Autore	Satterthwaite Frank
Edizione	[1st edition]
Pubbl/distr/stampa	Alexandria, Virginia : , : Association for Talent Development, , [2017]
Descrizione fisica	1 online resource (1 volume) : illustrations
Disciplina	658.302
Soggetto topico	Organizational effectiveness Teams in the workplace - Management
ISBN	1-60728-117-1
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Intro -- Title Page -- Copyright -- Dedication -- Contents -- Acknowledgments -- Introduction: Too Busy to Read This Book? -- 1. To Make the Can-Do Mind Shift: Be a Myth Buster -- 2. To Get the Right Stuff Done: Think TPL -- 3. To Unleash the Can-Do Spirit: Check Their VITALS -- 4. To Enhance Your Leadership: Engage in Situational Doing -- 5. To Build a Can-Do Team: Use Delegation That emPOWERS -- 6. To Keep Improving: Create a Can-Do Learning Culture -- 7. To Be a Star With Career Security: Be a Can-Do Champion -- The Can-Do Leader's Lexicon -- Appendix I: Can-Do Leader TPL Leadership Style Profiler -- Appendix II: Can-Do Spirit VITALS Checkup -- References -- About the Authors -- Index.
Record Nr.	UNINA-9910149556203321

Autore	CUNEO, Gianfilippo
Pubbl/distr/stampa	Milano : EGEA, 2001
Descrizione fisica	XII, 233 p. ; 23 cm
Disciplina	658.302
Collana	I saggi
Soggetto topico	Aziende - Personale - Gestione Dirigenti aziendali - Carriera
ISBN	88-238-0786-7
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	ita
Record Nr.	UNISA-990001023650203316

Autore	Holloway Elizabeth <1950->
Pubbl/distr/stampa	Thousand Oaks, Calif. ; ; London, : SAGE, 1995
Descrizione fisica	1 online resource (234 p.)
Disciplina	658.302
Soggetto topico	Psychotherapists - Supervision of Counselors - Supervision of
Soggetto genere / forma	Electronic books.
ISBN	1-322-41299-5 0-8039-4224-9 1-4522-1510-3
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Cover; Contents; List of Tables; List of Figures; List of Research Boxes; List of Transcripts; Preface: A Scientist-Practitioner's Journey; Acknowledgments; Chapter 1 - The Essence of Supervision; Describing Supervision; Models in Supervision; Theory and Research into Practice; Principles of a Systems Approach; A Systems Approach Model; Chapter 2 - Tasks and Functions of Supervision; Identifying Tasks and Functions in Practice; The Tasks of Supervision; Operationalizing the Tasks; Functions of Supervision; Operationalizing the Functions; Task + Function = Process Chapter 3 - The Relationship of Supervision Interpersonal Structure; Phases of the Relationship; Supervisory Contracts; Chapter 4 - Contextual Factors of Supervision; Supervisor Factors; Trainee Factors; Client Factors; Institutional Factors; Conclusions; Chapter 5 - Uncovering the Words of Supervision; Beginning the Interview: Focus on the Client; Impasse in the Supervisory Relationship; Emergence of the Reflective Relationship; Beginning of the Metaphor; Breaking Through the Impasse in the Counseling Relationship; Parallel Process Emerges: Return of the Metaphor; Endings Chapter 6 - Supervising the Consultation Group Three Relational Contexts; Stories of Teaching in Supervision; Case 1: The Long Reach of the Director; Case 2: Missing the Connection; Case 3: Just Teach Me How to do it!; Case 4: The Infection Spreads; Concluding Remarks; Appendix: The Association for Counselor Education and Supervision Standards for Counselor Supervision; References; Author Index; Subject Index; Epilogue: Words of Supervision; About the Author; The SAS Model: A Systems Approach to Clinical Supervision
