The project is planned to be developed on the offshore filling area. In order to enable small and large ships to enter and exit the port, the company has to pump and build a port of entry and exit, the pumped sediment will be filled at the location of the Kampot special economic zone and International Port.

ESIA for Propose Pacific Nickel Mining Ltd at Kolosori, Isabel

Phu Yang (Cambodia) Co., Ltd. plans to invest in a metal mining project in Phnom Prek Area, Phnom Prek District, Battambang Province on an area of 4 square kilometers. This report focuses on the environmental and social impact assessment of the metal mining development project.

The Artificial Intelligence (AI) mining market is rapidly evolving and playing a pivotal role in transforming various industries by enhancing data analysis and decision-making processes. As businesses strive to harness the vast amounts of data generated each day, AI-powered mining solutions are emerging as essential

Includes articles on: - Commonwealth government involvement in the Alligator Rivers Region (ARR). Knowledge directory and appendix on guidelines for research. - Commonwealth government involvement in the Alligator Rivers Region (ARR). Knowledge... Includes articles on: - Commonwealth government involvement in the Alligator Rivers Region (ARR). Knowledge directory and appendix on guidelines for research. - Commonwealth government involvement in the Alligator Rivers Region (ARR). Knowledge directory. - Report to the Minister of Aboriginal Affairs on the social impact of uranium mining on the Aborigines of the Northern Territory. - Social impact of uranium mining on Aborigines of the Northern Territory. Data. - Social impact of uranium mining on the Aborigines of the Northern Territory. Guidelines for present and future research. - Social impact of uranium mining on the Aborigines of the Northern Territory:(for the period 1 Oct 1980 to 31st Mar 1981. Report to Minister Aboriginal Affairs.

Additional file 2: Supplementary Table 2. TF-IDF analysis for mind split disorder after the revision of the schizophrenia name

The study adds to the knowledge of NSW mining impacts and their association with residential property sale values, although the impact measured at Broken Hill is less than that at other major mine sites in Australia; Mt Isa and Kalgoorlie (6.2 - 6.9%/km). If omitted variables were added to this study's regression analysis, up to 8.153% per km is possible. The study is the first to use a combined WMA/HPA approach in mine and property impact assessment. Metal market spot prices do not appear to trigger price variation in the residential market, and lead and zinc ore production from all NSW mines exhibits a long-term decline. Three Data formats are utilised, and all are stored digitally; Mine impact data, Sales data and Multiple Regression of Sales Data. 1. Mine Impact Assessment: Excel spreadsheet with values at the 33 sites where mining impacts were subjectively determined. Sites were at the centre of mining activity (Broken Hill Miners Memorial) 0 meters, 200m, 500m, 1000m, 1500m, 2000m, 3000m, 4000m and 5000m away in north, east, south and westerly directions. Each site records a range of biophysical, economic, social and other impacts of mining at each location, assessed by the investigator and weighted according to documented methodology. An overall impacts rating (positive or negative) is generated to reflect the impact and distance from mining activity. 2. Sales Data: Excel spreadsheet Broken Hill sales records of all residential properties sold during calendar years 2000, 2005, 2010, 2015 and 2019, comprising property address, characteristics of each residence, area of land on which residence is located, distance to a range of services, and the centre of mining activity. 3. Multiple Regression Calculations: Robust Multiple Regression, Correlation and other statistical calculations undertaken from Broken Hill sales data records. Excel spreadsheets, Multiple Regression output files Please direct all enquires to Dr Ian Lavering ORCID 0000-0002-2094-4653

