration in IS can accelerate the efficiency, relevance, and generalizability of implementation research. Strategies should be developed and tested to improve international collaborations and engage junior and experienced investigators in collaborations advancing implementation science and practice. 

 Date:                                      2023-05-30  Level:                                     Bachelor/Master thesis in Business Administration, 15 cr   Institution:                            School of Business, Society and Engineering, Mälardalen                                                 University   Authors:                                Daniela Abada                Naemi Estifanos                                                                           (99/12/11)                                       (01/06/12)  Title:                                  The influence of sales commission on the motivation of                        telemarketers  Supervisor:                       Johan Grinbergs  Keywords:                         3 keywords  Research questions          1.How do reward systems affect employee motivation? 2.What are the consequences of this impact?  Purpose:                            The purpose of this research is to investigate the effect of sales commission as a reward and how it works as a motivational factor for employees   Method:                             Qualitative research method, face to face interviews. Thematic analysis and coding of data which is then analyzed in the analysis.  Conclusion:                       Sales commissions have an effect on employee motivation, possibly not in the long term as the majority of salespeople want to change workplaces due to the side effects that are the result of sales commissions such as stress, pressure and mental illness. Development opportunities are also motivating for salespeople, but not as extensive as the commission. The topic has divided thoughts between salespeople and the management team.

With the increase in food consumption, new ideas, and technologies began to be developed. Inaddition, the developments generated by Industry 4.0 technologies have started to be applied tothe entire manufacturing sector and the indoor farming industry, which is currently trending.Many studies and articles have been prepared on this subject, and the main goal of each study isto produce quality products and to ensure continuity in production to cover the nonendingincrease in demand.

This paper discusses how simulation technology, which is one of the industry 4.0 technologies,can be used in the production system development of the indoor farming industry. According tomany researchers, the biggest obstacle for the vertical farming industry is start-up cost, andsimulation technologies can be the solution for this since it allows future production systems tobe analyzed without any investment. To have a clear vision of how these technologies can beadapted in the indoor farming industry, this paper will find the answers to these questions, RQ1:How can simulation facilitate production system development and Industry 4.0 projects withinthe indoor farming industry? RQ2: What are the benefits and challenges when using simulationas a tool for production system development within the indoor farming industry? To reach thegoal of this paper, the case study method was used, and an indoor farming company was selectedto get more realistic data about the vertical farming system. BlueRedGold AB is a start-upcompany in the indoor farming industry, and it has a huge growth potential since they aim totransform its current production lines to be fully automated. Many articles and studies were usedto approach the solution of the research questions from a more technical and academic point ofview, and the analysis of these articles was carried out with the structured literature review method.

After conducting this research, answers have been obtained for the research questions. Theauthors' solution to the layout issue, one of the case company's main challenges as indicated inthis study, was developed after extensive simulation model testing. As highlighted in this paper,it has been stated by many researchers, there are several simulation approaches to follow.However, the authors have developed a simulation modeling approach to be followed in theindoor vertical farming industry to overcome the complexity of these systems as well as thesimulation program complexity. In addition, several challenges and benefits have beenhighlighted in this paper such as the lack of ready models of the equipment used in indoorfarming which requires a knowledge of a programing language to overcome. Finally, despitechallenges, simulation technology can provide an applicable solution for production systemproblems of vertical farming companies/organizations to obtain continuous improvementphilosophy which is the main principle of Lean thinking. The generated simulation model in thisthesis project was successfully implemented, demonstrating how this technology might be aneffective solution for complex production systems as in the indoor farming sector. 

Problem: The goal of a software product line is to aid quick and quality delivery of software products, sharing common features. Effectively achieving the above-mentioned goals requires reuse analysis of the product line features. Existing requirements reuse analysis approaches are not focused on recommending product line features, that can be reused to realize new customer requirements. Hypothesis: Given that the customer requirements are linked to product line features' description satisfying them: then the customer requirements can be clustered based on patterns and similarities, preserving the historic reuse information. New customer requirements can be evaluated against existing customer requirements and reuse of product line features can be recommended. Contributions: We treated the problem of feature reuse analysis as a text classification problem at the requirements-level. We use Natural Language Processing and clustering to recommend reuse of features based on similarities and historic reuse information. The recommendations can be used to realize new customer requirements.

