Reaching Consensus in Crowdsourced Transcription of Biocollections Information
Andréa Matsunaga (ammatsun@ufl.edu), Austin Mast, and José A.B. Fortes
10th IEEE International Conference on e-Science
October 23, 2014
Guarujá, SP, Brazil
EF-1115210
Strong Baselines for Neural Semi-supervised Learning under Domain ShiftSebastian Ruder
Oral presentation given at ACL 2018 about our paper Strong Baselines for Neural Semi-supervised Learning under Domain Shift (http://aclweb.org/anthology/P18-1096).
Topic Extraction using Machine LearningSanjib Basak
This document discusses topic extraction using machine learning techniques. It provides a history of topic models, including TF-IDF, LSI, pLSI and LDA. It describes how LDA uses a hierarchical Bayesian model to represent documents as mixtures of topics and topics as mixtures of words. The document demonstrates LDA and k-means topic modeling in R and Spark. It concludes that LDA provides mixtures of topics while k-means provides distinct topics, and unsupervised LDA may need domain experts to improve topic representation.
The document discusses the benevolent outreach programs of the Ministerial Alliance of Grove, Oklahoma, including the H.E.L.P center local food bank and Abundant Blessing family resource center. It describes how the centers provide food, household items, and other assistance to those in need, as well as counseling and education programs. The Alliance hopes to develop a new, larger center that can house these programs and services as well as new initiatives, in order to help more members of the community.
This document summarizes the media landscape in Somalia. It notes that Somalia has a highly media literate society due to nomadic traditions. After the civil war in 1991, radio stations emerged that were either politically controlled by warlords or established by businesses. Over time, independent radio flourished thanks to investment from the Somali diaspora. However, the media environment is dangerous, with Al-Shabab intimidating and controlling some radio stations. Journalists have fled due to threats and attacks. The fractured political environment also influences media in Somaliland, Puntland and Mogadishu. Despite challenges, Somali media demonstrates resilience.
1. water availability presentation in englishglmcguire
1) Gnternational Alaska LLC offers 9.5 billion gallons of pure water from Blue Lake in Alaska for sale in Latin America and Asia. The water is available in tankers ranging from 12-18 million gallons or 270 million gallons per month.
2) The document provides water quality reports from the City of Sitka, Alaska where the water originates, showing the water meets all EPA standards.
3) The company aims to supply the highest quality water emerging from the pure Arctic region to customers in Mexico, Latin America and Asia from its headquarters in Dallas, Texas.
Strong Baselines for Neural Semi-supervised Learning under Domain ShiftSebastian Ruder
Oral presentation given at ACL 2018 about our paper Strong Baselines for Neural Semi-supervised Learning under Domain Shift (http://aclweb.org/anthology/P18-1096).
Topic Extraction using Machine LearningSanjib Basak
This document discusses topic extraction using machine learning techniques. It provides a history of topic models, including TF-IDF, LSI, pLSI and LDA. It describes how LDA uses a hierarchical Bayesian model to represent documents as mixtures of topics and topics as mixtures of words. The document demonstrates LDA and k-means topic modeling in R and Spark. It concludes that LDA provides mixtures of topics while k-means provides distinct topics, and unsupervised LDA may need domain experts to improve topic representation.
The document discusses the benevolent outreach programs of the Ministerial Alliance of Grove, Oklahoma, including the H.E.L.P center local food bank and Abundant Blessing family resource center. It describes how the centers provide food, household items, and other assistance to those in need, as well as counseling and education programs. The Alliance hopes to develop a new, larger center that can house these programs and services as well as new initiatives, in order to help more members of the community.
This document summarizes the media landscape in Somalia. It notes that Somalia has a highly media literate society due to nomadic traditions. After the civil war in 1991, radio stations emerged that were either politically controlled by warlords or established by businesses. Over time, independent radio flourished thanks to investment from the Somali diaspora. However, the media environment is dangerous, with Al-Shabab intimidating and controlling some radio stations. Journalists have fled due to threats and attacks. The fractured political environment also influences media in Somaliland, Puntland and Mogadishu. Despite challenges, Somali media demonstrates resilience.
1. water availability presentation in englishglmcguire
1) Gnternational Alaska LLC offers 9.5 billion gallons of pure water from Blue Lake in Alaska for sale in Latin America and Asia. The water is available in tankers ranging from 12-18 million gallons or 270 million gallons per month.
2) The document provides water quality reports from the City of Sitka, Alaska where the water originates, showing the water meets all EPA standards.
3) The company aims to supply the highest quality water emerging from the pure Arctic region to customers in Mexico, Latin America and Asia from its headquarters in Dallas, Texas.
