Jeroen Steenbeek Ecopath with Ecosim
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Ecopath with Ecosim (EwE) is an ecological modeling software that tracks energy flow through food webs using functional groups and relatively few input parameters. It has been in development for 30 years and can model both natural environments and human impacts. The software faces challenges because ecosystems are complex with feedback effects across scales, but the models can still provide useful insights despite uncertainties, especially around climate change and human impacts. The developer thanked the audience and provided his contact information.
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MUMS Opening Workshop - The Isaac Newton Institute Uncertainty Quantification...
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Between January and June 2018, the Isaac Newton Institute for Mathematical Sciences in the UK ran a six-month programme on uncertainty quantification. The aim of the programme was to bring together the applied mathematics/numerical analysis and the statistical communities, who have different approaches to the problem on quantifying uncertainty in complex numerical models. Despite joint initiatives from groups such as SIAM and the ASA on journals and conferences the two communities remain separate and there was little understanding from one group on what the other does. The programme was organised by Peter Challenor (University of Exeter), Max Gunzberger (Florida State University), Catherine Powell (University of Manchester) and Henry Wynn (London School of Economics). Our core themes were: surrogate models; multilevel, multi-scale, and multi-fidelity methods; dimension reduction methods; inverse UQ methods; and careful and fair comparisons. INI programme participants attend the programme for up six months and have opportunities to work together in a collaborative way. Most of our participants attended for between 2-4 weeks. In addition to the participants we had a number of workshops. Four one week workshops on: key UQ methodologies and motivating applications (an introductory workshop to give introductions to UQ methodologies from both traditions);, surrogate models for UQ in complex systems; reducing dimensions and cost for UQ in complex systems; and UQ for inverse problems in complex systems; and two one day workshops aimed at industry and other stakeholders. Most of the talks from the workshops are available on line. I will outline what happened during the programme and give my personal views on the achievements of the programme and what is still left to do.Sustainable Web Ecosystem Design
本スライドは2013年2月22日にPlone Users Group Japanが開催した「Plone Educational Symposium in Tokyo 2013」でご講演いただいた資料となります。
Agile large-scale machine-learning pipelines in drug discovery
This document discusses challenges in scaling machine learning for drug discovery as data grows. The author describes their work developing automated workflows and pipelines for building predictive models on large datasets using techniques like Hadoop, Spark, and cloud computing. Their goal is to enable non-experts to build accurate models and make predictions in real-time as structures are modified. The document outlines several projects applying these techniques to problems like site-of-metabolism prediction, target prediction, and next-generation sequencing analysis. It evaluates challenges in scaling modeling to many datasets and targets on high performance computing clusters and private clouds.
Presentation to BC Hydro
Johnny Rodgers is a graduate student researching ways to make home resource consumption more visible to encourage sustainable living. His work includes a net-zero solar home and an interface system. He aims to design feedback combining information visualization, interaction design, and social influences. Recent projects include an energy-efficient laneway home and informative art display incorporating interactive control systems.
EOS_IJSCM_day 1
This document summarizes the goals and phases of the Mathematics and Informatics for Environmental ‘Omic Data Synthesis (‘Omics) TAP program. The program has five phases: 1) NERC consultation, 2) forming an advisory group, 3) administering bioinformatics fellowships, 4) building an environmental ‘omics network, and 5) wrapping up the program. All phases aim to establish the Environmental ‘Omics Synthesis (EOS) centre to synthesize ‘omics data as recommended by the NEOMICS strategy through building collaborations between researchers. The advisory group will oversee administering fellowships focused on using ‘omics to address challenges in understanding biodiversity, evolution, genetics, ecosystems, and more. The
Engineering Outside the Box (presented at Ewha Woman's University, 13/11/14)
This document discusses thinking outside the box in engineering. It encourages divergent thinking and considering the social context of engineering projects. Engineers should examine the assumptions behind specifications and consider how projects fit within larger systems and ecosystems. Appropriate technology is designed at a small scale to be sustainable, decentralized, and maintained locally. Ecological engineering emerged to address issues like unsustainability and restoring degraded environments, and it considers the policy and economic impacts of design decisions. The social relationships that cause unsustainability can be addressed through creative problem solving and whole system thinking in engineering.
