Studying and mapping the soils of the southern part Sea of Okhotsk sector of the Kunashir island, Kuril islands

2021 ◽  
Vol 969 (3) ◽  
pp. 19-27
Author(s):  
M.Yu. Grischchenko ◽  
V.V. Khlyustova ◽  
E.A. Izyumnikova ◽  
I.V. Kalimova
Keyword(s):  
Large Scale ◽  
Nature Reserve ◽  
Soil Cover ◽  
High Spatial Resolution ◽  
Field Surveys ◽  
Kunashir Island ◽  
Soil Forming Processes ◽  
Kuril Ridge ◽  
Different Levels ◽  
Zonal Soils

The paper deals with compilation of a large-scale soil map for the site of “Kurilsky” nature reserve, located in the southern part of Kunashir island, the Greater Kuril ridge. The islands make a remote and poorly studied area, and the soil is one of the least examined components of the local geosystems. The zonal soils here are cambisoil, but the variety of soil-forming processes characteristic of the island provides a comparative diversity of the cover. Modern volcanism affects the formation process significantly, although its role is sometimes overestimated. The study is based on field surveys performed in the considered area in 2014–2019, during which descriptions of soils were compiled according to standard methods. The map was compiled using a multispectral image of high spatial resolution from the Pleiades-1B satellite and topographic maps. Thus, the abundance of soils from different levels and divisions does not make a significant effect on the general heterogeneity of the territory soil cover due to the small area of intrazonal soils.

Soil Spatial Heterogeneity and Systems of Agriculture

2015 ◽  
Vol 2 (1) ◽  
pp. 50-59
Author(s):  
V. Medvedev
Keyword(s):  
Spatial Heterogeneity ◽  
Soil Cover ◽  
Regular Grid ◽  
Resource Saving ◽  
The Third ◽  
Soil Spatial Heterogeneity ◽  
Agriculture Systems ◽  
Zonal Soils

Aim. To consider soil continuality and discreteness as features of heterogeneity manifestation in a soil cover, important for construction of agriculture systems. Methods. Geostatistical research of soil spatial heterogeneity, revealing the contours of a fi eld with various parameters of fertility. Results. The use of principles of precise agriculture and inspection of indicative properties of fi eld soils using a regular grid allowed to divide a fi eld into contours with three levels of fertility: the fi rst one is characterized by optimal or close to optimum properties which allows refusing from (or reducing substantially) tillage, introduction of fertilizers or chemical ameliorates; the second one has average parameters of fertility corresponding to zonal soils and demands the application of zonal technologies; the third one (with the worst parameters of fertility) presupposes regular use of the improved technologies. Conclusions. The introduction of precise agriculture will allow replacing a traditional zonal system with thenew which is soil-protecting and resource-saving one.

Creation of large-scale and middle-scale geomorphological maps of Kunashir Island (Kuril Islands)

2020 ◽  
Vol 64 (4) ◽  
pp. 423-434
Author(s):  
Grishchenko M.Y. ◽  
◽  
Shishkin V.S. ◽  
◽  
◽  
...  
Keyword(s):  
Large Scale ◽  
Kuril Islands ◽  
Kunashir Island

Рассмотрены результаты продолжавшихся несколько лет работ по детальному геоморфологическому картографированию участка заповедника «Курильский», остров Кунашир, Большая Курильская гряда. Слабо изученная и труднодоступная территория обследована с применением методов полевых геоморфологических исследований и полевых методов дешифрирования космических снимков. В результате этой работы собран обширный полевой материал о рельефе южной части острова Кунашир, который проанализирован и обобщён в форме серии крупномасштабных геоморфологических карт. Ранее на рассматриваемую территорию карты такого масштаба и такой тематики не создавались

Classification of woody-shrub vegetation of the forest-steppe complex of Privolzhskaya Upland

2009 ◽  
pp. 27-53
Author(s):  
A. Yu. Kudryavtsev
Keyword(s):  
Plant Community ◽  
Plant Communities ◽  
Dominant Species ◽  
Large Scale ◽  
Nature Reserve ◽  
Vegetation Mapping ◽  
Vegetation Classification ◽  
Forest Steppe ◽  
Mapping Data

