Causal categories in discourse and cognition [[electronic resource] /] / edited by Ted Sanders, Eve Sweetser

• Record Nr.: UNINA9910456322203321
• Pubbl/distr/stampa: New York, NY, : Mouton de Gruyter, 2009
• ISBN: 1-282-71509-7; 9786612715099; 3-11-022442-9
• Descrizione fisica: 1 online resource (260 p.)
• Collana: Cognitive linguistics research ; ; 44
• Altri autori (Persone): SandersTed <1963->; SweetserEve
• Disciplina: 401.9; 401/.9
• Soggetti: Psycholinguistics; Causation; Causative (Linguistics); 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 and index.
• Nota di contenuto: Frontmatter -- Table of contents -- Introduction: Causality in language and cognition - what causal connectives and causal verbs reveal about the way we think / Sanders, Ted / Sweetser, Eve -- Causality, cognition and communication: A mental space analysis of subjectivity in causal connectives / Sanders, Ted / Sanders, José / Sweetser, Eve -- Causal Connectives in Dutch Biblical Translations A cognitive linguistic approach / Sanders, José -- Causes and consequences: Evidence from Polish, English, and Dutch / Dancygier, Barbara -- Categories of subjectivity in Dutch causal connectives: a usage-based analysis / Stukker, Ninke / Sanders, Ted / Verhagen, Arie -- Causes for causatives: the case of Dutch doen and laten / Speelman, Dirk / Geeraerts, Dirk -- Causal categories in discourse - Converging evidence from language use / Sanders, Ted / Spooren, Wilbert -- Backmatter
• Sommario/riassunto: All languages of the world provide their speakers with linguistic means to express causal relations in discourse. Causal connectives and ; causative auxiliaries are among the salient markers of causal construals. Cognitive scientists and linguists are interested in how much of this causal modeling is specific to a given culture and language, and how much is characteristic of general human cognition. Speakers of English, for example, can choose between because and since or between therefore and so. How different are these from the choices made by Dutch speakers, who speak a closely related language, but (unlike English speakers) have a dedicated marker for non-volitional causality (daardoor)? The central question in this volume is: What parameters of categorization shape the use of causal connectives and auxiliary verbs across languages? The book discusses how differences between even quite closely related languages (English, Dutch, Polish) can help us to elaborate the typology of levels and categories of causation represented in language. In addition, the volume demonstrates convergence of linguistic, corpus-linguistic and psycholinguistic methodologies in determining cognitive categories of causality. The basic notion of causality appears to be an ideal linguistic phenomenon to provide an overview of methods and, perhaps more importantly, invoke a discussion on the most adequate methodological approaches to study fundamental issues in language and cognition.

Information technology in disaster risk reduction : 6th IFIP WG 5.15 international conference, ITDRR 2021, Morioka, Japan, October 25-27, 2021, revised selected papers / / edited by Jun Sasaki [and three others]

• Record Nr.: UNISA996472066103316
• Pubbl/distr/stampa: Cham, Switzerland : , : Springer, , [2022]; ©2022
• ISBN: 3-031-04170-4
• Descrizione fisica: 1 online resource (182 pages)
• Collana: IFIP Advances in Information and Communication Technology Ser. ; ; v.638
• Disciplina: 353.950285
• Soggetti: Natural disasters; Emergency management
