Home and work [[electronic resource] ] : negotiating boundaries through everyday life / / Christena E. Nippert-Eng

• Record Nr.: UNINA9910459883703321
• Autore: Nippert-Eng Christena E
• Pubbl/distr/stampa: Chicago, IL, : University of Chicago Press, c1996
• ISBN: 1-282-73847-X; 9786612738470; 0-226-58147-0
• Descrizione fisica: 1 online resource (345 p.)
• Disciplina: 306.3/6/0973
• Soggetti: Corporate culture; Organizational sociology; Social psychology; Work and family; Electronic books.
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references (p. 307-312) and index.
• Nota di contenuto: Frontmatter -- CONTENTS -- PROLOGUE -- Acknowledgments -- Introduction -- One. Territories of the Self: Recognizing the Home-Work Boundary -- Two. Cognitive Engineering: Bridging Time, Space, and Self -- Three. Structural Constraints and Personal Discretion: Work Stakes Its Claims -- Four. Be It Ever So Humble, There Are Also Surveyors at Home -- Five. Jimmy, Eleanor, and the Logic of Boundary Work -- Conclusion. Beyond Home and Work: Boundary Theory -- Appendix. INTERVIEW QUESTIONNAIRE FOR HOME AND WORK -- References -- Index
• Sommario/riassunto: Do you put family photos on your desk at work? Are your home and work keys on the same chain? Do you keep one all-purpose calendar for listing home and work events? Do you have separate telephone books for colleagues and friends? In Home and Work, Christena Nippert-Eng examines the intricacies and implications of how we draw the line between home and work. Arguing that relationships between the two realms range from those that are highly "integrating" to those that are highly "segmenting," Nippert-Eng examines the ways people ; sculpt the boundaries between home and work. With remarkable sensitivity to the symbolic value of objects and actions, Nippert-Eng explores the meaning of clothing, wallets, lunches and vacations, and the places and ways in which we engage our family, friends, and co-workers. Commuting habits are also revealing, showing how we make the transition between home and work selves though ritualized behavior like hellos and goodbyes, the consumption of food, the way we dress, our choices of routes to and from work, and our listening, working, and sleeping habits during these journeys. The ways each of us manages time, space, and people not only reflect but reinforce lives that are more "integrating" or "segmenting" at any given time. In clarifying what we take for granted, this book will leave you thinking in different ways about your life and work.

Advances in Distributed Computing and Machine Learning : Proceedings of ICADCML 2024, Volume 2 / / edited by Umakanta Nanda, Asis Kumar Tripathy, Jyoti Prakash Sahoo, Mahasweta Sarkar, Kuan-Ching Li

• Record Nr.: UNINA9910878980403321
• Autore: Nanda Umakanta
• Pubbl/distr/stampa: Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024
• ISBN: 9789819735235; 9789819735228
• Edizione: [1st ed. 2024.]
• Descrizione fisica: 1 online resource (482 pages)
• Collana: Lecture Notes in Networks and Systems, , 2367-3389 ; ; 1015
• Altri autori (Persone): TripathyAsis Kumar; SahooJyoti Prakash; SarkarMahasweta; LiKuan-Ching
• Disciplina: 004.36
• Soggetti: Computational intelligence; Artificial intelligence; Machine learning; Blockchains (Databases); Internet of things; Computational Intelligence; Artificial Intelligence; Machine Learning; Blockchain; Internet of Things
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di contenuto: Intro -- Preface -- Contents -- Editors and Contributors -- OSNR Monitoring for QPSK and QAM in Fiber-Optic Networks Using Machine Learning -- 1 Introduction -- 2 Proposed Method -- 3 Support Vector Machine Algorithms -- 4 Simulation Results and Discussion -- 5 Conclusion and Future Research -- References -- Classification of Star and Galaxy Objects Utilizing Machine Learning Techniques and Deep Neural Networks -- 1 Introduction -- 2 Dataset -- 2.1 Processing Data -- 3 Machine Learning Approach for Star Versus Galaxy Classification -- 4 Convolutional Neural Networks-(CNN) -- 4.1 Convolutional Layers -- 4.2 Implementation Details -- 5 Result and Analysis -- 6 Conclusion -- References -- Probabilistic Forecasting Analysis on Electric Load Systems -- 1 Introduction -- 2 Review of Literature -- 3 Description of the Model -- 4 Sources of Data Generation -- 5 Computational Analysis and Results -- 5.1 Representation of ELG Units -- 5.2 Correlation Analysis -- 5.3 Bivariate