Bhanu new ppt
•Download as PPTX, PDF•
0 likes•11 views
The document discusses analyzing mobile cellular big data to link cyberspace and the physical world with social ecology. It describes preprocessing a data set collected from base stations to analyze human behavior credibly. The data visualization depicts the daily traffic profile and number of active users, showing patterns like daily sleep cycles. Human mobility in the physical world can be determined by their connections to base stations. Linking cyber and physical behavior with social ecology can provide understanding of how these spaces interrelate.
Report
Share
Report
Share
Recommended
Ecology
This document analyzes human behavior in cyberspace and the physical world using mobile cellular big data. It describes collecting data from base stations in a selected region, preprocessing the large-scale traffic logs to analyze human behavior patterns, and visualizing the normalized traffic data and number of active users over time. The analysis found that human mobility and traffic consumption have strong correlations and distinct periodic patterns. Both are also linked to social ecology, helping understand human behavior.
Collaborative Design Engineering Studio I(STU1231): Project 1
This is assignment 1 done for the Collaborative Design Engineering Studio I(STU1231) at Harvard University.
Adam bly sxsw
The document provides a summary of various data visualization projects related to cities, society, and human behavior that were presented at the 2011 South by Southwest conference. It lists the names and brief descriptions of projects like Globalization in Real Time, Locals and Tourists, Invisible Cities, and others that used social media and other data to visualize topics like influence networks during political events, patterns in human mobility, and depictions of friendships and relationships online. The document concludes by listing the credits for the various visualization projects and providing a URL for more information.
Modeling Crowds in Urban Spaces
Large scale crowd simulation and visualization combine computer graphics, artificial intelligence and high performance computing among other areas. This presentation gives an overview of our approach for computing people flows moving in urban spaces. This is done by combining on-line crowd simulation, spatio-temporal data, and real places geometric data running on GPU and HPC.
a data mining approach for location production in mobile environments
The document proposes a three-phase algorithm for predicting the next location of mobile users. In the first phase, mobility patterns are mined from historical user trajectory data. In the second phase, mobility rules are extracted from these patterns. In the third phase, predictions are made by matching mobility rules to a user's current trajectory. The algorithm aims to overcome limitations of prior work by discovering regular patterns in user movements and distinguishing between random and regular movements. A simulation evaluation found the proposed method achieved more accurate predictions than other methods.
Effects of mobility models and nodes distribution on wireless sensors networks
Wireless sensor networks (WSN) is an important future technology, in several applications in military,
health, environment and industries. Currently the integration of social and sensor is very important by
considering the characteristics of social networks in designing wireless sensor networks WSN for
improvement such as (number of messages from source to destination, radius of coverage, connectivity, and
spreading). This area has not received much attention and few researches focus on the performance
evaluation. In this paper we have studied the impact of different mobility and distribution models which is a
variable one should define which model is best for the infrastructure given their differences, also study
include the exact effect of nodes distribution and analyzed by calculation the number of messages of 12
cases to get a real performance evaluation under different conditions and same routing techniques. This
work provides us a greater understanding and clear an idea of the effect of mobility plus distribution.
Using Social Networking Data to Understand Urban Human Mobility
Social networking app has been growing very rapidly in the past decade. One of the important features of social media is the ability of system that can attach coordinate where users are located (check-in). The aim of this study is to identify the characteristic of human mobility patterns in Bandung city. We proposed a technique uses pixel matching approach. In this paper, we describe the visualization of the city is determined by the activity of people on Twitter social media. Our work includes firstly, characterize the pattern of user’s interest to different types of places. Secondly, to characterize the pattern of user visits to different neighborhoods with way choose the user’s activity pattern on the weekdays and weekends. We then categorize the existing place based on the period of time that people visiting. Meanwhile, to define the existing areas, we used official map the city planning department as parameters to determine the user’s movement. Our research will answer the question whether the Twitter App data is a viable resource to measure the human movement? The result indicates that it can be used as the one of the sources of information data to understand urban human mobility
Pedestrian behavior/intention modeling for autonomous driving II
The document discusses several papers related to modeling pedestrian behavior and predicting pedestrian trajectories for autonomous vehicles. It begins with an outline listing the paper titles and authors. It then provides more detailed summaries of three papers:
1) "Social LSTM: Human Trajectory Prediction in Crowded Spaces" which uses an LSTM model and social pooling layer to jointly predict paths of all people in a scene by taking into account social conventions.