We're specialists in online marketing for dentists and dental practices. Visit our website to get your complimentary copy of our Amazon Bestseller "How to get more new dental patients with the power of the web"
El documento resume la evolución de los trabajos de grado de los estudiantes de Diseño Gráfico entre 2014 y 2015. En septiembre de 2014, 78 estudiantes estaban atrasados con sus trabajos de grado, mientras que en mayo de 2015 este número aumentó a 85 estudiantes. Para junio de 2015, 19 estudiantes estaban listos para graduarse, mientras que 23 habían obtenido la resolución de su trabajo de grado y 23 estaban en proceso. En total, 36 estudiantes se graduaron entre 2014 y el primer semestre de 2015.
This document provides an introduction and overview of embedded systems. It discusses that embedded systems use microprocessors or microcontrollers to perform dedicated functions, unlike general purpose computers. The key aspects covered include:
- Embedded systems integrate hardware and software to perform specific tasks, with optimization for cost, size and performance.
- Examples of embedded systems include appliances, vehicles, network devices, medical equipment, and more.
- Embedded systems have constraints of limited resources, real-time performance, low power usage, and reliability.
- The document classifies embedded systems and discusses their components and features. Stand-alone, real-time, networked, and mobile embedded systems are described.
Gary Patterson has been interviewed or presented internationally to major publications and groups on a variety of business topics. The document provides a list of publications and descriptions of each, including information on their target audiences and topics covered related to business, management, and leadership.
macro research -First draft WITH TABLE OF CONTENTFerdous Mohammed
This document discusses unemployment in Egypt. It begins with background information on Egypt's geography, demographics, and economy. The purpose is to study Egypt's unemployment rate from 2010-2014, including causes like reduced foreign investment and job quality, and effects on GDP. The unemployment rate remained at 13.4% in 2013. Solutions discussed include government job training programs and encouraging agriculture. Recommendations focus on increasing aggregate demand through fiscal and monetary policy to boost GDP and decrease unemployment, as well as improving the business environment to encourage private sector growth and job creation. Addressing unemployment, especially among youth, remains an important issue.
Prashant Yadav is seeking a position that allows him to utilize his skills and experience. He has over 8 years of experience working in finance and accounting roles for companies like Accenture and ACS. His experience includes financial analysis, revenue recognition, budgeting, reporting, and account reconciliation. He also has 1 year of experience working as a visa officer processing UK visa applications. He holds a B.Com degree and is proficient in SAP FICO, Tally, and Microsoft Office applications.
The poem describes a prodigal son who finds himself living and working in deplorable conditions in a pigsty after wasting his money on alcohol. He is so immersed in the filth and stench of the pigs that he can no longer think clearly about his situation. Though some mornings the beauty of the sunrise makes him feel he can endure this exile a while longer, he knows he cannot stay forever. It will take him a long time to fully decide to leave this life behind and finally return home.
Ion Armanu is a Romanian national seeking a new challenging position. He has over 10 years of work experience in various industries such as drilling rigs manufacturing, metalurgy, energy, and insurance. His most recent role was as a Project Manager for Upet Targoviste, where he was responsible for acquiring clients and negotiating contracts resulting in over 5.9 million Euro in revenue. He has a Bachelor's degree in Economics from the University of Oil and Gas in Ploiesti, Romania.
This document discusses hypothesis testing for claims about population proportions and the difference between two population proportions. It provides information on type I and type II errors. Examples are provided to demonstrate hypothesis testing for a single proportion claim and the difference between two proportions. The examples show setting up the null and alternative hypotheses, checking assumptions, calculating the test statistic, determining the p-value or comparing to the critical value, and making a conclusion. Confidence intervals are also discussed as a way to estimate population proportions and differences between proportions. The examples provide step-by-step workings to test claims about spending behaviors with different denominations of money.
This document provides an overview of ClimateGPT, an AI model developed by AppTek to improve the fluency of answers to climate change questions. Some key points:
- ClimateGPT was developed by fine-tuning a generative language model on 4.2B tokens of climate-related text from various sources and training it with 10K demonstration question-answer pairs curated with climate scientists.
- It uses hierarchical retrieval and information from 700 scientific documents tagged along three climate dimensions to provide supportive information for its answers.