CORBEL West-Life webinar slides
This webinar discusses lessons learned from developing West-Life, a virtual research environment for integrative structural biology. West-Life brought together software tools from different disciplines to facilitate complex multi-technique research projects. Key lessons included understanding researchers' needs, promoting interoperability between existing tools, and involving the user community in strategic decisions through a "middle-out" approach. The webinar also highlights the maturity of structural biology users and the importance of semantic technologies and community development.
Module 1 Introduction to systems thinking
The document provides an introduction to systems thinking. It discusses how systems thinking views complex situations holistically rather than focusing on individual parts. A system is defined as consisting of interconnected elements that interact to serve a common purpose. In contrast, a collection lacks interactions between parts. The document outlines why systems thinking is needed to address today's complex and dynamic issues, and gives examples of applying systems thinking in various fields like business, health, and education.
Session ii g2 overview chemical modeling mmc
The document provides an introduction to systems biology. It begins with an overview of what systems biology is, including definitions that emphasize studying biological functions and mechanisms through signal and system-oriented approaches. It then discusses why systems biology is used, including to better understand biological systems as a whole rather than individual parts, and to aid in areas like drug development. The document also covers common techniques in systems biology, such as modeling biological networks and integrating different types of data. It concludes by listing some examples of case studies where systems biology has been applied, including for metabolic and gene regulatory network modeling.
Ecosystem Services & Social Science
- Ecosystem services aim to incorporate the value of nature into decisions but have failed to fully understand social and ecological interconnectedness.
- Social science can help reveal the complex relationships between society and nature through participatory mapping of cultural values and lived experiences of ecosystems.
- An integrated project in the Cotswolds uses a social learning approach and participatory ecosystem services framework to engage farmers, businesses, communities and agencies in improving water quality and other services.
What is the Integrative Analysis?
This is an introduction about the goal, key concepts and the method of the Integrative Analysis.
The Integrative Analysis seeks
to clarify complex problem
situations and conceive
changes coherent with adjacent
ecosystems.
It inquires conceptual systems in
relation to a broadened concept of
ecological patterns and energy
transformations in society and
integrates them with the personal
experience and viewpoints of
practitioners.
Thereby it ensures the integrity of resulting actions,
extending them with ulterior perspectives and an
ethic of earth and people care.
Similar to Jeroen Steenbeek Ecopath with Ecosim (20)
Varieties of Self-Awareness and Their Uses in Natural and Artificial Systems ...
Varieties of Self-Awareness and Their Uses in Natural and Artificial Systems ...
Dr Lael Parrott at the Landscape Science Cluster Seminar, May 2009
Dr Lael Parrott at the Landscape Science Cluster Seminar, May 2009
MUMS Opening Workshop - The Isaac Newton Institute Uncertainty Quantification...
MUMS Opening Workshop - The Isaac Newton Institute Uncertainty Quantification...
Agile large-scale machine-learning pipelines in drug discovery
Agile large-scale machine-learning pipelines in drug discovery
Engineering Outside the Box (presented at Ewha Woman's University, 13/11/14)
Engineering Outside the Box (presented at Ewha Woman's University, 13/11/14)
More from David LeBauer
Software and data as scaffolds for integrative science
This document discusses using software and data as scaffolds for integrative science. It describes challenges in agriculture and scientific problems that require knowledge across many scales and formats. Computational solutions are proposed to combine expert knowledge, data, and mechanistic models through platforms like PEcAn and TERRA REF. PEcAn provides common formats and tools to link models and data. TERRA REF aims to create open reference datasets from automated phenotyping to enable interdisciplinary collaboration. Future directions include expanding software, data sharing, and training to support more scientists in data-driven research.
Reusable Software and Open Data To Optimize Agriculture
Abstract:
Humans need a secure and sustainable food supply, and science can help. We have an opportunity to transform agriculture by combining knowledge of organisms and ecosystems to engineer ecosystems that sustainably produce food, fuel, and other services. The challenge is that the information we have. Measurements, theories, and laws found in publications, notebooks, measurements, software, and human brains are difficult to combine. We homogenize, encode, and automate the synthesis of data and mechanistic understanding in a way that links understanding at different scales and across domains. This allows extrapolation, prediction, and assessment. Reusable components allow automated construction of new knowledge that can be used to assess, predict, and optimize agro-ecosystems.
