Mälardalen University

The determination of upper bounds on execution times, commonly called worst-case execution times (WCETs), is a necessary step in the development and validation process for hard real-time systems. This problem is hard if the underlying processor architecture has components, such as caches, pipelines, branch prediction, and other speculative components. This article describes different approaches to this problem and surveys several commercially available tools 1 and research prototypes.

This paper seeks to identify the contributions of artificial intelligence (AI) to supply chain management (SCM) through a systematic review of the existing literature. To address the current scientific gap of AI in SCM, this study aimed to determine the current and potential AI techniques that can enhance both the study and practice of SCM. Gaps in the literature that need to be addressed through scientific research were also identified. More specifically, the following four aspects were covered: (1) the most prevalent AI techniques in SCM; (2) the potential AI techniques for employment in SCM; (3) the current AI-improved SCM subfields; and (4) the subfields that have high potential to be enhanced by AI. A specific set of inclusion and exclusion criteria are used to identify and examine papers from four SCM fields: logistics, marketing, supply chain and production. This paper provides insights through systematic analysis and synthesis.

Social learning (learning through observation or interaction with other individuals) is widespread in nature and is central to the remarkable success of humanity, yet it remains unclear why copying is profitable and how to copy most effectively. To address these questions, we organized a computer tournament in which entrants submitted strategies specifying how to use social learning and its asocial alternative (for example, trial-and-error learning) to acquire adaptive behavior in a complex environment. Most current theory predicts the emergence of mixed strategies that rely on some combination of the two types of learning. In the tournament, however, strategies that relied heavily on social learning were found to be remarkably successful, even when asocial information was no more costly than social information. Social learning proved advantageous because individuals frequently demonstrated the highest-payoff behavior in their repertoire, inadvertently filtering information for copiers. The winning strategy (discountmachine) relied nearly exclusively on social learning and weighted information according to the time since acquisition.

Global and regional trends indicate that energy demand will soon be covered by a widespread deployment of renewable energy sources. However, the weather and climate driven energy sources are characterized by a significant spatial and temporal variability. One of the commonly mentioned solutions to overcome the mismatch between demand and supply provided by renewable generation is a hybridization of two or more energy sources into a single power station (like wind-solar, solar-hydro or solar-wind-hydro). The operation of hybrid energy sources is based on the complementary nature of renewable sources. Considering the growing importance of such systems and increasing number of research activities in this area this paper presents a comprehensive review of studies which investigated, analyzed, quantified and utilized the effect of temporal, spatial and spatiotemporal complementarity between renewable energy sources. The review starts with a brief overview of available research papers, formulates detailed definition of major concepts, summarizes current research directions and ends with prospective future research activities. The review provides a chronological and spatial information with regard to the studies on the complementarity concept.

Organisations are becoming increasingly aware of the importance of employees in gaining and maintaining competitive advantage. The happy worker–productive worker thesis suggests that workers who experience high levels of well-being also perform well and vice versa; however, organisations need to know how to ensure such happy and productive workers. The present review and meta-analysis identifies workplace resources at the individual, the group, the leader, and the organisational levels that are related to both employee well-being and organisational performance. We examine which types of resources are most important in predicting both employee well-being and performance. We identified 84 quantitative studies published in print and online from 2003 to November 2015. Resources at either of the four levels were related to both employee well-being and performance. We found no significant differences in employee well-being and organisational performance between the four levels of workplace resources, suggesting that interventions may focus on any of these levels. Cross-sectional studies showed stronger relationships with well-being and performance than longitudinal studies. Studies using objective performance ratings provided weaker relationships between resources and performance than self-rated and leader/third-party-rated studies.

BACKGROUND: A woman's dissatisfaction with the experience of labor and birth may affect her emotional well-being and willingness to have another baby. The aim of this study was to investigate the prevalence and risk factors of a negative birth experience in a national sample. METHODS: A longitudinal cohort study of 2541 women recruited from all antenatal clinics in Sweden during 3 weeks spread over 1 year was conducted. Data were collected by three questionnaires, which measured women's global experience of labor and birth 1 year after the birth, and obtained information on possible risk factors during pregnancy and 2 months after the birth. RESULTS: Seven percent of the women had a negative birth experience. The following risk factors were found: (1) factors related to unexpected medical problems, such as emergency operative delivery, induction, augmentation of labor, and infant transfer to neonatal care; (2) factors related to the woman's social life, such as unwanted pregnancy and lack of support from partner; (3) factors related to the woman's feelings during labor, such as pain and lack of control; and (4) factors that may be easier to influence by the caregivers, such as insufficient time allocated to the woman's own questions at antenatal checkups, lack of support during labor, and administration of obstetric analgesia. CONCLUSIONS: Many risk factors were related to unexpected medical problems and participants' social background. Of the established methods to improve women's birth experience, childbirth education and obstetric analgesia seemed to be less effective, whereas support in labor and listening to the woman's own issues may be underestimated.