- The model was evaluated on standard language and climate tasks, matching the performance of a much larger model but with fewer parameters and less energy usage. It also allows for multilingual responses
Evaluating Classification Algorithms Applied To Data Streams Esteban DonatoEsteban Donato
This document summarizes and evaluates several algorithms for classification of data streams: VFDTc, UFFT, and CVFDT. It describes their approaches for handling concept drift, detecting outliers and noise. The algorithms were tested on synthetic data streams generated with configurable attributes like drift frequency and noise percentage. Results show VFDTc and UFFT performed best in accuracy, while CVFDT and UFFT were fastest. The study aims to help choose algorithms suitable for different data stream characteristics like gradual vs sudden drift or frequent vs infrequent drift.
The document discusses terminology management software developed by the Olanto Foundation. It presents Olanto's terminology software called myTERM, which is based on the TBX standard and supports multiple terminology models. The document also describes experiments conducted using myTERM to validate term derivations across languages using transitivity and corpus correlation methods. It introduces a new software component called How2Say that infers terminological translations across languages based on frequent n-grams found in corpora.
Genetic algorithms are optimization techniques inspired by biological evolution that can efficiently search large spaces to find optimal solutions; they work by evolving a population of potential solutions through mechanisms like selection, crossover and mutation. Genetic algorithms have been successfully applied to problems in many domains and are now widely used in business, science and engineering for applications like scheduling, design, control, and machine learning.
The data streaming processing paradigm and its use in modern fog architecturesVincenzo Gulisano
Invited lecture at the University of Trieste.
The lecture covers (briefly) the data streaming processing paradigm, research challenges related to distributed, parallel and deterministic streaming analysis and the research of the DCS (Distributed Computing and Systems) groups at Chalmers University of Technology.
The document proposes streaming algorithms for performing Pearson's chi-square goodness-of-fit test in a streaming setting with minimal assumptions. It presents algorithms for the one-sample and two-sample continuous chi-square tests that use O(K^2log(N)√N) space, where K is the number of bins and N is the stream length. It also shows that no sublinear solution exists for the categorical chi-square test and provides a heuristic algorithm. The algorithms are validated on real and synthetic data and can detect deviations from distributions or differences between streams with low memory requirements.
F. Serdio, E. Lughofer, K. Pichler, T. Buchegger, M. Pichler and H. Efendic, Multivariate Fault Detection using Vector Autoregressive Moving Average and Orthogonal Transformation in the residual Space, Annual Conference of the Prognostics and Health Management Society, PHM 2013, New Orleans, LA, USA, 2013, pp. 548-555.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
Modern Computing: Cloud, Distributed, & High Performanceinside-BigData.com
In this video, Dr. Umit Catalyurek from Georgia Institute of Technology presents: Modern Computing: Cloud, Distributed, & High Performance.
Ümit V. Çatalyürek is a Professor in the School of Computational Science and Engineering in the College of Computing at the Georgia Institute of Technology. He received his Ph.D. in 2000 from Bilkent University. He is a recipient of an NSF CAREER award and is the primary investigator of several awards from the Department of Energy, the National Institute of Health, and the National Science Foundation. He currently serves as an Associate Editor for Parallel Computing, and as an editorial board member for IEEE Transactions on Parallel and Distributed Computing, and the Journal of Parallel and Distributed Computing.
Learn more: http://www.bigdatau.org/data-science-seminars
Watch the video presentation: http://wp.me/p3RLHQ-ghU
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
Cyclone DDS Unleashed: Scalability in DDS and Dealing with Large SystemsZettaScaleTechnology
The document discusses scalability in distributed data systems and mechanisms to address it. It introduces concepts like participant discovery, endpoint discovery, and acknacks that can impact scalability as systems grow. To reduce these effects, it recommends separating components in time and space through controlled startup, delayed acknacks, system partitioning, and using a hub-and-spoke architecture with data forwarding instead of a flat network. Experiments show the hub-and-spoke approach completes faster and with less busy processing than a flat network as the number of components increases.
Presentation to ImmPort Science Meeting, February 27, 2014 on the proper treatment of value sets in the Immport Immunology Database and Analysis Portal
We're specialists in online marketing for dentists and dental practices. Visit our website to get your complimentary copy of our Amazon Bestseller "How to get more new dental patients with the power of the web"
El documento resume la evolución de los trabajos de grado de los estudiantes de Diseño Gráfico entre 2014 y 2015. En septiembre de 2014, 78 estudiantes estaban atrasados con sus trabajos de grado, mientras que en mayo de 2015 este número aumentó a 85 estudiantes. Para junio de 2015, 19 estudiantes estaban listos para graduarse, mientras que 23 habían obtenido la resolución de su trabajo de grado y 23 estaban en proceso. En total, 36 estudiantes se graduaron entre 2014 y el primer semestre de 2015.