[Context and Motivation] Content-based recommender systems for requirements are typically built on the assumption that similar requirements can be used as proxies to retrieve similar software. When a new requirement is proposed by a stakeholder, natural language processing (NLP)-based similarity metrics can be exploited to retrieve existing requirements, and in turn, identify previously developed code. [Question/problem] Several NLP approaches for similarity computation are available, and there is little empirical evidence on the adoption of an effective technique in recommender systems specifically oriented to requirements-based code reuse. [Principal ideas/results] This study compares different state-of-the-art NLP approaches and correlates the similarity among requirements with the similarity of their source code. The evaluation is conducted on real-world requirements from two industrial projects in the railway domain. Results show that requirements similarity computed with the traditional tf-idf approach has the highest correlation with the actual software similarity in the considered context. Furthermore, results indicate a moderate positive correlation with Spearman's rank correlation coefficient of more than 0.5. [Contribution] Our work is among the first ones to explore the relationship between requirements similarity and software similarity. In addition, we also identify a suitable approach for computing requirements similarity that reflects software similarity well in an industrial context. This can be useful not only in recommender systems but also in other requirements engineering tasks in which similarity computation is relevant, such as tracing and categorization.

Recommender systems for requirements are typically built on the assumption that similar requirements can be used as proxies to retrieve similar software. When a stakeholder proposes a new requirement, natural language processing (NLP)-based similarity metrics can be exploited to retrieve existing requirements, and in turn, identify previously developed code. Several NLP approaches for similarity computation between requirements are available. However, there is little empirical evidence on their effectiveness for code retrieval. This study compares different NLP approaches, from lexical ones to semantic, deep-learning techniques, and correlates the similarity among requirements with the similarity of their associated software. The evaluation is conducted on real-world requirements from two industrial projects from a railway company. Specifically, the most similar pairs of requirements across two industrial projects are automatically identified using six language models. Then, the trace links between requirements and software are used to identify the software pairs associated with each requirements pair. The software similarity between pairs is then automatically computed with JPLag. Finally, the correlation between requirements similarity and software similarity is evaluated to see which language model shows the highest correlation and is thus more appropriate for code retrieval. In addition, we perform a focus group with members of the company to collect qualitative data. Results show a moderately positive correlation between requirements similarity and software similarity, with the pre-trained deep learning-based BERT language model with preprocessing outperforming the other models. Practitioners confirm that requirements similarity is generally regarded as a proxy for software similarity. However, they also highlight that additional aspect comes into play when deciding software reuse, e.g., domain/project knowledge, information coming from test cases, and trace links. Our work is among the first ones to explore the relationship between requirements and software similarity from a quantitative and qualitative standpoint. This can be useful not only in recommender systems but also in other requirements engineering tasks in which similarity computation is relevant, such as tracing and change impact analysis.

Requirements prioritization plays an important role in driving project success during software development. Literature reveals that existing requirements prioritization approaches ignore vital factors such as interdependency between requirements. Existing requirements prioritization approaches are also generally time-consuming and involve substantial manual effort. Besides, these approaches show substantial limitations in terms of the number of requirements under consideration. There is some evidence suggesting that models could have a useful role in the analysis of requirements interdependency and their visualization, contributing towards the improvement of the overall requirements prioritization process. However, to date, just a handful of studies are focused on model-based strategies for requirements prioritization, considering only conflict-free functional requirements. This paper uses a meta-model-based approach to help the requirements analyst to model the requirements, stakeholders, and inter-dependencies between requirements. The model instance is then processed by our modified PageRank algorithm to prioritize the given requirements. An experiment was conducted, comparing our modified PageRank algorithm’s efficiency and accuracy with five existing requirements prioritization methods. Besides, we also compared our results with a baseline prioritized list of 104 requirements prepared by 28 graduate students. Our results show that our modified PageRank algorithm was able to prioritize the requirements more effectively and efficiently than the other prioritization methods.

The software system controlling a train is typically deployed on various hardware architectures and is required to process various signals across those deployments. Increases of such customization scenarios, as well as the needed adherence of the software to various safety standards in different application domains, has led to the adoption of product line engineering within the railway domain. This paper explores the current state-of-practice of software product line development within a team developing industrial embedded software for a train propulsion control system. Evidence is collected by means of a focus group session with several engineers and through inspection of archival data. We report several benefits and challenges experienced during product line adoption and deployment. Furthermore, we identify and discuss research opportunities, focusing in particular on the areas of product line evolution and test automation.

Categorizing existing test specifications can provide insights on coverage of the test suite to extra-functional properties. Manual approaches for test categorization can be time-consuming and prone to error. In this short paper, we propose a semi-automated approach for semantic keywords-based textual test categorization for extra-functional properties. The approach is the first step towards coverage-based test case selection based on extra-functional properties. We report a preliminary evaluation of industrial data for test categorization for safety aspects. Results show that keyword-based approaches can be used to categorize tests for extra-functional properties and can be improved by considering contextual information of keywords.

This tutorial explores requirements-based reuse recommendation for product line assets in the context of clone-and-own product lines.

