LEADER 03560nam 2200601Ia 450 001 9910437898803321 005 20200520144314.0 010 $a9783642310003 010 $a3642310001 024 7 $a10.1007/978-3-642-31000-3 035 $a(CKB)3390000000030197 035 $a(SSID)ssj0000746049 035 $a(PQKBManifestationID)11430134 035 $a(PQKBTitleCode)TC0000746049 035 $a(PQKBWorkID)10860381 035 $a(PQKB)11438766 035 $a(DE-He213)978-3-642-31000-3 035 $a(MiAaPQ)EBC3070998 035 $a(PPN)168318210 035 $a(EXLCZ)993390000000030197 100 $a20120602d2013 uy 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aModeling users' experiences with interactive systems /$fEvangelos Karapanos 205 $a1st ed. 2013. 210 $aHeidelberg ;$aNew York $cSpringer$dc2013 215 $a1 online resource (XII, 164 p.) 225 1 $aStudies in computational intelligence,$x1860-949X ;$v436 300 $aBibliographic Level Mode of Issuance: Monograph 311 08$a9783642433603 311 08$a364243360X 311 08$a9783642309991 311 08$a3642309992 320 $aIncludes bibliographical references (p. [151]-161). 327 $aPersonal Attribute Judgments -- Analyzing Personal Attribute Judgments -- User Experience Over Time -- iScale: studying long-term experiences through memory -- A semi-automated approach to the content analysis of experience narratives. 330 $aOver the past decade the field of Human-Computer Interaction has evolved from the study of the usability of interactive products towards a more holistic understanding of how they may mediate desired human experiences.  This book identifies the notion of diversity in users? experiences with interactive products and proposes methods and tools for modeling this along two levels: (a) interpersonal diversity in users? responses to early conceptual designs, and (b) the dynamics of users? experiences over time. The Repertory Grid Technique is proposed as an alternative to standardized psychometric scales for modeling interpersonal diversity in users? responses to early concepts in the design process, and new Multi-Dimensional Scaling procedures are introduced for modeling such complex quantitative data. iScale, a tool for the retrospective assessment of users? experiences over time is proposed as an alternative to longitudinal field studies, and a semi-automated technique for the analysis of the elicited experience narratives is introduced. Through these two methodological contributions, this book argues against averaging in the subjective evaluation of interactive products. It proposes the development of interactive tools that can assist designers in moving across multiple levels of abstraction of empirical data, as design-relevant knowledge might be found on all these levels. Foreword by Jean-Bernard Martens and Closing Note by Marc Hassenzahl. 410 0$aStudies in computational intelligence ;$vv. 436. 606 $aHuman-computer interaction 606 $aUser interfaces (Computer systems) 615 0$aHuman-computer interaction. 615 0$aUser interfaces (Computer systems) 676 $a004.019 700 $aKarapanos$b Evangelos$01064593 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910437898803321 996 $aModeling Users' Experiences with Interactive Systems$92539322 997 $aUNINA LEADER 13002nam 22006735 450 001 9910886994303321 005 20250701050212.0 010 $a3-031-70011-2 024 7 $a10.1007/978-3-031-70011-8 035 $a(MiAaPQ)EBC31650817 035 $a(Au-PeEL)EBL31650817 035 $a(CKB)34842784600041 035 $a(DE-He213)978-3-031-70011-8 035 $a(OCoLC)1455348681 035 $a(EXLCZ)9934842784600041 100 $a20240905d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aComplex, Intelligent and Software Intensive Systems $eProceedings of the 18th International Conference on Complex, Intelligent and Software Intensive Systems (CISIS-2024) /$fedited by Leonard Barolli 205 $a1st ed. 2024. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2024. 215 $a1 online resource (537 pages) 225 1 $aLecture Notes on Data Engineering and Communications Technologies,$x2367-4520 ;$v87 311 08$a3-031-70010-4 320 $aIncludes bibliographical references and index. 