This document provides an introduction and overview of embedded systems. It discusses that embedded systems use microprocessors or microcontrollers to perform dedicated functions, unlike general purpose computers. The key aspects covered include:
- Embedded systems integrate hardware and software to perform specific tasks, with optimization for cost, size and performance.
- Examples of embedded systems include appliances, vehicles, network devices, medical equipment, and more.
- Embedded systems have constraints of limited resources, real-time performance, low power usage, and reliability.
- The document classifies embedded systems and discusses their components and features. Stand-alone, real-time, networked, and mobile embedded systems are described.
Gary Patterson has been interviewed or presented internationally to major publications and groups on a variety of business topics. The document provides a list of publications and descriptions of each, including information on their target audiences and topics covered related to business, management, and leadership.
macro research -First draft WITH TABLE OF CONTENTFerdous Mohammed
This document discusses unemployment in Egypt. It begins with background information on Egypt's geography, demographics, and economy. The purpose is to study Egypt's unemployment rate from 2010-2014, including causes like reduced foreign investment and job quality, and effects on GDP. The unemployment rate remained at 13.4% in 2013. Solutions discussed include government job training programs and encouraging agriculture. Recommendations focus on increasing aggregate demand through fiscal and monetary policy to boost GDP and decrease unemployment, as well as improving the business environment to encourage private sector growth and job creation. Addressing unemployment, especially among youth, remains an important issue.
Prashant Yadav is seeking a position that allows him to utilize his skills and experience. He has over 8 years of experience working in finance and accounting roles for companies like Accenture and ACS. His experience includes financial analysis, revenue recognition, budgeting, reporting, and account reconciliation. He also has 1 year of experience working as a visa officer processing UK visa applications. He holds a B.Com degree and is proficient in SAP FICO, Tally, and Microsoft Office applications.
The poem describes a prodigal son who finds himself living and working in deplorable conditions in a pigsty after wasting his money on alcohol. He is so immersed in the filth and stench of the pigs that he can no longer think clearly about his situation. Though some mornings the beauty of the sunrise makes him feel he can endure this exile a while longer, he knows he cannot stay forever. It will take him a long time to fully decide to leave this life behind and finally return home.
Ion Armanu is a Romanian national seeking a new challenging position. He has over 10 years of work experience in various industries such as drilling rigs manufacturing, metalurgy, energy, and insurance. His most recent role was as a Project Manager for Upet Targoviste, where he was responsible for acquiring clients and negotiating contracts resulting in over 5.9 million Euro in revenue. He has a Bachelor's degree in Economics from the University of Oil and Gas in Ploiesti, Romania.
This document discusses hypothesis testing for claims about population proportions and the difference between two population proportions. It provides information on type I and type II errors. Examples are provided to demonstrate hypothesis testing for a single proportion claim and the difference between two proportions. The examples show setting up the null and alternative hypotheses, checking assumptions, calculating the test statistic, determining the p-value or comparing to the critical value, and making a conclusion. Confidence intervals are also discussed as a way to estimate population proportions and differences between proportions. The examples provide step-by-step workings to test claims about spending behaviors with different denominations of money.
This document provides an overview of ClimateGPT, an AI model developed by AppTek to improve the fluency of answers to climate change questions. Some key points:
- ClimateGPT was developed by fine-tuning a generative language model on 4.2B tokens of climate-related text from various sources and training it with 10K demonstration question-answer pairs curated with climate scientists.
- It uses hierarchical retrieval and information from 700 scientific documents tagged along three climate dimensions to provide supportive information for its answers.
- The model was evaluated on standard language and climate tasks, matching the performance of a much larger model but with fewer parameters and less energy usage. It also allows for multilingual responses
Evaluating Classification Algorithms Applied To Data Streams Esteban DonatoEsteban Donato
This document summarizes and evaluates several algorithms for classification of data streams: VFDTc, UFFT, and CVFDT. It describes their approaches for handling concept drift, detecting outliers and noise. The algorithms were tested on synthetic data streams generated with configurable attributes like drift frequency and noise percentage. Results show VFDTc and UFFT performed best in accuracy, while CVFDT and UFFT were fastest. The study aims to help choose algorithms suitable for different data stream characteristics like gradual vs sudden drift or frequent vs infrequent drift.
The document discusses terminology management software developed by the Olanto Foundation. It presents Olanto's terminology software called myTERM, which is based on the TBX standard and supports multiple terminology models. The document also describes experiments conducted using myTERM to validate term derivations across languages using transitivity and corpus correlation methods. It introduces a new software component called How2Say that infers terminological translations across languages based on frequent n-grams found in corpora.