Record Nr.	UNINA-9910478857903321

Pubbl/distr/stampa	Gateway East, Singapore : , : Springer, , [2022]
Descrizione fisica	1 online resource (548 pages)
Disciplina	658.302
Collana	Communications in Computer and Information Science
Soggetto topico	Teams in the workplace - Data processing
ISBN	981-19-4549-7
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Intro -- Preface -- Organization -- Contents - Part II -- Contents - Part I -- Crowd Intelligence and Crowd Cooperative Computing -- Locally Linear Embedding Discriminant Feature Learning Model -- 1 Introduction -- 2 Related Work -- 3 UD-LLE Model -- 3.1 Construction of UD-LLE -- 3.2 Algorithm Based on UD-LLE Model -- 4 Experimental Results -- 4.1 Evaluation Measures -- 4.2 Experimental Settings -- 4.3 Comparison Results -- 5 Conclusion -- References -- Cache Optimization Based on Linear Regression and Directed Acyclic Task Graph -- 1 Introduction -- 2 Prearrangement Knowledge -- 2.1 Multiple Linear Regression Algorithm -- 2.2 DAG Task Graph -- 3 Method -- 3.1 Problem Definition -- 3.2 Feature Processing -- 3.3 Model Training -- 3.4 Component Design -- 4 Experimental Analysis -- 4.1 Evaluation Index -- 4.2 Experimental Results -- 5 Summary -- References -- A University Portrait System Incorporating Academic Social Network -- 1 Introduction -- 2 Preliminary -- 2.1 Text Mining Technique -- 2.2 Scraping Techniques -- 2.3 SCHOLAT Data -- 3 System Design -- 3.1 Data Collection and Data Cleaning -- 3.2 University Tags Extraction -- 4 Implementation -- 4.1 Data Collection -- 4.2 University Tagging -- 4.3 Portrait Construction and Updating -- 5 Evaluation -- 5.1 Evaluation of University Portrait -- 5.2 Comparison -- 5.3 Discussion -- 6 Conclusion -- References -- Multi-objective Optimization of Ticket Assignment Problem in Large Data Centers -- 1 Introduction -- 2 Related Work -- 2.1 Ticket Routing -- 2.2 Ticket Scheduling -- 3 Problem Description -- 4 Proposed GAMOA* -- 4.1 Transforming Ticket Scheduling to Routing -- 4.2 Multi-objective A* for Scheduling Ordered Tickets -- 4.3 Genetic Algorithm for Ticket Ordering -- 5 Performance Evaluation -- 5.1 Experimental Results -- 6 Conclusion -- References. Joint Embedding Multiple Feature and Rule for Paper Recommendation -- 1 Introduction -- 2 Related Work -- 2.1 Recommendations Based on Content and Rating Features -- 2.2 Recommendations Based on Structural Features -- 3 Joint Multi-feature and Rules Paper Embedding Method -- 3.1 Problem Definition -- 3.2 Overall Framework -- 3.3 Rule-Based Sample Selection Strategy -- 3.4 Joint Embedding Based Academic Paper Recommendation -- 4 Experiments -- 4.1 Dataset -- 4.2 Baselines and Experiment Setup -- 4.3 Results -- 5 Conclusion -- References -- Predicting Drug-Target Interactions Binding Affinity by Using Dual Updating Multi-task Learning -- 1 Introduction -- 2 Related Work -- 3 Materials and Methods -- 3.1 Datasets -- 3.2 Model Architecture -- 3.3 Training Procedure -- 3.4 Adaptation Strategy -- 4 Experiments and Results -- 4.1 Experimental Setup -- 4.2 Comparative Study -- 4.3 Results -- 5 Conclusions and Discussion -- References -- GRE: A GAT-Based Relation Embedding Model of Knowledge Graph for Recommendation -- 1 Introduction -- 2 Related Work -- 2.1 Graph Attention Networks -- 2.2 Knowledge Graph Aware Recommender