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Search results for: context-aware
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Design and Configuration of Context-aware VoIP Telephony Systems
PublicationVoice over IP is a widely used concept with regard to a realization technology of different types of telephony systems, including those that are used in enterprises. Such systems of a call procesing component and a set of desk endpoints that are pervasove from a user perspective. Those andpoints are usually not mobile, but in result can deliver a much greater set of functions needed in an everyday office work. Those functions also...
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Towards better understanding of context-aware knowledge transformation
PublicationConsidering different aspects of knowledge functioning, context is poorly understood in spite of intuitively identifying this concept with environmental recognition. For dynamic knowledge, context especially seems to be an essential factor of change. Investigation on the impact of context on knowledge dynamics or more generally on the relationship between knowledge and its contextual interpretation is important in order to understand...
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A New Model for context aware applications analysis and design
PublicationW artykule zostały opisane aplikacje kontekstowe, które działają w przestrzeniach inteligentnych, oraz zostały przeanalizowane ich właściwości. Na podstawie analizy zaproponowano nowe podejście do ich modelowania które zapewnia oddzielenie logiki aplikacji w zakresie adaptacji (do zmian środowiska) od jej realizacji. Zostały wykorzystane MVC i modele zmian stanu. Zaproponowano ilościową miarę poziomu kontekstowości a także sposób...
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Context-aware User Modelling and Generation of Recommendations in Recommender Systems
PublicationRecommender systems are software tools and techniques which aim at suggesting new items that may be of interest to a user. This dissertation is focused on four problems in recommender systems domain. The first one is context-awareness, i.e. how to obtain relevant contextual information, how to model user preferences in a context and use them to make predictions. The second one is multi-domain recommendation, which aim at suggesting...
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Context-Aware Indexing and Retrieval for Cognitive Systems Using SOEKS and DDNA
PublicationVisual content searching, browsing and retrieval tools have been a focus area of interest as they are required by systems from many different domains. Context-based, Content-Based, and Semantic-based are different approaches utilized for indexing/retrieving, but have their drawbacks when applied to systems that aim to mimic the human capabilities. Such systems, also known as Cognitive Systems, are still limited in terms of processing...
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Multi-domain and Context-Aware Recommendations Using Contextual Ontological User Profile
PublicationRecommender 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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CMGNet: Context-aware middle-layer guidance network for salient object detection
PublicationSalient object detection (SOD) is a critical task in computer vision that involves accurately identifying and segmenting visually significant objects in an image. To address the challenges of gridding issues and feature...
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1D convolutional context-aware architectures for acoustic sensing and recognition of passing vehicle type
PublicationA network architecture that may be employed to sensing and recognition of a type of vehicle on the basis of audio recordings made in the proximity of a road is proposed in the paper. The analyzed road traffic consists of both passenger cars and heavier vehicles. Excerpts from recordings that do not contain vehicles passing sounds are also taken into account and marked as ones containing silence....
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Towards a Framework for Context Awareness Based on Textual Process Data
PublicationContext awareness is critical for the successful execution of processes. In the abundance of business process management (BPM) research, frameworks exclusively devoted to extracting context from textual process data are scarce. With the deluge of textual data and its increasing value for organizations, it be-comes essential to employ relevant text analytics techniques to increase the awareness of business process (BP) workers,...
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Ontology Oriented Approach to Service Selection and Invocation in Complex Context Analysis
PublicationContext-aware applications running in the intelligent space are taken into account and their execution in the service oriented environment is considered. It has been presented where and how SOA services can be utilized during their execution: to analyze current context of the application and to support execution of strictly determined actions suitable for that context. The proposed mechanism of context-aware service selection and...
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A CONTEXT IN RECOMMENDER SYSTEMS
PublicationRecommender systems aim to propose potentially interesting items to a user based on his preferences or previous interaction with the system. In the last decade, researcher found out that known recommendation techniques are not sufficient to predict user decisions. It has been noticed that user preferences strongly depend on the context in which he currently is. This raises new challenges for the researchers such as how to obtain...
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Serendipitous Recommendations Through Ontology-Based Contextual Pre-filtering
PublicationContext-aware Recommender Systems aim to provide users with better recommendations for their current situation. Although evaluations of recommender systems often focus on accuracy, it is not the only important aspect. Often recommendations are overspecialized, i.e. all of the same kind. To deal with this problem, other properties can be considered, such as serendipity. In this paper, we study how an ontology-based and context-aware...
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Paweł Lubomski dr inż.
PeoplePaweł Lubomski is the director of the IT Services Centre at the Gdańsk University of Technology. He is responsible for developing and maintaining the central information systems of the university. He is also in charge of the R&D team and works on new approaches to IT systems’ protection. He also acts as the project manager of two big innovative IT projects co-financed by the European Funds. He received a PhD degree in computer...