Software product lines (SPLs) are based on reuse rationale to aid quick and quality delivery of complex products at scale. Deriving a new product from a product line requires reuse analysis to avoid redundancy and support a high degree of assets reuse. In this paper, we propose and evaluate automated support for recommending SPL assets that can be reused to realize new customer requirements. Using the existing customer requirements as input, the approach applies natural language processing and clustering to generate reuse recommendations for unseen customer requirements in new projects. The approach is evaluated both quantitatively and qualitatively in the railway industry. Results show that our approach can recommend reuse with 74% accuracy and 57.4% exact match. The evaluation further indicates that the recommendations are relevant to engineers and can support the product derivation and feasibility analysis phase of the projects. The results encourage further study on automated reuse analysis on other levels of abstractions.

Denna studie undersöker hur lärare beskriver att de arbetar för att främja läsförståelseförmågan hos elever som talar svenska som andraspråk i årskurs f-3. För att undersöka detta genomförs en tematisk analys av sex semistrukturerade intervjuer med lärare från olika kommuner som arbetar i skolor med många andraspråkselever. 

Resultatet pekar på att lärarna arbetar strukturerat med att undervisa elever om lässtrategier som kan användas för att förstå en text enligt undervisningsmodellen Reciprocal teaching. Den vanligaste strategin som används enligt lärarna är att reda ut oklarheter, då andraspråkselever ofta har ett bristande ordförråd. Strategierna summera, förutspå och ställa frågor används också men i mindre utsträckning. 

Resultatet visar dessutom att lärarna är positiva till att använda elevernas modersmål i undervisningen för att främja deras läsförståelse. Deras resonemang pekar på att de använder en del av de strategier som föreslås i ramverket pedagogiskt transspråkande, dock ofta på ett spontant och oplanerat sätt.

Slutsatsen blir således att lärare behöver mer kunskap och utbildning om hur elevernas modersmål kan användas som resurser. Detta för att underlätta för dem att utforma mer planerade, medvetna och varierade arbetssätt och komma bort från den spontana tillämpningen av pedagogiskt transspråkande som för tillfället ofta sker. Studien understryker att strategier för att främja andraspråkselevers läsförståelse i svenska inte är något som enbart SVA-lärare behöver förhålla sig till, utan en viktig fråga för alla lärare i skolan.

Syftet med studien är att undersöka hur lärare resonerar didaktiskt kring SO-undervisning i årskurs f-3 i demokratifrågor och vilka möjligheter och utmaningar som kan finnas i den undervisningen.

För att kunna besvara detta syfte har semistrukturerade intervjuer genomförts med fyra informanter med varierande yrkeserfarenhet och aktuella undervisningsårskurser.

Resultat för studien visar att informanterna har bra koll på varför det är viktigt att undervisa om demokrati, hur undervisningen ska genomföras och vad den ska innehålla. För att kunna uppnå skolans demokratiuppdrag behöver demokratiundervisningen genomsyra hela skolans verksamhet, utgå ifrån elevernas individuella förutsättningar, behov, intressen och erfarenheter, göra eleverna delaktiga i utformandet av sin utbildning och få de att inse att deras röst är betydelsefull. Kommunikation är a och o i demokratiundervisningen och ska ske både med och mellan elever, kollegor och vårdnadshavare.

Studiens syfte var att ta reda på hur förskollärare arbetar med nationella minoriteter och ta reda på vilka påverkansfaktorer som inverkar på undervisningen om de nationella minoriteterna. Studien är en flermetods-studie kring ett arbetsmaterial som skapats för förskolans arbete med minoriteter (Sametinget,2018), förskollärare har genomfört semistrukturerade enkäter och semistrukturerade intervjuer och frågorna har berört förskollärares resonemang kring arbetet med nationella minoriteter utifrån arbetsmaterialet. I analysen och diskussionen framgår påverkansfaktorer och förskollärares tolkningar och planerade undervisningar blir centrala. Vår forskning har närmat sig svaret på vad som är påverkansfaktorer för förskollärares undervisning om nationella minoriteter. Studien bidrar till forskningen kring förskolepedagogik, med fokus på förskollärares behov i sitt arbete med barn om och med nationella minoriteter. Det erbjuder insikter om hur man bäst kan stödja dessa barns utveckling och främjar en mer inkluderande utbildning. 

Sinusitis, a common disease of the maxillary sinus, is initially managed with saline solution and medication, resulting in the resolution of symptoms within a few days in most cases. However, Functional Endoscopic Sinus Surgeries are recommended if pharmacological treatments prove ineffective. This research aims to investigate the effects of maxillary sinus surgery on the airflow field, pressure distribution within the nasal cavity, and overall ventilation. This study utilized a three-dimensional realistic nasal cavity model constructed from CT images of a healthy adult. Virtual surgery including uncinectomy with Middle Meatal Antrostomy, two standard procedures performed during such surgeries, was performed on the model under the supervision of a clinical specialist. Two replicas representing pre- and post-operative cases were created using 3D printing for experimental purposes. Various breathing rates ranging from 3.8 to 42.6 L/min were examined through experimental and numerical simulations. To ensure the accuracy of the numerical simulations, the results were compared to measured pressure data, showing a reasonable agreement between the two. The findings demonstrate that uncinectomy and Middle Meatal Antrostomy significantly enhance the ventilation of the maxillary sinuses. Furthermore, increasing inspiratory rates leads to further improvements in ventilation. The static pressure distribution within the maxillary sinuses remains relatively uniform, except in regions close to the sinus ostium, even after surgical intervention.