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Intro -- Preface -- Organization -- Contents -- Information Analysis for Situation Awareness -- Automatic Calculation of Damage Rate of Roofs Based on Image Segmentation -- 1 Introduction -- 1.1 Problem in Building Damage Investigation -- 1.2 Usage of Aerial Photos Images During Disaster -- 1.3 Study Purpose -- 2 Previous Study -- 3 Development of Automatic Method to Calculate the Rate of Damage on Roof -- 3.1 The Method to Calculate the Rate of Damage on the Roof in the Building Damage Investigation -- 3.2 The Method to Calculate Damage Rate of Roof in This Study -- 3.3 Trimming Algorithm -- 3.4 Shortcomings of this Study -- 3.5 Increase of Data by Division of Roof Surface -- 4 Division of Roof Surface -- 4.1 Previous Study About Roof Surface -- 4.2 Segmentation Model -- 4.3 Used Data -- 4.4 Training Method -- 4.5 Result of Division in the First Experiment -- 4.6 Roof Image with Some Features -- 4.7 Result of Division in Additional Experiment -- 4.8 Image Processing After Division -- 5 Classification of Damage Degree -- 5.1 Classification Model -- 5.2 Data Used -- 5.3 Training Method -- 5.4 Classification Result -- 6 Calculation of Damage Rate -- 6.1 Calculation Method of Estimated Damage Rate -- 6.2 Error of Correct Answer -- 6.3 ; Comparison of Correct Damage Rate and Estimated Damage Rate -- 6.4 Evaluation of Model Accuracy -- 7 Discussion and Future Tasks -- References -- Flood Disaster Mitigation System Adopting Meteorological Data and Geographic Information Systems -- 1 Introduction -- 2 Related Work -- 3 System Design Requirement Analysis of FDMS Using SD -- 3.1 Outlines of SD -- 3.2 Iceberg Model Analysis -- 3.3 Causal Loop Diagram Analysis -- 3.4 Leverage Points -- 3.5 Observed Data Examples at River -- 3.6 System Concept -- 4 Basic Design and Integration of System -- 4.1 Basic Design of System -- 4.2 Integration of System.; 5 System Verification -- 6 Conclusion -- References -- Flood Disaster Management System for Situation Awareness and Response Using Twitter Data -- 1 Introduction -- 2 Related Work -- 2.1 Situation Awareness -- 2.2 Usage of Social Media for Situation Awareness During Disasters -- 2.3 Disaster Response and Relief -- 2.4 Originality of the Present Study -- 3 System Design -- 3.1 System Configuration -- 3.2 Data Collection -- 3.3 Extraction of Information Location -- 3.4 Web Application -- 3.5 Situation Awareness -- 4 System Development -- 4.1 System Frontend -- 4.2 System Backend -- 4.3 System Operation Environment -- 4.4 Operation Target Area -- 5 Conclusion -- References -- Evacuation and Rescue -- Proposed Evacuation Behavior Model Using Open-Source Data: Flood Disaster Case Study -- 1 Introduction -- 2 Related Studies -- 3 Evacuation Model Concept -- 3.1 Evacuation Decision Process Model -- 3.2 Calculation of Evacuation Shelter Choice Probability -- 3.3 Evacuee Rate Calculation -- 4 Simulation -- 4.1 Algorithm Overview -- 4.2 Target Area and Data -- 4.3 Data Used in the Simulation -- 4.4 Explanatory Variables -- 4.5 Scenarios -- 4.6 Optimization Method -- 4.7 Comparison Between Actual and Predicted Number of Evacuees -- 4.8 Field Survey -- 5 Conclusion -- References -- Agent-Based Tsunami Crowd Evacuation Simulation for Analysis of Evacuation Start Time and Disaster Rate in Zushi City -- 1 Introduction -- 2 Methods -- 2.1 Modelling of Target Areas -- 2.2 Tsunami Model and Evacuation Behaviour of Agents -- 3 Results and Discussion -- 4 Conclusion -- References -- Rescue Strategy in Case of Large-Scale Flood Damage in the Koto Delta Region -- 1 Introduction -- 2 Research Background -- 2.1 Characteristics of Flooding in the Koto Delta Region -- 2.2 Issues of Wide-Area Evacuation -- 3 Previous Studies and Purpose of this Study.; 4 Estimation of Changes in the