检索结果-内蒙古大学图书馆

Transforming agriculture with Machine Learning, Deep Learning, and IoT: perspectives from Ethiopia—challenges and opportunities

引用

Discover Agriculture 2024年第1期2卷 1-34页

作者： Benti, Natei Ermias Chaka, Mesfin Diro Semie, Addisu Gezahegn Warkineh, Bikila Soromessa, Teshome Computational Data Science Program College of Natural and Computational Sciences Addis Ababa University Addis Ababa Ethiopia Department of Plant Biology and Biodiversity Management College of Natural and Computational Sciences Addis Ababa University Addis Ababa Ethiopia Center for Environmental Science College of Natural and Computational Sciences Addis Ababa University Addis Ababa Ethiopia

Agriculture holds a crucial position in maintaining livelihoods and securing food sources, particularly in nations such as Ethiopia, where a substantial portion of the population depends on agricultural pursuits. However, meeting the growing demand for food production amidst population growth presents considerable challenges. Recent advancements in technology, particularly in the areas of Machine Learning (ML), Deep Learning (DL), and the Internet of Things (IoT) offer promising solutions to address these challenges. This paper explores the potential of integrating ML, DL, and IoT technologies in agriculture to revolutionize the sector. By harnessing data-driven insights, farmers can make informed decisions regarding crop management, soil health, and weather patterns, leading to optimized resource allocation and increased productivity. Moreover, IoT devices enable the real-time monitoring and control of agricultural operations, enhancing sustainability and productivity. Despite the opportunities presented by these technologies, there are also challenges to overcome, such as data quality, connectivity issues, and the need for farmer education. However, with concerted efforts and investment, Ethiopia and other agricultural regions can unlock the full potential of ML, DL, and IoT technologies to ensure food security, alleviate poverty, and drive economic development. This review paper offers perspectives on the present status, challenges, and future possibilities regarding the integration of ML, DL, and IoT in agriculture. It underscores the transformative potential of these technologies within the sector.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Ultrasound for the degradation of endocrine disrupting compounds in aqueous solution: A review on mechanisms, influence of operating parameters and cost estimation

引用

Chemosphere 2024年 349卷 140864页

作者： Ghosh, Saptarshi Sahu, Manoranjan Aerosol and Nanoparticle Technology Laboratory Environmental Science and Engineering Department Indian Institute of Technology Bombay Mumbai400076 India Inter-Disciplinary Program in Climate Studies Indian Institute of Technology Bombay Mumbai400076 India Centre for Machine Intelligence and Data Science Indian Institute of Technology Bombay Mumbai400076 India

Availability of drinking water is one of the basic humanitarian goals but remains as a grand challenge that the world is facing today. Currently, water bodies are contaminated not only with conventional pollutants but also with numerous recalcitrant pollutants, such as PPCPs, endocrine disrupting compounds, etc. These emerging pollutants require special attention because of their toxicity to living organisms, bio-resistant and can sustain even after primary and secondary treatments of wastewater. Among different treatment technologies, sonolysis is found to be an innovative and promising technique for the treatment of emerging pollutants present in aqueous solution. Sonolysis is the use of ultrasound to enhance or alter chemical reactions by the formation of free radicals and shock waves which ultimately helps in degradation of pollutants. This review summarizes several studies in the sonochemical literature, including mechanisms of sonochemical process, physical and chemical effects of ultrasound, and the influence of several process variables such as ultrasound frequency, power density, temperature and pH of the medium on degradation performance for endocrine disrupting compounds. In addition, this review highlighted techno-economic perspectives focusing on the total cost required for translating the ultrasound-based processes on a large scale. Overall, the objective of this study is to exhibit a critical review of information available in the literature to encourage and promote future research on sonolysis for the degradation of Endocrine Disrupting Compounds (EDCs). © 2023 Elsevier Ltd

关键词： Wastewater treatment

来源：评论

学校读者我要写书评

暂无评论

Scale setting and hadronic properties in the light quark sector with (2+1)-flavor Wilson fermions at the physical point