Developing reusable software and open-access databases is hard, and examples will illustrate how we use the Predictive Ecosystem Analyzer (PEcAn, pecanproject.org), the Biofuel Ecophysiological Traits and Yields database (BETYdb, betydb.org), and ecophysiological crop models to predict crop yield, decide which crops to plant, and which traits can be selected for the next generation of data driven crop improvement. A next step is to automate the use of sensors mounted on robots, drones, and tractors to assess plants in the field. The TERRA Reference Phenotyping Platform (TERRA-Ref, terraref.github.io) will provide an open access database and computing platform on which researchers can use and develop tools that use sensor data to assess and manage agricultural and other terrestrial ecosystems.
TERRA-Ref will adopt existing standards and develop modular software components and common interfaces, in collaboration with researchers from iPlant, NEON, AgMIP, USDA, rOpenSci, ARPA-E, many scientists and industry partners. Our goal is to advance science by enabling efficient use, reuse, exchange, and creation of knowledge.
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Invited talk for the "Informatics for Reproducibility in Earth and Environmental Science Research" session at the American Geophysical Union Fall Meeting, Dec 17 2015.
Yiqi Luo EcoPAD
Yiqi Luo at the University of Oklahoma has developed EcoPAD, an ecological platform for assimilating data into models to facilitate data-model integration and ecological forecasting. EcoPAD has functionality for workflows and a user menu to input weather and soil property data from 1895-2003, which is processed using DA algorithms and ECOPAD and TECO models to output metrics like GPP, ER, NPP, and Rh at the county level for 476 Great Plains counties under different global change scenarios of elevated CO2, warming, and altered precipitation.
David LeBauer PEcAn
PEcAn is a framework that aims to synthesize heterogeneous data and bridge the gap between conceptual and computational ecosystem models. It allows users to summarize current knowledge based on available data and mechanistic models, and identify sources of uncertainty to prioritize future data collection and model improvement. PEcAn has a modular design that allows models to be coupled within it or embedded in other workflows. It includes high-level functions and a web interface for remote execution and visualization of simulation models on high-performance computers. PEcAn modules support analysis, modeling, utilities, and an informatics backend database.
David Kelly SWIFT
Swift is a parallel scripting language that makes parallelism, failure recovery, and computing location transparent for running loosely-coupled application programs and utilities linked by exchanging files on clusters, clouds, and grids. It allows scripts to run on multiple distributed sites and diverse computing resources in a simple way. The example MODIS script processes land use images in parallel across different resources without needing to specify specific sites, and Swift's location independence lets users focus on science instead of configuration details.
Matt Jones software-interoperability
Matthew B. Jones discusses software for ecological forecasting and synthesis. He describes several existing software tools like the Ocean Health Index and Kepler that support scientific workflows for data access, analysis across packages, documentation, and provenance tracking. Scientific workflows promote interoperability and ensure executability, replicability, reproducibility, transparency, modularity, reusability, and provenance of analyses. Harnessing the "long tail" of science requires efficient data federation, interoperable software workflows, central search for discovery, and just-in-time data integration with loose coupling and schema-less storage.
Aaron Ellison: Analytic Web
This document discusses the motivation for creating reproducible science through documenting data provenance using an R implementation. It describes challenges such as standard R tools not collecting provenance and specialized tools having a steep learning curve. It then presents an approach where R scripts are instrumented to collect provenance information as data and process dependencies are executed, generating a directed acyclic graph database of the provenance that can be explored and visualized.
Ilkay Altintas: Kepler
Kepler is a scientific workflow system that facilitates the end-to-end computational scientific process of building, sharing, running, and learning from workflows. It provides features like an experiment-oriented workflow notebook, efficient data movement, multi-scale workflow building, and provenance tracking for reproducibility. Kepler builds upon the open-source Ptolemy II framework and is a cross-project collaboration involving multiple contributors and projects. Typical Kepler workflows consist of actors that perform tasks connected by data flow, and workflow parameters can be specified by users. Kepler enables programmable scalability for applications involving large-scale data access, computational analysis, and reuse across various scientific domains.