327 $aIntro -- Welcome Message of CISIS-2024 International Conference Organizers -- CISIS-2024 Organizing Committee -- CISIS-2024 Keynote Talks -- Integrating AI, Citizen-Science, Social-Media and Innovative Hardware Tech for Public Health -- Application of Artificial Intelligence and Internet of Things for Building Smart Services -- Contents -- A Systematic Review of the External Influence Factors in Multifactor Analysis and the Prediction of Carbon Credit Prices -- 1 Background and Motivation -- 2 Systematic Review Protocol -- 3 Result and Discussion -- 4 Conclusion and Future Work -- References -- Stock Market Prediction Using Social Media Sentiments -- 1 Introduction -- 2 Related Work -- 3 Proposed Model -- 3.1 Data Collection -- 3.2 Data Pre-processing -- 3.3 Sentiment Analysis -- 3.4 Stock Movement Prediction -- 4 Simulation Results -- 5 Conclusion -- References -- Investigation of Location Problem in Logistics Centers Using ADMM Algorithm -- 1 Introduction -- 2 Modeling -- 2.1 Problem Description -- 2.2 Model Assumptions -- 2.3 Model Building -- 3 Algorithm Solving -- 3.1 ADMM Algorithm -- 3.2 Calculation Steps -- 4 Numerical Experiments -- 4.1 Data Simulation -- 4.2 Experimental Results -- 5 Conclusion -- References -- Stock Price Prediction Based on FinBERT-LSTM Model -- 1 Introduction -- 1.1 Research Background -- 1.2 Research Status -- 1.3 Main Contributions -- 2 FinBERT-LSTM Model -- 2.1 FinBERT for Sentiment Analysis -- 2.2 LSTM for Time Series Prediction -- 3 Experimental Process -- 3.1 Experimental Data and Preprocessing -- 3.2 Fine-Tuning the FinBERT Model -- 3.3 Investor Sentiment Analysis -- 3.4 Stock Price Prediction -- 4 Experimental Results -- 4.1 Evaluating Metrics -- 4.2 Comparison of Results -- 5 Conclusion -- References. 327 $aHyperparameter Tuning on Classical Machine Learning Models in Orthopedic Disease Prediction on Biomechanical Features -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Dataset -- 3.2 Algorithms for Classification -- 4 Experimental Results -- 4.1 The Performance with Logistic Regression -- 4.2 The Performance with KNN -- 4.3 Random Forest Classifier -- 4.4 The Performance with LightGBM -- 4.5 Comparison with Previous Studies -- 5 Conclusion -- References -- Interpreting Large-Scale Attacks Against Open-Source Medical Systems Using eXplainable AI -- 1 Introduction -- 2 Related Works -- 3 XGBoost Tree -- 4 SHAP Explainer -- 5 Experimental Evaluation -- 6 Conclusions and Future Work -- References -- Jupyter-Based Java Development Environment for Programming Education -- 1 Introduction -- 2 Related Work -- 2.1 Reasons for Using Jupyter in CS -- 2.2 Previous Research -- 3 System Design -- 3.1 Traditional X11 Server -- 3.2 System Overview -- 4 Evaluations -- 4.1 Reproducibility -- 4.2 Performance -- 5 Conclusions -- References -- A Customizable Intelligent System for Cervical Cytology Image Classifications -- 1 Introduction -- 2 Background Information and Related Works -- 2.1 Epithelial Cell Types Used in the Experiment -- 2.2 Machine Learning Shallow and Deep Models -- 3 The Proposed Method -- 4 Results -- 4.1 Data Sets Analysis -- 4.2 Performance Evaluation Metrics -- 5 Conclusions -- References -- Feature Selection Based on Ranking Metagenomic Relative Abundance for Inflammatory Bowel Disease Prediction -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Data Description -- 3.2 Ranking Relative Abundance on Inflammatory Bowel Disease Datasets -- 3.3 Algorithms for Disease Classification -- 4 Experimental Results -- 4.1 The Number of Selected Features Affecting the Performance -- 4.2 Discussion -- 5 Conclusion -- References. 