IEEE Technology and Society Magazine最新文献_第8页

Food Security and Agriculture: Technology, Policy, Choices 粮食安全与农业：技术、政策、选择

IF 2.1 4区工程技术

IEEE Technology and Society Magazine Pub Date : 2024-10-03 DOI: 10.1109/MTS.2024.3455388

Ketra Schmitt

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Technology, Society, and Generational Interoperability—An Incredible July 2024 技术、社会和代际互操作性--不可思议的 2024 年 7 月

IF 2.1 4区工程技术

IEEE Technology and Society Magazine Pub Date : 2024-10-03 DOI: 10.1109/MTS.2024.3455389

Luis Kun

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TechRxiv TechRxiv

IF 2.1 4区工程技术

IEEE Technology and Society Magazine Pub Date : 2024-10-03 DOI: 10.1109/MTS.2024.3468490

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The Gap Between Policy and Implementation Has Roots in Academia: How Policy Schools Can Narrow the Gap 政策与执行之间的差距源于学术界：政策学院如何缩小差距

IF 2.1 4区工程技术

IEEE Technology and Society Magazine Pub Date : 2024-10-03 DOI: 10.1109/MTS.2024.3410307

Evagelia Emily Tavoulareas

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Understanding the Role of Technology in Society 了解技术在社会中的作用

IF 2.1 4区工程技术

IEEE Technology and Society Magazine Pub Date : 2024-10-03 DOI: 10.1109/MTS.2024.3457100

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Sensemaking National Security: Applying Design Practice to Explore AI in Cybersecurity

IF 2.1 4区工程技术

IEEE Technology and Society Magazine Pub Date : 2024-09-26 DOI: 10.1109/MTS.2024.3457679

Mariana Zafeirakopoulos

{"title":"Sensemaking National Security: Applying Design Practice to Explore AI in Cybersecurity","authors":"Mariana Zafeirakopoulos","doi":"10.1109/MTS.2024.3457679","DOIUrl":"https://doi.org/10.1109/MTS.2024.3457679","url":null,"abstract":"Intelligence analysis provides decision support in national security contexts. The current approach to supported decision-making tends toward reductivism and analysis, regardless of the type of national security issue. Currently, there is little research available on the alternative approaches and practices needed for intervening in national security contexts that are emerging and, therefore, not well understood. Consequently, this article explores the idea that a homogenous approach to national security problem-solving is insufficient, and we suggest that different national security issues require different approaches. In this article, we apply practices of exploration, relationality, and participation from the field of design as established approaches to sensemaking. We offer sensemaking as an alternative to reductive analytic thinking by applying it to a national security issue: the role of artificial intelligence (AI) in cybersecurity. To explore sensemaking, six workshops were conducted over six months in 2021. These workshops used design practices (thinking and tools) to explore AI in cybersecurity. From studying the workshop activities and analyzing interviews conducted by the core design team (CDT) (Project Steering Group), the study’s findings suggest new practices for Intelligence to support decision-making in future-oriented contexts. These practices include using design tools such as personas and scenarios to anchor the exploration of future harms, which also give legitimacy to lived experience alongside expert knowledge. This study also identifies possibilities for future engagement, participation, and dialog between government functions such as Intelligence and civil society to explore unknown and emerging issues together. Consequently, a relational approach gives legitimacy to seemingly unconventional ways of thinking, approaching, and knowing about future unknown contexts.","PeriodicalId":55016,"journal":{"name":"IEEE Technology and Society Magazine","volume":"43 4","pages":"72-82"},"PeriodicalIF":2.1,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143183854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Social and Environmental Impact of a Plant Disease Analysis Method Based on Object Extraction 基于对象提取的植物病害分析方法对社会和环境的影响

IF 2.1 4区工程技术

IEEE Technology and Society Magazine Pub Date : 2024-09-23 DOI: 10.1109/MTS.2024.3455110