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Top k Recommendations using Contextual Conditional Preferences Model
PublicationRecommender systems are software tools and techniques which aim at suggesting to users items they might be interested in. Context-aware recommender systems are a particular category of recommender systems which exploit contextual information to provide more adequate recommendations. However, recommendation engines still suffer from the cold-start problem, namely where not enough information about users and their ratings is available....
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Doing well by doing good — CSR in a global context
PublicationMotivation: Nowadays, there is a general understanding that stakeholders are crucial for the successful enterprise. There is also a need to think about Corporate Social Responsibility (CSR) in a global context. Never before corporations enjoyed so much power and authority. Corporations need to evolve, re-think their strategies and change their processes accordingly. However, as of now, there is no agreed way of measuring overall...
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An Ontology-based Contextual Pre-filtering Technique for Recommender Systems
PublicationContext-aware Recommender Systems aim to provide users with the most adequate recommendations for their current situation. However, an exact context obtained from a user could be too specific and may not have enough data for accurate rating prediction. This is known as the data sparsity problem. Moreover, often user preference representation depends on the domain or the specific recommendation approach used. Therefore, a big effort...
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Performance and Energy Aware Training of a Deep Neural Network in a Multi-GPU Environment with Power Capping
PublicationIn this paper we demonstrate that it is possible to obtain considerable improvement of performance and energy aware metrics for training of deep neural networks using a modern parallel multi-GPU system, by enforcing selected, non-default power caps on the GPUs. We measure the power and energy consumption of the whole node using a professional, certified hardware power meter. For a high performance workstation with 8 GPUs, we were...
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Doing Well by Doing Good- CSR in a Global Context
PublicationNowadays, there is a general understanding that stakeholders are crucial for the successful enterprise. There is also a need to think about Corporate Social Responsibility (CSR) in a global context. Never before corporations enjoyed so much power and authority. Corporations need to evolve, re-think their strategies and change their processes accordingly. However, as of now, there is no agreed way of measuring overall sustainability...
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Elements of six sigma methodoloygy in polish smes. the pomeranian region context
PublicationIn this article, it has been suggested that the effectiveness of the design and implementation of the process approach in the SMEs sector affects the effectiveness and efficiency of the application of elements of the Six Sigma ™ concept. The selected results of the research have been presented to answer the question to what extent small and medium-sized manufacturing, service and production - service companies in Pomeranian region...
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Universal and contextualized public services: Digital public service innovation framework
PublicationIn view of the rising social and economic inequalities, public service delivery should be both universal, i.e. independent of the recipients' social or economic status, and contextualized, i.e. able to compensate for different local needs and conditions. Reconciling both properties requires various forms of innovations, chief among them innovations in digital public services. Building upon the four-stage model underpinning the...
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Theoretical and Architectural Framework for Contextual Knowledge Bases
PublicationThe paper presents the approach aimed at building modularized knowledge bases in a systematic, context-aware way. The paper focuses on logical modeling of such knowledge bases, including an underlying SIM metamodel. The architecture of a comprehensive set of tools for knowledge-base systems engineering is presented. The tools enable an engineer to design, create and edit a knowledge base schema according to a novel context approach...
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Improving Re-rankCCP with Rules Quality Measures
PublicationRecommender 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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An Analysis of Contextual Aspects of Conceptualization: A Case Study and Prospects
PublicationIn this chapter we present a new approach to development of modularized knowledge bases. We argue that modularization should start from the very beginning of modeling, i.e. from the conceptualization stage. To make this feasible, we propose to exploit a context-oriented, semantic approach to modularization. This approach is based on the Structural Interpretation Model (SIM) presented earlier elsewhere. In the first part of thischapter...
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Digital Public Service Innovation: Framework Proposal
PublicationThis paper proposes the Digital Public Service Innovation Framework that extends the "standard" provision of digital public services according to the emerging, enhanced, transactional and connected stages underpinning the United Nations Global e-Government Survey, with seven example "innovations" in digital public service delivery -- transparent, participatory, anticipatory, personalized, co-created, context-aware and context-smart....
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Don't forget the dark side of green transformation
PublicationDesign/methodology/approach – The study is a continuation of the research by Durst and Zieba (2019) related to knowledge risks and their potential outcomes. This present study makes an update on the literature on knowledge risks and green transformation and describes knowledge risks that can be faced in this process. Originality/value – The paper offers new insights for researchers dealing with the topic of knowledge risks in...
