Generic Model for Adaptive Systems Realization

The permanent acquisition of the technical environment state and the ability to react to changes in this environment as well as to adapt to it are nowadays crucial for any information system. In this article, the authors present a well-defined model to guarantee in a simple way the design and the realization of adaptive information systems. This model is based on the Unified Modeling Language (UML) which is a widely known modeling standard. Its coverage is limited to bringing out the graded parties in the design of adaptive information systems. A future definition of a metamodel less related to UML language is therefore possible. The authors also present a code generator based on a model transformation technique. This generator allows you to partially produce domain-specific code as needed. A more complete code generator will come to ensure automatic generation of the code.

Formal Specification of Non-Functional Properties of Context-Aware Systems

During the recent years, there is an increasing demand for software systems that dynamically adapt their behavior at run-time in response to changes in user preferences, execution environment, and system requirements, being thus context-aware. Authors are referring here to requirements related to both functional and non-functional aspects of system behavior since changes can also be induced by failures or unavailability of parts of the software system itself. To ensure the coherence and correctness of the proposed model, all relevant properties of system entities are precisely and formally described. This is especially true for non-functional properties, such as performance, availability, and security. This article discusses semantic concepts for the specification of non-functional requirements, taking into account the specific needs of a context-aware system. Based on these semantic concepts, we present a specification language that integrates non-functional requirements design and validation in the development process of context-aware self-adaptive systems.

Generic Model for Adaptive Systems Realization

The permanent acquisition of the technical environment state and the ability to react to changes in this environment as well as to adapt to it are nowadays crucial for any information system. In this article, the authors present a well-defined model to guarantee in a simple way the design and the realization of adaptive information systems. This model is based on the Unified Modeling Language (UML) which is a widely known modeling standard. Its coverage is limited to bringing out the graded parties in the design of adaptive information systems. A future definition of a metamodel less related to UML language is therefore possible. The authors also present a code generator based on a model transformation technique. This generator allows you to partially produce domain-specific code as needed. A more complete code generator will come to ensure automatic generation of the code.

A design of a multi-agent recommendation system using ontologies and rule-based reasoning: pandemic context

Learners attend their courses in remote or hybrid systems find it difficult to follow one size fits all courses. These difficulties have increased with the pandemic, lockdown, and the stress they cause. Hence, the role of adaptive systems to recommend personalized learning resources according to the learner's profile. The purpose of this paper is to design a system for recommending learning objects according learner's condition, including his mental state, his COVID-19 history, as well as his social situation and ability to connect to the e-learning system on a regular basis. In this article, we present an architecture of a recommendation system for personalized learning objects based on ontologies and on rule-based reasoning, and we will also describe the inference rules required for the adaptation of the educational content to the needs of the learners, taking into account the learner’s health and mental state, as well as his social situation. The system designed, and validated using the unified modeling language (UML). It additionally allows teachers to have a holistic view of learners’ progress and situations.

Exploring the remote work challenges in the era of COVID-19 pandemic: review and application model

PurposeRemote work (RW) literature is a megatrend in HRM literature, and the COVID-19 pandemic has highlighted the importance of RW as a concept and an organisational practice. Given the large number of papers being published on remote work, there is a need for a critical review of the extant literature using bibliometric analysis. This paper examines the literature on remote working to identify the factors crucial for managing a remote workforce. This study uses the complex adaptive systems theory as a foundation to build a framework that organisations can use to manage their remote workforce, focusing on three outcomes: employee engagement, collaboration and organisational agility.Design/methodology/approachBibliometric analysis was conducted on the research published in Scopus journal in the area of remote work, followed by critical literature analysis.FindingsThe bibliometric analysis identified five clusters that reflect five organisational factors which the management can align to achieve the desired outcomes of engagement, collaboration and agility: technology orientation, leadership, HRM practices, external processes and organisational culture. The present findings have important implications for managing the remote workforce.Originality/valueThe five factors were mapped to propose a conceptual model on engaging individual employees, fostering team collaboration and building organisational agility while working remotely. We also propose an application model for using technology to achieve the outcomes of engagement, collaboration and agility in the organisation. Practitioners could use this framework to focus on the factors that can create a conducive environment to improve work efficiency in a remote workforce.

Labor and environment in global value chains: an evolutionary policy study with a three-sector and two-region agent-based macroeconomic model

The world economy crucially depends on multi-layered value chains with high degrees of sector-related specialization. Its final products are of international character and serve the needs and wants of the global citizen. However, many production processes are causing severe damage to the environment and moreover create health hazard for workers and local populations. This research article focuses on the increasing global unequal economic- and ecological exchange, fundamentally embedded in international trade. Resource extraction and labor conditions in the Global South as well as the implications for climate change originating from industry emissions in the North are investigated with an agent-based model. The model serves as a testbed for simulation experiments with evolutionary political economic policies. An international institution is introduced sanctioning the polluting extractivist sector in the Global South as well as the emitting industrial capital good producers in the North with the aim of subsidizing innovation reducing environmental and social impacts. Both regions are modelled as macroeconomic complex adaptive systems where international trade is restricted to a three-sector value chain, originating from mining resources in the South that are traded to capital good producers in the North crafting machinery which is eventually traded to consumer good firms, both in the North and South. The main outcome of the study is that sanctions alone are not effective in countering unequal exchange. They only make a difference in combination with subsidies for innovation activities, which are protecting labor and reducing local pollution in mines as well as reducing carbon-emissions in capital good production.

Using In-Vehicle Monitoring Data to Assess Road Conditions of Traffic Flows

Developments in adaptive systems for maintenance and repair of automotive vehicles set the task of monitoring the conditions of their operation. One of the main factors determining these conditions is the type of road surface.The article describes the results of identification of the type (and condition) of the road surface obtained by theoretical and experimental methods based on the analysis of vertical accelerations recorded on the vehicle body.The purpose of research was to provide a possibility of continuous monitoring of the type of road surface on which a vehicle is driving, with the subsequent application of the obtained data to correct maintenance intervals. The results of experiments have shown the dependence of the vertical acceleration of the body on the micro-profile of the road surface. The described experimentally obtained profiles of vertical accelerations refer to different types of road surface in different conditions. For quantitative assessment, it is proposed to calculate the average level of accelerations as an integral average over a certain time interval.The results of the experiments have allowed to substantiate the empirical dependence of the average level of accelerations on speed of a vehicle. Based on this dependence, a method is proposed for recalculating the current values of the average levels of accelerations obtained at different speeds into values adjusted to the base speed to ensure the possibility of their comparison.It is shown that based on the values of average acceleration levels obtained through operation monitoring regarding a previously known type of road surface, it is possible to determine its condition. A short algorithm is formulated for practical implementation and assessment of road conditions of traffic flows. As for hardware, it is proposed not to equip a vehicle with additional sensors but to use operational standard accelerometers as part of in-vehicle emergency call systems, e.g., ERA-GLONASS equipment units.