The global market for Human Rights and Social Impact Services is experiencing robust growth, driven by increasing corporate social responsibility (CSR) initiatives, heightened regulatory scrutiny regarding ethical business practices, and growing consumer demand for transparency and accountability. The market's expansion is fueled by a rising awareness of environmental, social, and governance (ESG) factors among investors and stakeholders. Businesses are increasingly seeking expert guidance to navigate complex human rights challenges, assess social impact, and ensure compliance with evolving international standards and national laws. This demand is particularly pronounced in sectors with significant social and environmental footprints, such as mining, energy, and apparel. Furthermore, the increasing adoption of sophisticated data analytics and technology solutions to measure and report on social impact are contributing to market growth. We estimate the 2025 market size to be approximately $15 billion, with a Compound Annual Growth Rate (CAGR) of 8% projected through 2033. This projection considers factors such as ongoing regulatory changes, technological advancements, and the continued global focus on sustainability. Key players in this market, including Anthesis Group, Environmental Resources Management (ERM), KPMG, and PwC, are expanding their service offerings to meet this growing demand. They are increasingly integrating human rights and social impact assessments into broader sustainability consulting services, offering a holistic approach to helping businesses manage ESG risks and opportunities. While the market faces restraints such as the varying levels of regulatory frameworks across different regions and the potential for inconsistent data collection and reporting practices, the overall trend points towards sustained and significant growth. The fragmentation of the market, with numerous smaller specialized consultancies, also presents opportunities for consolidation and strategic partnerships in the coming years. The segmentation of the market is evolving, with increased specialization in areas such as labor rights, human trafficking, and community engagement.

Bluesky Social Dataset Pollution of online social spaces caused by rampaging d/misinformation is a growing societal concern. However, recent decisions to reduce access to social media APIs are causing a shortage of publicly available, recent, social media data, thus hindering the advancement of computational social science as a whole. To address this pressing issue, we present a large, high-coverage dataset of social interactions and user-generated content from Bluesky Social.

The dataset contains the complete post history of over 4M users (81% of all registered accounts), totaling 235M posts. We also make available social data covering follow, comment, repost, and quote interactions.

Since Bluesky allows users to create and bookmark feed generators (i.e., content recommendation algorithms), we also release the full output of several popular algorithms available on the platform, along with their timestamped “like” interactions and time of bookmarking.

This dataset allows unprecedented analysis of online behavior and human-machine engagement patterns. Notably, it provides ground-truth data for studying the effects of content exposure and self-selection, and performing content virality and diffusion analysis.

Dataset Here is a description of the dataset files.

followers.csv.gz. This compressed file contains the anonymized follower edge list. Once decompressed, each row consists of two comma-separated integers u, v, representing a directed following relation (i.e., user u follows user v). posts.tar.gz. This compressed folder contains data on the individual posts collected. Decompressing this file results in 100 files, each containing the full posts of up to 50,000 users. Each post is stored as a JSON-formatted line. interactions.csv.gz. This compressed file contains the anonymized interactions edge list. Once decompressed, each row consists of six comma-separated integers, and represents a comment, repost, or quote interaction. These integers correspond to the following fields, in this order: user_id, replied_author, thread_root_author, reposted_author ,quoted_author, and date. graphs.tar.gz. This compressed folder contains edge list files for the graphs emerging from reposts, quotes, and replies. Each interaction is timestamped. The folder also contains timestamped higher-order interactions emerging from discussion threads, each containing all users participating in a thread. feed_posts.tar.gz. This compressed folder contains posts that appear in 11 thematic feeds. Decompressing this folder results in 11 files containing posts from one feed each. Posts are stored as a JSON-formatted line. Fields are correspond to those in posts.tar.gz, except for those related to sentiment analysis (sent_label, sent_score), and reposts (repost_from, reposted_author); feed_bookmarks.csv. This file contains users who bookmarked any of the collected feeds. Each record contains three comma-separated values, namely the feed name, the user id, and the timestamp. feed_post_likes.tar.gz. This compressed folder contains data on likes to posts appearing in the feeds, one file per feed. Each record in the files contains the following information, in this order: the id of the ``liker'', the id of the post's author, the id of the liked post, and the like timestamp; scripts.tar.gz. A collection of Python scripts, including the ones originally used to crawl the data, and to perform experiments. These scripts are detailed in a document released within the folder.