Aaron Ellison Keynote: Reaching the 99%
This document discusses statistical software options for ecologists and the need for software that is reproducible, traceable, usable, and comparable. It notes that R is a useful option as it has many relevant packages and the code is open-source, allowing others to verify and build on the work. However, some R packages can be difficult for newcomers and require additional software. The document evaluates different statistical modeling packages available in R.
Andrew Thomas OpenBUGS
The document describes the BUGS software and its use in Bayesian statistical modeling and inference. It provides an example model code in BUGS language to analyze a dataset with 30 observations and 5 time points, measuring the relationship between a response variable Y and a covariate x. The BUGS software is then used to analyze the model and data, producing posterior summaries and trace plots of key parameter estimates like alpha0, beta.c, and sigma.
Martyn Plummer JAGS
This document summarizes Just Another Gibbs Sampler (JAGS), a software program for Bayesian statistical modeling and analysis. It discusses JAGS' goals of providing a portable implementation of the BUGS modeling language with interfaces to R and other software. The document also outlines JAGS' history and releases, technical implementation using a virtual graphical model, strengths like being portable and widely used, limitations such as high memory overhead, and applications in epidemiology for building models to handle complex data. Future development may include Hamiltonian Monte Carlo for generalized linear mixed models, parallel computing capabilities, and other improvements.
Anders Nielsen AD Model-Builder
This document provides an introduction to AD Model Builder, a tool for developing and optimizing nonlinear models. It supports C++ programming with an automatic differentiation-aided quasi-Newton minimizer and libraries for parameters, data objects, uncertainty quantification, and random effects. AD Model Builder is used for complex, nonlinear models in fisheries science that should run quickly. A brief example fits a negative binomial distribution to data in just a few lines of code. A more complex fisheries catch-at-age model with over 100 parameters optimizes and runs output in 0.3 seconds. The document demonstrates how random effects can be easily incorporated.
Daniel Lee STAN
Stan is a probabilistic programming language that allows users to define statistical models and perform Bayesian inference. It uses Hamiltonian Monte Carlo (HMC) and the No-U-Turn Sampler (NUTS) for scalable and efficient sampling. NUTS adapts the number of HMC steps during sampling to reduce sensitivity to tuning parameters and improve effective sample sizes compared to basic HMC.
Ed Ionides POMP
The pomp R package provides tools for time series analysis using Partially Observed Markov Process (POMP) models, supporting various statistical methodologies like iterated filtering, particle Markov chain Monte Carlo, and approximate Bayesian computation. POMP models are defined by user-specified functions that simulate the latent Markov process and measurement models. The pomp package has been used to study disease and population ecology systems like malaria, measles, cholera, and Nicholson's blowflies.
Janine Illian R-INLA
INLA provides a fast alternative to MCMC for fitting Bayesian models, using Gaussian Markov random fields, latent Gaussian models, and Laplace approximations. It allows for complex spatial and spatiotemporal models to be fit that were previously too computationally expensive. The R-INLA library provides a user-friendly interface and the models can be specified using stochastic partial differential equations, providing flexibility for non-stationary, anisotropic, and other advanced models on different domains like spheres. The methodology continues to be expanded by its developers.
Andy Fox DART
The Data Assimilation Research Testbed (DART) is open source software that provides ensemble data assimilation and filtering algorithms to enable ecological forecasting. It has been used with over 100 models and assimilates many observation types. DART is being applied at the National Ecological Observatory Network (NEON) to help predict ecological processes by assimilating NEON field observations into land surface models.
Mike Dietze PEcAn
The document describes the PEcAn Project, which aims to provide accessible ecoinformatic tools for carbon-cycle model-data analysis and assimilation. It faces challenges from large and diverse data that requires fusing models and data. PEcAn creates a standardized database and modular tools in R to analyze data, assimilate it into models, and visualize outputs. It allows remote execution of models on databases and visualization. As a testbed, it aims to reconcile carbon information from multiple data streams in the Chequamegon-Ecosystem Atmosphere Study region.
de Valpine NIMBLE
NIMBLE is a modeling language and algorithm programming framework for Bayesian and likelihood-based statistical analysis. It allows users to write custom algorithms that operate on statistical models specified in the BUGS language. The framework processes BUGS models to extract relationships, builds a graphical model object, generates C++ code, and provides interfaces to compiled algorithm functions. This allows for flexible and distributed development of advanced Bayesian computational methods.
