Krzysztof Kutt

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Krzysztof verified their affiliation via an institutional email.

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• PhD
• Professor (Assistant) at Jagiellonian University

In our work, we focus on detection of affective states, their proper identification and interpretation with use of wearable and mobile devices. We propose a data acquisition layer based on wearable devices able to gather physiological data, and we integrate it with mobile context-aware framework. Furthermore, we formulate a method for personalizati...

In this article, we propose using personality assessment as a way to adapt affective intelligent systems. This psychologically-grounded mechanism will divide users into groups that differ in their reactions to affective stimuli for which the behaviour of the system can be adjusted. In order to verify the hypotheses, we conducted an experiment on 20...

In the paper we present an original semantic data mining solution for Internet of Things. We designed an ontology for sensors used in the monitoring of goods and vehicles. Moreover, we developed a practical implementation for this solution based on the state of the art semantic tools, namely RDF triple stores with dedicated interfaces. However, due...

Generic emotion prediction models based on physiological data developed in the field of affective computing apparently are not robust enough. To improve their effectiveness, one needs to personalize them to specific individuals and incorporate broader contextual information. To address the lack of relevant datasets, we propose the 2nd Study in Bio-...

We present Loki, a semantic wiki designed to support the collaborative knowledge engineering process with the use of software engineering methods. Designed as a set of DokuWiki plug-ins, it provides a variety of knowledge representation methods, including semantic annotations, Prolog clauses, and business processes and rules oriented to specific ta...

We present TAO (The Arcarium Ontology), an ontology that will serve as the backbone of the forthcoming Arcarium knowledge base for storing and retrieving rich metadata of manuscript collections housed at Jagiellonian University (Kraków, Poland). The main motivation for its creation is the ongoing digitization of the precious Autograph Collection fr...

Experiments in affective computing are based on stimulus datasets that, in the process of standardization, receive metadata describing which emotions each stimulus evokes. In this paper, we explore an approach to creating stimulus datasets for affective computing using generative adversarial networks (GANs). Traditional dataset preparation methods...

In response to several cultural heritage initiatives at the Jagiellonian University, we have developed a new digitization workflow in collaboration with the Jagiellonian Library (JL). The solution is based on easy-to-access technological solutions -- Microsoft 365 cloud with MS Excel files as metadata acquisition interfaces, Office Script for valid...

As part of ongoing research projects, three Jagiellonian University units -- the Jagiellonian University Museum, the Jagiellonian University Archives, and the Jagiellonian Library -- are collaborating to digitize cultural heritage documents, describe them in detail, and then integrate these descriptions into a linked data cloud. Achieving this goal...

Experiments in affective computing are based on stimulus datasets that, in the process of standardization, receive metadata describing which emotions each stimulus evokes. In this paper, we explore an approach to creating stimulus datasets for affective computing using generative adversarial networks (GANs). Traditional dataset preparation methods...

Despite over 20 years of research in affective computing, emotion prediction models that would be useful in real-life out-of-the-lab scenarios such as health care or intelligent assistants have still not been developed. The identification of the fundamental problems behind this concern led to the initiation of the BIRAFFE series of experiments, who...

In recent years, one can observe an increasing interest in dynamic models in the personality psychology research. Opposed to the traditional paradigm—in which personality is recognized as a set of several permanent dispositions called traits—dynamic approaches treat it as a complex system based on feedback loops between individual and the environme...

Current review papers in the area of Affective Computing and Affective Gaming point to a number of issues with using their methods in out-of-the-lab scenarios, making them virtually impossible to be deployed. On the contrary, we present a game that serves as a proof-of-concept designed to demonstrate that—being aware of all the limitations and addr...

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tas...

Groundbreaking advances in theoretical and applied Artificial Intelligence (AI). Deep Learning (DL) algorithms are grounded in non-linear and complex artificial neural systems that progressively extract higher-level features from data. DL is frequently compared with human-level performance in real-world tasks, such as clinical diagnostics. It is al...

Facial expressions convey the vast majority of the emotional information contained in social utterances. From the point of view of affective intelligent systems, it is therefore important to develop appropriate emotion recognition models based on facial images. As a result of the high interest of the research and industrial community in this proble...

The paper provides insights into two main threads of analysis of the BIRAFFE2 dataset concerning the associations between personality and physiological signals and concerning the game logs' generation and processing. Alongside the presentation of results, we propose the generation of event-marked maps as an important step in the exploratory analysi...

The paper presents the design of a game that will serve as a research environment in the BIRAFFE series experiment planned for autumn 2021, which uses affective and personality computing methods to develop methods for interacting with intelligent assistants. A key aspect is grounding the game design on the taxonomy of player types designed by Bartl...

In this paper, we present a Virtual Reality (VR) based environment where the engineer interacts with incoming data from a fleet of aeroengines. This data takes the form of 3D computer-aided design (CAD) engine models coupled with characteristic plots for the subsystems of each engine. Both the plots and models can be interacted with and manipulated...

Mining ubiquitous sensing data is important but also challenging, due to many factors, such as heterogeneous large-scale data that is often at various levels of abstraction. This also relates particularly to the important aspects of the explainability and interpretability of the applied models and their results, and thus ultimately to the outcome o...

We introduce J.A.N.E. – a proof-of-concept voice-based travel assistant. It is an attempt to show how to handle increasingly complex user queries against the web while balancing between an intuitive user interface and a proper knowledge quality level. As the use case, the search for travel directions based on user preferences regarding cuisine, art...