The connection between objects and information exchange has been possible in recent years, with the advent of the Internet of Things (IoT) in different industries. We can meet different requirements in each industry utilizing this feature. Intelligent transportation uses the Internet of Vehicles (IoV) as a solution for communication among vehicles. It improves traffic management applications and services to guarantee safety on roads. We categorize services, applications, and architectures and propose a taxonomy for IoV. Then, we study open issues and challenges for future works. We highlighted applications and services due to drivers' requirements and nonfunctional requirements, considering the qualitative characteristic. This paper summarizes the current state of the IoV in architectures, services, and applications. It can be a start view to provide the solutions for challenges in traffic management in cities. The present study is beneficial for smart city developments and management. According to this paper's result, the services and applications evaluate performance with 34% frequency, safety and data accuracy, and security with a 13% frequency in selected papers. These measurements are essential due to the IoV characteristics such as real-time operation, accident avoidance in applications, and complicated user data management. 

Over the years, a range of Internet of Vehicles services has emerged, along with improved quality parameters. However, the field still faces several limitations, including resource constraints and the time response requirement. This paper extracts cost, energy, processing power, service management, and resource allocation parameters. Mathematical equations are then defined based on these parameters. To simplify the process complexity and ensure scalability, we propose an algorithm that uses the genetic algorithm for fault and cost management during resource allocation to services. The main concept is to pick resources for services using a genetic algorithm. We discuss the processing and energy costs associated with this function, which is the algorithm's objective function and is created to optimize cost. Our approach goes beyond the conventional genetic algorithm in two stages. In the first step, services are prioritized, and resources are allocated in accordance with those priorities; in the second step, load balancing in message transmission paths is ensured, and message failures are avoided. The algorithm's performance is evaluated using various parameters, and it was shown to outperform other metaheuristic algorithms like the classic genetic algorithm, particle swarm, and mathematical models. Different scenarios with various nodes and service variables are defined in various system states, including fault occurrences to various percentages of 10, 20, and 30. To compare methods, we consider different parameters, the most significant being performance success rate. Moreover, the cost optimization has a good convergence after iterations, and the rate of improvement in the big scenario has slowed down after 150 iterations. Besides, it provides acceptable performance in response time for services.

Industrial cybersecurity has risen as an important topic of research nowadays. The heavy connectivity by the Internet of Things (IoT) and the growth of cyberattacks against industrial assets cause this risen and attract attention to the cybersecurity field. While fostering current software applications and use-cases, the ubiquitous access to the Internet has also exposed operational technologies to new and challenging security threats that need to be addressed. As the number of attacks increases, their visibility decreases. An attack can modify the Cyber-Physical Systems (CPSs) quality to avoid proper quality assessment. They can disrupt the system design process and adversely affect a product’s design purpose. This working progress paper presents our approach to modeling, analyzing, and mitigating cyberattacks in CPS. We model the normal behavior of the application as well as cyberattacks with the help of Microsoft Security Development Lifecycle (SDL) and threat modeling approach (STRIDE). Then verify the application and attacks model using a model checking tool and propose mitigation strategies to decrease the risk of vulnerabilities. The results can be used to improve the system design to overcome the vulnerabilities.

This article presents a runtime verification tool for embedded software executing under the open source real-time operating system FreeRTOS. The tool detects and diagnoses concurrency bugs such as deadlock, starvation, and suspension based-locking. The tool finds concurrency bugs at runtime without debugging and tracing the source code. The tool uses the Tracealyzer tool for logging relevant events. Analysing the logs, our tool can detect the concurrency bugs by applying algorithms for diagnosing each concurrency bug type individually. In this paper, we present the implementation of the tool, as well as its functional architecture, together with illustration of its use. The tool can be used during program testing to gain interesting information about embedded software executions. We present initial results of running the tool on some classical bug examples running on an AVR 32-bit board SAM4S. 

Concurrent programming puts demands on software debugging and testing, as concurrent software may exhibit problems not present in sequential software, e.g., deadlocks and race conditions. In aiming to increase efficiency and effectiveness of debugging and bug-fixing for concurrent software, a deep understanding of concurrency bugs, their frequency and fixing-times would be helpful. Similarly, to design effective tools and techniques for testing and debugging concurrent software, understanding the differences between non-concurrency and concurrency bugs in real-word software would be useful. This paper presents an empirical study focusing on understanding the differences and similarities between concurrency bugs and other bugs, as well as the differences among various concurrency bug types in terms of their severity and their fixing time, and reproducibility. Our basis is a comprehensive analysis of bug reports covering several generations of five open source software projects. The analysis involves a total of 11860 bug reports from the last decade, including 351 reports related to concurrency bugs. We found that concurrency bugs are different from other bugs in terms of their fixing time and severity while they are similar in terms of reproducibility. Our findings shed light on concurrency bugs and could thereby influence future design and development of concurrent software, their debugging and testing, as well as related tools.