2) "A Data-driven Model for Interaction-aware Pedestrian Motion Prediction in Object Cluttered Environments" which uses an LSTM model incorporating static obstacles and surrounding pedestrians to forecast trajectories.
3) "Social GAN: Socially Acceptable Trajectories with Generative
Recommended
Ecology
This document analyzes human behavior in cyberspace and the physical world using mobile cellular big data. It describes collecting data from base stations in a selected region, preprocessing the large-scale traffic logs to analyze human behavior patterns, and visualizing the normalized traffic data and number of active users over time. The analysis found that human mobility and traffic consumption have strong correlations and distinct periodic patterns. Both are also linked to social ecology, helping understand human behavior.
Collaborative Design Engineering Studio I(STU1231): Project 1
This is assignment 1 done for the Collaborative Design Engineering Studio I(STU1231) at Harvard University.
Adam bly sxsw
The document provides a summary of various data visualization projects related to cities, society, and human behavior that were presented at the 2011 South by Southwest conference. It lists the names and brief descriptions of projects like Globalization in Real Time, Locals and Tourists, Invisible Cities, and others that used social media and other data to visualize topics like influence networks during political events, patterns in human mobility, and depictions of friendships and relationships online. The document concludes by listing the credits for the various visualization projects and providing a URL for more information.
Modeling Crowds in Urban Spaces
Large scale crowd simulation and visualization combine computer graphics, artificial intelligence and high performance computing among other areas. This presentation gives an overview of our approach for computing people flows moving in urban spaces. This is done by combining on-line crowd simulation, spatio-temporal data, and real places geometric data running on GPU and HPC.
a data mining approach for location production in mobile environments
The document proposes a three-phase algorithm for predicting the next location of mobile users. In the first phase, mobility patterns are mined from historical user trajectory data. In the second phase, mobility rules are extracted from these patterns. In the third phase, predictions are made by matching mobility rules to a user's current trajectory. The algorithm aims to overcome limitations of prior work by discovering regular patterns in user movements and distinguishing between random and regular movements. A simulation evaluation found the proposed method achieved more accurate predictions than other methods.
Effects of mobility models and nodes distribution on wireless sensors networks
Wireless sensor networks (WSN) is an important future technology, in several applications in military,
health, environment and industries. Currently the integration of social and sensor is very important by
considering the characteristics of social networks in designing wireless sensor networks WSN for
improvement such as (number of messages from source to destination, radius of coverage, connectivity, and
spreading). This area has not received much attention and few researches focus on the performance
evaluation. In this paper we have studied the impact of different mobility and distribution models which is a
variable one should define which model is best for the infrastructure given their differences, also study
include the exact effect of nodes distribution and analyzed by calculation the number of messages of 12
cases to get a real performance evaluation under different conditions and same routing techniques. This
work provides us a greater understanding and clear an idea of the effect of mobility plus distribution.
Using Social Networking Data to Understand Urban Human Mobility
Social networking app has been growing very rapidly in the past decade. One of the important features of social media is the ability of system that can attach coordinate where users are located (check-in). The aim of this study is to identify the characteristic of human mobility patterns in Bandung city. We proposed a technique uses pixel matching approach. In this paper, we describe the visualization of the city is determined by the activity of people on Twitter social media. Our work includes firstly, characterize the pattern of user’s interest to different types of places. Secondly, to characterize the pattern of user visits to different neighborhoods with way choose the user’s activity pattern on the weekdays and weekends. We then categorize the existing place based on the period of time that people visiting. Meanwhile, to define the existing areas, we used official map the city planning department as parameters to determine the user’s movement. Our research will answer the question whether the Twitter App data is a viable resource to measure the human movement? The result indicates that it can be used as the one of the sources of information data to understand urban human mobility
Pedestrian behavior/intention modeling for autonomous driving II
The document discusses several papers related to modeling pedestrian behavior and predicting pedestrian trajectories for autonomous vehicles. It begins with an outline listing the paper titles and authors. It then provides more detailed summaries of three papers:
1) "Social LSTM: Human Trajectory Prediction in Crowded Spaces" which uses an LSTM model and social pooling layer to jointly predict paths of all people in a scene by taking into account social conventions.