In this paper, the internal model control (IMC) method is applied to AC machine current control. Permanent magnet synchronous machines and induction machines are considered. The result is synchronous-frame proportional integral (PI) or PI-type controllers, the parameters (gain and integration time) of which are expressed directly in certain machine parameters and the desired closed-loop bandwidth. This simplifies the controller design procedure, eliminating or reducing the need for trial-and-error steps, and is the main purpose for using IMC.

The purpose of this paper is to critically analyse research about inclusive education. Prior reviews and the outcome of a recent search of databases are analysed with regard to (a) how inclusion is defined and (b) what empirical knowledge there is regarding factors that make schools and classrooms more inclusive. Our point of departure is that we regard inclusion as an idea about what school systems, schools and classrooms should accomplish, and as such, an expression of an educational philosophy. Four different understandings of inclusive education were found: (a) inclusion as the placement of pupils with disabilities in mainstream classrooms, (b) inclusion as meeting the social/academic needs of pupils with disabilities, (c) inclusion as meeting the social/academic needs of all pupils and (d) inclusion as creation of communities. Under a strict definition of inclusive education, hardly any research was found which reliably identified factors that give rise to inclusive processes. The outcome of our analyses are discussed from the perspective that different understandings of inclusion should be seen, to a large extent, as expressions of different views of what schools should accomplish. We also propose that some of the adherents to inclusion as creation of communities can be placed in the grand educational tradition reaching back to Dewey that tries to establish new ideals for school systems in a society in which individualism is perhaps the main ideology. The main conclusions are that the operative meaning of inclusion in reviews and empirical research should be much more clearly defined and that new types of studies are needed.

The increased use of temporary contracts has instigated debates on possible implications for employees’ attitudes, well‐being and behaviour. The complex issues related to this debate are reviewed from a theoretical, empirical and conceptual point of view. First, the definitions of temporary employment that are currently used in OECD countries are reviewed. Second, theoretical views concerning possible determinants are elaborated. The theoretical frameworks discussed include Work Stress Theory, Social Comparison Theory and Social Exchange Theory. The determinants proposed in these theories have served to form the basis of hypotheses on differences between temporary and permanent workers on various psychological outcomes. Third, research on associations between temporary employment and the variables job satisfaction, organizational commitment, well‐being and behaviour are reviewed. These variables are most frequently used in the realm of temporary work research. This review concludes that research results have been inconsistent and inconclusive, unlike the predictions that follow from the theoretical frameworks. This leads to a fourth section in which potential explanations for these inconsistent findings are advanced. In conclusion, a conceptual model is developed to inspire future research.

Abstract This paper draws attention to several corporate social responsibility (CSR) questions in developing countries. (1) Illustrations from, for example, South America and Africa, including African voices critical to foreign aid, show that societies are different in many respects. This implies different capacities of organizations and their managers to understand and address pressing CSR issues in different cultural contexts. (2) Weak institutional environments, such as in developing countries, often harbor illicit financial outflow from poor countries to rich ones. This strips developing nations of critical resources and contributes to failed states, a point hardly ever discussed in the CSR literature. We argue for corporate actions in areas such as enhancing capacity in detecting tax fraud, antitrust and the unveiling of corruption cases. Obviously, legislation is a task of politicians, governments and international governmental bodies. However, if business enterprises can ‘legally misuse’ the system, then the matter should be seen as a CSR issue also. There is thus an urgency for concerted efforts by the private sector, public sector and non‐governmental organizations to develop structures and institutions that contribute to social justice, environmental protection and poverty eradication. Copyright © 2009 John Wiley & Sons, Ltd and ERP Environment.

Deep Learning (DL) has recently become a topic of study in different applications including healthcare, in which timely detection of anomalies on Electrocardiogram (ECG) can play a vital role in patient monitoring. This paper presents a comprehensive review study on the recent DL methods applied to the ECG signal for the classification purposes. This study considers various types of the DL methods such as Convolutional Neural Network (CNN), Deep Belief Network (DBN), Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU). From the 75 studies reported within 2017 and 2018, CNN is dominantly observed as the suitable technique for feature extraction, seen in 52% of the studies. DL methods showed high accuracy in correct classification of Atrial Fibrillation (AF) (100%), Supraventricular Ectopic Beats (SVEB) (99.8%), and Ventricular Ectopic Beats (VEB) (99.7%) using the GRU/LSTM, CNN, and LSTM, respectively.