Multicore hardware development increases the popularity of parallel and multicore software, while testing and debugging the software become more difficult, frustrating and costly. Among all types of software bugs, concurrency bugs are both important and troublesome. This type of bugs is increasingly becoming an issue, particularly due to the growing prevalence of multicore hardware. Suspension-based-locking bug is one type of concurrency bugs. This position paper proposes a model based on runtime verification and reflection technique in the context of multicore and parallel software to monitor and detect suspension-based-locking bugs. The model is not only able to detect faults, but also diagnose and even repair them. The model is composed of four layers: Logging, Monitoring, Suspension Bug Diagnosis and Mitigation. The logging layer will observe the events and save them into a file system. The monitoring layer will detect the presents of bugs in the software. The suspension bug diagnosis will identify Suspension bugs by comparing the captured data with the suspension bug properties. Finally, the mitigation layer will reconfigure the software to mitigate the suspension bugs. A functional architecture of a runtime verification tool is also proposed in this paper. This architecture is based on the proposed model and is comprised of different modules. 

Recent advances in artificial intelligence and machine learning (ML) led to effective methods and tools for analyzing the human behavior. Human Activity Recognition (HAR) is one of the fields that has seen an explosive research interest among the ML community due to its wide range of applications. HAR is one of the most helpful technology tools to support the elderly’s daily life and to help people suffering from cognitive disorders, Parkinson’s disease, dementia, etc. It is also very useful in areas such as transportation, robotics and sports. Deep learning (DL) is a branch of ML based on complex Artificial Neural Networks (ANNs) that has demonstrated a high level of accuracy and performance in HAR. Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) are two types of DL models widely used in the recent years to address the HAR problem. The purpose of this paper is to investigate the effectiveness of their integration in recognizing daily activities, e.g., walking. We analyze four hybrid models that integrate CNNs with four powerful RNNs, i.e., LSTMs, BiLSTMs, GRUs and BiGRUs. The outcomes of our experiments on the PAMAP2 dataset indicate that our proposed hybrid models achieve an outstanding level of performance with respect to several indicative measures, e.g., F-score, accuracy, sensitivity, and specificity. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.

Pattern recognition algorithms have been widely used to map surface electromyographic signals to target movements as a source for prosthetic control. However, most investigations have been conducted offline by performing the analysis on pre-recorded datasets. While real-time data analysis (i.e., classification when new data becomes available, with limits on latency under 200-300 milliseconds) plays an important role in the control of prosthetics, less knowledge has been gained with respect to real-time performance. Recent literature has underscored the differences between offline classification accuracy, the most common performance metric, and the usability of upper limb prostheses. Therefore, a comparative offline and real-time performance analysis between common algorithms had yet to be performed. In this study, we investigated the offline and real-time performance of nine different classification algorithms, decoding ten individual hand and wrist movements. Surface myoelectric signals were recorded from fifteen able-bodied subjects while performing the ten movements. The offline decoding demonstrated that linear discriminant analysis (LDA) and maximum likelihood estimation (MLE) significantly (p < 0.05) outperformed other classifiers, with an average classification accuracy of above 97%. On the other hand, the real-time investigation revealed that, in addition to the LDA and MLE, multilayer perceptron also outperformed the other algorithms and achieved a classification accuracy and completion rate of above 68% and 69%, respectively.

We study Hilbert functions, Lefschetz properties, and Jordan type of Artinian Gorenstein algebras associated to Perazzo hypersurfaces in projective space. The main focus lies on Perazzo threefolds, for which we prove that the Hilbert functions are always unimodal. Further we prove that the Hilbert function determines whether the algebra is weak Lefschetz, and we characterize those Hilbert functions for which the weak Lefschetz property holds. By example, we verify that the Hilbert functions of Perazzo fourfolds are not always unimodal. In the particular case of Perazzo threefolds with the smallest possible Hilbert function, we give a description of the possible Jordan types for multiplication by any linear form.