Genetic algorithms are optimization techniques inspired by biological evolution that can efficiently search large spaces to find optimal solutions; they work by evolving a population of potential solutions through mechanisms like selection, crossover and mutation. Genetic algorithms have been successfully applied to problems in many domains and are now widely used in business, science and engineering for applications like scheduling, design, control, and machine learning.
The data streaming processing paradigm and its use in modern fog architecturesVincenzo Gulisano
Invited lecture at the University of Trieste.
The lecture covers (briefly) the data streaming processing paradigm, research challenges related to distributed, parallel and deterministic streaming analysis and the research of the DCS (Distributed Computing and Systems) groups at Chalmers University of Technology.
The document proposes streaming algorithms for performing Pearson's chi-square goodness-of-fit test in a streaming setting with minimal assumptions. It presents algorithms for the one-sample and two-sample continuous chi-square tests that use O(K^2log(N)√N) space, where K is the number of bins and N is the stream length. It also shows that no sublinear solution exists for the categorical chi-square test and provides a heuristic algorithm. The algorithms are validated on real and synthetic data and can detect deviations from distributions or differences between streams with low memory requirements.
F. Serdio, E. Lughofer, K. Pichler, T. Buchegger, M. Pichler and H. Efendic, Multivariate Fault Detection using Vector Autoregressive Moving Average and Orthogonal Transformation in the residual Space, Annual Conference of the Prognostics and Health Management Society, PHM 2013, New Orleans, LA, USA, 2013, pp. 548-555.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
Modern Computing: Cloud, Distributed, & High Performanceinside-BigData.com
In this video, Dr. Umit Catalyurek from Georgia Institute of Technology presents: Modern Computing: Cloud, Distributed, & High Performance.
Ümit V. Çatalyürek is a Professor in the School of Computational Science and Engineering in the College of Computing at the Georgia Institute of Technology. He received his Ph.D. in 2000 from Bilkent University. He is a recipient of an NSF CAREER award and is the primary investigator of several awards from the Department of Energy, the National Institute of Health, and the National Science Foundation. He currently serves as an Associate Editor for Parallel Computing, and as an editorial board member for IEEE Transactions on Parallel and Distributed Computing, and the Journal of Parallel and Distributed Computing.
Learn more: http://www.bigdatau.org/data-science-seminars
Watch the video presentation: http://wp.me/p3RLHQ-ghU
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
Cyclone DDS Unleashed: Scalability in DDS and Dealing with Large SystemsZettaScaleTechnology
The document discusses scalability in distributed data systems and mechanisms to address it. It introduces concepts like participant discovery, endpoint discovery, and acknacks that can impact scalability as systems grow. To reduce these effects, it recommends separating components in time and space through controlled startup, delayed acknacks, system partitioning, and using a hub-and-spoke architecture with data forwarding instead of a flat network. Experiments show the hub-and-spoke approach completes faster and with less busy processing than a flat network as the number of components increases.
Presentation to ImmPort Science Meeting, February 27, 2014 on the proper treatment of value sets in the Immport Immunology Database and Analysis Portal
Presentation for the Softskills Seminar course @ Telecom ParisTech. Topic is the paper by Domings Hulten "Mining high speed data streams". Presented by me the 30/11/2017
Creating a dataset of peer review in computer science conferences published b...Aliaksandr Birukou
Computer science (CS) as a field is characterised by higher publication numbers and prestige of conference proceedings as opposed to scholarly journal articles. In this presentation we present preliminary results of the extraction and analysis of peer review information from computer science conferences published by Springer in almost 10,000 proceedings volumes. The results will be uploaded to lod.springer.com, with the purpose of creation of the largest dataset of peer review processes in CS conferences.
Semantic Analysis to Compute Personality Traits from Social Media PostsGiulio Carducci
This document discusses using semantic analysis of social media posts to automatically compute personality traits based on the Five Factor Model. It presents the background on using language to predict personality traits and describes word embeddings to represent words as vectors. An experiment is described that uses a dataset of social media posts with known personality scores to train models like SVM and LASSO to predict the Big Five personality traits of openness, conscientiousness, extraversion, agreeableness, and neuroticism. The models are tested on datasets from MyPersonality and Twitter, achieving mean squared errors between 0.3-0.7. Future work proposes expanding the approach to larger datasets and additional features.
Introduction to Data streaming - 05/12/2014Raja Chiky
Raja Chiky is an associate professor whose research interests include data stream mining, distributed architectures, and recommender systems. The document outlines data streaming concepts including what a data stream is, data stream management systems, and basic approximate algorithms used for processing massive, high-velocity data streams. It also discusses challenges in distributed systems and using semantic technologies for data streaming.