2) "A Data-driven Model for Interaction-aware Pedestrian Motion Prediction in Object Cluttered Environments" which uses an LSTM model incorporating static obstacles and surrounding pedestrians to forecast trajectories.
3) "Social GAN: Socially Acceptable Trajectories with Generative
E223539
International Refereed Journal of Engineering and Science (IRJES) is a peer reviewed online journal for professionals and researchers in the field of computer science. The main aim is to resolve emerging and outstanding problems revealed by recent social and technological change. IJRES provides the platform for the researchers to present and evaluate their work from both theoretical and technical aspects and to share their views.
Sampling of User Behavior Using Online Social Network
The popularity of online networks provides an opportunity to study the characteristics of online social network graphs is important, both to improve current systems and to design new application of online social networks. Although personalized search has been proposed for many years and many personalization strategies have been investigated, it is still unclear whether personalization is consistently effective on different queries for different users, and under different search contexts. In this paper, we study performance of information collection in a dynamic social network. By analyzing the results, we reveal that personalized search has significant improvement over common web search.
The mixing time of thee sampling process strongly depends on the characteristics of the graph.
P Sweta
This document discusses location-based services (LBS). LBS utilize mobile devices, communication networks, and positioning systems to determine a user's location and provide tailored information and services. The key components of LBS are mobile devices, communication networks, positioning systems, service providers, and data providers. Popular LBS applications include navigation assistance, local search and advertising, and social networking features that share a user's location. For LBS to be useful, they must meet users' information needs by answering questions about their own or others' locations.
DeepCrowd A Deep Model for Large-Scale Citywide Crowd Density and Flow Predic...
https://okokprojects.com/
IEEE PROJECTS 2023-2024 TITLE LIST
WhatsApp : +91-8144199666
From Our Title List the Cost will be,
Mail Us: okokprojects@gmail.com
Website: : https://www.okokprojects.com
: http://www.ieeeproject.net
Support Including Packages
=======================
* Complete Source Code
* Complete Documentation
* Complete Presentation Slides
* Flow Diagram
* Database File
* Screenshots
* Execution Procedure
* Video Tutorials
* Supporting Softwares
Support Specialization
=======================
* 24/7 Support
* Ticketing System
* Voice Conference
* Video On Demand
* Remote Connectivity
* Document Customization
* Live Chat Support
Temporal Reasoning Graph for Activity Recognition
This document discusses using a convolutional neural network and background subtraction for human activity recognition in videos. It proposes a model that uses CNN to extract features from video frames and classify human activities. The proposed system first acquires and preprocesses video data. It then extracts frames from the videos using background subtraction. These frames are split into training and testing sets for the CNN model. The CNN model is tested on the testing set to evaluate its ability to accurately classify human activities. Experimental results show the CNN model combined with background subtraction achieves good performance for human activity recognition.
Human activity recognition updated 1 - Copy.pptx
This document discusses human activity recognition using inertial sensors. It begins by introducing human activity recognition and how inertial sensors are commonly used to build HAR systems. It then discusses applications of HAR systems and how deep learning models are increasingly being used for activity recognition. The document also discusses challenges with using deep learning for activity recognition on resource-constrained devices and how edge computing is a viable solution. It provides literature on the topic and discusses existing system drawbacks. The conclusion discusses a proposed new HAR system that achieves high accuracy with low power consumption.