Purpose: This essay aims to examine the organizational and technical fire protection for the new emergency hospital in Västerås and analyze what measures are needed to ensure a safe hospital. By involving the staff and ensuring that they have the necessary knowledge and participation, one can ensure a safe care environment for the patients and create the conditions for dealing with potential dangers in an effective manner. Method: To achieve the objectives of the study the method involved carefully selected interviews with various professional roles possessing expertise in fire risks. Through these interviews, the aim was to attain a more comprehensive depiction of the results. In addition to the interviews, a versatile approach was adopted, encompassing surveys, site visits, literature reviews, and meticulous calculations of airlocks. Furthermore, data collection was augmented by utilizing documents from the Västmanland Region. Result: The outcome of the study showed a lack of knowledge, experience and ability to act when it comes to evacuation situations. The building was designed with fire safety in mind. Despite this, the opportunity to implement measures to further improve safety was identified. With regard to the building's fire protection, the possibility of implementing airlocks was identified to supplement and strengthen fire protection in departments where there were fewer fire cells. Conclusion: l the implementation of airlocks is important to improve the evacuation situation and safety. Regular evacuation drills should be prioritized to increase staff preparation and confidence. Measures such as clear fire separations, reliable fire alarm systems, automatic extinguishing systems and well-designed emergency escape routes need to be implemented to increase robustness and improve fire protection. This requires cooperation with fire safety experts. Airlocks can streamline the evacuation process for bedridden patients and staff, which is crucial for quick and safe evacuation in emergency situations. 

Non-invasive monitoring of cardiovascular health through photoplethysmography (PPG) waveforms has emerged as a crucial area of research. The Windkessel 4-Element (WK4) model is a mathematical approach used to estimate key physiological parameters related to cardiovascular health, including arterial compliance, peripheral resistance, inertance, and total arterial resistance. This study aimed to evaluate key physiological parameters associated with cardiovascular health using the WK4 model, leveraging real-life PPG waveform data obtained from volunteers across three distinct age groups. To achieve this, an algorithm was developed to automatically determine optimal parameter values for each volunteer. The results revealed a mean correlation coefficient of 0.96 between the automatically generated waveforms by the algorithm and the actual real-life PPG waveforms, indicating robust agreement. Notably, only the total arterial resistance parameter exhibited significant differences among the age groups, suggesting that the algorithm holds promise for detecting agerelated changes in cardiovascular health. These findings emphasize the potential for the development of a non-invasive tool to assess cardiovascular health status and enhance healthcare outcomes. Furthermore, they underscore the capability of the developed algorithm as a non-invasive means to evaluate various aspects of cardiovascular physiology. Additionally, the versatility of this algorithm opens doors for its application in educational settings, promoting knowledge advancement, empowering research endeavors, and facilitating advancements in the field.

Accurate bladder monitoring is critical in the management of conditions such as urinary incontinence, voiding dysfunction, and spinal cord injuries. Electrical bioimpedance (EBI) has emerged as a cost-effective and non-invasive approach to monitoring bladder activity in daily life, with particular relevance to patient groups who require measurement of bladder urine volume (BUV) to prevent urinary leakage. However, the impact of activities in daily living (ADLs) on EBI measurements remains incompletely characterized. In this study, we investigated the impact of normal ADLs such as sitting, standing, and walking on EBI measurements using the MAX30009evkit system with four electrodes placed on the lower abdominal area. We developed an algorithm to identify artifacts caused by the different activities from the EBI signals. Our findings demonstrate that various physical activities clearly affected the EBI measurements, indicating the necessity of considering them during bladder monitoring with EBI technology performed during physical activity (or normal ADLs). We also observed that several specific activities could be distinguished based on their impedance values and waveform shapes. Thus, our results provide a better understanding of the impact of physical activity on EBI measurements and highlight the importance of considering such physical activities during EBI measurements in order to enhance the reliability and effectiveness of EBI technology for bladder monitoring.

Bladder monitoring, including urinary incontinence management and bladder urinary volume monitoring, is a vital part of urological care. Urinary incontinence is a common medical condition affecting the quality of life of more than 420 million people worldwide, and bladder urinary volume is an important indicator to evaluate the function and health of the bladder. Previous studies on non-invasive techniques for urinary incontinence management technology, bladder activity and bladder urine volume monitoring have been conducted. This scoping review outlines the prevalence of bladder monitoring with a focus on recent developments in smart incontinence care wearable devices and the latest technologies for non-invasive bladder urine volume monitoring using ultrasound, optical and electrical bioimpedance techniques. The results found are promising and their application will improve the well-being of the population suffering from neurogenic dysfunction of the bladder and the management of urinary incontinence. The latest research advances in bladder urinary volume monitoring and urinary incontinence management have significantly improved existing market products and solutions and will enable the development of more effective future solutions.

Development in the field of smart wearable products for monitoring daily life health status is beginning to spread in society. Textile electronic methods are improving and facilitating the manufacturing of sensorized garments. This paper evaluates a newly developed t-shirt incorporating electronic sensing and interconnecting elements integrated into the T-shirt with textile-friendly techniques sensorized with a Movesense device for monitoring ECG and HR and activity. The measurement results obtained from the t-shirt are entirely in agreement with the measurements obtained with other textile garments and encourage us for a near future where wearable sensors are just textile garments sensorized seamlessly without suboptimal textile-electronic integrated elements.