Data analytics for engineers- introductionRINUSATHYAN
This document discusses key concepts in data analytics and statistics. It defines data and how data can be collected and used for decision making. It then discusses the evolution of analytic scalability, including traditional analytic architectures that pull all data into a separate environment for analysis, and modern in-database architectures that keep processing and analysis within the database. The document also covers statistical concepts like sampling, sampling frames, sampling designs, statistics versus parameters, sampling error, and definitions of mean, median, mode, and standard deviation.
70 C o m m u n i C at i o n s o f t h E a C m | j u ly 2 0 1 3 | v o l . 5 6 | n o . 7
contributed articles
V o i c e i n p u t i s a major requirement for practical
question answering (QA) systems designed for
smartphones. Speech-recognition technologies are
not fully practical, however, due to fundamental
problems (such as a noisy environment, speaker
diversity, and errors in speech). Here, we define the
information distance between a speech-recognition
result and a meaningful query from which we can
reconstruct the intended query, implementing this
framework in our RSVP system.
In 12 test cases covering male, female, child, adult,
native, and non-native English speakers, each with
57 to 300 questions from an independent test set of
300 questions, RSVP on average re-
duced the number of errors by 16% for
native speakers and by 30% for non-
native speakers over the best-known
speech-recognition software. The idea
was then extended to translation in
the QA domain.
In our project, which is supported
by Canada’s International Develop-
ment Research Centre (http://www.
idrc.ca/), we built a voice-enabled
cross-language QA search engine for
cellphone users in the developing
world. Using voice input, a QA system
would be a convenient tool for people
who do not write, for people with im-
paired vision, and for children who
might wish their Talking Tom or R2-
D2 really could talk.
The quality of today’s speech-rec-
ognition technologies, exemplified
by systems from Google, Microsoft,
and Nuance does not fully meet such
needs for several reasons:
˲ Noisy environments in common
audio situations;1
˲ Speech variations, as in, say,
adults vs. children, native speakers
vs. non-native speakers, and female
vs. male, especially when individual
voice-input training is not possible, as
in our case; and
˲ Incorrect and incomplete sen-
tences; even customized speech-rec-
ognition systems would fail due to
coughing, breaks, corrections, and
the inability to distinguish between,
say, “sailfish” and “sale fish.”
Speech-recognition systems can be
trained for a “fixed command set” of
up to 10,000 items, a paradigm that
information
Distance
Between What
i said and
What it heard
D o i : 1 0 . 1 1 4 5 / 2 4 8 3 8 5 2 . 2 4 8 3 8 6 9
The RSVP voice-recognition search engine
improves speech recognition and translation
accuracy in question answering.
BY YanG tanG, Di WanG, JinG Bai, XiaoYan Zhu, anD minG Li
key insights
focusing on an infinite but highly
structured domain (such as Qa),
we significantly improve general-purpose
speech recognition results and
general-purpose translation results.
assembling a large amount of internet
data is key to helping us achieve these
goals; in the highly structured Qa domain,
we collected millions of human-asked
questions covering 99% of question types.
RsVP development is guided by a theory
involving informatio.
1) Scientists at the Advanced Photon Source use the Argonne Leadership Computing Facility for data reconstruction and analysis from experimental facilities in real-time or near real-time. This provides feedback during experiments.
2) Using the Swift parallel scripting language and ALCF supercomputers like Mira, scientists can process terabytes of data from experiments in minutes rather than hours or days. This enables errors to be detected and addressed during experiments.
3) Key applications discussed include near-field high-energy X-ray diffraction microscopy, X-ray nano/microtomography, and determining crystal structures from diffuse scattering images through simulation and optimization. The workflows developed provide significant time savings and improved experimental outcomes.
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Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...Aggregage
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!
The Building Blocks of QuestDB, a Time Series Databasejavier ramirez
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.
Global Situational Awareness of A.I. and where its headedvikram sood
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.
Enhanced Enterprise Intelligence with your personal AI Data Copilot.pdfGetInData
Recently we have observed the rise of open-source Large Language Models (LLMs) that are community-driven or developed by the AI market leaders, such as Meta (Llama3), Databricks (DBRX) and Snowflake (Arctic). On the other hand, there is a growth in interest in specialized, carefully fine-tuned yet relatively small models that can efficiently assist programmers in day-to-day tasks. Finally, Retrieval-Augmented Generation (RAG) architectures have gained a lot of traction as the preferred approach for LLMs context and prompt augmentation for building conversational SQL data copilots, code copilots and chatbots.
