scholarly journals Citizen Participation in the Co-Production of Urban Natural Resource Assets

2022 ◽  
Vol 30 (6) ◽  
pp. 1-21
Author(s):  
Lei Li ◽  
Shaojun Ma ◽  
Runqi Wang ◽  
Yiping Wang ◽  
Yilin Zheng
Keyword(s):  
Natural Resources ◽  
Citizen Participation ◽  
Language Processing ◽  
Natural Resource ◽  
Urban Areas ◽  
Latent Dirichlet Allocation ◽  
Learning Algorithm ◽  
Analysis Method ◽  
Natural Landscape ◽  
Key Factor

Abundant natural resources are the basis of urbanisation and industrialisation. Citizens are the key factor in promoting a sustainable supply of natural resources and the high-quality development of urban areas. This study focuses on the co-production behaviours of citizens regarding urban natural resource assets in the age of big data, and uses the latent Dirichlet allocation algorithm and the stepwise regression analysis method to evaluate citizens’ experiences and feelings related to the urban capitalisation of natural resources. Results show that, firstly, the machine learning algorithm based on natural language processing can effectively identify and deal with the demands of urban natural resource assets. Secondly, in the experience of urban natural resources, citizens pay more attention to the combination of history, culture, infrastructure and natural landscape. Unique natural resource can enhance citizens’ sense of participation. Finally, the scenery, entertainment and quality and value of urban natural resources are the influencing factors of citizens’ satisfaction.

scholarly journals Analysis of the current state and features of natural resource potential management

2020 ◽  
Vol 157 ◽  
pp. 03005
Author(s):  
Anna Ermakova ◽  
Ludmila Oznobihina ◽  
Tatiana Avilova
Keyword(s):  
Natural Resources ◽  
Natural Resource ◽  
Swot Analysis ◽  
Nature Management ◽  
Analysis Method ◽  
Resource Potential ◽  
Detailed Consideration ◽  
Current State ◽  
Recreational Resources ◽  
Land Water

The article is devoted to the analysis of the current state of nature management in Mongolia. The natural resource potential of Mongolia, which includes mineral, land, water, biological and recreational resources, is shown. Administrative and legal mechanisms for managing natural resources in Mongolia and Russia are analyzed. Similar management methods of the two countries and distinctive aspects are revealed. For a more detailed consideration of the nature management features of Mongolia, the SWOT analysis method was used to identify strengths, weaknesses, opportunities and threats. Establishing chains of links between them can be useful in the future for formulating a country’s strategy for the use of natural resources.

scholarly journals Research on application of GPS-based wireless communication system in highway landslide

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Zhiwen Xiong
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Wireless Communication ◽  
Language Processing ◽  
Learning Algorithm ◽  
Detection System ◽  
Early Stage ◽  
Small Error ◽  
Deformation Monitoring ◽  
Analysis Method

AbstractMachine learning is a branch of the field of artificial intelligence. Deep learning is a complex machine learning algorithm that has unique advantages in image recognition, speech recognition, natural language processing, and industrial process control. Deep learning has It is widely used in the field of wireless communication. Prediction of geological disasters (such as landslides) is currently a difficult problem. Because landslides are difficult to detect in the early stage, this paper proposes a GPS-based wireless communication continuous detection system and applies it to landslide deformation monitoring to achieve early treatment and prevention. This article introduces the GPS multi-antenna detection system based on deep learning wireless communication, and introduces the time series analysis method and its application. The test results show that the GPS multi-antenna detection system of the wireless communication network has great advantages in response time, with high accuracy and small error. The horizontal accuracy is controlled at 0–2 mm and the vertical accuracy is about 1 mm. The analysis method is simple and efficient, and can obtain good results for short-term deformation prediction.

scholarly journals A Light Recommendation Algorithm of We-Media Articles Based on Content

2020 ◽  
Vol 12 (4) ◽  
pp. 68-81
Author(s):  
Xin Zheng ◽  
Jun Li ◽  
Qingrong Wu
Keyword(s):  
Deep Learning ◽  
Language Processing ◽  
Recurrent Neural Networks ◽  
Latent Dirichlet Allocation ◽  
Topic Model ◽  
Learning Algorithm ◽  
Personalized Recommendation ◽  
Combined Method ◽  
Recommendation Algorithm ◽  
Deep Learning Algorithm

Since the explosive growth of we-medias today, personalized recommendation is playing an increasingly important role to help users to find their target articles in vast amounts of data. Deep learning, on the other hand, has shown good results in image processing, computer vision, natural language processing, and other fields. But it's a relative blank in the application of we-media articles recommendation. Combining the new features of we-media articles, this paper puts forward a recommendation algorithm of we-media articles based on topic model, Latent Dirichlet Allocation (LDA), and deep learning algorithm, Recurrent Neural Networks (RNNs). Experiments on the real datasets show that the combined method outperforms the traditional collaborative filtering recommendation and non-personalized recommendation method.