The development of smart wearable solutions for monitoring daily life health status is increasingly popular, with chest straps and wristbands being predominant. This study introduces a novel sensorized T-shirt design with textile electrodes connected via a knitting technique to a Movesense device. We aimed to investigate the impact of stationary and movement actions on electrocardiography (ECG) and heart rate (HR) measurements using our sensorized T-shirt. Various activities of daily living (ADLs), including sitting, standing, walking, and mopping, were evaluated by comparing our T-shirt with a commercial chest strap. Our findings demonstrate measurement equivalence across ADLs, regardless of the sensing approach. By comparing ECG and HR measurements, we gained valuable insights into the influence of physical activity on sensorized T-shirt development for monitoring. Notably, the ECG signals exhibited remarkable similarity between our sensorized T-shirt and the chest strap, with closely aligned HR distributions during both stationary and movement actions. The average mean absolute percentage error was below 3%, affirming the agreement between the two solutions. These findings underscore the robustness and accuracy of our sensorized T-shirt in monitoring ECG and HR during diverse ADLs, emphasizing the significance of considering physical activity in cardiovascular monitoring research and the development of personal health applications.

This paper presents a grid-connected double storage system (DSS) consisting of pumped-storage hydropower (PSH) and battery. The system is supplied by photovoltaics and wind turbines. In the proposed hybrid system, batteries absorb excess renewable energy that cannot be stored in PSH and they cover loads that cannot be supplied from the water turbine. To improve the system performance, a novel energy management strategy for the DSS is proposed. The strategy is based on an optimized factor that governs the charging process of the DSS. The problem of the optimal system design is solved by a non-dominated sorting genetic algorithm (NSGA-II). The multi-objective function considers simultaneously the minimal investment cost and minimal CO2 emissions. A comparative study of photovoltaic/wind/pumped-storage hydropower and photovoltaic/wind/double storage system is performed to show the effectiveness of the proposed strategy in terms of system economic and environmental performance. The considered location of the PSH station is on Attaqa Mountain at Suez (Egypt). The results indicate the effectiveness of the proposed energy management strategy for the storage system from economic and environmental perspectives. Coupling the battery with the PSH reduces the electricity cost by 22.2% and results in minimal energy exchange with the national grid (5% of the annual demand). A sensitivity analysis shows the largest variation of the electricity cost with changing the capital cost of the solar and wind generators. Also, it is observed that when the load increases, the optimal size of the system components increases, but it isn't proportional with the demand increase as could be expected. (C) 2019 Elsevier Ltd. All rights reserved.

Most construction companies want to deliver the best possible results for their customers while spending the least possible resources. Nevertheless, the construction industry has traditionally been full of unnecessary inefficiency regarding workflows. One of the most successful methods to prevent inefficiency workflow is lean construction. Lean construction consists of various methods that aim to streamline workflow as optimally as possible. Purpose: The purpose of the degree project is to use specific lean methods and tools to identify different waste and be able to use them to reduce downtime of a studied construction project. Method: A case study has been carried out where the project Heby - care homes has been studied. To gather more information a survey study has been done. To gather even further information about the project an interview was conducted with a person who has a leading role. Results: The result shows a analysis of the survey and the interviewe answers. It also includs working methods, transparency and waste minimization. Furthermore it includs solutions like identify problems, create order and structure, standardize and work on improvements. Conclusions: The conclusion that can be drawn is that standardizations in the form of checklists and guides need to be in each project. More openness and to review your chosen forms of agreement. To have a more dynamic working group that strives to achieve common goals and continuous improvements. These are the most important aspects of making a project effective.

The aim of the study is to assist the management of Ica Skrapan Västerås with promotional suggestions of innovation and creativity, as well as to analyze and address the current lack of engagement and motivation of the employees working in the grocery store. A qualitative and semi- structured research method has been conducted to collect data for the study. Using the data collected, the study has been able to analyze the current lack of engagement and motivation to see if innovative and creative suggestions can improve employee’s existence at work. The results have shown that both the management has a willingness to implement their employees ‘views, and the employees have a willingness to be involved in more creative and innovative proposals within the organization.

In today's modern work environment, the demand for innovation and creativity is crucial for the survival and success of organizations. The role of leadership is central in creating an environment that promotes creativity and idea generation among employees. This study aims to investigate the role of transformational leadership in creating an environment that promotes creativity and idea generation among employees in technology companies. The method section carefully describes the research methodology and the selection of respondents, as well as the conduct of the interviews and the J&D test. In the study, three different respondent groups were interviewed: two employees, two managers and an informant, in order to answer the research question. The results of these interviews provided insights into how transformative leadership promotes creativity and idea generation in the workplace. Furthermore, issues related to research ethics and how these have been handled and taken into account during the research process are also discussed. In the theory section, the concept of leadership is defined and three different leadership styles are discussed: transformative, transactional and servant leadership. Furthermore, the concept of creativity is explored, including individual, group and organizational creativity, as well as innovation and idea generation. In the empirical section, the results of the interviews and the J&D test are presented. The interviews have been analyzed using the thematic analysis method and organized under different themes, each of which is linked to a specific overarching theme. The analysis from the interviews shows that transformative leaders create an environment that inspires and engages employees, while challenging traditional thought patterns and encouraging divergent thinking. The results of the J&D test provide further insight into the creative abilities of the participants and show that these technology companies with a transformative leadership have a favorable work environment for individual creativity and idea generation. The conclusion is that transformative leadership is crucial for fostering creativity and idea generation within technology companies, and such a leadership style is a key factor for successful innovation processes.