Diversity of plant communities in the nature reserve “Privolzhskaya Forest-Steppe”, Ostrovtsovsky area, is analyzed on the basis of the large-scale vegetation mapping data from 2000. The plant community classi­fication based on the Russian ecologic-phytocoenotic approach is carried out. 12 plant formations and 21 associations are distinguished according to dominant species and a combination of ecologic-phytocoenotic groups of species. A list of vegetation classification units as well as the characteristics of theshrub and woody communities are given in this paper.

scholarly journals Classification of Very-High-Spatial-Resolution Aerial Images Based on Multiscale Features with Limited Semantic Information

2021 ◽  
Vol 13 (3) ◽  
pp. 364
Author(s):  
Han Gao ◽  
Jinhui Guo ◽  
Peng Guo ◽  
Xiuwan Chen
Keyword(s):  
Deep Learning ◽  
Land Cover ◽  
Spatial Resolution ◽  
Large Scale ◽  
High Spatial Resolution ◽  
Training Data ◽  
Aerial Images ◽  
Rural Landscapes ◽  
Feature Representations ◽  
Object Based

Recently, deep learning has become the most innovative trend for a variety of high-spatial-resolution remote sensing imaging applications. However, large-scale land cover classification via traditional convolutional neural networks (CNNs) with sliding windows is computationally expensive and produces coarse results. Additionally, although such supervised learning approaches have performed well, collecting and annotating datasets for every task are extremely laborious, especially for those fully supervised cases where the pixel-level ground-truth labels are dense. In this work, we propose a new object-oriented deep learning framework that leverages residual networks with different depths to learn adjacent feature representations by embedding a multibranch architecture in the deep learning pipeline. The idea is to exploit limited training data at different neighboring scales to make a tradeoff between weak semantics and strong feature representations for operational land cover mapping tasks. We draw from established geographic object-based image analysis (GEOBIA) as an auxiliary module to reduce the computational burden of spatial reasoning and optimize the classification boundaries. We evaluated the proposed approach on two subdecimeter-resolution datasets involving both urban and rural landscapes. It presented better classification accuracy (88.9%) compared to traditional object-based deep learning methods and achieves an excellent inference time (11.3 s/ha).

scholarly journals Potential Energy Implications of Connected and Automated Vehicles: Exploring Key Leverage Points through Scenario Screening and Analysis

2019 ◽  
Vol 2673 (5) ◽  
pp. 84-94 ◽  
Author(s):  
Brian Bush ◽  
Laura Vimmerstedt ◽  
Jeff Gonder
Keyword(s):  
Systems Engineering ◽  
Large Scale ◽  
Operating Cost ◽  
Dynamics Model ◽  
Transportation Service ◽  
Service Outcomes ◽  
Behavioral Parameters ◽  
Computationally Intensive ◽  
Different Levels ◽  
Selection Of

Connected and automated vehicle (CAV) technologies could transform the transportation system over the coming decades, but face vehicle and systems engineering challenges, as well as technological, economic, demographic, and regulatory issues. The authors have developed a system dynamics model for generating, analyzing, and screening self-consistent CAV adoption scenarios. Results can support selection of scenarios for subsequent computationally intensive study using higher-resolution models. The potential for and barriers to large-scale adoption of CAVs have been analyzed using preliminary quantitative data and qualitative understandings of system relationships among stakeholders across the breadth of these issues. Although they are based on preliminary data, the results map possibilities for achieving different levels of CAV adoption and system-wide fuel use and demonstrate the interplay of behavioral parameters such as how consumers value their time versus financial parameters such as operating cost. By identifying the range of possibilities, estimating the associated energy and transportation service outcomes, and facilitating screening of scenarios for more detailed analysis, this work could inform transportation planners, researchers, and regulators.

