This document discusses the Doppler effect and its various applications. The Doppler effect refers to the change in frequency of a wave for an observer moving relative to its source. It causes the change in siren pitch of an approaching/receding emergency vehicle. In astronomy, it allows measurement of star/galaxy velocities and detection of binary stars. It is used in radar to detect object speed, in medical imaging to measure blood flow velocity, and in other applications like flow measurement, satellite communication, and vibration measurement.
This document presents two papers on analyzing bursty topics from microblogs and modeling latent topic transitions in social media. The first paper proposes using temporal information from microblog posts and users' interests to detect bursty topics. The second paper introduces TM-LDA, a topic model that captures latent topic transitions over time in sequentially posted documents and efficiently updates online. Both papers aim to model topics in a temporally-aware manner from streaming social media data.
This document proposes a method to analyze the maturity ratings of mobile apps on Android and iOS. It develops an algorithm called ALM to automatically predict app maturity ratings based on descriptions and reviews. By comparing ratings of apps on both platforms, it finds that Android ratings are often inconsistent with iOS ratings. The document examines factors that could lead to untruthful maturity ratings on Android like app content, developer attributes, and platform policies. The goal is to verify maturity ratings and investigate reasons for incorrect ratings to improve rating systems.
Human Systems International provides diagnostics and assessments to benchmark organizational project, program, and portfolio management capabilities. It holds the largest database of PPPM benchmarks and helps clients improve performance through independent diagnosis. Membership in its global knowledge-sharing network provides access to workshops, insights from leaders, and resources to fast-track improvement. The network allows organizations to measure and improve their PPPM capabilities by benchmarking against practices in different industries and regions.
This document discusses the Doppler effect and its various applications. The Doppler effect refers to the change in frequency of a wave for an observer moving relative to its source. It causes the change in siren pitch of an approaching/receding emergency vehicle. In astronomy, it allows measurement of star/galaxy velocities and detection of binary stars. It is used in radar to detect object speed, in medical imaging to measure blood flow velocity, and in other applications like flow measurement, satellite communication, and vibration measurement.
This document presents two papers on analyzing bursty topics from microblogs and modeling latent topic transitions in social media. The first paper proposes using temporal information from microblog posts and users' interests to detect bursty topics. The second paper introduces TM-LDA, a topic model that captures latent topic transitions over time in sequentially posted documents and efficiently updates online. Both papers aim to model topics in a temporally-aware manner from streaming social media data.
This document proposes a method to analyze the maturity ratings of mobile apps on Android and iOS. It develops an algorithm called ALM to automatically predict app maturity ratings based on descriptions and reviews. By comparing ratings of apps on both platforms, it finds that Android ratings are often inconsistent with iOS ratings. The document examines factors that could lead to untruthful maturity ratings on Android like app content, developer attributes, and platform policies. The goal is to verify maturity ratings and investigate reasons for incorrect ratings to improve rating systems.
Human Systems International provides diagnostics and assessments to benchmark organizational project, program, and portfolio management capabilities. It holds the largest database of PPPM benchmarks and helps clients improve performance through independent diagnosis. Membership in its global knowledge-sharing network provides access to workshops, insights from leaders, and resources to fast-track improvement. The network allows organizations to measure and improve their PPPM capabilities by benchmarking against practices in different industries and regions.
- The document presents a study analyzing factors that influence continued participation in Twitter group chats. It develops a 5F model examining individual initiative, group characteristics, perceived receptivity, linguistic affinity, and geographic proximity.
- The study analyzes data from 30 educational Twitter chats over two years involving over 71,000 users. It also conducted a user survey.
- The 5F model effectively predicts whether a new user who attends one session will return based on analysis of their contributions, how well they fit with the group linguistically, and other metrics.
Using content and interactions for discovering communities inmoresmile
1. The document proposes methods for discovering communities in social networks using content and interactions by modeling communities based on discussed topics and social connections between users. This allows discovering both user interests and popular topics within each community.
2. Bayesian models are used to extract latent communities from the network, assuming community relationships depend on user interests in topics and their links. Different models are proposed to handle different network structures like broadcast vs conversation networks.
3. The models aim to utilize both content and link information to discover communities in incomplete social networks with missing link information. A distance metric is learned using observed links and used for hierarchical clustering.
Generating event storylines from microblogsmoresmile
The document presents a study that analyzes factors influencing tweet rates about weather events. It finds that tweet rates correlate most strongly with weather extremeness, followed by change in weather and expectation. Data on tweets and weather from 2010-2011 across 56 North American cities were analyzed using linear regression models to correlate daily tweet volumes with measures of weather expectation, extremeness, and change from historical records. The study provides quantitative insight into how inherent biases in self-reported social media data relate to characteristics of real-world events.