We propose an experimental framework for Affective Computing based of video games. We developed a set of specially designed mini-games, based of carefully selected game mechanics, to evoke emotions of participants of a larger experiment. We believe, that games provide a controllable yet overall ecological environment for studying emotions. We discu...

The paper describes BIRAFFE2 data set, which is a result of an affective computing experiment conducted between 2019 and 2020, that aimed to develop computer models for classification and recognition of emotion. Such work is important to develop new methods of natural Human-AI interaction. As we believe that models of emotion should be personalized...

This is our 2nd Study in Bio-Reactions and Faces for Emotion-based Personalization for AI Systems (BIRAFFE2). It is a dataset consisting of electrocardiogram (ECG), galvanic skin response (GSR), changes in facial expression signals and hand movements (represented by gamepad's accelerometer and gyroscope) recorded during affect elicitation by means...

In this paper we introduce the BIRAFFE data set which is the result of the experiment in affective computing we conducted in early 2019. The experiment is part of the work aimed at the development of computer models for emotion classification and recognition. We strongly believe that such models should be personalized by design as emotional respons...

We present BIRAFFE, a dataset consisting of electrocardiogram (ECG), galvanic skin reaction (GSR) and changes in facial expression signals recorded during affect elicitation by means of audio-visual stimuli (from IADS and IAPS databases) and our two proof-of-concept affective games ("Affective SpaceShooter 2" and "Fred Me Out 2"). All the signals w...

Tools for automatization of knowledge on game mechanics and their interrelationships are still lacking. Game design patterns, as proposed by Björk and Holopainen, seem promising in this area, as they can be represented formally as an ontology. This paper presents our proposal of such a representation, developed using OWL2. We discuss the design of...

In this paper, we consider the use of wearable sensors for providing affect-based adaptation in Ambient Intelligence (AmI) systems. We begin with discussion of selected issues regarding the applications of affective computing techniques. We describe our experiments for affect change detection with a range of wearable devices, such as wristbands and...

As technology becomes more ubiquitous and pervasive, special attention should be given to human-computer interaction, especially to the aspect related to the emotional states of the user. However, this approach assumes very specif c mode of data collection and storage. This data is used in the affective computing experiments for human emotion recog...

This dissertation concerns methods for supporting the knowledge engineering (KE) process. In recent years, a shift from the traditional KE to collaborative KE has been visible -- one that represents a transformation from process, in which the main role was played by knowledge engineers, to a collaborative effort, in which domain experts are main co...

The paper outlines a mobile sensor platform aimed at processing physiological data from wearable sensors. We discuss the requirements related to the use of low-cost portable devices in this scenario. Experimental analysis of four such devices, namely Microsoft Band 2, Empatica E4, eHealth Sensor Platform and BITalino (r)evolution is provided. Criti...

In this overview paper we focus on our recent progress in the work on the mobile platform for AfC. We provide the main assumptions about the platform, as well as describe affective data acquisition and interpretation. We discuss our most recent experiments and provide an outlook of our future works.

We present a navigation system combining augmented reality with semantic annotations of POIs. The prototype was implemented using regular Android smartphone and Google Cardboard. For semantic annotations we use RDF, SPARQL and a triplestore on the server. We developed a semantic information system integrated with a basic augmented reality interface...

Business Process models help to visualize the processes of an organization. There exist several techniques of semantization of Business Processes. We give an overview of Business Process semantization techniques, focusing on the existing approaches in several Business Process Management tools. We also present the use of the existing techniques in t...

A new dimension in human-computer interaction, that can be used to improve the user experience, is the emotional state of the user. This is the domain of the affective computing paradigm. In our work we focus on the applications of affective techniques in the area of the design of video games. We assume that a change in the affective condition of a...

Design of Business Intelligence systems capable of effectively handling a domain knowledge is a well known, but currently not solved challenge for both Software and Knowledge Engineers. There exist several approaches to extract and model the Business Knowledge, most notably Business Processes and Business Rules. However, each of them has its own we...

One of the powerful and popular tools that are used to support Collaborative Knowledge Engineering are Semantic Wikis. They are easily accessible and provide ACL mechanisms, but they lack a good versioning mechanism. In this paper an extended version of such a mechanism is proposed. Besides elements that appear in every Wiki system, like simple cha...

Knowledge management in a business information systems often requires a unified dictionary of business concepts, that allows for a transparent integration of such systems. Thanks to it sharing the conceptualization between users becomes possible, and a better decision support facilities can be provided. The Prosecco project is a research and develo...

Use of the information technology increases chances of adapting to changing environments. This applies to wild jungle as it applies to the urban information jungle. Modern wearable devices will allow to improve physical and augmented mental capabilities of humans. An interdisciplinary approach aimed at improving human mental processes is cognitive...

SBVR is a mature standard for capturing expressive business rules along with their semantics, and is especially useful in the communication with business people. SBVRwiki is a novel tool that allows for an eective use of the SBVR notation. This online collaborative solution allows for distributed and incremental rule authoring for business analytic...

In this paper a proposal of a new black-box unit testing method based on decision tables is given. Its main part is an automatic generation of test cases using rule-based specification of a module. The tables containing rules are described in a formalized way using the XTT2 design method for rule-based systems. The paper also provides a presentatio...

In the paper a presentation of HaDEsclipse is given. It is an environment for design and implementation of rule-based systems within the Semantic Knowledge Engineering (SKE) approach. It is build with the use of the Eclipse framework, integrating the previously developed components of the HaDEs environment. HaDEsclipse integrates modules for concep...