Educating Democratic Character

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Natalia Rogach Alexander ◽  
Philip Kitcher
Keyword(s):  
Large Scale ◽  
Democratic Education ◽  
Political Life ◽  
Individual Experience ◽  
Main Work ◽  
Mutual Engagement ◽  
Democratic Character ◽  
Imminent Death ◽  
Different Levels

Abstract Many recent writers on democracy have lamented its decay and warned of its imminent death. We argue that the concerns are focused at three different levels of democracy. The most fundamental of these, celebrated by Tocqueville and by Dewey, recognizes the interactions and joint deliberations among citizens who seek sympathetic mutual engagement. Such engagement is increasingly rare in large-scale political life. In diagnosing and treating the problems, we recommend returning to the debate between Lippmann and Dewey, in which many of the concerns now prominent were already voiced. This inspires the main work of the paper – the reconstruction of Dewey’s conception of democracy as a ‘mode of associated living’. We focus on the thesis that democracy is educative and explicate Dewey’s notion of growth, showing how democratic education contributes to three important functions: the capacity for sustaining oneself, the enrichment of individual experience, and the ability to enter into cooperative discussions with fellow citizens. Dewey’s conception of democratic education is directed at fostering particular virtues and, if citizens come to possess them, the need for Lippmann’s ‘omnicompetent individual’ vanishes. We conclude by suggesting that Dewey’s project of educating democratic character is pertinent for addressing the disaffection of our times.

Construction of Essential Care Service Package for People Living with Dementia in Smoke-free Environment under Disease Pandemic in China

2021 ◽  
Vol 7 (4) ◽  
pp. 308-325
Author(s):  
Tongda Sun ◽  
Hongdao Meng ◽  
Mingze Zhu ◽  
Xiaoxin Dong ◽  
Naidan Tu ◽  
...  
Keyword(s):  
Large Scale ◽  
Care Service ◽  
Cluster Sampling ◽  
Service Needs ◽  
Public Attention ◽  
Term Care ◽  
Service Package ◽  
Care Services ◽  
Free Environment ◽  
Different Levels

Objectives: In recent years, the harm of smoking has attracted more and more public attention. Creating a healthy smoke-free environment has been widely favored and supported by the public. Smokeless environment has a certain positive effect on the rehabilitation of dementia patients. Sustained smoking cessation is associated with significantly decreased the future prevalence of dementia. Therefore, hospitals often establish a special organizational structure and management model for tobacco control, and carry out training and assessment for all staff. The nursing group also took it as the basic nursing standard. The 2019 disease pandemic has posed unique health threats to people living with dementia (PLWD). Therefore, a strict smoke-free environment is more necessary for the nursing group. One of the key challenges is scaling up long-term care services to meet the needs of the rapidly growing population of PLWD in developing countries. The aim of the study is to explore the care service needs, utilization and build an essential care service package (ECSP) for PLWD under the disease pandemic in China. Methods: From July 2018 to October 2019, a total of 1255 elderly with dementia in six cities in China by a cluster sampling were investigated with the self-designed questionnaire. Care service needs and utilization for PLWD with different levels of cognitive impairment were summarized. Results: The ECSP for PLWD was composed of 30 service items (7 for core care) in order to guarantee that all PLWD enjoy equal care services, basing on public financing and implementing strategies and taking China's situations into account. The selection plan for ECSP at different levels is designed as 'General Care Services + Selective Care Services ', in which respective service items for low, mid, and high-level care for PLWD are 7+3, 7+6, and 7+10, and requires 151.41 hours, 201.88 hours, and 252.35 hours per month, respectively. Conclusion: The present study provides the first large-scale data on care service needs and utilization for PLWD in mainland China. The ECSP for PLWD based on the needs advanced in the paper was a practicable and effective quantitative management means that deserves a large-scale application. Some safeguard mechanisms and operational implementing pathways of ECSP for PLWD during and after the disease pandemic in China are proposed.

Scale, Landscape and Indigenous Bedouin Land Use: Spatial Order and Agricultural Sedentarisation in the Negev Highland

2021 ◽  
Vol 25 (1) ◽  
pp. 4-35
Author(s):  
Ariel Meraiot ◽  
Avinoam Meir ◽  
Steve Rosen
Keyword(s):  
Large Scale ◽  
Small Scale ◽  
Scale Analysis ◽  
Structure Development ◽  
British Mandate ◽  
Field Surveys ◽  
Ordered Field ◽  
Modern Period ◽  
Ordered Space ◽  
Sustainable Planning

