scholarly journals Understanding of landslide risk through learning by doing: case study of Koroška Bela community, Slovenia

Landslides ◽  
2018 ◽  
Vol 16 (9) ◽  
pp. 1681-1690
Author(s):  
Mateja Jemec Auflič ◽  
Špela Kumelj ◽  
Tina Peternel ◽  
Jernej Jež
Keyword(s):  
Learning By Doing ◽  
Landslide Risk

Contamination Lab of Turin (CLabTo)

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Eleonora FIORE ◽  
Giuliano SANSONE ◽  
Chiara Lorenza REMONDINO ◽  
Paolo Marco TAMBORRINI
Keyword(s):  
University Students ◽  
Single Case ◽  
Real Life ◽  
Learning By Doing ◽  
Assessment Data ◽  
Entrepreneurial Skills ◽  
Fields Of Study ◽  
Education Levels ◽  
Positive Effect

Interest in offering Entrepreneurship Education (EE) to all kinds of university students is increasing. Therefore, universities are increasing the number of entrepreneurship courses intended for students from different fields of study and with different education levels. Through a single case study of the Contamination Lab of Turin (CLabTo), we suggest how EE may be taught to all kinds of university students. We have combined design methods with EE to create a practical-oriented entrepreneurship course which allows students to work in transdisciplinary teams through a learning-by-doing approach on real-life projects. Professors from different departments have been included to create a multidisciplinary environment. We have drawn on programme assessment data, including pre- and post-surveys. Overall, we have found a positive effect of the programme on the students’ entrepreneurial skills. However, when the data was broken down according to the students’ fields of study and education levels, mixed results emerged.

Landslide Risk Level Assessment Based on Erosion-Induced Landslide: A Case Study at Uitm Campus, Selangor

2017 ◽  
pp. 29-40
Author(s):  
Mohd Fozi Ali ◽  
Muhammad Solahuddeen Mohd Sabri ◽  
Khairi Khalid ◽  
Nor Faiza Abd Rahman
Keyword(s):  
Risk Level ◽  
Landslide Risk

Fish Habitat: Essential Fish Habitat and Rehabilitation

1999 ◽  
Keyword(s):  
Lake Erie ◽  
Habitat Management ◽  
Fish Habitat ◽  
Learning By Doing ◽  
Suitable Habitat ◽  
Physical Habitat ◽  
Fish Stocks ◽  
Habitat Features ◽  
Fish Habitats

<em>Abstract.—</em> The quality and quantity of habitats determine ecosystem productivity. Hence, they determine the potential fish productivity that sustains the fish harvests extractable from freshwaters and seas. Efforts to conserve and protect fish habitats are frustrated by key unanswered questions: which habitat types and how much must be protected to ensure natural self-sustaining fish stocks? Minns and Bakelaar presented a prototype method for assessing suitable habitat supply for fish stocks in Lake Erie, an analysis that can be used to address conservation issues. Here, the method is refined and extended, taking the assessment of habitat supply for pike <em>Esox lucius </em> in the Long Point region of Lake Erie as a case study. As with the previous study, much emphasis is placed on “learning by doing.” Because available inventories of habitat features are coarse and incomplete, improved guidelines for estimating habitat supply are expected from these prototype studies. The habitat supply method previously presented by Minns and Bakelaar is elaborated in three ways here: (1) the basic physical habitat assessment is derived from a remote-sensing inventory database; (2) methods of quantifying the thermal regime and integrating it with other habitat elements are examined; (3) habitat supply estimates are used in a pike population model, and pike biomass and production are simulated for the Long Point region of Lake Erie and then compared with available records. The roles of error and uncertainty are examined for all elements in the estimation and application of suitable habitat supply values. There is potential for supply measurement and analysis to guide fish habitat management.

scholarly journals Probabilistic landslide risk assessment: Case study of Bujumbura

2018 ◽  
Vol 251 ◽  
pp. 06011
Author(s):  
Gervais Shirambere ◽  
Maurice O. Nyadawa ◽  
Jean pierre Masekanya ◽  
Timothy Nyomboi
Keyword(s):  
Risk Assessment ◽  
Monte Carlo Simulation ◽  
Landslide Risk ◽  
Cell Level ◽  
Monte Carlo Simulation Technique ◽  
Mapping Model ◽  
Coulomb Failure ◽  
Landslide Risk Assessment ◽  
Coulomb Failure Criterion

A spatial probabilistic landslide risk assessment and mapping model has been applied in a data scare region. The probabilistic model is based on a physical model based on Mohr coulomb failure criterion. A Monte Carlo simulation technique is applied to field collected data. The results are integrated and a probability of landslide is obtained at each cell level. The results are compared to a prepared landslide inventory. The overall accuracy of the model is 79.69%.