SMSociety16_paper_209-FINAL VERSION
This document summarizes a study that analyzed location and social media data from attendees at the 2015 Roskilde Music Festival in Denmark. The study collected GPS location data from over 39,000 festival attendees who opted-in to sharing their location via a festival mobile app. It also collected over 20,000 geo-tagged social media posts from Instagram and over 35,000 geo-tagged tweets. The study analyzed how attendees moved around the festival grounds and compared this physical movement data to the places they discussed and shared photos of on social media. It found that these two data sources revealed how attendees appropriated the festival spaces and experiences through both physical presence and online sharing with their social networks.
Social and Spatial Clustering of People at Humanity’s Largest Gathering
This document summarizes a research article that analyzed call detail records from 61 million cell phone users at the 2013 Kumbh Mela festival in India, the largest gathering in human history. The researchers estimated attendance by state and found evidence of both social and spatial homophily, or clustering with others from the same state. Attendees from less represented states showed stronger tendencies towards homophily. Homophily effects were amplified on more crowded days with higher attendance. The findings confirm that homophily, likely arising from social influence, is evident even at the massive scale of this historic festival.
Application Of Android Enabled Mobile Device For Personal Information Systems
The document describes a proposed personal mobile information system (PMIS) developed on the Android platform. The PMIS would provide location-based services like GPS-enabled proximity alerts and a rating system for points of interest. It would also plot routes from a user's location to points of interest, alerting users of any crime incidents along the way based on police data. The system has two types of users: general users who can rate and find points of interest, and police users who can log crime events and update safety ratings to inform alerts for general users. The goal is to create a personalized mobile information system that enhances user safety during navigation.
Studying perceptions of urban space and neighbourhood with moblogging
This document describes a study that used a novel methodology called "moblogging" to examine people's perceptions of their neighborhoods. Moblogging involves using a mobile phone to record media like photos, audio notes, and location data during self-guided tours of one's neighborhood. The study collected qualitative data from 15 participants through moblogging activities and workshops. The results highlighted how people use public and private landmarks, differences in spatial knowledge between urban and rural dwellers, and individual strategies for orientation. The findings suggest guidelines for designing personalized spatial profiles in technologies.
www.ijerd.com
This document discusses improving the performance of mobility patterns in mobile ad-hoc sensor networks using Qualnet 5.0 simulation software. It proposes two models - a non-mobility model and a mobility model, and compares their performance. It then designs a mobility model with improved antenna frequency to transmit signals, called the design mobility model. The performance of the non-mobility, mobility, and design mobility models are analyzed and compared through simulations in Qualnet 5.0. The document reviews several existing mobility models and discusses the architecture and mobility model strategies for wireless sensor networks.
Service rating prediction by exploring social mobile users’ geographical loca...
Service rating prediction by exploring social mobile users’ geographical locations M-Tech IEEE 2017 Projects B-Tech Major Projects B-tech Main Projects Data mining Project
Rashed ieice
This introduces a method to track humans in crowded public spaces using a network of LIDAR sensors installed at shoulder height. The method models humans as ellipses and uses a particle filter framework to track their position and body orientation over time based on LIDAR point cloud data. The method was tested in an art gallery and was able to track visitors' positions, orientations, and trajectories to analyze their behaviors, which could help museum professionals better understand visitor engagement and improve exhibitions. However, the previous method had limitations handling occlusion, so this paper proposes an improved method using a larger network of more widely spaced LIDAR sensors to overcome occlusion issues and enable robust tracking even in dense crowds.
Social LSTMの紹介
Social LSTM is an important 2016 paper that introduced a method to model human-human interactions for the purpose of trajectory prediction in crowded spaces. It uses separate LSTMs for each trajectory connected through a social pooling layer, allowing spatially close LSTMs to share information. This helps the model account for how a person's behavior may be influenced by others in their immediate area. Experiments on standard datasets showed it reduces trajectory prediction error compared to methods without social modeling. Future work could extend it to model multiple object types and include static scene inputs.
