Remote Assisted Task Management for ISOBUS Equipped Tractor-Implement Combination

Rosana G. Moreira, Editor-in-Chief; Texas A&M UniversityThis is a paper from International Commission of Agricultural Engineering (CIGR, Commission Internationale du Genie Rural) E-Journal Volume 9 (2007): Remote Assisted Task Management for ISOBUS Equipped Tractor-Implement Combination. Manuscript ATOE 07 011. Vol. IX. July, 2007

Study on Unconventional Emergency Scenario Design: Taking Life-Rescuing of Dongfang Turbine Co., Ltd. in Wenchuan Earthquake for Example

Unconventional emergencies have attracted widespread concern in academic field due to its high uncertainty, huge destructiveness and complex management, and studies on unconventional emergencies shall change from “prediction-response” to “scenario-response”. By taking the life-rescuing of Dongfang Turbine Co., Ltd. in Wenchuan Earthquake for example, this paper divides scenarios in accordance with the specific investigations, and proposes several considerations about the unconventional emergency scenario study

FLY-CAPS- A Hybrid Firefly Feature Optimized Capsule Networks for Plant Disease Classification in Resource Constriant Internet of Things (IoT)

Recent advancements in artificial intelligence, automation, and the Internet of Things (IoT) enable farmers to better monitor and diagnose all agricultural procedures with super-intellectual accuracy. These technologies also contribute to boosting the productivity of agriculture, which increases the country’s economy. Though these technologies help farmers increase productivity, the detection of plant diseases still needs heightened scrutiny for prevention and cultivation. Plant disease categorization has expanded with the introduction of deep learning algorithms, but it still needs more innovation in terms of accuracy and computing burden. Thus, a novel deep learning model based on capsule networks with firefly optimization and potent multi-layered feedforward prediction networks is proposed in this research. The handcrafted features in this proposed system are optimized before being extracted using a capsule network, which reduces the complexity overhead and is suitable for IoT devices with limited resources. Finally fed to the feed forward layers for better classification. The extensive experimentation has been tested with the Plant Village databases, which contain more than 50,000 images of healthy and infected plants. Performance criteria including recall, specificity, recall, accuracy, and f1-score are used to assess the proposed algorithm's performance. Additionally, its efficiency and computational cost are contrasted with those of other recent models. The suggested model has greater performance (95%) with reduced computing overhead, according to experimental data, which is advantageous for the new prediction approach and the welfare of the farmer

Public health GIS news and information

I. Public health GIS (and related) events: special NCHS/CDC GIS lectures -- II. GIS news. A. General news and training opportunities -- GIS news. B. Department of Health and Human Services -- GIS news. C. Historically Black Colleges and Universities (HBCUs), Hispanic Association of Colleges and Universities (HACUs), and other minority health news -- GIS news. D. Other related agency or GIS news -- III. GIS outreach -- IV. Public health GIS presentations and literature [Notice: The guest lecture series will resume in the Fall, 2005, following a brief summer break.] -- V. Related Census, HHS, FGDC and other federal/state developments -- Final thoughts [11th International Medical Geography Symposium, Fort Worth, TX July 5-9, 2005] -- Appendix: Mapping health inequalities: Child Maltreatment, 1992 to 2002 (by Terry Lenahan) [Eighth in Series: See also May, July, September, November 2004, January, March and May 2005 editions].OtherOthe

From topic networks to distributed cognitive maps: Zipfian topic universes in the area of volunteered geographic information

Are nearby places (e.g., cities) described by related words? In this article, we transfer this research question in the field of lexical encoding of geographic information onto the level of intertextuality. To this end, we explore Volunteered Geographic Information (VGI) to model texts addressing places at the level of cities or regions with the help of so-called topic networks. This is done to examine how language encodes and networks geographic information on the aboutness level of texts. Our hypothesis is that the networked thematizations of places are similar, regardless of their distances and the underlying communities of authors. To investigate this, we introduce Multiplex Topic Networks (MTN), which we automatically derive from Linguistic Multilayer Networks (LMN) as a novel model, especially of thematic networking in text corpora. Our study shows a Zipfian organization of the thematic universe in which geographical places (especially cities) are located in online communication. We interpret this finding in the context of cognitive maps, a notion which we extend by so-called thematic maps. According to our interpretation of this finding, the organization of thematic maps as part of cognitive maps results from a tendency of authors to generate shareable content that ensures the continued existence of the underlying media. We test our hypothesis by example of special wikis and extracts of Wikipedia. In this way, we come to the conclusion that geographical places, whether close to each other or not, are located in neighboring semantic places that span similar subnetworks in the topic universe