Introduce a framework for landslide risk assessment using geospatial analysis: a case study from Kegalle District, Sri Lanka

2020 ◽  
Vol 6 (4) ◽  
pp. 2415-2431 ◽  
Author(s):  
E. N. C. Perera ◽  
D. T. Jayawardana ◽  
Manjula Ranagalage ◽  
D M S L B Dissanayake ◽  
H. M. D. S. Wijenayaka
Keyword(s):  
Risk Assessment ◽  
Sri Lanka ◽  
Geospatial Analysis ◽  
Landslide Risk ◽  
Landslide Risk Assessment

scholarly journals What Is WhatsApp for? Developing Transmedia Skills and Informal Learning Strategies Through the Use of WhatsApp—A Case Study With Teenagers From Spain

2020 ◽  
Vol 6 (3) ◽  
pp. 205630512094288
Author(s):  
Carmen Costa-Sánchez ◽  
Mar Guerrero-Pico
Keyword(s):  
Informal Learning ◽  
Learning Strategies ◽  
Learning By Doing ◽  
The Other ◽  
Management Skills ◽  
Social Content ◽  
Daily Lives ◽  
Case Study Methodology ◽  
Study Methodology

Smartphones and WhatsApp are, respectively, the medium and application that Spanish teenagers most want. However, research into the use of WhatsApp is still quantitatively and qualitatively limited. In addition, little research has been carried out regarding its impact on the development of transmedia skills and informal learning strategies outside the classroom. This article aims to expand the knowledge on teenagers’ motivations and their development of transmedia skills and informal learning strategies in relation to their use of WhatsApp. Specifically, a qualitative analysis of data gathered from workshops, interviews, and media diaries is applied as part of a case study methodology involving teenagers from 10 schools located in five different Spanish regions. The results reveal the new WhatsApp uses teenagers are applying in their daily lives as well as the skills and strategies they are developing through said uses in the context of interpersonal and group (WhatsApp groups) interactions: on one hand, production, social, content, and individual management skills, and on the other hand, learning by doing, teaching, and evaluating strategies.

DTM-based landslide detection using deep learning: A case study in Hong Kong

2020 ◽  
Author(s):  
Haojie Wang ◽  
Limin Zhang
Keyword(s):  
Hong Kong ◽  
Deep Learning ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Digital Terrain Model ◽  
Landslide Inventory ◽  
Landslide Risk ◽  
Visual Interpretation ◽  
Learning Techniques

&lt;p&gt;Landslide detection is an essential component of landslide risk assessment and hazard mitigation. It can be used to produce landslide inventories which are considered as one of the fundamental auxiliary data for regional landslide susceptibility analysis. In order to achieve high landslide interpretation accuracy, visual interpretation is frequently used, but suffers in time efficiency and labour demand. Hence, an automatic landslide detection method utilizing deep learning techniques is implemented in this work to conduct high-accuracy and fast landslide interpretation. As the ground characteristics and terrain features can precisely capture the three-dimensional space form of landslides, high-resolution digital terrain model (DTM) is taken as the data source for landslide detection. A case study in Hong Kong, China is conducted to validate the applicability of deep learning techniques in landslide detection. The case study takes multiple data layers derived from the DTM (e.g., elevation, slope gradient, aspect, etc.) and a local landslide inventory named enhanced natural terrain landslide inventory (ENTLI) as its data sources, and integrates them into a database for learning. Then, a deep learning technique (e.g., convolutional neural network) is used to train models on the database and perform landslide detection. Results of the case study show great performance and capacity of the applied deep learning techniques, which provides valuable references for advancing landslide detection.&lt;/p&gt;

Infrastructure, Commodity Spectra, and Trade Transitions in Economic Development

2009 ◽  
Vol 9 (2) ◽  
pp. 1850166
Author(s):  
Roger J. Bowden ◽  
Hui Huang
Keyword(s):  
Human Capital ◽  
Development Strategy ◽  
Financial Services ◽  
Learning By Doing ◽  
Social Spending ◽  
Accelerate Growth ◽  
Physical Infrastructure ◽  
Capital Services ◽  
Manufactured Exports

Infrastructure growth and its regional concentration can accelerate growth and diversification of international trade, in terms of both commodities and the implied factor content. The origins and mechanism are explored via a model of endogenous growth that internalizes social spending on physical infrastructure, leading to the accumulation of human capital as a result of learning by doing. Infrastructure developed in the first instance to enhance and diversify manufactured exports can create a supply push into the export of human capital services. As a leading case study, China's recent free trade agreements show clear signs of a development strategy shifting orientation towards the export of services, such as those relating to infrastructure construction and tourism, and the financial services required in support.

Heterogeneous IS Resources Acquisition: A Case Study

2010 ◽  
Vol 26-28 ◽  
pp. 426-429
Author(s):  
Bao Liang Hu
Keyword(s):  
Human Capital ◽  
Information Systems ◽  
Learning By Doing ◽  
Heterogeneous Information ◽  
Heterogeneous Information Systems ◽  
Learning By Using

Combined with the deep case study of Wahaha, this paper probe into the issue of enterprise heterogeneous information systems(IS) resources acquisition. And the findings show: learning by doing and learning by using are the effective approaches for the enterprise to acquire the heterogeneous IS human capital; initiative is crucial to acquire heterogeneous IS partnership; the preferred contractor is the important model for the enterprises to acquire the heterogeneous IS infrastructure. These findings not only enrich the theory of IS resources, but also expand the scope of existing research.

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