Talent Acquisition Process Optimization Using Machine Learning in Resumes’ Ranking and Matching to Job Descriptions

2021 ◽  
Author(s):  
Mohammed Alghazal
Keyword(s):  
Machine Learning ◽  
Language Processing ◽  
Optical Character Recognition ◽  
Computational Models ◽  
Latent Dirichlet Allocation ◽  
Learning Algorithm ◽  
Screening Tools ◽  
Job Descriptions ◽  
Job Description ◽  
Description File

Abstract Employers commonly use time-consuming screening tools or online matching engines that are driven by manual roles and predefined keywords, to search for potential job applicants. Such traditional techniques have not kept pace with the new digital revolution in machine learning and big data analytics. This paper presents advanced artificial intelligent solutions employed for ranking resumes and CV-to-Job Description matching. Open source resumes and job descriptions' documents were used to construct and validate the machine learning models in this paper. Documents were converted to images and processed via Google cloud using Optical Character Recognition algorithm (OCR) to extract text information from all resumes and job descriptions' documents, with more than 97% accuracy. Prior to modeling, the extracted text were processed via a series of Natural Language Processing (NLP) techniques by splitting/tokenizing common words, grouping together inflected form of words, i.e. lemmatization, and removal of stop words and punctuation marks. After text processing, resumes were trained using the unsupervised machine learning algorithm, Latent Dirichlet Allocation (LDA), for topic modeling and categorization. Given the type of resumes used, the algorithm was able to categorize them into 4 main job sectors: marketing and business, engineering, computer science/IT and health. Scores were assigned to each resume to represent the maximum LDA probability for ranking. Another more advanced deep learning algorithm, called Doc2Vec, was also used to train and match potential resumes to relevant job descriptions. In this model, resumes are represented by unique vectors that can be used to group similar documents, match and retrieve resumes related to a given job description document provided by HR. The similarity is measured between each resume and the given job description file to query the top job candidates. The model was tested against several job description files related to engineering, IT and human resources, and was able to identify the top-ranking resumes from over hundreds of trained resumes. This paper presents an innovative method for processing, categorizing and ranking resumes using advanced computational models empowered by the latest fourth industrial resolution technologies. This solution is beneficial to both job seekers and employers, providing efficient and unbiased data-driven method for finding top applicants for a given job.

scholarly journals Conscious approach to urban and extra-urban space restructuring as seen in the designs of Architecture students

2018 ◽  
Vol 174 ◽  
pp. 04016
Author(s):  
Joanna Gil-Mastalerczyk
Keyword(s):  
Natural Resources ◽  
Urban Space ◽  
Creative Process ◽  
Urban Areas ◽  
Interdisciplinary Approach ◽  
Urban Spaces ◽  
Architectural Education ◽  
Natural Landscape ◽  
Urban Forms ◽  
Future Work

In education of architects and urban planners, it is important to rely on interdisciplinary approach to many factors involved in the process. Especially in the built environment context, the awareness of the interaction of different components is of key importance. In their future work, architecture students need to have responsible and socially-oriented standpoint. It will be demonstrated in the creation of architectural objects in the natural landscape surroundings, and in the attitude to different type of architectural and urban spaces. Safety, the use of natural resources, the relations between architecture and the surrounds, the evaluation of the environmental components and their impact on the creative process are extremely important. The paper discusses examples of space solutions in the urban areas and those located outside cities. Those solutions involve daring architectural and urban forms that make use of the natural environment assets, and also quality architectural work and design. The presence of such objects is a response to the demand from the society, consequently it seems reasonable to explore the issues related to architectural education.