Anders Nielsen template model-builder
TMB is an R package for statistical modeling that was developed by Kasper Kristensen. It implements template-based models in C++ and allows for automatic differentiation, sparse matrices, parallel computing, and Laplace approximations for random effects. The document provides an introduction and overview of TMB, examples of simple linear and state-space models coded in TMB, and a table comparing the computation times of TMB to another template modeling software called ADMB.
Advancing Software for Ecological Forecasting: Public Sessions
This document announces a workshop bringing together scientists and developers to address challenges in ecological forecasting, including improving scientific workflows and statistical inference engines. The workshop consists of three sessions - the first introduces flexible spatial modeling with R-INLA, the second provides an overview of relevant software projects through short talks, and the third features a keynote on making statistical software useful for ecologists.
More from David LeBauer (20)
Software and data as scaffolds for integrative science
Software and data as scaffolds for integrative science
Reusable Software and Open Data To Optimize Agriculture
Reusable Software and Open Data To Optimize Agriculture
Advancing Software for Ecological Forecasting: Public Sessions
Advancing Software for Ecological Forecasting: Public Sessions
Recently uploaded
The Building Blocks of QuestDB, a Time Series Database
Talk Delivered at Valencia Codes Meetup 2024-06.
Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
一比一原版(Bradford毕业证书)布拉德福德大学毕业证如何办理
原版定制【微信:41543339】【(Bradford毕业证书)布拉德福德大学毕业证】【微信:41543339】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信41543339】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信41543339】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
一比一原版(Adelaide毕业证书)阿德莱德大学毕业证如何办理
原版定制【微信:41543339】【(Adelaide毕业证书)阿德莱德大学毕业证】【微信:41543339】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信41543339】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信41543339】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
Population Growth in Bataan: The effects of population growth around rural pl...
A population analysis specific to Bataan.
University of New South Wales degree offer diploma Transcript
澳洲UNSW毕业证书制作新南威尔士大学假文凭定制Q微168899991做UNSW留信网教留服认证海牙认证改UNSW成绩单GPA做UNSW假学位证假文凭高仿毕业证申请新南威尔士大学University of New South Wales degree offer diploma Transcript
一比一原版(Chester毕业证书)切斯特大学毕业证如何办理
毕业原版【微信:41543339】【(Chester毕业证书)切斯特大学毕业证】【微信:41543339】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信41543339】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信41543339】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
一比一原版(Harvard毕业证书)哈佛大学毕业证如何办理
毕业原版【微信:41543339】【(Harvard毕业证书)哈佛大学毕业证】【微信:41543339】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信41543339】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信41543339】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
一比一原版(UniSA毕业证书)南澳大学毕业证如何办理
原版定制【微信:41543339】【(UniSA毕业证书)南澳大学毕业证】【微信:41543339】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信41543339】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信41543339】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...
"Join us for STATATHON, a dynamic 2-day event dedicated to exploring statistical knowledge and its real-world applications. From theory to practice, participants engage in intensive learning sessions, workshops, and challenges, fostering a deeper understanding of statistical methodologies and their significance in various fields."
State of Artificial intelligence Report 2023
Artificial intelligence (AI) is a multidisciplinary field of science and engineering whose goal is to create intelligent machines.
We believe that AI will be a force multiplier on technological progress in our increasingly digital, data-driven world. This is because everything around us today, ranging from culture to consumer products, is a product of intelligence.
The State of AI Report is now in its sixth year. Consider this report as a compilation of the most interesting things we’ve seen with a goal of triggering an informed conversation about the state of AI and its implication for the future.
We consider the following key dimensions in our report:
Research: Technology breakthroughs and their capabilities.
Industry: Areas of commercial application for AI and its business impact.
Politics: Regulation of AI, its economic implications and the evolving geopolitics of AI.
Safety: Identifying and mitigating catastrophic risks that highly-capable future AI systems could pose to us.
Predictions: What we believe will happen in the next 12 months and a 2022 performance review to keep us honest.
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...
This webinar will explore cutting-edge, less familiar but powerful experimentation methodologies which address well-known limitations of standard A/B Testing. Designed for data and product leaders, this session aims to inspire the embrace of innovative approaches and provide insights into the frontiers of experimentation!