Normal Distribution -- 5.4 Linear Regression and ARIMA Models -- 5.5 Electricity Consumption Charges -- 6 Conclusion -- References -- Smart City Survey on AIoT Using Machine Learning, Deep Learning, and Its Computing Tools -- 1 Introduction -- 2 IoT-Oriented Perspective -- 2.1 Smart Infrastructure -- 2.2 Air Management -- 2.3 Traffic Management -- 2.4 Waste Management -- 3 ML-Orient Perspective -- 3.1 Infrastructure -- 3.2 Air Management -- 3.3 Traffic Analysis -- 3.4 Waste Management -- 4 Deep Learning-Oriented Perspective -- 4.1 Supervised Learning -- 4.2 Unsupervised Learning -- 4.3 Reinforcement Learning -- 5 Computing Tools for Smart City -- 5.1 Cloud Computing -- 5.2 Fog Computing -- 5.3 Edge Computing -- 6 Conclusion -- References -- Energy Harvesting Integrated Sensor Node Architecture for Sustainable IoT Networks -- 1 Introduction -- 1.1 Contributions Made in This Research.; 2 Literature Study on Energy Harvesting -- 3 System Architecture -- 3.1 Hardware Requirements -- 3.2 Circuit Implementation -- 3.3 Energy Source: The PV Cell -- 3.4 Energy Storage Structures -- 3.5 Power Management Protocols -- 4 Lifetime Evaluation with Solar Energy Harvester -- 4.1 System Implementation and Analysis -- 5 Conclusion -- References -- Enhancing Real Estate Price Prediction in Smart Cities: A Comparative Analysis of Machine Learning Techniques -- 1 Introduction -- 2 Related Work -- 3 Limitation -- 4 Methodology -- 4.1 Feature Engineering -- 4.2 Model Description and Predicting the Value -- 5 Results -- 6 Conclusion -- 7 Future Work -- References -- Real-Time AI-Based Face-Mask Detection -- 1 Introduction -- 2 Proposed Design Approach -- 2.1 Custom Dataset Gathering -- 2.2 Data Augmentation for Best Results -- 2.3 Training Model -- 3 Methodology -- 3.1 YOLO Algorithm -- 3.2 MobileNetV2 -- 4 Results and Discussion -- 5 Conclusion -- References -- A Logical Model for Multiple People Activity Recognition Using Non-intrusive Sensors for Geriatric Care -- 1 Introduction -- 2 Related Work -- 3 Problem Scenario -- 4 Logical FHMM for Multiple People Activity Recognition -- 4.1 Solution Overview -- 5 Experiments -- 5.1 Experimental Setup -- 6 Conclusion -- References -- From Sea to Table: A Blockchain-Enabled Framework for Transparent and Sustainable Seafood Supply Chains -- 1 Introduction -- 2 Related Work -- 3 Seafood Supply Chain and ; Blockchain -- 4 Conceptual Blueprint -- 4.1 The Flow of Code Implementation -- 5 Result -- 6 Discussion -- 7 Conclusion and Future Scope -- References -- Distributed State Estimation for GPS Navigation: The Correntropy Extended Kalman Filter Approach -- 1 Introduction -- 2 Literature Study -- 3 Correntropy Extended Kalman Filter -- 4 Results and Discussion -- 5 Conclusion -- References.; Nayantara: Crime Analysis from CCTV Footage Using MobileNet-V2 and Transfer Learning -- 1 Introduction -- 2 Related Works -- 3 Proposed Methodology -- 3.1 System Architecture -- 3.2 Detection Model -- 3.3 Web Application -- 4 Experiments and Results -- 4.1 Dataset -- 4.2 Data Preprocessing -- 4.3 Working of the Detection Algorithm -- 4.4 CNN Model -- 4.5 Results -- 5 Conclusion -- References -- Bird Detection in Microlight Aircraft Strip Using YOLOv8for Adventure Tourism -- 1 Introduction -- 2 Bigdata Analytics Unlocks for Tourism Industry -- 2.1 Why is Microlight Aircraft Safety Important? -- 3 Literature Review -- 4 Implementation and Discussion -- 4.1 Methodology Used -- 4.2 Dataset Used -- 5 Performance Analysis and Results -- 6 Conclusion -- References -- A Graphical Tuning Method-Based Robust PID Controller for Twin-Rotor MIMO System with Loop Shaping Technique -- 1 Introduction -- 2 Preliminaries -- 2.1 Description of Twin-Rotor MIMO System -- 2.2 Design of Decouplers -- 2.3 FOPDT Model -- 3 upper H Subscript normal infinityHinfty Controller -- 4 Results an Discussions -- 5 Conclusion -- References -- Signature Verification Using Deep Learning: An Empirical Study -- 1 Introduction -- 2 Proposed Method -- 2.1 Data Acquisition -- 2.2 Pre-processing -- 2.3 Feature Extraction -- 2.4 Model and Algorithm Hyperparameters -- 2.5 Optimizing Algorithm -- 2.6 Batch Normalization and Dropout -- 3 Results -- 3.1 Performance Stats -- 3.2 Evaluation Metrics -- 4 Discussion -- 5 Conclusion -- References -- An Intelligent and Automated Machine Learning-Based Approach for Heart Disease Prediction and Personalized Care -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Dataset Description -- 3.2 Data Pre-processing -- 3.3 Handling Imbalanced Classes -- 3.4 Data Normalization -- 3.5 Feature Relevance Analysis -- 4 Results and Discussion.; 4.1 Comparative Analysis -- 5 Conclusion -- References -- Parkinson's Disease Diagnosis Through Deep Learning: A Novel LSTM-Based Approach for Freezing of Gait Detection -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Dataset -- 3.2 Data Pre-processing -- 3.3 LSTM Architecture -- 4 Results and Discussion -- 4.1 Comparative Analysis -- 5 Conclusion -- References -- Polarity Detection of Online News Articles Using Deep Learning Techniques -- 1 Introduction -- 1.1 Deep Learning and Polarity Detection -- 2 Literature Survey -- 2.1 RNN with GRU -- 2.2 RNN with LSTM -- 2.3 Bidirectional RNN -- 2.4 CNN -- 2.5 Dynamic Dictionaries -- 3 Proposed Method -- 4 Experiment and Result Discussion -- 5 Conclusion and Future Work -- References -- Harnessing ResNet50 and EfficientNetB5 for Detection of Diabetic Retinopathy Using Explainable AI -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 4 Results -- 4.1 Model Performance -- 4.2 Interpretation of Result -- 4.3 Model Explainability -- 5 Conclusion -- References -- A Grey Wolf and Rough Set Hybrid Approach for the Detection of Chronic Kidney Disease -- 1 Introduction -- 2 Schematic Representation of Proposed Research -- 3 Experimental Research on Chronic Kidney Disease -- 4 Result Analysis -- 4.1 Proposed GWRSO Data Analysis -- 5 Conclusion -- References -- Efficient Rice Disease Classification Using Intelligent Techniques -- 1 Introduction -- 2 Methodology -- 3 Data Description -- 3.1 Bacterial Leaf Blight -- 3.2 Brown Spot -- 3.3 Blast -- 3.4 Tungro -- 4 Experimental Setup ; and Performance Analysis -- 5 Conclusion -- References -- Maize Crop Yield Prediction Using Machine Learning Regression Approach -- 1 Introduction -- 2 Methodology -- 2.1 Dataset -- 2.2 Data Preprocessing -- 2.3 Feature Selection -- 2.4 Data Transformation -- 2.5 Model Building Algorithms -- 2.6 Evaluation Metrics.; 3 Experiment and Results -- 3.1 Model Building, Training, and Testing -- 3.2 Dimension Reduction Using Principal Component Analysis (PCA) -- 3.3 Comparison of the Results -- 3.4 Identification of Main Features -- 3.5 Discussion of the Findings -- 4 Conclusion -- References -- Mode Division Multiplexing-Based Passive Optical Networks for High-Capacity Data Rate via Radio Over Fiber Technology -- 1 Introduction -- 2 Proposed Mode Division Multiplexing Passive Optical Network -- 3 Mode Division Multiplexing Layout Simulation by Using OptiSystemV20 -- 4 Simulation Design of MDM with QAM and DSPK -- 5 Simulation Design of MDM for Noise Removal Systems -- 6 Result and Discussion -- 7 Conclusion -- References -- Enhancing Urban Connectivity: Free Space Optics as a Resilient Backup Link for Fiber Networks in Urban Environments -- 1 Introduction -- 2 Proposed Block Diagram of FSO-NRZ System Model -- 3 Result and Discussion -- 4 Conclusion -- References -- Integrating ANSYS Simulation and Machine Learning Techniques for Thermo-Mechanical Analysis of PCBs -- 1 Introduction -- 2 Problem Statement and Methodology -- 3 Results and Discussions -- 4 Conclusions -- References -- Automation of Quality Assessment Procedures in School Education -- 1 Introduction -- 2 Software Tool for Quality Evaluation: Design and Software Prototype Development -- 3 Experiments -- 4 Conclusions -- References -- The FGSM Attack on Image Classification Models and Distillation as Its Defense -- 1 Introduction -- 2 Related Work -- 3 Theoretical Background -- 4 Results of the FGSM Attack -- 4.1 The Classification Results in the Absence of the FGSM Attack -- 4.2 The Classification Results in the Presence of the FGSM Attack -- 5 Distillation for Defense Against the FGSM Attack -- 6 Conclusion -- References -- An Experimentation of Firefly Algorithm Using a Different Set of Objective Functions.; 1 Introduction.
• Sommario/riassunto: This book is a collection of peer-reviewed best selected research papers presented at the Fifth International Conference on Advances in Distributed Computing and Machine Learning (ICADCML 2024), organized by School of Electronics and Engineering, VIT-AP University, Amaravati, Andhra Pradesh, India, during 5–6 January 2024. This book presents recent innovations in the field of scalable distributed systems in addition to cutting edge research in the field of Internet of Things (IoT) and blockchain in distributed environments.