Great attention has been paid to develop non-fossil fuel energy sources to reduce carbon emissions and create a sustainable energy system for the future. Storing the intermittent energy is one of the challenges related to electricity production from renewable energy resources. The Sabatier reaction produces methane from carbon dioxide and hydrogen, with the latter produced by electrolysis. Methane could be stored and transported through the natural gas infrastructure already in place, and be a viable option for renewable energy storage. Current technology for biogas upgrading focuses on removing carbon dioxide from the biogas. However, the biogas could potentially be used directly as feed gas for the Sabatier reaction, thereby removing the cost associated with carbon dioxide removal and increasing the methane yield and carbon utilization from biological sources. Carbon dioxide methanation requires a catalyst to be active at relatively low temperatures and selective towards methane. Nickel based catalyst are most widely investigated, and commercial catalysts are typically nickel on alumina support. Focus on catalyst development for carbon dioxide methanation is predominantly related to support modification, promoter addition, as well as utilizing new class of materials such as hydrotalcite-derived catalysts.

▪ Abstract It is common to categorize social scientific theories as either individualistic or holistic, and to assume that they are opposites. This neat picture is not so much wrong as too simple. There are different versions of both doctrines, and some versions combine elements from both. In this article I distinguish a number of versions of methodological individualism that differ significantly in strength. The main divide is between strong versions of methodological individualism, which suggest that all social phenomena should be explained only in terms of individuals and their interaction, and weak versions of methodological individualism, which also assign an important role to social institutions and/or social structure in social science explanations.

Many key aspects of society, such as transport, housing and health care, have been significantly improved by the advent of a range of electricity applications, and the power generation for electricity applications has been a major field of research. Photovoltaic (PV) self-powered technologies are promising technologies for addressing applications' power supply challenges and alleviating conventional electricity load and environmental pollution. This study reviews solar energy harvesting (SEH) technologies for PV self-powered applications. First, the PV power generation and scenarios of PV self-powered applications are analyzed. Second, analysis of system design for PV self-powered applications is presented. Third, key components for PV self-powered applications, including maximum power point tracking (MPPT) techniques and power management (PM) systems are discussed in detail. Furthermore, numerous PV self-powered applications and utilizations of energy harvesting are summarized. Finally, some recommendations are proposed for further research.

OBJECTIVE: To investigate accidental falls and near fall incidents in people with multiple sclerosis with respect to clinical variables and the predictive values of four tests. DESIGN: A longitudinal, multi-centred cohort study with prospectively collected falls. PROCEDURES: Self-reported incidents during the three months following a standardized test procedure. SUBJECTS: Seventy-six people with multiple sclerosis and an Expanded Disability Status Scale score between 3.5 and 6.0. MAIN OUTCOME MEASURES: Berg Balance Scale, Timed Up and Go cognitive, Four Square Step Test (FSST) and 12-item Multiple Sclerosis Walking Scale. RESULTS: Forty-eight people (63%) registered 270 falls. Most falls occurred indoors during activities of daily life. We found a correlation of r(s)=0.57 between near falls and falls, and of r(s) = 0.82 between registered and retrospectively recalled falls. Fallers and non-fallers differed significantly regarding Expanded Disability Status Score (odds ratio (OR) 1.99, 95% confidence interval (CI) 1.22; 3.40), spasticity (OR 1.14, CI 1.02; 1.31), proprioception (OR 2.50, CI 1.36; 5.12) and use of walking aids (OR 2.27, CI 1.23; 4.37). Reported use of walking aids both indoors and outdoors increased the odds of falling fivefold while disturbed proprioception increased the odds 2.5-15.6 times depending on severity. The odds of falling were doubled for each degree of increased Expanded Disability Status Score and more than doubled for each degree of increased spasticity. The Berg Balance Scale, use of walking aids and Timed Up and Go cognitive best identified fallers (73-94%) and proprioception, Expanded Disability Status Score, 12-item Multiple Sclerosis Walking Scale and Four Square Step Test best identified non-fallers (75-93%). CONCLUSIONS: In clinical practice, looking at the use of walking aids, investigating proprioception and spasticity, rating Expanded Disability Status Score and using Berg Balance Scale or Timed Up and Go cognitive all contribute when identifying fallers.