Number of Isolated People in the Koto Delta Region When Rescue Operations are Conducted -- 4.1 Data and Estimation Methods -- 4.2 Comparison of the Difference in the Size of Population Aggregation Unit Area -- 4.3 Comparison of the Difference in the Order of Rescuing Isolated People -- 4.4 Comparison of the Difference in the Evacuation Rate of the Residents on Upper Floors -- 4.5 Estimation of the Evacuation Rate Required to Complete Rescue in 7 days -- 5 Summary and Future Work -- References -- COVID-19 Issues -- Trial of Building a Resilient Face-To-Face Classroom Based on CO2-Based Risk Awareness -- 1 Introduction -- 2 Case Study and Issues -- 2.1 Case Study -- 2.2 Ventilation Issues -- 3 Measurement System -- 4 Experiments -- 4.1 Measurement at an Event -- 4.2 Measurement of the Whole Campus -- 5 Conclusion -- References -- Analysis of Quote Retweets for COVID-19 State of Emergency Related Tweets Posted from Prefectural Governors' Accounts in Japan -- 1 Introduction -- 2 Related Studies -- 3 Analysis of Tweets -- 3.1 Governors' Accounts to Be Analyzed -- 3.2 Tweets Collection -- 3.3 Analysis of Quote Retweets of Governors' Tweets -- 4 Conclusions -- References -- Insights from the COVID-19 Pandemic for Systemic Risk Assessment and Management -- 1 ; Introduction -- 1.1 Have We Learnt Enough from COVID-19 to Manage New Pandemic Waves Better? -- 1.2 The Aim of This Paper and How It Is Organized -- 2 Characteristics of a Major Pandemic in the Globalization Era -- 3 Risks in the Light of Systemic Interdependencies -- 3.1 Adequate Risk Definition in the Presence of Dynamic Complexity -- 3.2 Quantitative Analysis of Qualitative Models of Systemic Risk -- 4 Order of Magnitude of Pandemic Cascading Effects -- 4.1 The Risk Systemicity Approach -- 4.2 Cascading Effects as Vicious Cycles -- 5 Discussion -- References.; IT Use for Risk and Disaster Management -- Leveraging Geospatial Technology in Disaster Management -- 1 Introduction -- 1.1 Disaster Scenario -- 1.2 Geospatial Technology -- 1.3 Geospatial Technology Innovations in Disaster Management -- 2 Karnataka State Disaster Management Information System (KSDMIS) - A Geospatial Web Application for Collecting Data on Disaster Events -- 2.1 About Karnataka -- 2.2 Objectives of KSDMIS Application Software -- 2.3 Benefits of KSDMIS Application Software -- 2.4 KSDMIS Application Software Structure -- 2.5 Mobile Interface for Data Collection and Updation -- 2.6 Web Interface to the KSDMIS Application Software -- 2.7 Adopting Geospatial Technology in KSDMIS -- 3 Geospatial Enabled - District Disaster Management Plan - GEDDMP System -- 3.1 Operation Strategy -- 3.2 Continuous Data Updation -- 3.3 Benefits of Geospatial Enabled-DDMP System -- 3.4 Geospatial Technology for Different Phases of Disaster Management -- 3.5 Geospatial Enabled DDMP Application Software Structure -- 3.6 Core Technology of Geospatial-DDMP Application Software -- 3.7 Workflow -- 3.8 Features of Survey Template HOOKs -- 3.9 Roadmap and Futuristic View -- References -- Information Technologies for Assessing the Effectiveness of the Quarantine Measures -- 1 Importance of Quarantine Measures -- 2 Variety of Quarantine Measures -- 3 Application of Restrictive Measures and the Need to Assess Their Efficiency -- 4 Selection of Modelling Approach for Quarantine Measure Efficiency -- 5 Overview of Epidemiology Models -- 6 Model Description and Development of Software -- 7 Model Description and Software Development -- 8 Discussion of Modelling Results -- 9 Scope of Application and Further Improvement of the Simulation Tool -- 10 Comparison of Modeling Results -- 11 Conclusions -- References -- Author Index.