Citation If used for research purposes, please cite the following paper describing the dataset details:

Andrea Failla and Giulio Rossetti. "I'm in the Bluesky Tonight": Insights from a Year Worth of Social Data. (2024) arXiv:2404.18984

Acknowledgments: This work is supported by :

the European Union – Horizon 2020 Program under the scheme “INFRAIA-01-2018-2019 – Integrating Activities for Advanced Communities”, Grant Agreement n.871042, “SoBigData++: European Integrated Infrastructure for Social Mining and Big Data Analytics” (http://www.sobigdata.eu); SoBigData.it which receives funding from the European Union – NextGenerationEU – National Recovery and Resilience Plan (Piano Nazionale di Ripresa e Resilienza, PNRR) – Project: “SoBigData.it – Strengthening the Italian RI for Social Mining and Big Data Analytics” – Prot. IR0000013 – Avviso n. 3264 del 28/12/2021; EU NextGenerationEU programme under the funding schemes PNRR-PE-AI FAIR (Future Artificial Intelligence Research).

Additional file 4: Supplementary table 4. Hospitalization statistics of schizophrenia patients in South Korea

Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information

International Journal of Engineering and Advanced Technology Impact Factor 2024-2025 - ResearchHelpDesk - International Journal of Engineering and Advanced Technology (IJEAT) is having Online-ISSN 2249-8958, bi-monthly international journal, being published in the months of February, April, June, August, October, and December by Blue Eyes Intelligence Engineering & Sciences Publication (BEIESP) Bhopal (M.P.), India since the year 2011. It is academic, online, open access, double-blind, peer-reviewed international journal. It aims to publish original, theoretical and practical advances in Computer Science & Engineering, Information Technology, Electrical and Electronics Engineering, Electronics and Telecommunication, Mechanical Engineering, Civil Engineering, Textile Engineering and all interdisciplinary streams of Engineering Sciences. All submitted papers will be reviewed by the board of committee of IJEAT. Aim of IJEAT Journal disseminate original, scientific, theoretical or applied research in the field of Engineering and allied fields. dispense a platform for publishing results and research with a strong empirical component. aqueduct the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research. seek original and unpublished research papers based on theoretical or experimental works for the publication globally. publish original, theoretical and practical advances in Computer Science & Engineering, Information Technology, Electrical and Electronics Engineering, Electronics and Telecommunication, Mechanical Engineering, Civil Engineering, Textile Engineering and all interdisciplinary streams of Engineering Sciences. impart a platform for publishing results and research with a strong empirical component. create a bridge for a significant gap between research and practice by promoting the publication of original, novel, industry-relevant research. solicit original and unpublished research papers, based on theoretical or experimental works. Scope of IJEAT International Journal of Engineering and Advanced Technology (IJEAT) covers all topics of all engineering branches. Some of them are Computer Science & Engineering, Information Technology, Electronics & Communication, Electrical and Electronics, Electronics and Telecommunication, Civil Engineering, Mechanical Engineering, Textile Engineering and all interdisciplinary streams of Engineering Sciences. The main topic includes but not limited to: 1. Smart Computing and Information Processing Signal and Speech Processing Image Processing and Pattern Recognition WSN Artificial Intelligence and machine learning Data mining and warehousing Data Analytics Deep learning Bioinformatics High Performance computing Advanced Computer networking Cloud Computing IoT Parallel Computing on GPU Human Computer Interactions 2. Recent Trends in Microelectronics and VLSI Design Process & Device Technologies Low-power design Nanometer-scale integrated circuits Application specific ICs (ASICs) FPGAs Nanotechnology Nano electronics and Quantum Computing 3. Challenges of Industry and their Solutions, Communications Advanced Manufacturing Technologies Artificial Intelligence Autonomous Robots Augmented Reality Big Data Analytics and Business Intelligence Cyber Physical Systems (CPS) Digital Clone or Simulation Industrial Internet of Things (IIoT) Manufacturing IOT Plant Cyber security Smart Solutions – Wearable Sensors and Smart Glasses System Integration Small Batch Manufacturing Visual Analytics Virtual Reality 3D Printing 4. Internet of Things (IoT) Internet of Things (IoT) & IoE & Edge Computing Distributed Mobile Applications Utilizing IoT Security, Privacy and Trust in IoT & IoE Standards for IoT Applications Ubiquitous Computing Block Chain-enabled IoT Device and Data Security and Privacy Application of WSN in IoT Cloud Resources Utilization in IoT Wireless Access Technologies for IoT Mobile Applications and Services for IoT Machine/ Deep Learning with IoT & IoE Smart Sensors and Internet of Things for Smart City Logic, Functional programming and Microcontrollers for IoT Sensor Networks, Actuators for Internet of Things Data Visualization using IoT IoT Application and Communication Protocol Big Data Analytics for Social Networking using IoT IoT Applications for Smart Cities Emulation and Simulation Methodologies for IoT IoT Applied for Digital Contents 5. Microwaves