In this presentation, we will show how we built upon these three concepts a robust Data Copilot that can help to democratize access to company data assets and boost performance of everyone working with data platforms.
Why do we need yet another (open-source ) Copilot?
How can we build one?
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Analysis insight about a Flyball dog competition team's performance
Matsunaga crowdsourcing IEEE e-science 2014
1. iDigBio is funded by a grant from the National Science Foundation’s Advancing Digitization of Biodiversity Collections Program (Cooperative Agreement EF-1115210). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. Reaching Consensus in Crowdsourced Transcription of BiocollectionsInformation
Andréa Matsunaga (ammatsun@ufl.edu), Austin Mast, and José A.B. Fortes
10th IEEE International Conference on e-Science
October 23, 2014
Guarujá, SP, Brazil
2. 2
Background and Motivation
•Estimated 1-billion biological specimens in the US
•iDigBio+ Thematic Collections Network (TCN) + Partners to Existing Network (PEN)
3. 3
Background and Motivation
•TCNs and PENs performing digitization work
•Generating images, transcribing information about what/when/where/who
•If digitization took 1 second and if we performed in sequence:
–1,000,000,000 seconds > 30 years
•Parallelism:
–Crowdsourcing!!
4. 4
Crowdsourcing Transcription Projects
•NotesFromNature(http://www.notesfromnature.org/)
–Zooniverseplatform
•Once the user selects the region with the label, s/he can start transcribing and parsing information to a number of pre- defined fields
•For a requester, a pre-defined number of transcriptions are returned
5. 5
Crowdsourcing Transcription Projects
•ALA (http://volunteer.ala.org.au/)
–Platform: Grails
•User zooms in to read the label and parse to the custom pre- defined terms
•Single worker followed by expert approval
6. 6
Crowdsourcing Transcription Projects
•Symbiota(http://lbcc1.acis.ufl.edu/volunteer)
–Platform: PHP
•Ability to OCR and parse data
•Single worker followed by expert approval
7. 7
The transcription task
Location
Scientific Name
Scientific Author
Collected by
Habitat and description
County
Collector Number
Collection Date
State/Province
8. 8
Proposed Consensus Approach
•Goal:
–Reach consensus with minimum number of transcriptions
•Method:
–Control the number of workers per task
–Apply lossless and/or lossyalgorithms per field
Transcription task Queue
Crowdsourcing
Volunteer’s Transcription
Pick task
ti
ti’ Past Transcriptions
Lossless algorithms
No
Lossyalgorithms
Consensus reached?
Yes
No
Consensus reached?
Yes
Solution
9. 9
Lossless normalization algorithms
Code
Lossless functionality
b
Removes all extra whitespaces
n
Apply specific transformation functions on a per-field basis (e.g., to normalize section/township/range, proper names, and latitude/longitude)
t
Apply specific translation tables on a per-field basis to expand abbreviations (e.g., hy, hwy, and hiwayto highway) or to shorten expansions (e.g., Florida to FL)
10. 10
Lossynormalization algorithms
Code
Lossyfunctionality
w
Approximate comparison by ignoring all whitespace (e.g., “0–3” is equivalent to “0 –3”)
c
Case insensitive approximate comparison (e.g., “Road” and “road” are considered equivalent)
s
Consider two sequences equivalent when one is a substring of another or one sequence contains all words from the other sequence
p
Punctuation insensitive approximate comparison (e.g., separation of sentences with comma, semi-colon or period are considered equivalent)
f
Approximate fingerprint comparison ignoring the order of words in sentences
l
Approximate equivalency when sequences have Levenshteindistance within a configurable threshold (l2 indicates a maximum distance of 2)
11. 11
Alternative voting and consensus output
Code
Voting and consensus
v
Consensus is reached when there is a single group (set of matching answers) that has the most votes, instead of requiring strict majority vote among all answers
a
Outputs best available answers when consensus is not achieved
n=4
Majority voting requires 3 matching answers
→Consensus not reached
v: Blue set has most votes
→Consensus reached 푛 2+1
12. 12
Experimental Setup
•Notes from Nature
•Herbarium specimens from a single institution
•Configured to require 10 workers per task that yielded close-to- linear distribution due to empty tasks and skips
•23,557 total transcriptions completed by at least 1,089 distinct workers
0
50
100
150
200
250
300
350
400
1
56
111
166
221
276
331
386
441
496
551
606
661
716
771
826
881
936
991
1046