327 $aChild Abuse Behaviors Identification from Surveillance Videos -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Child Abuse Behaviors -- 3.2 Dataset -- 3.3 Building Child Abuse Behaviors Detection Model with YOLO -- 3.4 Evaluating Child Abuse Behaviors Detection Model -- 4 Experimental Results -- 4.1 Environmental Settings -- 4.2 Abuse Behavior Detection Using YOLOv5 and YOLOv8 -- 4.3 Abuse Behavior Detection Using Augmented Dataset -- 4.4 Discussion -- 5 Conclusion -- References -- A Fuzzy-Based System for Selection of Radio Access Technology in 5G Wireless Networks Considering RAT Load as a New Parameter -- 1 Introduction -- 2 Software-Defined Networks (SDNs) -- 3 Fuzzy Logic -- 4 Proposed Fuzzy-Based System -- 5 Simulation Results -- 6 Conclusions and Future Work -- References -- Assessment of WMN-CS Intelligent Simulation System for Uniform, Weibull and Chi-Square Distribution of Mesh Clients -- 1 Introduction -- 2 Related Work -- 3 Node Placement Problem in WMNs -- 4 Cuckoo Search Algorithm -- 4.1 Overview of Cuckoo Search -- 4.2 Lévy Flight -- 5 WMN-CS Simulation System -- 6 Simulation Results -- 7 Conclusions -- References -- Performance Evaluation of a Distracted Driving Detection System Considering Smoking Behavior -- 1 Introduction -- 2 Deep Neural Networks: An Overview -- 3 Intelligent Distracted Driving Detection System -- 3.1 System Model -- 3.2 Detection Targets and Classes -- 4 Evaluation Results -- 4.1 Hand Detection and Improving Detection Accuracy -- 4.2 Classification Accuracy for Different Batches -- 5 Conclusions -- References -- Trusted Computing in Advanced Cybersecurity Solutions -- 1 Introduction -- 2 Cognitive Inference for Trusted Computation -- 3 Trusted Computing Based on Feature Vectors -- 4 Trusted Computing in Data Sharing Protocols -- 5 Trusted Computing in Cloud-to-Things. 327 $a6 Security of Trusted Computing Protocols -- 7 Conclusions -- References -- DP-ACO: Differentially Private Average Consensus Optimization in Decentralized Learning -- 1 Introduction -- 1.1 Background -- 1.2 Our Contributions -- 2 Our Proposed System for Differentially Private Average Consensus Optimization -- 3 Experiments -- 4 Conclusion -- References -- A Method for Job Management Using MPI Profiling Interface -- 1 Introduction -- 2 Problems of Job Schedulers and Their Case Study -- 2.1 Problems of Job Schedulers -- 2.2 Case Study of Gang Scheduling -- 3 The Approach Using MPI Profiling Interface -- 3.1 Overview of Our Approach -- 3.2 Monitor the Running Status of the Job -- 3.3 Obtain Properties of the Job -- 4 Architecture of Our System -- 4.1 Requirements of Our System -- 4.2 Notification of the Job Running Status -- 4.3 Notification of the Job Properties -- 4.4 Structure and Flow of Our System -- 5 Evaluation -- 5.1 Purpose of Evaluation -- 5.2 Method for Evaluation -- 5.3 Result of Evaluation -- 6 Conclusion -- References -- Early Design Mechanism for Upgrading Smart Contract Business Processes -- 1 Introduction -- 2 Related Work -- 3 Case Study: Telecom Service Center (TSC) -- 4 Research Methodology: An Early FT-Based Upgrade Design Mechanism for SC BP -- 4.1 BP Modeling -- 4.2 Deriving SC BP -- 4.3 Upgrading SC BP -- 5 Conclusion -- References -- Energy-Efficient Concurrency Control with Role and Purpose Concepts -- 1 Introduction -- 2 System Model -- 2.1 Transactions -- 2.2 Power Consumption and Computation Models of a Server -- 2.3 Significancy of Transactions -- 3 EESPO Scheduler -- 4 Evaluation -- 5 Concluding Remarks -- References -- An Architecture Proposal Using Hybrid Blockchain Applied for Supply Chain Tracking -- 1 Introduction -- 2 Work Motivation -- 3 Related Works -- 3.1 Discussion -- 4 Proposed Architecture. 