Global Situational Awareness of A.I. and where its headed
You can see the future first in San Francisco.
Over the past year, the talk of the town has shifted from $10 billion compute clusters to $100 billion clusters to trillion-dollar clusters. Every six months another zero is added to the boardroom plans. Behind the scenes, there’s a fierce scramble to secure every power contract still available for the rest of the decade, every voltage transformer that can possibly be procured. American big business is gearing up to pour trillions of dollars into a long-unseen mobilization of American industrial might. By the end of the decade, American electricity production will have grown tens of percent; from the shale fields of Pennsylvania to the solar farms of Nevada, hundreds of millions of GPUs will hum.
The AGI race has begun. We are building machines that can think and reason. By 2025/26, these machines will outpace college graduates. By the end of the decade, they will be smarter than you or I; we will have superintelligence, in the true sense of the word. Along the way, national security forces not seen in half a century will be un-leashed, and before long, The Project will be on. If we’re lucky, we’ll be in an all-out race with the CCP; if we’re unlucky, an all-out war.
Everyone is now talking about AI, but few have the faintest glimmer of what is about to hit them. Nvidia analysts still think 2024 might be close to the peak. Mainstream pundits are stuck on the wilful blindness of “it’s just predicting the next word”. They see only hype and business-as-usual; at most they entertain another internet-scale technological change.
Before long, the world will wake up. But right now, there are perhaps a few hundred people, most of them in San Francisco and the AI labs, that have situational awareness. Through whatever peculiar forces of fate, I have found myself amongst them. A few years ago, these people were derided as crazy—but they trusted the trendlines, which allowed them to correctly predict the AI advances of the past few years. Whether these people are also right about the next few years remains to be seen. But these are very smart people—the smartest people I have ever met—and they are the ones building this technology. Perhaps they will be an odd footnote in history, or perhaps they will go down in history like Szilard and Oppenheimer and Teller. If they are seeing the future even close to correctly, we are in for a wild ride.
Let me tell you what we see.
The Ipsos - AI - Monitor 2024 Report.pdf
According to Ipsos AI Monitor's 2024 report, 65% Indians said that products and services using AI have profoundly changed their daily life in the past 3-5 years.
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...
The Modern Marketing Reckoner (MMR) is a comprehensive resource packed with POVs from 60+ industry leaders on how AI is transforming the 4 key pillars of marketing – product, place, price and promotions.
办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样
原版一模一样【微信：741003700 】【(uts毕业证书)悉尼科技大学毕业证学历证书】【微信：741003700 】学位证，留信认证（真实可查，永久存档）offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原海外各大学 Bachelor Diploma degree, Master Degree Diploma
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
在线办理(英国UCA毕业证书)创意艺术大学毕业证在读证明一模一样
学校原件一模一样【微信：741003700 】《(英国UCA毕业证书)创意艺术大学毕业证》【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
End-to-end pipeline agility - Berlin Buzzwords 2024
We describe how we achieve high change agility in data engineering by eliminating the fear of breaking downstream data pipelines through end-to-end pipeline testing, and by using schema metaprogramming to safely eliminate boilerplate involved in changes that affect whole pipelines.
A quick poll on agility in changing pipelines from end to end indicated a huge span in capabilities. For the question "How long time does it take for all downstream pipelines to be adapted to an upstream change," the median response was 6 months, but some respondents could do it in less than a day. When quantitative data engineering differences between the best and worst are measured, the span is often 100x-1000x, sometimes even more.
A long time ago, we suffered at Spotify from fear of changing pipelines due to not knowing what the impact might be downstream. We made plans for a technical solution to test pipelines end-to-end to mitigate that fear, but the effort failed for cultural reasons. We eventually solved this challenge, but in a different context. In this presentation we will describe how we test full pipelines effectively by manipulating workflow orchestration, which enables us to make changes in pipelines without fear of breaking downstream.
Making schema changes that affect many jobs also involves a lot of toil and boilerplate. Using schema-on-read mitigates some of it, but has drawbacks since it makes it more difficult to detect errors early. We will describe how we have rejected this tradeoff by applying schema metaprogramming, eliminating boilerplate but keeping the protection of static typing, thereby further improving agility to quickly modify data pipelines without fear.
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