引用

Physical Review D 2024年第9期110卷 094502页

作者： Tatsumi Aoyama Takahiro M. Doi Takumi Doi Etsuko Itou Yan Lyu Kotaro Murakami Takuya Sugiura Institute for Solid State Physics University of Tokyo Chiba 277-8581 Japan Department of Physics Interdisciplinary Theoretical and Mathematical Sciences Program (iTHEMS) Center for Gravitational Physics Yukawa Institute for Theoretical Physics Faculty of Data Science

We report scale setting and hadronic properties for our new lattice QCD gauge configuration set (HAL-conf-2023). We employ (2+1)-flavor nonperturbatively improved Wilson fermions with stout smearing and the Iwasaki gauge action on a 964 lattice, and generate configurations of 8000 trajectories at the physical point. We show the basic properties of the configurations such as the plaquette value, topological charge distribution and their autocorrelation times. The scale setting is performed by detailed analyses of the Ω baryon mass. We calculate the physical results of quark masses, decay constants of pseudoscalar mesons and single hadron spectra in light quark sector. The masses of the stable hadrons are found to agree with the experimental values within a subpercent level.

关键词： Lattice QCD

来源：评论

学校读者我要写书评

暂无评论

Evaluating the Ability to Use Contextual Features to Map Deprived Areas ‘Slums’ in Multiple Cities

Evaluating the Ability to Use Contextual Features to Map Dep...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Ryan Engstrom Maxwell Owusu Arathi Nair Amir Jafari Dana Thomson Monika Kuffer Department of Geography George Washington University Washington DC USA Data Science Program George Washington University Washington DC USA Faculty of Geo-Information Science and Earth Observation University of Twente Twente Netherlands

Population living in deprived conditions continues to grow, highlighting the urgent need for accurate high-resolution maps and detailed statistics to plan interventions and monitor changes. Unfortunately, data on deprived areas or "slums" is often unavailable, incomplete, or outdated. Leveraging satellite imagery can offer timely, and consistent information on deprived areas over large area However, there are limited studies that use free and open source data that can be used to map deprived areas over large areas and across multiple cities. To address these challenges, this study examines a scalable and transferable modeling approach to map deprived areas using contextual features extracted from freely available Sentinel-2 data. Models were trained and tested on three Sub-Sahara cities: Lagos Nigeria, Accra Ghana, and Nairobi, Kenya. The results indicate that models in individual city achieved F1 scores from 0.78-0.95 for the three cities. Additionally, the results indicate that the proposed approach may allow for the ability to transfer models from city to city allowing for large area and across city mapping.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Enhancing Sustainable Development Goals Through Future Vapor Pressure Deficit Analysis In The Nile River Basin

Enhancing Sustainable Development Goals Through Future Vapor...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Surendra Maharjan Wenzhao Li Shahryar Fazli Hani Sewilam Hesham El-Askary Computational and Data Sciences Graduate Program Schmid College of Science and Technology Chapman University Orange CA USA Earth Systems Science and Data Solutions Lab Chapman University Orange CA USA The Center for Applied Research on the Environment and Sustainability The American University in Cairo Cairo Egypt Department of Engineering Hydrology RWTH Aachen University Aachen Germany Department of Environmental Sciences Faculty of Science Alexandria University Alexandria Egypt