Systems -- 3 The Proposed Model -- 3.1 Problem Formulation -- 3.2 Triple Set and Triple Group Extraction -- 3.3 GAT-Based Entity Aggregation and Relation Embedding -- 3.4 Click-Through-Rate Prediction -- 4 Experiments -- 4.1 Datasets -- 4.2 Baselines -- 4.3 Experiment Setup -- 4.4 Experiment Results -- 5 Conclusion -- References -- Locating Hidden Sources in Evolutionary Games Based on Fuzzy Cognitive Map -- 1 Introduction -- 2 Background -- 2.1 Fuzzy Cognitive Maps -- 2.2 EG Model -- 3 Locating Hidden Agents in FCMs -- 3.1 Overall Design Process -- 3.2 Learning FCMs from Time Series -- 3.3 Model EG Using FCM -- 3.4 Measuring Anomaly -- 4 Experiment -- 4.1 Performance Measures -- 4.2 Case 1: Brazilian Amazon Example. 4.3 Case 2: Supervisory Control Systems -- 4.4 Case 3: Mobile Payment System Project -- 4.5 Effect of NMon LHN -- 5 Conclusions -- References -- Deep Bug Triage Model Based on Multi-head Self-attention Mechanism -- 1 Introduction -- 2 Related Work -- 3 MSDBT Model -- 3.1 Input Layer -- 3.2 Feature Extraction Layer -- 3.3 Multi-head Self-attention Layer -- 3.4 Output Layer -- 4 Experimental -- 4.1 Data Set -- 4.2 Metrics -- 4.3 Comparative Models -- 4.4 Experimental Result -- 5 Conclusion -- References -- Taxi Pick-Up Area Recommendation via Integrating Spatio-Temporal Contexts into XDeepFM -- 1 Introduction -- 2 Related Work -- 3 The Framework of Taxi Pick-Up Area Recommendation -- 3.1 Related Definition -- 3.2 Recommendation Framework -- 4 Methodology Overview -- 4.1 XDeepFM -- 4.2 Construction of Spatio-Temporal Contexts Matrix -- 4.3 Pick-Up Area Recommendation -- 5 Experiments -- 5.1 Data Set -- 5.2 Performance Comparison with Other Recommendation Methods -- 5.3 Performance Evaluation of Spatio-Temporal Contexts -- 6 Conclusion -- References -- Learning When to Communicate Among Actors with the Centralized Critic for the Multi-agent System -- 1 Introduction -- 2 Related Works -- 3 Methods -- 4 Experiments -- 4.1 Setup -- 4.2 Results and Analysis -- 5 Conclusions -- References -- Social Media and Online Communities -- Academic Article Classification Algorithm Based on Pre-trained Model and Keyword Extraction -- 1 Introduction -- 2 Background and Related Work -- 3 Our Model -- 3.1 Problem Formulation -- 3.2 The Design of Neural Network -- 3.3 Fine-Tuning Technique Based on Keyword Extraction -- 4 Experimental Setup -- 4.1 Dataset Description -- 4.2 Dataset Preparation -- 4.3 Evaluation Metrics -- 4.4 Pre-experiments -- 4.5 Experiments -- 5 Results and Discussion -- 5.1 Results -- 5.2 Discussion -- 5.3 Future Trend -- 6 Conclusion and Future Work. References -- ResConvE: Deeper Convolution-Based Knowledge Graph Embeddings -- 1 Introduction -- 2 Related Work -- 3 Background -- 4 ResConvE -- 4.1 Overview -- 4.2 Detail -- 5 Experiments -- 5.1 Knowledge Graph Datasets -- 5.2 Evaluation Protocol -- 5.3 Experimental Setup -- 6 Result -- 6.1 Comparison of Performance -- 7 Conclusion and Future Work -- References -- Extractive-Abstractive: A Two-Stage Model for Long Text Summarization -- 1 Introduction -- 2 Related Work -- 3 Our Model -- 3.1 Extractive Model -- 3.2 Abstractive Model -- 4 Experimental Setup -- 4.1 Experimental Dataset -- 4.2 Evaluation Metrics -- 4.3 Model Settings -- 5 Results and Analysis -- 5.1 Results -- 5.2 Analysis -- 5.3 Application Case -- 6 Conclusion and Future Work -- References -- A Random-Walk-Based Heterogeneous