The japanese invasion of manchuria and the rape of nanking : The history of the most notorious events of the second sino-japanese war. / / Charles River Editors

• Record Nr.: UNINA9910158876003321
• Autore: Editors Charles River
• Pubbl/distr/stampa: Solon, : Charles River Editors, 2016
• ISBN: 1-5094-2194-7
• Edizione: [Unabridged.]
• Descrizione fisica: 1 online resource (3 audio files) : digital
• Classificazione: HIS027100HIS037070
• Altri autori (Persone): FluxmanColin
• Soggetti: Nonfiction; History; Military
• Lingua di pubblicazione: Inglese
• Formato: Audiolibro
• Livello bibliografico: Monografia
• Note generali: Unabridged.
• Sommario/riassunto: Though scarcely mentioned in the world of early 21st century politics, Manchuria represented a key region of Asia during the first half of the 20th century. Once the heartland of the fierce Manchu empire, this northeastern Chinese region's rich natural resources made it a prize for nations in the process of entering the modern age, and three ambitious nations in the midst of such a transformation lay close enough to Manchuria to attempt to claim it: Japan, Russia, and China. For countries attempting to shake off their feudal past and enter a dynamic era of industrialization, Manchuria's resources presented an irresistible lure. With immense natural resources coupled to economic activity more concentrated than elsewhere in China, this region, abutting Mongolia, Korea, the Yellow Sea, and the Great Wall "accounted for 90 percent of China's oil, 70 percent of its iron, 55 percent of its gold, and 33 percent of its trade. If Shanghai remained China's commercial center, by 1931 Manchuria had become its industrial center." (Paine, 2012, 15). Thus, it's not altogether surprising that Japan's invasion of Manchuria in 1931 resulted from a long, complex chain of historical events stretching back to the late 19th century. Approximately 380,000 square miles in extent, or 1.4 times the size of the American state of ; Texas, Manchuria came into Imperial Russia's possession in 1900 due to the "Boxer Rebellion" in China, but the Russians held it only briefly; their defeat in the Russo-Japanese War shook loose their control from important parts of Manchuria by the end of 1905. The Japanese gained two important footholds in Manchuria thanks to their victory. One consisted of Port Arthur (renamed Ryojun by the Japanese), an economically and strategically vital harbor city on the Liaodung Peninsula, plus the peninsula itself. The other comprised the South Manchurian Railway, which the Russians gave to the Japanese as a prize of war, in lieu of a cash indemnity. Three days of plundering traditionally befell cities taken by storm, a fate usually avoided by those surrendering before the first attacking soldier penetrated beyond the outer walls. In Europe and areas influenced by Enlightenment thinkers, this practice faded rapidly after the Napoleonic Wars. In 1937, however, as the Imperial Army of Japan invaded China, this custom returned in a horrifying new form – the Rape of Nanking or the Nanking Massacre, a bloodbath lasting more than six weeks and possibly claiming more than a quarter of a million lives. Even the Japanese participating in the Nanking Massacre provided no rationale for their actions. They made no effort to explain it as a measure to terrorize other Chinese cities into surrender, or even to extract the location of hidden valuables. Instead, the Rape appears on the page of history as a psychopathic orgy of sadism for sadism's sake. Insatiably driven by hatred and, apparently, an unabashed relish for cruelty, the Japanese soldiery abandoned any semblance of restraint. Women of every age, from small children to ancient elders, suffered innumerable rapes, in many cases dying from the mass raping alone. Those who did not die from sexual assault suffered death in other forms – shot, decapitated, or tortured to death once the soldiers found themselves sexually exhausted. Other women suffered fatal sexual torture involving the introduction of sharp foreign objects into their vagina or the placement of firecrackers or live grenades inside. Even Third Reich personnel in the city interceded in a sometimes futile effort to rescue victims from their tormentors.