Elektrifiering i transportsektorn och Rysslands anfallskrig mot Ukraina är de främsta bidragande orsak till de nuvarande höga energipriserna. Ryssland använder energi som ett politiskt vapen genom att minska gasflöde vilket har resulterat i höga gaspriser i Europa. Dessutom går elektrifieringen av transportsektorn i hög varv i många europiska länder vilket också bidrar till att energikrisen på den europeiska energimarknaden höjs ännu mer. 

Merparten av den energi som används idag kommer från fossila bränslen som bidrar till koldioxidutsläpp som påverkar miljön negativt. Något måste förändras för att minska utsläppen av växthusgaser och beroendet av fossila energikällor. En hållbar och miljövänlig lösning är att investera i solenergi som producerar förnybar energikälla. Med rätt teknik kan man enkelt installera villor och bostäder med solceller och solfångare och för att kunna producera el och värme. Syftet med detta examensarbete är att undersöka om ett solcellssystem i en villa kan tillgodose bostadens energibehov under olika årstider, och även att ta redo på om investeringen för solceller är lönsam. 

Arbetsmetoden bygger på beräkningar, simulering och litteraturstudier för att nå ett tillförlitligt resultat. Resultatet redovisar villans totala elförbrukning i 2023 samt solcellernas energiproduktion. Genom att analysera resultatet visade det sig att solcellsanläggnings elproduktion täcker 53 % av hushållens totala elförbrukning. Detta betyder att huset köper el för sex av årets 12 månader enligt tabell 10. Resultaten redovisar även beräkningen av återbetalningstiden för olika fall av solceller, solceller utan batteri och solcell med batteri. 

Av resultatet dras slutsatsen att solcellanläggningen är en bra investering 2024. Förutom att anläggningen producerar förnybara energikällor så betalar den sig även efter cirka 8-15år och ger också en besparing på cirka 649 654,75 kronor under en livslängd på 25år. Slutligen om elpriset stiger och priset på solceller fortsätter att sjunka kan återbetalningstiden bli ännu kortare. 

In this paper, we present a hierarchical model for time predictable task scheduling in edge-cloud computing architecture for industrial cyber-physical systems. Regarding the scheduling problem, we also investigate the common problem-solving approaches and discuss our preliminary plan to realize the proposed architecture. Furthermore, an Integer linear programming (ILP) model is proposed for task scheduling problem in the cloud layer. The model considers timing and security requirements of applications and the objective is to minimize the financial cost of their execution.

The edge-cloud computing continuum effectively uses fog and cloud servers to meet the quality of service (QoS) requirements of tasks when edge devices cannot meet those requirements. This paper focuses on the workflow offloading problem in edge-cloud computing and formulates this problem as a nonlinear mathematical programming model. The objective function is to minimize the monetary cost of executing a workflow while satisfying constraints related to data dependency among tasks and QoS requirements, including security and deadlines. Additionally, it presents a genetic algorithm for the workflow offloading problem to find near-optimal solutions with the cost minimization objective. The performance of the proposed mathematical model and genetic algorithm is evaluated on several real-world workflows. Experimental results demonstrate that the proposed genetic algorithm can find admissible solutions comparable to the mathematical model and outperforms particle swarm optimization, bee life algorithm, and a hybrid heuristic-genetic algorithm in terms of workflow execution costs.

A hybrid cloud is an efficient solution to deal with the problem of insufficient resources of a private cloud when computing demands increase beyond its resource capacities. Cost-efficient workflow scheduling, considering security requirements and data dependency among tasks, is a prominent issue in the hybrid cloud. To address this problem, we propose a mathematical model that minimizes the monetary cost of executing a workflow and satisfies the security requirements of tasks under a deadline. The proposed model fulfills data dependency among tasks, and data transmission time is formulated with exact mathematical expressions. The derived model is a Mixed-integer linear programming problem. We evaluate the proposed model with real-world workflows over changes in the input variables of the model, such as the deadline and security requirements. This paper also presents a post-optimality analysis that investigates the stability of the assignment problem. The experimental results show that the proposed model minimizes the cost by decreasing inter-cloud communications for dependent tasks. However, the optimal solutions are affected by the limitations that are imposed by the problem constraints.