327 $a4.1 Data Representation and Storage -- 4.2 Proposed Architecture -- 5 Architecture Implementation -- 5.1 Typical Use Case -- 6 Results -- 6.1 Test Case 1 - Evaluation of Response Time for Data Storage -- 6.2 Test Case 2 - Evaluation of Response Time for Data Insertion in the Hybrid Database Layer -- 6.3 Test Case 3: Performance Evaluation of the Insertion Queue for Hyperledger Fabric -- 6.4 Transparency and Security Overview -- 7 Conclusion -- References -- New Convergence Analysis of the BEER Algorithm in Decentralized Nonconvex Optimization -- 1 Introduction -- 2 Preliminaries and Assumptions -- 3 The BEER Algorithm -- 4 New Convergence Theorem for BEER -- 5 Conclusion -- References -- Fog Node Selection Algorithm in Information Flow Control -- 1 Introduction -- 2 System Model -- 2.1 CBAC Model -- 2.2 Component Degree -- 3 Information Flow Relations -- 4 Information Flow Control -- 5 Evaluation -- 6 Concluding Remarks -- References -- Implementing Deep Reinforcement Learning Algorithms on the Tennis Environment -- 1 Introduction -- 2 Literature Review -- 3 Deep RL Algorithms -- 3.1 Deep Q-Learning (DQN) -- 3.2 Cross Entropy -- 3.3 Deep Deterministic Policy Gradient -- 4 Simulation and Results -- 4.1 Implementing DQN -- 4.2 Implementing Cross Entropy -- 4.3 Implementing DDPG -- 5 Conclusion -- References -- A Survey on Cooperative Intelligent Transportation Systems (C-ITS): Opportunities and Challenges -- 1 Introduction -- 2 Challenges and Solutions -- 2.1 Wireless Communication -- 2.2 Data Privacy and Cybersecurity -- 2.3 Interoperability and Standardization -- 2.4 Public Acceptance and User Adoption -- 2.5 Sustainability and Safety -- 3 Conclusion -- References -- Conceptualizing a Digital Twin Architecture for Enhanced Control in Precast Concrete Production -- 1 Introduction -- 1.1 Digital Twins: Concept and Application -- 2 Literature Review. 327 $a3 Precast Concrete Process. 330 $a Software Intensive Systems are systems, which heavily interact with other systems, sensors, actuators, devices, other software systems and users. More and more domains are involved with software intensive systems, e.g. automotive, telecommunication systems, embedded systems in general, industrial automation systems and business applications. Moreover, the outcome of web services delivers a new platform for enabling software intensive systems. Complex Systems research is focused on the overall understanding of systems rather than its components. Complex Systems are very much characterized by the changing environments in which they act by their multiple internal and external interactions. They evolve and adapt through internal and external dynamic interactions. The development of Intelligent Systems and agents, which is each time more characterized by the use of ontologies and their logical foundations build a fruitful impulse for both Software Intensive Systems and Complex Systems. Recent research in the field of intelligent systems, robotics, neuroscience, artificial intelligence, and cognitive sciences are very important factor for the future development and innovation of software intensive and complex systems. The aim of the volume ?Complex, Intelligent and Software Intensive Systems? is to deliver a platform of scientific interaction between the three interwoven challenging areas of research and development of future ICT-enabled applications: Software Intensive Systems, Complex systems and Intelligent Systems. 410 0$aLecture Notes on Data Engineering and Communications Technologies,$x2367-4520 ;$v87 606 $aComputational intelligence 606 $aEngineering$xData processing 606 $aDynamics 606 $aNonlinear theories 606 $aComputational Intelligence 606 $aData Engineering 606 $aApplied Dynamical Systems 615 0$aComputational intelligence. 615 0$aEngineering$xData processing. 615 0$aDynamics. 615 0$aNonlinear theories. 615 14$aComputational Intelligence. 615 24$aData Engineering. 615 24$aApplied Dynamical Systems. 676 $a629.8 702 $aBarolli$b Leonard 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910886994303321 996 $aComplex, Intelligent, and Software Intensive Systems$91965963 997 $aUNINA