Magnet community identification on social networksmoresmile
This document proposes a topic modeling approach called cross-collection topic-aspect model (ccTAM) to generate complementary summaries from news and social media streams. ccTAM jointly discovers representative and complementary information from the two sources by combining a two-dimensional topic-aspect model with a cross-collection method. It also introduces a measure to assess sentence-level complementarity and generates summaries by co-ranking news sentences and tweets based on their complementary relationship.
Topical keyphrase extraction from twittermoresmile
This document proposes methods to extract topical keyphrases from Twitter to summarize content. It introduces a context-sensitive topical PageRank method for ranking keywords and a probabilistic scoring function to consider the relevance and interestingness of keyphrases. The method involves three steps: topic discovery using a modified author-topic model for Twitter, keyword ranking and candidate generation using topical PageRank, and keyphrase ranking using a probabilistic model considering relevance and interestingness.
This document proposes a framework for personalized question recommendation that considers relevance as well as diversity and freshness. It introduces three models for question profiles - LDA topic model, lexical model and category model. It also describes building user profiles based on questions users have answered. For question recommendation, it matches question and user profiles, applies proactive diversification through thematic sampling, and uses a recommendation merging algorithm. The framework was evaluated offline on active and new users, and online through an A/B test comparing different recommendation strategies.
This document discusses simulation of ultrasound Doppler signals. It begins by explaining how Doppler ultrasound works to measure blood velocity non-invasively by detecting changes in frequency between transmitted and returned ultrasound waves based on blood movement. It then reviews several previous studies that have developed models for simulating Doppler ultrasound signals, including accounting for moving scatterers in vessels or modeling pulsatile blood flow. The document proposes using a linear time variant model based on Rayleigh integral equations to calculate RF signals and account for the Doppler effect by modifying signal shape based on scatterer speed. It will consider a disk transducer and hamming windowed sinusoidal signal for transmission.
Exploring social influence via posterior effect of word of-mouthmoresmile
This document presents research on exploring social influence through word-of-mouth recommendations. The study finds that word-of-mouth recommendations can significantly increase users' posterior evaluations of recommended products or services. Two models of this phenomenon are proposed and tested statistically. The results support the conclusion that recommendations directly influence higher ratings rather than common unknown factors explaining both. The paper also develops a method to identify influential friends based on their social positions and characteristics.
This document provides an overview of accounting principles and the conceptual framework that underlies the establishment of accounting standards. It explains that the conceptual framework establishes the objective of financial accounting, key qualitative characteristics of financial statements, elements of financial accounting, and criteria for recognition and measurement. It also discusses the assumptions, principles, and constraints that form the foundation of the accounting process and standards development. The principles include revenue recognition, matching, cost, and full disclosure, and the document provides examples of how these principles are applied. It concludes that the conceptual framework aims to ensure consistent and effective accounting practices and standards over time.
This document describes research on using hidden Markov models to summarize Twitter events. It discusses segmenting event timelines into key sub-events and selecting tweets to describe each segment. The researchers trained HMMs on words from tweets about American football games to learn the sub-event structure. They evaluated the method by comparing selected tweets to the actual game play-by-play. The results demonstrated the HMM approach could accurately summarize sports events based on tweets.
Doppler effect experiment and applicationsmarina fayez
The document discusses the Doppler effect and its applications. It begins by explaining the Doppler effect as a change in frequency observed by a detector moving relative to a wave source. It then provides the classical physics formula relating observed and emitted frequencies based on the velocities of the source and detector. Several key applications are then summarized: use in astronomy to measure radial velocities of stars and galaxies, use in medical imaging to measure blood flow velocities, use in police radar guns to detect speeding vehicles, and use in flow measurement devices like laser Doppler velocimeters.
- The document presents a study analyzing factors that influence continued participation in Twitter group chats. It develops a 5F model examining individual initiative, group characteristics, perceived receptivity, linguistic affinity, and geographic proximity.
- The study analyzes data from 30 educational Twitter chats over two years involving over 71,000 users. It also conducted a user survey.
- The 5F model effectively predicts whether a new user who attends one session will return based on analysis of their contributions, how well they fit with the group linguistically, and other metrics.
Using content and interactions for discovering communities inmoresmile
1. The document proposes methods for discovering communities in social networks using content and interactions by modeling communities based on discussed topics and social connections between users. This allows discovering both user interests and popular topics within each community.
2. Bayesian models are used to extract latent communities from the network, assuming community relationships depend on user interests in topics and their links. Different models are proposed to handle different network structures like broadcast vs conversation networks.