and Photonics Microwave filter Micro Strip antenna Microwave Link design Microwave oscillator Frequency selective surface Microwave Antenna Microwave Photonics Radio over fiber Optical communication Optical oscillator Optical Link design Optical phase lock loop Optical devices 6. Computation Intelligence and Analytics Soft Computing Advance Ubiquitous Computing Parallel Computing Distributed Computing Machine Learning Information Retrieval Expert Systems Data Mining Text Mining Data Warehousing Predictive Analysis Data Management Big Data Analytics Big Data Security 7. Energy Harvesting and Wireless Power Transmission Energy harvesting and transfer for wireless sensor networks Economics of energy harvesting communications Waveform optimization for wireless power transfer RF Energy Harvesting Wireless Power Transmission Microstrip Antenna design and application Wearable Textile Antenna Luminescence Rectenna 8. Advance Concept of Networking and Database Computer Network Mobile Adhoc Network Image Security Application Artificial Intelligence and machine learning in the Field of Network and Database Data Analytic High performance computing Pattern Recognition 9. Machine Learning (ML) and Knowledge Mining (KM) Regression and prediction Problem solving and planning Clustering Classification Neural information processing Vision and speech perception Heterogeneous and streaming data Natural language processing Probabilistic Models and Methods Reasoning and inference Marketing and social sciences Data mining Knowledge Discovery Web mining Information retrieval Design and diagnosis Game playing Streaming data Music Modelling and Analysis Robotics and control Multi-agent systems Bioinformatics Social sciences Industrial, financial and scientific applications of all kind 10. Advanced Computer networking Computational Intelligence Data Management, Exploration, and Mining Robotics Artificial Intelligence and Machine Learning Computer Architecture and VLSI Computer Graphics, Simulation, and Modelling Digital System and Logic Design Natural Language Processing and Machine Translation Parallel and Distributed Algorithms Pattern Recognition and Analysis Systems and Software Engineering Nature Inspired Computing Signal and Image Processing Reconfigurable Computing Cloud, Cluster, Grid and P2P Computing Biomedical Computing Advanced Bioinformatics Green Computing Mobile Computing Nano Ubiquitous Computing Context Awareness and Personalization, Autonomic and Trusted Computing Cryptography and Applied Mathematics Security, Trust and Privacy Digital Rights Management Networked-Driven Multicourse Chips Internet Computing Agricultural Informatics and Communication Community Information Systems Computational Economics, Digital Photogrammetric Remote Sensing, GIS and GPS Disaster Management e-governance, e-Commerce, e-business, e-Learning Forest Genomics and Informatics Healthcare Informatics Information Ecology and Knowledge Management Irrigation Informatics Neuro-Informatics Open Source: Challenges and opportunities Web-Based Learning: Innovation and Challenges Soft computing Signal and Speech Processing Natural Language Processing 11. Communications Microstrip Antenna Microwave Radar and Satellite Smart Antenna MIMO Antenna Wireless Communication RFID Network and Applications 5G Communication 6G Communication 12. Algorithms and Complexity Sequential, Parallel And Distributed Algorithms And Data Structures Approximation And Randomized Algorithms Graph Algorithms And Graph Drawing On-Line And Streaming Algorithms Analysis Of Algorithms And Computational Complexity Algorithm Engineering Web Algorithms Exact And Parameterized Computation Algorithmic Game Theory Computational Biology Foundations Of Communication Networks Computational Geometry Discrete Optimization 13. Software Engineering and Knowledge Engineering Software Engineering Methodologies Agent-based software engineering Artificial intelligence approaches to software engineering Component-based software engineering Embedded and ubiquitous software engineering Aspect-based software engineering Empirical software engineering Search-Based Software engineering Automated software design and synthesis Computer-supported cooperative work Automated software specification Reverse engineering Software Engineering Techniques and Production Perspectives Requirements engineering Software analysis, design and modelling Software maintenance and evolution Software engineering tools and environments Software engineering decision support Software design patterns Software product lines Process and workflow management Reflection and metadata approaches Program understanding and system maintenance Software domain modelling and analysis Software economics Multimedia and hypermedia software engineering Software engineering case study and experience reports Enterprise software, middleware, and tools Artificial intelligent methods, models, techniques Artificial life and societies Swarm intelligence Smart Spaces Autonomic computing and agent-based systems Autonomic computing Adaptive Systems Agent architectures, ontologies, languages and protocols Multi-agent systems Agent-based learning and knowledge discovery Interface agents Agent-based auctions and marketplaces Secure mobile and multi-agent systems Mobile agents SOA and Service-Oriented Systems Service-centric software engineering Service oriented requirements engineering Service oriented architectures Middleware for service based systems Service discovery and composition Service level