François Xavier Sikounmo;Cedric Deffo;Clémentin Tayou Djamegni

{"title":"Social and Environmental Impact of a Plant Disease Analysis Method Based on Object Extraction","authors":"François Xavier Sikounmo;Cedric Deffo;Clémentin Tayou Djamegni","doi":"10.1109/MTS.2024.3455110","DOIUrl":"https://doi.org/10.1109/MTS.2024.3455110","url":null,"abstract":"Plant leaf infections are a common threat to global production in both the long and short terms, affecting not only many farmers but also consumers around the world. Early detection and treatment of plant leaf diseases are essential to promote healthy plant growth in agriculture and ensure sufficient supply and health security for the world’s geometric (population) growth. Detection of plant leaf diseases using computer-aided technologies is widespread today. In the first part of this thesis, we describe an artificial intelligence (AI) model that enables image analysis to facilitate disease detection and then present its contribution at the societal level. We used images of maize leaves and images of apples in fields from the standard PlantVillage repository for object localization. An efficient deep learning (DL) modified mask region convolutional neural network (Mask R-CNN) is proposed for autonomous segmentation and detection of the object to be analyzed in this research. The proposed work exploited the features learned by the Mask R-CNN model at various processing hierarchies. We achieved improved code generation of singular images of the detected objects and an overall accuracy of 98.89% on the validation sets. In the rest of our research, we wanted to show the impact of our solution at a social level while highlighting the important aspects that characterize good development. The specificity of this approach is to present the different AI solutions used for the analysis of agricultural crops, with the aim of highlighting their benefits and their impact on human activities.","PeriodicalId":55016,"journal":{"name":"IEEE Technology and Society Magazine","volume":"43 3","pages":"65-71"},"PeriodicalIF":2.1,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142376981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Harvesting Insights: Sentiment Analysis on Smart Farming YouTube Comments for User Engagement and Agricultural Innovation 收获洞察：对智能农业 YouTube 评论进行情感分析，促进用户参与和农业创新

IF 2.1 4区工程技术

IEEE Technology and Society Magazine Pub Date : 2024-09-18 DOI: 10.1109/MTS.2024.3455754

Abhishek Kaushik;Sargam Yadav;Shubham Sharma;Kevin McDaid

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Intermittent Light Scheduling for Energy Cost Reduction in Vertical Farming 间歇性光照调度降低垂直种植的能源成本

IF 2.1 4区工程技术

IEEE Technology and Society Magazine Pub Date : 2024-09-13 DOI: 10.1109/MTS.2024.3455103

Giulia Robbiani;Eric Törn

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Smart Farming Adoption in Europe 欧洲智能农业的采用情况

IF 2.1 4区工程技术

IEEE Technology and Society Magazine Pub Date : 2024-08-27 DOI: 10.1109/MTS.2024.3443542

Konstantinos Kiropoulos;Stamatia Bibi

{"title":"Smart Farming Adoption in Europe","authors":"Konstantinos Kiropoulos;Stamatia Bibi","doi":"10.1109/MTS.2024.3443542","DOIUrl":"https://doi.org/10.1109/MTS.2024.3443542","url":null,"abstract":"The Population of the world is now eight billion people, but it is expected to reach 9.7 billion by 2050 due to ongoing population growth \u0000<xref>[1]</xref>\u0000. A population of this size confronts several challenges, the most significant being the requirement for expanded global food production to meet nutritional demands. Due to the inefficient use of natural resources that overburdens the ecosystem, traditional agricultural practices are thought to be unable to meet these demands \u0000<xref>[2]</xref>\u0000. We are, thus, forced to adopt more ecologically friendly agricultural methods. By lowering the need for external inputs and assisting farmers in coping with unfavorable weather, which is becoming more frequent due to climate change, smart farming technologies (SFTs) can increase crop output in a sustainable manner, enhancing its resilience and lowering carbon dioxide emissions. The United States had a \u0000<inline-formula> <tex-math>$91 %$ </tex-math></inline-formula>\u0000 acceptance rate for SFT as of 2020 \u0000<xref>[3]</xref>\u0000, with Canada, Australia, and other European nations lagging behind as the most adopting nations. A wider use of SFT is needed to achieve the objective of feeding the world’s population sustainably, even if certain emerging nations are accelerating their adoption rates.","PeriodicalId":55016,"journal":{"name":"IEEE Technology and Society Magazine","volume":"43 3","pages":"51-64"},"PeriodicalIF":2.1,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142376630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0