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Rok 2022
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Game-based Sprint retrospectives: multiple action research
PublikacjaIn today’s fast-paced world of rapid technological change, software development teams need to constantly revise their work practices. Not surprisingly, regular reflection on how to become more effective is perceived as one of the most important principles of Agile Software Development. Nevertheless, running an effective and enjoyable retrospective meeting is still a challenge in real environments. As reported by several studies,...
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Improving medical experts’ efficiency of misinformation detection: an exploratory study
PublikacjaFighting medical disinformation in the era of the pandemic is an increasingly important problem. Today, automatic systems for assessing the credibility of medical information do not offer sufficient precision, so human supervision and the involvement of medical expert annotators are required. Our work aims to optimize the utilization of medical experts’ time. We also equip them with tools for semi-automatic initial verification...
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Improving Re-rankCCP with Rules Quality Measures
PublikacjaRecommender Systems are software tools and techniques which aim at suggesting new items that may possibly be of interest to a user. Context-Aware Recommender Systems exploit contextual information to provide more adequate recommendations. In this paper we described a modification of an existing contextual post-filtering algorithm which uses rules-like user representation called Contextual Conditional Preferences. We extended the...
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Landscape of Automated Log Analysis: A Systematic Literature Review and Mapping Study
PublikacjaLogging is a common practice in software engineering to provide insights into working systems. The main uses of log files have always been failure identification and root cause analysis. In recent years, novel applications of logging have emerged that benefit from automated analysis of log files, for example, real-time monitoring of system health, understanding users’ behavior, and extracting domain knowledge. Although nearly every...
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Lessons learned from developing an Industry 4.0 mobile process management system supported by Artificial Intelligence
PublikacjaResearch, development and innovation (RDI) projects are undertaken in order to improve existing, or develop new, more efficient products and services. Moreover, the goal of innovation is to produce new knowledge through research, and disseminating it through education and training. In this line of thinking, this paper reports and discusses the lessons learned from the undertaken project, regarding three areas: machine learning...
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Monolithic vs. Microservice Architecture: A Performance and Scalability Evaluation
PublikacjaContext. Since its proclamation in 2012, microservices-based architecture has gained widespread popularity due to its advantages, such as improved availability, fault tolerance, and horizontal scalability, as well as greater software development agility. Motivation. Yet, refactoring a monolith to microservices by smaller businesses and expecting that the migration will bring benefits similar to those reported by top global companies,...
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Multi-domain and Context-Aware Recommendations Using Contextual Ontological User Profile
PublikacjaRecommender Systems (RS) became popular tools in many Web services like Netflix, Amazon, or YouTube, because they help a~user to avoid an information overload problem. One of the types of RS are Context-Aware RS (CARS) which exploit contextual information to provide more adequate recommendations. Cross-Domain RS (CDRS) were created as a response to the data sparsity problem which occurs when only few users can provide reviews or...
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Scaled agile framework. Dealing with software process‐related challenges of a financial group with the action research approach
PublikacjaThis article reports on a domain-specific software development venture at Nordea. We explore organizational constraints, challenges, and corrective actions undertaken when scaling the agile development approach of their Core Banking Platform program. The fit and required customizations of the rather complex and rigid SAFe framework in a policy-heavy financial institution are audited against the organic growth of the program. In...
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Stress Detection of Children With ASD Using Physiological Signals
PublikacjaThis paper proposes a physiological signal-based stress detection approach for children with autism spectrum disorder (ASD) to be used in social and assistive robot inter- vention. Electrodermal activity (EDA) and blood volume pulse (BVP) signals are collected with an E4 smart wristband from children with ASD in different countries. The peak count and signal amplitude features are derived from EDA signal and used in order to detect...
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Stress Detection of Children with Autism using Physiological Signals in Kaspar Robot-Based Intervention Studies
PublikacjaThis study aims to develop a stress detection system using the blood volume pulse (BVP) signals of children with Autism Spectrum Disorder (ASD) during robot-based interven- tion. This study presents the heart rate variability (HRV) analysis method to detect the stress, where HRV features are extracted from raw BVP signals recorded from an E4 wristband during interaction studies with the social robot Kaspar. Low frequency power...