Through Telegram API, the authors collected this database over four months ago. These data are Telegram's comments of over eight professional Telegram channels about cryptocurrencies from December 2023 to March 2024. The theory of Behavioral economics shows that the opinions of people, especially experts, can impact the stock market trend (here, cryptocurrencies). Existing databases often cover tweets or Telegram's comments on one or more cryptocurrencies. Also, in these databases, no attention is paid to the user's expertise, and most of the data is extracted using hashtags. Failure to pay attention to the user's expertise causes the irrelevant volume to increase and the neutral polarity considerably. This database has a main table with eight columns. The columns of the main table are explained in the attached document. Researchers can use this dataset in various machine learning tasks, such as sentiment analysis and deep transfer learning with sentiment analysis. Also, this data can be used to check the impact of influencers' opinions on the cryptocurrency market trend. The use of this database is allowed by mentioning the source. Furthermore, we have added Python code to extract Telegram's comments. We used the RoBERTa pre-trained deep neural network and BiGRU deep neural network with an attention layer-based HDRB model(https://ieeexplore.ieee.org/document/10292644) for sentiment analysis.

Abstract

South Africa has 230 operating mines located in diverse natural and social settings. Over 6 million people live in urban and rural mining host communities who will be significantly affected by mine closure. The national, provincial and local governments need guidance in identifying high-risk areas and relevant policy and programmatic interventions. This dataset includes data collected on mines in South Africa for the development of a quantitative mine closure risk rating system that assesses the likelihood of mine closure, the risk of social impact and the risk of environmental impact of mine closure for every operating mine in the country. The rating system was tested with 10 mines and 19 mining experts. The shape files for maps resulting from the research are also included in the dataset.The data is also available for viewing on the South African Mine Closure Risk and Opportunity Atlas https://experience.arcgis.com/experience/f8bbd7f733674b9d99cd320b4f5b98f5/ Data projection: GCS_WGS_1984 The data provides evidence for the research publication Cole, M.J. A Mine Closure Risk Rating System for South Africa. Mining 2024, 4, 58-78. https://doi.org/10.3390/mining4010005

Analysis unit

Institutions

Kind of data

Other

Mode of data collection

Other

Big Data and Society CiteScore 2024-2025 - ResearchHelpDesk - Big Data & Society (BD&S) is open access, peer-reviewed scholarly journal that publishes interdisciplinary work principally in the social sciences, humanities and computing and their intersections with the arts and natural sciences about the implications of Big Data for societies. The Journal's key purpose is to provide a space for connecting debates about the emerging field of Big Data practices and how they are reconfiguring academic, social, industry, business, and government relations, expertise, methods, concepts, and knowledge. BD&S moves beyond usual notions of Big Data and treats it as an emerging field of practice that is not defined by but generative of (sometimes) novel data qualities such as high volume and granularity and complex analytics such as data linking and mining. It thus attends to digital content generated through online and offline practices in social, commercial, scientific, and government domains. This includes, for instance, the content generated on the Internet through social media and search engines but also that which is generated in closed networks (commercial or government transactions) and open networks such as digital archives, open government, and crowdsourced data. Critically, rather than settling on a definition the Journal makes this an object of interdisciplinary inquiries and debates explored through studies of a variety of topics and themes. BD&S seeks contributions that analyze Big Data practices and/or involve empirical engagements and experiments with innovative methods while also reflecting on the consequences for how societies are represented (epistemologies), realized (ontologies) and governed (politics). Article processing charge (APC) The article processing charge (APC) for this journal is currently 1500 USD. Authors who do not have funding for open access publishing can request a waiver from the publisher, SAGE, once their Original Research Article is accepted after peer review. For all other content (Commentaries, Editorials, Demos) and Original Research Articles commissioned by the Editor, the APC will be waived. Abstract & Indexing Clarivate Analytics: Social Sciences Citation Index (SSCI) Directory of Open Access Journals (DOAJ) Google Scholar Scopus