By taking a small-scale perspective, Bedouin pastoral space in the Israeli Negev in the modern period has been misinterpreted as chaotic by various Israeli institutions. In critiquing this ontology we suggest that a knowledge gap with regard to an appropriate scale of understanding Bedouin settlement patterns and mechanisms of sedentarisation is at its root, and that a larger-scale analysis indicates that their space is in fact highly ordered. Field surveys and interviews with the local Bedouin showed that household cultivation plots in the Negev Highland during the period of the British Mandate were organised at a large scale through natural and man-made landscape features reflecting their structure, development and deployment in a highly ordered space. This analysis carries significant implications for understanding pastoral spaces at the local scale, particularly offering better comprehension of various sedentary forms and suggesting new approaches to sustainable planning and development for the Bedouin.

scholarly journals Phát triển Framework ứng dụng AI hỗ trợ tự động khai thác lỗ hổng bảo mật

2022 ◽  
Vol 1 (13) ◽  
pp. 80-92
Author(s):  
Nguyễn Mạnh Thiên ◽  
Phạm Đăng Khoa ◽  
Nguyễn Đức Vượng ◽  
Nguyễn Việt Hùng
Keyword(s):  
Information System ◽  
Reinforcement Learning ◽  
Information Security ◽  
Vulnerability Assessment ◽  
Large Scale ◽  
Learning Technology ◽  
Security Assessment ◽  
Security Vulnerability ◽  
Different Levels

Tóm tắt—Hiện nay, nhiệm vụ đánh giá an toàn thông tin cho các hệ thống thông tin có ý nghĩa quan trọng trong đảm bảo an toàn thông tin. Đánh giá/khai thác lỗ hổng bảo mật cần được thực hiện thường xuyên và ở nhiều cấp độ khác nhau đối với các hệ thống thông tin. Tuy nhiên, nhiệm vụ này đang gặp nhiều khó khăn trong triển khai diện rộng do thiếu hụt đội ngũ chuyên gia kiểm thử chất lượng ở các cấp độ khác nhau. Trong khuôn khổ bài báo này, chúng tôi trình bày nghiên cứu phát triển Framework có khả năng tự động trinh sát thông tin và tự động lựa chọn các mã để tiến hành khai thác mục tiêu dựa trên công nghệ học tăng cường (Reinforcement Learning). Bên cạnh đó Framework còn có khả năng cập nhật nhanh các phương pháp khai thác lỗ hổng bảo mật mới, hỗ trợ tốt cho các cán bộ phụ trách hệ thống thông tin nhưng không phải là chuyên gia bảo mật có thể tự động đánh giá hệ thống của mình, nhằm giảm thiểu nguy cơ từ các cuộc tấn công mạng. Abstract—Currently, security assessment is one of the most important proplem in information security. Vulnerability assessment/exploitation should be performed regularly with different levels of complexity for each information system. However, this task is facing many difficulties in large-scale deployment due to the lack of experienced testing experts. In this paper, we proposed a Framework that can automatically gather information and automatically select suitable module to exploit the target based on reinforcement learning technology. Furthermore, our framework has intergrated many scanning tools, exploited tools that help pentesters doing their work. It also can be easily updated new vulnerabilities exploit techniques.

scholarly journals Importance-Aware Learning for Neural Headline Editing

2020 ◽  
Vol 34 (05) ◽  
pp. 9282-9289
Author(s):  
Qingyang Wu ◽  
Lei Li ◽  
Hao Zhou ◽  
Ying Zeng ◽  
Zhou Yu
Keyword(s):  
Social Media ◽  
Large Scale ◽  
Network Models ◽  
Language Models ◽  
Neural Network Models ◽  
Generation Task ◽  
Social Media Platforms ◽  
Editing Process ◽  
Different Levels

Many social media news writers are not professionally trained. Therefore, social media platforms have to hire professional editors to adjust amateur headlines to attract more readers. We propose to automate this headline editing process through neural network models to provide more immediate writing support for these social media news writers. To train such a neural headline editing model, we collected a dataset which contains articles with original headlines and professionally edited headlines. However, it is expensive to collect a large number of professionally edited headlines. To solve this low-resource problem, we design an encoder-decoder model which leverages large scale pre-trained language models. We further improve the pre-trained model's quality by introducing a headline generation task as an intermediate task before the headline editing task. Also, we propose Self Importance-Aware (SIA) loss to address the different levels of editing in the dataset by down-weighting the importance of easily classified tokens and sentences. With the help of Pre-training, Adaptation, and SIA, the model learns to generate headlines in the professional editor's style. Experimental results show that our method significantly improves the quality of headline editing comparing against previous methods.

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