Attention Network for Community Detection -- 1 Introduction -- 2 Related Work -- 2.1 NRL Algorithms on Homogeneous Networks -- 2.2 NRL Algorithms on Heterogeneous Networks -- 3 Preliminaries -- 4 RHAN -- 4.1 Random Walk with Classification -- 4.2 Intra-type Attention Computation -- 4.3 Inter-type Attention Computation -- 4.4 Loss Function for Training -- 4.5 Time Complexity Analysis -- 5 Experiments -- 5.1 Datasets -- 5.2 Evaluation Metrics -- 5.3 Baseline Algorithms -- 5.4 Parameter Settings -- 5.5 Parameter Experiment -- 5.6 Ablation Experiment -- 5.7 Accuracy Experiment -- 6 Conclusions -- References -- Attributed Network Embedding Based on Attributed-Subgraph-Based Random Walk for Community Detection -- 1 Introduction -- 2 Related Work -- 3 ANE_ASRW Algorithm -- 3.1 Structure Information Extraction -- 3.2 Attribute Information Extraction -- 3.3 Embedding Vector Generation -- 3.4 Embedding Vector Enhancement -- 3.5 Time Complexity Analysis -- 4 Experiments -- 4.1 Datasets -- 4.2 Baseline Algorithms -- 4.3 Parameter Settings -- 4.4 Evaluation Metric. 4.5 Parameter Experiment -- 4.6 Accuracy Experiment -- 4.7 Ablation Experiment -- 4.8 Embedding Vectors Visualization -- 5 Conclusions -- References -- Adaptive Seed Expansion Based on Composite Similarity for Community Detection in Attributed Networks -- 1 Introduction -- 2 Related Work -- 2.1 Community Detection Based on Seed Expansion -- 2.2 Community Detection in Attributed Networks -- 2.3 Community Detection Based on High-Order Structure -- 3 Preliminaries -- 4 ASECS -- 4.1 Weighted KNN Graph Generation -- 4.2 Community Detection by Seed Expansion -- 4.3 Complexity Analysis -- 5 Experiments -- 5.1 Datasets Description -- 5.2 Experimental Settings -- 5.3 Parameter Experiments -- 5.4 Accuracy Experiments -- 6 Conclusions -- References -- MDN: Meta-transfer Learning Method for Fake News Detection -- 1 Introduction -- 2 Related Work -- 2.1 Fake New Detection -- 2.2 Few-Shot Learning -- 3 Methodology -- 3.1 Problem Statement -- 3.2 The MDN Framework -- 3.3 Training of MDN -- 4 Experiments -- 4.1 Datasets -- 4.2 Model Training -- 4.3 Detection Results -- 5 Conclusion -- References -- Local Community Detection Algorithm Based on Core Area Expansion -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Concepts and Definitions -- 3.2 The Proposed Algorithm -- 3.3 Complexity -- 4 Experiments -- 4.1 Datesets -- 4.2 Comparison Algorithms and Evaluation Metrics -- 4.3 Parameter Experiments -- 4.4 Accuracy Experiments -- 4.5 Visualization Experiments -- 5 Conclusion -- References -- Federated Clique Percolation for Overlapping Community Detection on Attributed Networks -- 1 Introduction -- 2 Related Work -- 2.1 Clique Percolation Algorithms -- 2.2 Privacy-Preserving Community Detection -- 2.3 Federated Learning on Graphs -- 3 Preliminaries -- 3.1 Problem Definition -- 3.2 Network Privacy -- 4 Proposed Method -- 4.1 SCPAN -- 4.2 FCPAN. 4.3 Complexity Analysis.
Record Nr.	UNISA-996483161303316

Autore	Weitzel Sloan R.
Edizione	[Seconda édicion.]
Pubbl/distr/stampa	[Place of publication not identified] : , : Center for Creative Leadership, , 2019
Descrizione fisica	1 online resource (65 pages)
Disciplina	658.302
Soggetto topico	Supervision of employees
Soggetto genere / forma	Electronic books.
ISBN	1-60491-973-6
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	spa
Record Nr.	UNINA-9910479985703321