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

Vapor Pressure Deficit (VPD) is crucial in meteorology and agriculture for understanding plant-environment interactions. Its application as an indicator in agricultural practices notably advances Sustainable Development Goals such as Zero Hunger (SDG 2) and Climate Action (SDG 13). This research focuses on the impact of climate change on agricultural productivity and food security in the Nile River Basin (NRB), emphasizing the role of VPD, temperature, and precipitation. Utilizing Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets from NEX-GDDP-CMIP6, the study analyzes key climatic variables that influence agricultural conditions. The study applies the Mann-Kendall test to evaluate VPD trends from 2000 to 2060 under two Shared Socioeconomic Pathways (SSPs), SSP2-4.5 and SSP5-8.5. The study's findings on the implications of rising VPD levels in the Nile River Basin (NRB), particularly under the SSP 5-8.5 scenario, highlight a critical challenge for the region's agricultural productivity and food security. The increased VPD, indicative of drier conditions, leads to a moisture deficit for crops, potentially reducing agricultural yields. This scenario poses a significant threat to food security, as lower crop yields can result in food shortages and higher food prices, adversely affecting vulnerable populations. The study underscores the necessity of integrating VPD insights into agricultural and water resource management strategies to uphold food security against climatic variations in support of the SDGs.

关键词： Productivity Climate change Precipitation Food security Agriculture Rivers Sustainable development

来源：评论

学校读者我要写书评

暂无评论

Correction: Learning distribution-free anchored linear structural equation models in the presence of measurement error

引用

Journal of the Korean Statistical Society 2025年 1-2页

作者： Chung, Junhyoung Ahn, Youngmin Shin, Donguk Park, Gunwoong Department of Statistics Seoul National University Seoul Republic of Korea Institute for Data Innovation in Science Seoul National University Donguk Shin Seoul Republic of Korea Interdisciplinary Program in Artificial Intelligence Seoul National University Seoul Republic of Korea

来源：评论

学校读者我要写书评

暂无评论

Implementation Challenge of Artificial Intelligence in Human Resource Management for Employee Performance Monitoring Indonesia Companies Perspective

Implementation Challenge of Artificial Intelligence in Human...

引用

International Conference on ICT For Smart Society (ICISS)

作者： Edi Yusuf Wirawan Merios Gusan Putra Budi Nugroho Doctoral Program of Management Brawijaya University Jakarta Campus Indonesia Doctoral Program of Information Systen Diponegoro University Semarang Indonesia Program of Information System STMIK TAZKIA Bogor Indonesia Res. Center for Data and Information Science National Research and Innovation Agency Bandung Indonesia

ISBN: (数字)9798350389654

ISBN: (纸本)9798350389661

The main problem solved is to Improve Employee Performance Monitoring by Integrating Artificial Intelligence (AI) in Human Resource Management for Indonesian Companies. The paper suggests using AI technologies to analyze and process employee performance data. The overarching goal of this new approach is to identify patterns and red flags at the individual and team levels that can be used to inform stronger performance management strategies such as guided coaching, pointed feedback, or calibrated evaluations. This study is written as a schematic literature review, using sourced research articles from Indonesia and other countries to obtain the effects of AI on employee performance. This exercise showed how AI works in performance patterns and assists HR strategies. The findings AI has an impact on recognizing patterns in empirical data of how employees perform, helps to tailor training/development programs, and improves talent management and succession planning. Those results signify that AI has the potential to be a game-changer for HR practices in Indonesia. AI in HRM using employee performance monitoring seems an encouraging alternative for Indonesia. Through data-driven decision-making and automated HR routine tasks with many challenges and should prepare well to implement.

关键词： Leadership Smart cities Employment Ecosystems Decision making Companies Planning Pattern recognition Artificial intelligence Monitoring

来源：评论

学校读者我要写书评

暂无评论

Style-Friendly SNR Sampler for Style-Driven Generation

arXiv

引用

arXiv 2024年

作者： Choi, Jooyoung Shin, Chaehun Oh, Yeongtak Kim, Heeseung Lee, Jungbeom Yoon, Sungroh Data Science and AI Laboratory ECE Seoul National University Korea Republic of Amazon United States AIIS ASRI INMC ISRC Interdisciplinary Program in AI Seoul National University France