Integration of Human/Social Dimensions into the Traditional European Model of Natural Resource Education and Management

2005 ◽  
Vol 156 (8) ◽  
pp. 264-268
Author(s):  
James J. Kennedy ◽  
Niels Elers Koch
Keyword(s):  
Natural Resources ◽  
Natural Resource ◽  
Life Forms ◽  
Western World ◽  
Social Dimensions ◽  
Roles And Responsibilities ◽  
Resource Managers ◽  
Natural Resource Managers ◽  
Rural Ecosystem ◽  
Professional Roles And Responsibilities

The increasing diversity, complexity and dynamics of ecosystem values and uses over the last 50 years requires new ways for natural resource managers (foresters, wildlife biologists, etc.)to understand and relate to their professional roles and responsibilities in accommodating urban and rural ecosystem users, and managing the complimentary and conflicting interactions between them. Three stages in Western-world natural resources management are identified and analyzed, beginning with the (1) Traditional stage: natural resources first, foremost and forever, to (2) Transitional stage: natural resource management,for better or worse, involves people, to (3) Relationship stage: managing natural resources for valued people and ecosystem relationships. The impacts of these three perspectives on how natural resource managers view and respond to ecosystems,people and other life-forms is basic and can be profound.

Designing a Chat-Bot for College Information using Information Retrieval and Automatic Text Summarization Techniques

2020 ◽  
Vol 01 ◽  
Author(s):  
Radha Guha
Keyword(s):  
Information Retrieval ◽  
Language Processing ◽  
Latent Dirichlet Allocation ◽  
Semantic Analysis ◽  
Text Summarization ◽  
The Internet ◽  
Specific Domain ◽  
User Query ◽  
College Information ◽  
Chat Bot

Background:: In the era of information overload it is very difficult for a human reader to make sense of the vast information available in the internet quickly. Even for a specific domain like college or university website it may be difficult for a user to browse through all the links to get the relevant answers quickly. Objective:: In this scenario, design of a chat-bot which can answer questions related to college information and compare between colleges will be very useful and novel. Methods:: In this paper a novel conversational interface chat-bot application with information retrieval and text summariza-tion skill is designed and implemented. Firstly this chat-bot has a simple dialog skill when it can understand the user query intent, it responds from the stored collection of answers. Secondly for unknown queries, this chat-bot can search the internet and then perform text summarization using advanced techniques of natural language processing (NLP) and text mining (TM). Results:: The advancement of NLP capability of information retrieval and text summarization using machine learning tech-niques of Latent Semantic Analysis(LSI), Latent Dirichlet Allocation (LDA), Word2Vec, Global Vector (GloVe) and Tex-tRank are reviewed and compared in this paper first before implementing them for the chat-bot design. This chat-bot im-proves user experience tremendously by getting answers to specific queries concisely which takes less time than to read the entire document. Students, parents and faculty can get the answers for variety of information like admission criteria, fees, course offerings, notice board, attendance, grades, placements, faculty profile, research papers and patents etc. more effi-ciently. Conclusion:: The purpose of this paper was to follow the advancement in NLP technologies and implement them in a novel application.

Language Movement and Civil War in West Africa

2018 ◽  
Author(s):  
Ericka A. Albaugh
Keyword(s):  
Civil War ◽  
Sierra Leone ◽  
Citizen Participation ◽  
Urban Areas ◽  
Political Process ◽  
The Political ◽  
Political Consequences ◽  
Language Spread ◽  
The 1960S

This chapter examines how civil war can influence the spread of language. Specifically, it takes Sierra Leone as a case study to demonstrate how Krio grew from being primarily a language of urban areas in the 1960s to one spoken by most of the population in the 2000s. While some of this was due to “normal” factors such as population movement and growing urbanization, the civil war from 1991 to 2002 certainly catalyzed the process of language spread in the 1990s. Using census documents and surveys, the chapter tests the hypothesis at the national, regional, and individual levels. The spread of a language has political consequences, as it allows for citizen participation in the political process. It is an example of political scientists’ approach to uncovering the mechanisms for and evidence of language movement in Africa.

Water for Life

2017 ◽  
Author(s):  
Madeline Baer
Keyword(s):  
Human Rights ◽  
Citizen Participation ◽  
Urban Areas ◽  
Water Policy ◽  
State Capacity ◽  
National Level ◽  
Human Right ◽  
Political Will ◽  
Water And Sanitation ◽  
The Right

Chapter 5 provides a case study of the human rights-based approach to water policy through an analysis of the Bolivian government’s attempts to implement the human right to water and sanitation. It explores these efforts at the local and national level, through changes to investments, institutions, and policies. The analysis reveals that while Bolivia meets the minimum standard for the human right to water and sanitation in some urban areas, access to quality water is low in poor and marginalized communities. While the Bolivian government expresses a strong political will for a human rights approach and is increasing state capacity to fulfill rights, the broader criteria for the right to water and sanitation, including citizen participation and democratic decision-making, remain largely unfulfilled. This case suggests political will and state capacity might be necessary but are not sufficient to fulfill the human right to water and sanitation broadly defined.

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