Travel Recommendation Approach using Collaboration Filter in Social Networking
This document discusses a travel recommendation approach using collaboration filtering in social networks. It proposes personalized travel sequence recommendations based on travelogues and community photos posted on social media. Unlike other travel recommendation systems, it recommends a sequence of points of interest rather than individual locations. It maps user preferences and route descriptions to topic categories to calculate similarity and recommend routes. The system was evaluated on a dataset of over 7 million Flickr photos and 24,000 travelogues covering 864 travel locations in 9 cities.
An updated look at social network extraction system a personal data analysis ...
An updated look at social network extraction system a personal data analysis ...eSAT Publishing House
This document summarizes a study on analyzing personal social network data over time. The study extracted data from Facebook, calculated social network analysis metrics like degree distribution and betweenness centrality, and analyzed how the network changed dynamically over time. Key findings included identifying influential and non-influential users, detecting communities that formed within the network, and identifying the celebrity or most influential user within one person's local network. Analyzing how social networks and interactions change dynamically provides insights useful for applications like marketing and recommendations.Human mobility,urban structure analysis,and spatial community detection from ...
1) The document summarizes Song Gao's research interests in human mobility patterns, urban structure analysis, and spatial community detection using mobile phone data.
2) Key research questions include how human mobility and physical movements are impacted by distance and information communication technologies.
3) The document outlines methods for analyzing individual and aggregate mobility patterns, dynamic urban landscapes, and detecting spatial communities in interaction networks.
4) Preliminary results suggest distance still constrains human interactions and mobility, and that a relationship exists between communication technologies and physical movements.
IEEE-ROBIO-2013-115-120
I'm sorry, I don't have control of the wheelchair motors. Please use the joystick or remote control.
User: Navigate to the kitchen.
A boring presentation about social mobile communication patterns and opportun...
This document provides an outline and summary of a survey on social communication patterns and opportunistic forwarding in mobile networks. It begins with an introduction on opportunistic networking in infrastructureless environments. It then outlines key areas covered in the survey, including useful knowledge on social behavior patterns, how social patterns can impact opportunistic forwarding, and how social information can be exploited to enhance network performance. The document evaluates the state of the art in research on this topic and concludes with directions for future work, such as considering power consumption and marketing-oriented social behaviors.
City Data Dating: emerging affinities between diverse urban datasets
Cities are complex environments in which digital technologies are more and more pervasive; this digitization of the urban space has led to a rich ecosystem of data producers and data consumers. Moreover, heterogeneous sources differ in terms of data complexity, spatio-temporal resolution and curation/maintenance costs. Do those diverse urban sources reflect the same picture of the city? Do distinct perspectives share some commonalities?
We present our data analytics empirical experiments on a set of urban sources related to the city of Milano; our investigation is aimed at discovering “affinities” between datasets by means of different quantitative and qualitative correlation analyses. We also explore the influence of spatial resolution and data complexity on the dependence strength between heterogeneous urban sources, to pave the way to a meaningful information fusion.
Vitthal Shirke Java Microservices Resume.pdf
Software Engineering, Software Consulting, Tech Lead, Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Transaction, Spring MVC, OpenShift Cloud Platform, Kafka, REST, SOAP, LLD & HLD.
8 Best Automated Android App Testing Tool and Framework in 2024.pdf
Regarding mobile operating systems, two major players dominate our thoughts: Android and iPhone. With Android leading the market, software development companies are focused on delivering apps compatible with this OS. Ensuring an app's functionality across various Android devices, OS versions, and hardware specifications is critical, making Android app testing essential.
More Related Content
Similar to Bhanu new ppt
E223539
International Refereed Journal of Engineering and Science (IRJES) is a peer reviewed online journal for professionals and researchers in the field of computer science. The main aim is to resolve emerging and outstanding problems revealed by recent social and technological change. IJRES provides the platform for the researchers to present and evaluate their work from both theoretical and technical aspects and to share their views.