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Design of residential buildings in architecture education
PublicationThis article is based on an analysis of residential building designs made by students of the Faculty of Architecture at Gdańsk University of Technology (FA-GUT), Poland, and on the results of a survey conducted among these students. The purpose of the survey was to verify the broad, interdisciplinary knowledge of the students required in preparation for taking up design issues, as well as their ability to use this knowledge in...
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Knowledge Risks Arising from Digitalization
PublicationPurpose - This conceptual paper aims to identify and analyse knowledge risks resulting from digitalization. Additionally, the paper tries to present factors influencing knowledge risks arising from digitalization and ways of handling them. Design/methodology/approach – The study is a continuation of the research by Durst and Zieba (2019) related to knowledge risks and their potential outcomes. This present study makes an update...
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Musical Instrument Tagging Using Data Augmentation and Effective Noisy Data Processing
PublicationDeveloping signal processing methods to extract information automatically has potential in several applications, for example searching for multimedia based on its audio content, making context-aware mobile applications (e.g., tuning apps), or pre-processing for an automatic mixing system. However, the last-mentioned application needs a significant amount of research to reliably recognize real musical instruments in recordings....
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Quiet Quitting and its Link With Knowledge Risks in Organizations – Theoretical Insights
PublicationPurpose: Quiet quitting has become a widely publicized concept, driven by social media in the United States and other countries in 2022. It is a term used to describe the phenomenon by which employees do the least amount of their work, just enough to meet the requirements of one’s job description (Mahand and Caldwell, 2023). The trend is spreading quickly among young workers. It can potentially harm individuals, job performance,...
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Quiet Quitting and its Link With Knowledge Risks in Organizations – Theoretical Insights
PublicationPurpose: Quiet quitting has become a widely publicized concept, driven by social mediain the United States and other countries in 2022. It is a term used to describe thephenomenon by which employees do the least amount of their work, just enough tomeet the requirements of one’s job description (Mahand and Caldwell, 2023). The trendis spreading quickly among young workers. It can potentially harm individuals,...
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An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
PublicationSentiment analysis is an automated approach which is utilized in process of analysing textual data to describe public opinion. The sentiment analysis has major role in creating impact in the day-to-day life of individuals. However, a precise interpretation of text still relies as a major concern in classifying sentiment. So, this research introduced Bidirectional Long Short Term Memory with Ranger AdaBelief Optimizer (Bi-LSTM RAO)...
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Smart Knowledge Engineering for Cognitive Systems: A Brief Overview
PublicationCognition in computer sciences refers to the ability of a system to learn at scale, reason with purpose, and naturally interact with humans and other smart systems, such as humans do. To enhance intelligence, as well as to introduce cognitive functions into machines, recent studies have brought humans into the loop, turning the system into a human–AI hybrid. To effectively integrate and manipulate hybrid knowledge, suitable technologies...
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Affect aware video games
PublicationIn this chapter a problem of affect aware video games is described, including such issue as: emotional model of the player, design, development and UX testing of affect-aware video games, multimodal emotion recognition and a featured review of affect-aware video games.
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Rapid tolerance‐aware design of miniaturized microwave passives by means of confined‐domain surrogates
PublicationThe effects of uncertainties, primarily manufacturing tolerances but also incomplete information about operating conditions or material parameters, can be detrimental to the performance of microwave components. Quantification of such effects is essential to ensure a meaningful evaluation of the structure, in particular, its reliability under imperfect fabrication procedures. The improvement of the circuit robustness can be achieved...
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Design Elements of Affect Aware Video Games
PublicationIn this paper issues of design and development process of affect-aware video games are presented. Several important design aspects of such games are pointed out. A concept of a middleware framework is proposed that separates the development of affect-aware video games from emotion recognition algorithms and support from input sensors. Finally, two prototype affect-aware video games are presented that conform to the presented architecture...
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Emotion Recognition for Affect Aware Video Games
PublicationIn this paper the idea of affect aware video games is presented. A brief review of automatic multimodal affect recognition of facial expressions and emotions is given. The first result of emotions recognition using depth data as well as prototype affect aware video game are presented
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Using Different Information Channels for Affect-Aware Video Games - A Case Study
PublicationThis paper presents the problem of creating affect-aware video games that use different information channels, such as image, video, physiological signals, input devices, and player’s behaviour, for emotion recognition. Presented case studies of three affect-aware games show certain conditions and limitations for using specific signals to recognize emotions and lead to interesting conclusions.
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Evaluation of affective intervention process in development of affect-aware educational video games
PublicationIn this paper initial experiences are presented on implementing specific methodology of affective intervention design (AFFINT) for development of affect-aware educational video games. In the described experiment, 10 student teams are to develop affect-aware educational video games using AFFINT to formalize the whole process. Although all projects are still in progress, first observations and conclusions may already be presented.