Recent text-to-image diffusion models generate high-quality images but struggle to learn new, personalized styles, which limits the creation of unique style templates. In style-driven generation, users typically supply reference images exemplifying the desired style, together with text prompts that specify desired stylistic attributes. Previous approaches popularly rely on fine-tuning, yet it often blindly utilizes objectives and noise level distributions from pre-training without adaptation. We discover that stylistic features predominantly emerge at higher noise levels, leading current fine-tuning methods to exhibit suboptimal style alignment. We propose the Style-friendly SNR sampler, which aggressively shifts the signal-to-noise ratio (SNR) distribution toward higher noise levels during fine-tuning to focus on noise levels where stylistic features emerge. This enhances models’ ability to capture novel styles indicated by reference images and text prompts. We demonstrate improved generation of novel styles that cannot be adequately described solely with a text prompt, enabling the creation of new style templates for personalized content creation. © 2024, CC BY-NC-SA.

关键词： 3D modeling

来源：评论

学校读者我要写书评

暂无评论

Exploring the Transformer-Based and Diffusion-Based Models for Single Image Deblurring

SSRN

引用

SSRN 2024年

作者： Park, Seunghwan Shin, Chaehun Lew, Jaihyun Yoon, Sungroh Data Science and AI Laboratory ECE and Interdisciplinary Program in AI Seoul National University Seoul Korea Republic of Large Display Development Center Samsung Display Corporation Yongin Korea Republic of

Image deblurring is a fundamental task in image restoration (IR) aimed at removing blurring artifacts caused by factors such as defocusing, motions, and others. Since a blurry image could be originated from various sharp images, deblurring is regarded as an ill-posed problem with multiple valid solutions. The evolution of deblurring techniques spans from rule-based algorithms to deep learning-based models. Early research focused on estimating blur kernels using maximum a posteriori (MAP) estimation, but advancements in deep learning have shifted the focus toward directly predicting sharp images. The performance of deblurring models was significantly improved by leveraging deep learning techniques such as convolutional neural networks (CNNs), generative adversarial networks (GANs), recurrent neural networks (RNNs), and others. Especially, models utilizing Transformers and Vision Transformers (ViTs) demonstrate state-of-the-art (SOTA) performance. The advent of diffusion probabilistic models (DPMs) has further enhanced this progress by leveraging their generative capabilities for image restoration tasks. We provide an in-depth investigation of representative deblurring models, from traditional approaches to state-of-the-art deep learning models, categorizing them according to their foundational technologies. In addition, a detailed evaluation of representative models using standardized metrics is also presented, highlighting advances in both methodology and practical performance. © 2024, The Authors. All rights reserved.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Child-Centred AI Design: Definition, Operation, and Considerations

Child-Centred AI Design: Definition, Operation, and Consider...

引用

Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, CHI EA 2023

作者： Wang, Ge Sun, Kaiwen Atabey, Ayça Pothong, Kruakae Lin, Grace C. Zhao, Jun Yip, Jason Department of Computer Science University of Oxford United Kingdom School of Information University of Michigan United States School of Law Centre for Data Culture & Society University of Edinburgh United Kingdom Department of Media and Communications The London School of Economics and Political Science 5Rights Foundation United Kingdom Scheller Teacher Education Program The Education Arcade The Massachusetts Institute of Technology United States Information School University of Washington United States

ISBN: (纸本)9781450394222

AI systems and related algorithms are starting to play a variety of roles in the digital ecosystems of children - being embedded in the connected toys, smart home IoT technologies, apps, and services they interact with on a daily basis. Going forward, AI systems will, in all likelihood, become even more pervasive in children's applications simply due to their sheer usefulness in creating compelling, adaptive, and personal user experiences. Yet, understanding the ways that AI-driven systems used by children operate, and how AI could be designed to better anticipate and respond to children's diverse requirements is still a new and emerging area of investigation. Our goals of this workshop are to (1) extend the current critically constructive dialogue around the meaning of child-centred AI design and (2) explore ways to operationalise such child-centred AI design in practice, and finally (3) further expand and foster a community for those who are interested in designing and developing child-centred AI systems. © 2023 Owner/Author.

关键词： Automation

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：