Sampling of User Behavior Using Online Social Network
The popularity of online networks provides an opportunity to study the characteristics of online social network graphs is important, both to improve current systems and to design new application of online social networks. Although personalized search has been proposed for many years and many personalization strategies have been investigated, it is still unclear whether personalization is consistently effective on different queries for different users, and under different search contexts. In this paper, we study performance of information collection in a dynamic social network. By analyzing the results, we reveal that personalized search has significant improvement over common web search.
The mixing time of thee sampling process strongly depends on the characteristics of the graph.
P Sweta
This document discusses location-based services (LBS). LBS utilize mobile devices, communication networks, and positioning systems to determine a user's location and provide tailored information and services. The key components of LBS are mobile devices, communication networks, positioning systems, service providers, and data providers. Popular LBS applications include navigation assistance, local search and advertising, and social networking features that share a user's location. For LBS to be useful, they must meet users' information needs by answering questions about their own or others' locations.
DeepCrowd A Deep Model for Large-Scale Citywide Crowd Density and Flow Predic...
https://okokprojects.com/
IEEE PROJECTS 2023-2024 TITLE LIST
WhatsApp : +91-8144199666
From Our Title List the Cost will be,
Mail Us: okokprojects@gmail.com
Website: : https://www.okokprojects.com
: http://www.ieeeproject.net
Support Including Packages
=======================
* Complete Source Code
* Complete Documentation
* Complete Presentation Slides
* Flow Diagram
* Database File
* Screenshots
* Execution Procedure
* Video Tutorials
* Supporting Softwares
Support Specialization
=======================
* 24/7 Support
* Ticketing System
* Voice Conference
* Video On Demand
* Remote Connectivity
* Document Customization
* Live Chat Support
Temporal Reasoning Graph for Activity Recognition
This document discusses using a convolutional neural network and background subtraction for human activity recognition in videos. It proposes a model that uses CNN to extract features from video frames and classify human activities. The proposed system first acquires and preprocesses video data. It then extracts frames from the videos using background subtraction. These frames are split into training and testing sets for the CNN model. The CNN model is tested on the testing set to evaluate its ability to accurately classify human activities. Experimental results show the CNN model combined with background subtraction achieves good performance for human activity recognition.
Human activity recognition updated 1 - Copy.pptx
This document discusses human activity recognition using inertial sensors. It begins by introducing human activity recognition and how inertial sensors are commonly used to build HAR systems. It then discusses applications of HAR systems and how deep learning models are increasingly being used for activity recognition. The document also discusses challenges with using deep learning for activity recognition on resource-constrained devices and how edge computing is a viable solution. It provides literature on the topic and discusses existing system drawbacks. The conclusion discusses a proposed new HAR system that achieves high accuracy with low power consumption.
SMSociety16_paper_209-FINAL VERSION
This document summarizes a study that analyzed location and social media data from attendees at the 2015 Roskilde Music Festival in Denmark. The study collected GPS location data from over 39,000 festival attendees who opted-in to sharing their location via a festival mobile app. It also collected over 20,000 geo-tagged social media posts from Instagram and over 35,000 geo-tagged tweets. The study analyzed how attendees moved around the festival grounds and compared this physical movement data to the places they discussed and shared photos of on social media. It found that these two data sources revealed how attendees appropriated the festival spaces and experiences through both physical presence and online sharing with their social networks.
Social and Spatial Clustering of People at Humanity’s Largest Gathering
This document summarizes a research article that analyzed call detail records from 61 million cell phone users at the 2013 Kumbh Mela festival in India, the largest gathering in human history. The researchers estimated attendance by state and found evidence of both social and spatial homophily, or clustering with others from the same state. Attendees from less represented states showed stronger tendencies towards homophily. Homophily effects were amplified on more crowded days with higher attendance. The findings confirm that homophily, likely arising from social influence, is evident even at the massive scale of this historic festival.