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CSR at HEIs: Between Ignorance, Awareness and Knowledge
PublicationThe paper focuses on CSR education in Higher Education Institutions. It analyzes current approaches to this education and the enhancements already deployed in the international perspective. The main aim is to conceptualize CSRS education forms within the context of technology-oriented HEIs and propose the model for this education. This model has also been partially verified using the cases of four technical universities. This research...
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Modeling emotions for affect-aware applications
PublicationThe chapter concerns emotional states representation and modeling for software systems, that deal with human affect. A review of emotion representation models is provided, including discrete, dimensional and componential models. The paper provides also analysis of emotion models used in diverse types of affect-aware applications: games, mood trackers or tutoring systems. The analysis is supported with two design cases. The study...
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Affect-awareness framework for intelligent tutoring systems
PublicationThe paper proposes a framework for construction of Intelligent Tutoring Systems (ITS), that take into consideration student emotional states and make affective interventions. The paper provides definitions of `affect-aware systems' and `affective interventions' and describes the concept of the affect-awareness framework. The proposed framework separates emotion recognition from its definition, processing and making decisions on...
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Investigation into MPI All-Reduce Performance in a Distributed Cluster with Consideration of Imbalanced Process Arrival Patterns
PublicationThe paper presents an evaluation of all-reduce collective MPI algorithms for an environment based on a geographically-distributed compute cluster. The testbed was split into two sites: CI TASK in Gdansk University of Technology and ICM in University of Warsaw, located about 300 km from each other, both connected by a fast optical fiber Ethernet-based 100 Gbps network (900 km part of the PIONIER backbone). Each site hosted a set...
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Energy-Aware High-Performance Computing: Survey of State-of-the-Art Tools, Techniques, and Environments
PublicationThe paper presents state of the art of energy-aware high-performance computing (HPC), in particular identification and classification of approaches by system and device types, optimization metrics, and energy/power control methods. System types include single device, clusters, grids, and clouds while considered device types include CPUs, GPUs, multiprocessor, and hybrid systems. Optimization goals include various combinations of...
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Affective reactions to playing digital games
PublicationThe paper presents a study of emotional states during a gameplay. An experiment of two-player Tetris game is reported, followed by the analysis of the results - self-reported emotional states as well as physiological signals measurements interpretation. The study reveals the diversity of emotional reactions and concludes, that a representative player's emotional model is hard to define. Instead, an adaptive approach to emotion...
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Emotion Recognition and Its Applications
PublicationThe paper proposes a set of research scenarios to be applied in four domains: software engineering, website customization, education and gaming. The goal of applying the scenarios is to assess the possibility of using emotion recognition methods in these areas. It also points out the problems of defining sets of emotions to be recognized in different applications, representing the defined emotional states, gathering the data and...
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Model of emotions for game players
PublicationAffect-aware video games can respond to a game player's emotions. Such games seem to be more attractive for users. Therefore for that kind of games it is necessary to create a model of the player's emotions to know to which emotions the application should react. The paper describes different models of emotions. The questionnaire and experiment for video game players is presented. Some results of the tests are shown. Then the model...
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Spatial Modelling in Environmental Analysis and Civil Engineering
PublicationAs can be seen, Spatial Modelling in Environmental Analysis and Civil Engineering applies to a multitude of applications. In an attempt to bring the topic closer to potential readers, the special issue referred to security methods, optimization of calculations, conducting measurements and empirical tests. Each article has made an original contribution to the development of practical science that can be replicated by researchers...
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EvOLAP Graph – Evolution and OLAP-Aware Graph Data Model
PublicationThe objective of this paper is to propose a graph model that would be suitable for providing OLAP features on graph databases. The included features allow for a multidimensional and multilevel view on data and support analytical queries on operational and historical graph data. In contrast to many existing approaches tailored for static graphs, the paper addresses the issue for the changing graph schema. The model, named Evolution...
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Deep Learning Optimization for Edge Devices: Analysis of Training Quantization Parameters
PublicationThis paper focuses on convolution neural network quantization problem. The quantization has a distinct stage of data conversion from floating-point into integer-point numbers. In general, the process of quantization is associated with the reduction of the matrix dimension via limited precision of the numbers. However, the training and inference stages of deep learning neural network are limited by the space of the memory and a...
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Generalization of Phylogenetic Matching Metrics with Experimental Tests of Practical Advantages
PublicationThe ability to quantify a dissimilarity of different phylogenetic trees is required in various types of phylogenetic studies, for example, such metrics are used to assess the quality of phylogeny construction methods and to define optimization criteria in supertree building algorithms. In this article, starting from the already described concept of matching metrics, we define three new metrics for rooted phylogenetic trees. One...