Several research studies have ranked indoor pollution among the top environmental risks to public health in recent years. Good indoor air quality is an essential component of a healthy indoor environment and significantly affects human health and well-being. Poor air quality in such environments may cause respiratory disease for millions of pupils around the globe and, in the current pandemic-dominated era, require ever more urgent actions to tackle the burden of its impacts. The poor indoor quality in such environments could result from poor management, operation, maintenance, and cleaning. Pupils are a different segment of the population from adults in many ways, and they are more exposed to the poor indoor environment: They breathe in more air per unit weight and are more sensitive to heat/cold and moisture. Thus, their vulnerability is higher than adults, and poor conditions may affect proper development. However, a healthy learning environment can reduce the absence rate, improves test scores, and enhances pupil/teacher learning/teaching productivity. In this article, we analyzed recent literature on indoor air quality and health in schools, with the primary focus on ventilation, thermal comfort, productivity, and exposure risk. This study conducts a comprehensive review to summarizes the existing knowledge to highlight the latest research and solutions and proposes a roadmap for the future school environment. In conclusion, we summarize the critical limitations of the existing studies, reveal insights for future research directions, and propose a roadmap for further improvements in school air quality. More parameters and specific data should be obtained from in-site measurements to get a more in-depth understanding at contaminant characteristics. Meanwhile, site-specific strategies for different school locations, such as proximity to transportation routes and industrial areas, should be developed to suit the characteristics of schools in different regions. The socio-economic consequences of health and performance effects on children in classrooms should be considered. There is a great need for more comprehensive studies with larger sample sizes to study on environmental health exposure, student performance, and indoor satisfaction. More complex mitigation measures should be evaluated by considering energy efficiency, IAQ and health effects.

The International Classification of Functioning, Disability and Health-ICF addresses the broad need for a common language and classification of functioning and disability. A parallel need is appropriate measures compatible with the content of the ICF to document the nature and impact of limitations of function, activities and participation. The interaction of developmental characteristics and disability among children represent special challenges for classification as well as measurement. Demographic trends emphasize the need for universal measures that encompass the components of the ICF and can be used in surveillance, screening and evaluation. This paper identifies issues related to application of the ICF to measure disability in childhood; reviews approaches and tools to assess childhood disability and identifies priorities for the development of measures of functioning and disability in children based on the ICF. The development of measures should be framed within a framework of children's rights and application of the biopsychosocial model to document profiles of functioning and disability of children.

Cooperative Cyber-Physical Systems (Co-CPSs) can be enabled using wireless communication technologies, which in principle should address reliability and safety challenges. Safety for Co-CPS enabled by wireless communication technologies is a crucial aspect and requires new dedicated design approaches. In this paper, we provide an overview of five Co-CPS use cases, as introduced in our SafeCOP EU project, and analyze their safety design requirements. Next, we provide a comprehensive analysis of the main existing wireless communication technologies giving details about the protocols developed within particular standardization bodies. We also investigate to what extent they address the non-functional requirements in terms of safety, security and real time, in the different application domains of each use case. Finally, we discuss general recommendations about the use of different wireless communication technologies showing their potentials in the selected real-world use cases. The discussion is provided under consideration in the 5G standardization process within 3GPP, whose current efforts are inline to current gaps in wireless communications protocols for Co-CPSs including many future use cases.

Modelling of real-time systems requires accurate and tight estimates of the Worst-Case Execution Time (WCET) of each task scheduled to run. In the past two decades, two main paradigms have emerged within the field of WCET analysis: static analysis and hybrid measurement-based analysis. These techniques have been succesfully implemented in prototype and commercial toolsets. Yet, comparison among the WCET estimates derived by such tools remains somewhat elusive as it requires a common set of benchmarks which serve a multitude of needs. The Maelardalen WCET research group maintains a large number of WCET benchmark programs for this purpose. This paper describes properties of the existing benchmarks, including their relative strengths and weaknesses. We propose extensions to the benchmarks which will allow any type of WCET tool evaluate its results against other state-of-the-art tools, thus setting a high standard for future research and development. We also propose an organization supporting the future work with the benchmarks. We suggest to form a committee with a responsibility for the benchmarks, and that the benchmark web site is transformed to an open wiki, with possibility for the WCET community to easily update the benchmarks.

A growing trend in the automation industry is to use wireless technologies to reduce cable cost, deployment time, unlocking of stranded information in previously deployed devices, and enabling wireless control applications. Despite a huge research effort in the area of wireless sensor networks (WSNs), there are several issues that have not been addressed properly such that WSNs can be adopted properly in the process automation domain. This article presents the major requirements for typical applications in process automation and we also aim to outline the research direction for industrial wireless sensor networks (IWSNs) in industrial automation. The major issues that need to be addressed are safety, security and availability before industrial wireless sensor networks will be adopted in full scale in process automation.