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Systematic Literature Review for Emotion Recognition from EEG Signals
PublikacjaResearchers have recently become increasingly interested in recognizing emotions from electroencephalogram (EEG) signals and many studies utilizing different approaches have been conducted in this field. For the purposes of this work, we performed a systematic literature review including over 40 articles in order to identify the best set of methods for the emotion recognition problem. Our work collects information about the most...
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Systematic Literature Review for Emotion Recognition from EEG Signals
PublikacjaResearchers have recently become increasingly interested in recognizing emotions from electroencephalogram (EEG) signals and many studies utilizing different approaches have been conducted in this field. For the purposes of this work, we performed a systematic literature review including over 40 articles in order to identify the best set of methods for the emotion recognition problem. Our work collects information about the most...
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Toward a unified model of mobile Business Intelligence (m-BI) acceptance and use
PublikacjaFactors affecting mobile business intelligence (m-BI) acceptance and use have become an increasingly important topic in practice due to the growing complexity of organizations, and their underlying information systems (IS). Since, one can notice considerable interest in m-BI, however, to the best of our knowledge few studies (if any) aim to synthesize the existing body of knowledge with regards to the factors affecting m-BI acceptance...
Rok 2023
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Addressing Challenges in AI-based Systems Development: A Proposal of Adapted Requirements Engineering Process
Publikacja[Context] Present-day IT systems are more and more dependent on artificial intelligence (AI) solutions. Developing AI-based systems means facing new challenges, not known for more conventional systems. Such challenges need to be identified and addressed by properly adapting the existing development and management processes. [Objective] In this paper, we focus on the requirements engineering (RE) area of IT projects and aim to propose...
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AffecTube — Chrome extension for YouTube video affective annotations
PublikacjaThe shortage of emotion-annotated video datasets suitable for training and validating machine learning models for facial expression-based emotion recognition stems primarily from the significant effort and cost required for manual annotation. In this paper, we present AffecTube as a comprehensive solution that leverages crowdsourcing to annotate videos directly on the YouTube platform, resulting in ready-to-use emotion-annotated...
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Development of the System Assurance Reference Model for Generating Modular Assurance Cases
PublikacjaAssurance cases are structured arguments used to demonstrate specific system properties such as safety or security. They are used in many industrial sectors including automotive, aviation and medical devices. Larger assurance cases are usually divided into modules to manage the complexity and distribute the work. Each of the modules is developed to address specific goals allocated to the specific objects i.e. components of the...
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DevEmo—Software Developers’ Facial Expression Dataset
PublikacjaThe COVID-19 pandemic has increased the relevance of remote activities and digital tools for education, work, and other aspects of daily life. This reality has highlighted the need for emotion recognition technology to better understand the emotions of computer users and provide support in remote environments. Emotion recognition can play a critical role in improving the remote experience and ensuring that individuals are able...
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Discovering relationships between data in an enterprise information system using log analysis
PublikacjaEnterprise systems are inherently complex and maintaining their full, up-to-date overview poses a serious challenge to the enterprise architects’ teams. This problem encourages the search for automated means of discovering knowledge about such systems. An important aspect of this knowledge is understanding the data that are processed by applications and their relationships. In our previous work, we used application logs of an enterprise...
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Exploring Stock Traders’ Cognitive Biases: Research Design and Simulator Framework
PublikacjaCognitive bias is a phenomenon that has been extensively studied in stock trading and many other fields. This paper presents a framework for a Mobile Stock Trading Simulator (MSTS) that facilitates automatic investment in stocks with minimal human influence, by investigating the behavioral patterns and cognitive errors of stock market investors. The paper aims to determine whether investors’ investment strategies can be improved...
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Exploring the Prevalence of Anti-patterns in the Application of Scrum in Software Development Organizations
PublikacjaThe paper presents a survey-based study that aimed to determine the prevalence of anti-patterns in the Scrum software development methodology. A total of 35 anti-patterns were selected from the literature review, and 42 respondents indicated whether they had encountered each anti-pattern in their organizations. The study found that``Unfinished Tasks'' was the most prevalent anti-pattern, highlighting the importance of proper planning...