Despite their importance, there is limited evidence on how institutions can be strengthened. Evaluating the effects of specific reforms is complicated by the lack of exogenous variation in institutions, the difficulty of measuring institutional performance, and the temptation to “cherry pick” estimates from among the large number of indicators required to capture this multifaceted subject. We evaluate one attempt to make local institutions more democratic and egalitarian by imposing participation requirements for marginalized groups (including women) and test for learning-by-doing effects. We exploit the random assignment of a governance program in Sierra Leone, develop innovative real-world outcome measures, and use a preanalysis plan (PAP) to bind our hands against data mining. The intervention studied is a “community-driven development” program, which has become a popular strategy for foreign aid donors. We find positive short-run effects on local public goods and economic outcomes, but no evidence for sustained impacts on collective action, decision making, or the involvement of marginalized groups, suggesting that the intervention did not durably reshape local institutions. We discuss the practical trade-offs faced in implementing a PAP and show how in its absence we could have generated two divergent, equally erroneous interpretations of program impacts on institutions.

***************************************************************************The 64 datasets and their test and training datasets.***************************************************************************For detailed information, you may read the following article.XXXXXXXXX, "The Impact of Word-Length and Tweet-Length on Emoji Recommendation for Short Turkish Texts", Journal Name, Vol. XX, Issue. XX, pp. XX-XX, Date.***************************************************************************If you want to use all or a part of these datasets, you are free to use. However, please consider the following.Copyright belongs to the author.Do not redistribute all or a part of these datasets.These datasets come without any warranty. The author is not responsible for any damage caused.All studies that include all or a part of these datasets should cite the following article:XXXXXXXXXX, "The Impact of Word-Length and Tweet-Length on Emoji Recommendation for Short Turkish Texts", Journal Name, Vol. XX, Issue. XX, pp. XX-XX, Date.***************************************************************************

The Mining Industry Software market has emerged as a crucial component in enhancing operational efficiency and productivity within the sector. These software solutions encompass a wide range of functionalities, including exploration, data management, production planning, and equipment maintenance, all aimed at optim

This dataset 'Interview - Roger Clarke’ is a component of a Doctor Of Philosophy conducted by candidate Alexander Hayes (3919493) titled 'The Socioethical Implications Of Body Worn Computers: An Ethnographic Study'. The full thesis can be accessed at https://ro.uow.edu.au/theses1/853This research was conducted in the Faculty of Engineering and Information Systems, School of Computing and Information Technology (SCIT), University of Wollongong with research strength Innovation in Business & Social Research under Principal Supervisor Professor Katina Michael (University of Wollongong) and Associate Supervisor Dr Teemu Leinonen (Aalto University Finland). This thesis explores the socioethical implications of body worn computers (BWC) using an ethnographic approach. Furthermore, a subset, body worn cameras (BWCs), combines data with value added constancy through Location Based Services (LBS) over wireless network connections. The aim of this investigation was to engage global leaders from transdisciplinary stakeholder groups in semi-structured interviews, conversations and events, situating a review of the social impact and ethical implications of BWCs. A critical discourse analysis using a Foucauldian approach reveals power relations, which are then infused through narrative with unique intercultural perspectives, differentiating ‘location’ from ‘place’. The author of this study has subsequently identified through Grounded Theory that BWCs are causal agency for disconnect from proper culture which can be addressed through the application of Ngikalikarra, a unique framework for empathetic understanding of place and community engagement.

The Mining Products Logistics market plays a crucial role in the global mining industry, facilitating the efficient transportation and management of resources extracted from the earth. This sector encompasses a wide range of activities, including the logistics of raw materials like coal, minerals, metals, and aggreg