3. The models aim to utilize both content and link information to discover communities in incomplete social networks with missing link information. A distance metric is learned using observed links and used for hierarchical clustering.
Generating event storylines from microblogsmoresmile
The document presents a study that analyzes factors influencing tweet rates about weather events. It finds that tweet rates correlate most strongly with weather extremeness, followed by change in weather and expectation. Data on tweets and weather from 2010-2011 across 56 North American cities were analyzed using linear regression models to correlate daily tweet volumes with measures of weather expectation, extremeness, and change from historical records. The study provides quantitative insight into how inherent biases in self-reported social media data relate to characteristics of real-world events.
Magnet community identification on social networksmoresmile
This document proposes a topic modeling approach called cross-collection topic-aspect model (ccTAM) to generate complementary summaries from news and social media streams. ccTAM jointly discovers representative and complementary information from the two sources by combining a two-dimensional topic-aspect model with a cross-collection method. It also introduces a measure to assess sentence-level complementarity and generates summaries by co-ranking news sentences and tweets based on their complementary relationship.
Topical keyphrase extraction from twittermoresmile
This document proposes methods to extract topical keyphrases from Twitter to summarize content. It introduces a context-sensitive topical PageRank method for ranking keywords and a probabilistic scoring function to consider the relevance and interestingness of keyphrases. The method involves three steps: topic discovery using a modified author-topic model for Twitter, keyword ranking and candidate generation using topical PageRank, and keyphrase ranking using a probabilistic model considering relevance and interestingness.
This document proposes a framework for personalized question recommendation that considers relevance as well as diversity and freshness. It introduces three models for question profiles - LDA topic model, lexical model and category model. It also describes building user profiles based on questions users have answered. For question recommendation, it matches question and user profiles, applies proactive diversification through thematic sampling, and uses a recommendation merging algorithm. The framework was evaluated offline on active and new users, and online through an A/B test comparing different recommendation strategies.
This document discusses simulation of ultrasound Doppler signals. It begins by explaining how Doppler ultrasound works to measure blood velocity non-invasively by detecting changes in frequency between transmitted and returned ultrasound waves based on blood movement. It then reviews several previous studies that have developed models for simulating Doppler ultrasound signals, including accounting for moving scatterers in vessels or modeling pulsatile blood flow. The document proposes using a linear time variant model based on Rayleigh integral equations to calculate RF signals and account for the Doppler effect by modifying signal shape based on scatterer speed. It will consider a disk transducer and hamming windowed sinusoidal signal for transmission.
Exploring social influence via posterior effect of word of-mouthmoresmile
This document presents research on exploring social influence through word-of-mouth recommendations. The study finds that word-of-mouth recommendations can significantly increase users' posterior evaluations of recommended products or services. Two models of this phenomenon are proposed and tested statistically. The results support the conclusion that recommendations directly influence higher ratings rather than common unknown factors explaining both. The paper also develops a method to identify influential friends based on their social positions and characteristics.
This document provides an overview of accounting principles and the conceptual framework that underlies the establishment of accounting standards. It explains that the conceptual framework establishes the objective of financial accounting, key qualitative characteristics of financial statements, elements of financial accounting, and criteria for recognition and measurement. It also discusses the assumptions, principles, and constraints that form the foundation of the accounting process and standards development. The principles include revenue recognition, matching, cost, and full disclosure, and the document provides examples of how these principles are applied. It concludes that the conceptual framework aims to ensure consistent and effective accounting practices and standards over time.
This document describes research on using hidden Markov models to summarize Twitter events. It discusses segmenting event timelines into key sub-events and selecting tweets to describe each segment. The researchers trained HMMs on words from tweets about American football games to learn the sub-event structure. They evaluated the method by comparing selected tweets to the actual game play-by-play. The results demonstrated the HMM approach could accurately summarize sports events based on tweets.
Doppler effect experiment and applicationsmarina fayez
The document discusses the Doppler effect and its applications. It begins by explaining the Doppler effect as a change in frequency observed by a detector moving relative to a wave source. It then provides the classical physics formula relating observed and emitted frequencies based on the velocities of the source and detector. Several key applications are then summarized: use in astronomy to measure radial velocities of stars and galaxies, use in medical imaging to measure blood flow velocities, use in police radar guns to detect speeding vehicles, and use in flow measurement devices like laser Doppler velocimeters.
Презентация для семинара "Интернет, как инновационный канал продвижения креди...Alexey Sidorov
Семинар "Интернет, как инновационный канал продвижения кредитов для МФО в Казахстане" был организован командой prodengi.kz и cpc.kz для членов Ассоциации Микро-финансовых Организаций. Казахстана (АМФОК)
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