Transcriptions per Worker
Distinct Worker ID
Transcriptions Performed by Individual Workers
Total of 23557 transcriptions completed
9950anonymous transcriptions
1089 distinct known workers
255 single transcription workers
Top worker:
381 transcriptions
2.00%
4.42%
6.99%
8.76%
11.10%
10.75%
11.87%
11.95%
15.43%
16.63%
0.11%
0%
5%
10%
15%
20%
1
2
3
4
5
6
7
8
9
10
11
Workers per Task
Worker Distribution Per Task
Field
Uniq#
Field
Uniq#
Country
39
Location
16,161
State/Province
288
Habitat
15,134
County
655
Collected by
3,380
Scientific name
5,941
Collector Number
3,665
Scientific author
4,088
Collection date
2,287
13. 13
1.8%
53.2%
61.4%
84.2%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Consensus Achievement (%)
Consensus Achievement Varying Algorithms
nf
bnt
bntwcsp
bntwcspf
bntwcspfl2
bntwcspfl2v
Overall Performance
•Full consensus improvement from 1.8% to 84.2%
•Confirms intuition that country, state/province, county, collector numberand collector dateare “easy”
•Lossless algorithms have small impact except for scientific authorand collected by
•Being insensitive to whitespace, punctuation, and letter case as well as considering substrings, provide the greatest improvement when including lossyalgorithms in “difficult” fields
14. 14
Additional Verification
•Consensus reached mainly with lossless algorithms
•Low percentage of blank responses
15. 15
Consensus Accuracy
•300 labels were transcribed by an expert
•Expert had access to information across labels that workers did not have
•Effect on the overall accuracy is minimal
–0.9% drop for accepting cases that did not reach consensus
–2.3% drop for minimizing the needed workforce
92.0%
91.1%
59
57
54
33
28
27
37
54
55
53
59
0
50
100
150
200
250
300
0%
20%
40%
60%
80%
100%
Above 90% Thresold
Character Score (%)
Consensus Accuracy (Consensus Needed vs. Accept Best)
Consensus Needed (%)
Accept Best (%)
Consensus Needed
Accept Best
92.0%
89.7%
0
50
100
150
200
250
300
0%
20%
40%
60%
80%
100%
Above 90% Threshold
Character Score
Consensus Accuracy (Min. Workers vs. All Workers)
All Workers (%)
Min. Workers (%)
All Workers
Min. Workers2∗푚푎푡푐ℎ푒푠 푙푒푛푠1+푙푒푛(푠2)
16. 16
Workforce Savings
•Can be as high as 55.8% for the distribution in the studied dataset
•Good for a fixed setting: 3 workers
•Controller advantage: 3 workers is just a good average, and our results show that there are cases where up to 9 workers were needed to reach overall consensus
2.00
2.75
2.93
3.11
3.16
3.30
3.29
3.25
3.20
3.00
0
2
4
6
8
10
2
3
4
5
6
7
8
9
10
11
Workers per Task
Workforce Savings
Original Number of Workers
Minimum Number of Workers
55.8% of jobs saved with controller
17. 17
Task Design Improvement recommendations
•Restricted user interface improves consensus and accuracy
–Caution to not restrict valid scenarios (e.g., partial dates, range of dates)
–Broadly defined fields could be engineered to capture more parsed data (e.g., lat/long, TRS)
•Exploring relationships between tasks
–Enter collector number and collection date first
–Update related record to have the same information
•Additional training
–Problems pronounced in separating scientific names from its authorship
18. 18
Additional Improvements to Consensus Algorithms
•Code is modular and open; thus, opportunity for:
–Custom dictionaries could be applied (general dictionaries led to a high number of false positives due to the amount of abbreviation and names)
–Scientific name parsers
–External contributions
–https://github.com/idigbio-citsci- hackathon/CrowdConsensus
•Merge matched outputs after lossyalgorithms are applied
–R. E. Perdue, Jr. and K. Blum
–Re Perdue Jr and K. Blum
–R. R. Perdue Jr, K. Blum
•Additional validation across fields (consistency)
•Apply consensus controller on a per-field basis
19. 19
Recommendations Beyond Crowdsourcing
•Leveraging and improving:
–Optical Character Recognition (OCR)
–Natural Language Processing (NLP)
•2-way street scenarios:
–Use crowdsourcing to select clean text for OCR
–Use even poor OCR to guide tasks to the right crowd by creating clusters of tasks
–Use NLP to parse verbatim data from the crowd
–Improve NLP and OCR training with additional data from the crowd
21. iDigBio is funded by a grant from the National Science Foundation’s Advancing Digitization of
Biodiversity Collections Program (Cooperative Agreement EF-1115210). Any opinions, findings,
and conclusions or recommendations expressed in this material are those of the author(s) and
do not necessarily reflect the views of the National Science Foundation.
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