Application Of Android Enabled Mobile Device For Personal Information Systems
The document describes a proposed personal mobile information system (PMIS) developed on the Android platform. The PMIS would provide location-based services like GPS-enabled proximity alerts and a rating system for points of interest. It would also plot routes from a user's location to points of interest, alerting users of any crime incidents along the way based on police data. The system has two types of users: general users who can rate and find points of interest, and police users who can log crime events and update safety ratings to inform alerts for general users. The goal is to create a personalized mobile information system that enhances user safety during navigation.
Studying perceptions of urban space and neighbourhood with moblogging
This document describes a study that used a novel methodology called "moblogging" to examine people's perceptions of their neighborhoods. Moblogging involves using a mobile phone to record media like photos, audio notes, and location data during self-guided tours of one's neighborhood. The study collected qualitative data from 15 participants through moblogging activities and workshops. The results highlighted how people use public and private landmarks, differences in spatial knowledge between urban and rural dwellers, and individual strategies for orientation. The findings suggest guidelines for designing personalized spatial profiles in technologies.
www.ijerd.com
This document discusses improving the performance of mobility patterns in mobile ad-hoc sensor networks using Qualnet 5.0 simulation software. It proposes two models - a non-mobility model and a mobility model, and compares their performance. It then designs a mobility model with improved antenna frequency to transmit signals, called the design mobility model. The performance of the non-mobility, mobility, and design mobility models are analyzed and compared through simulations in Qualnet 5.0. The document reviews several existing mobility models and discusses the architecture and mobility model strategies for wireless sensor networks.
Service rating prediction by exploring social mobile users’ geographical loca...
Service rating prediction by exploring social mobile users’ geographical locations M-Tech IEEE 2017 Projects B-Tech Major Projects B-tech Main Projects Data mining Project
Rashed ieice
This introduces a method to track humans in crowded public spaces using a network of LIDAR sensors installed at shoulder height. The method models humans as ellipses and uses a particle filter framework to track their position and body orientation over time based on LIDAR point cloud data. The method was tested in an art gallery and was able to track visitors' positions, orientations, and trajectories to analyze their behaviors, which could help museum professionals better understand visitor engagement and improve exhibitions. However, the previous method had limitations handling occlusion, so this paper proposes an improved method using a larger network of more widely spaced LIDAR sensors to overcome occlusion issues and enable robust tracking even in dense crowds.
Social LSTMの紹介
Social LSTM is an important 2016 paper that introduced a method to model human-human interactions for the purpose of trajectory prediction in crowded spaces. It uses separate LSTMs for each trajectory connected through a social pooling layer, allowing spatially close LSTMs to share information. This helps the model account for how a person's behavior may be influenced by others in their immediate area. Experiments on standard datasets showed it reduces trajectory prediction error compared to methods without social modeling. Future work could extend it to model multiple object types and include static scene inputs.
Travel Recommendation Approach using Collaboration Filter in Social Networking
This document discusses a travel recommendation approach using collaboration filtering in social networks. It proposes personalized travel sequence recommendations based on travelogues and community photos posted on social media. Unlike other travel recommendation systems, it recommends a sequence of points of interest rather than individual locations. It maps user preferences and route descriptions to topic categories to calculate similarity and recommend routes. The system was evaluated on a dataset of over 7 million Flickr photos and 24,000 travelogues covering 864 travel locations in 9 cities.
An updated look at social network extraction system a personal data analysis ...
An updated look at social network extraction system a personal data analysis ...eSAT Publishing House
This document summarizes a study on analyzing personal social network data over time. The study extracted data from Facebook, calculated social network analysis metrics like degree distribution and betweenness centrality, and analyzed how the network changed dynamically over time. Key findings included identifying influential and non-influential users, detecting communities that formed within the network, and identifying the celebrity or most influential user within one person's local network. Analyzing how social networks and interactions change dynamically provides insights useful for applications like marketing and recommendations.Human mobility,urban structure analysis,and spatial community detection from ...
1) The document summarizes Song Gao's research interests in human mobility patterns, urban structure analysis, and spatial community detection using mobile phone data.
2) Key research questions include how human mobility and physical movements are impacted by distance and information communication technologies.
3) The document outlines methods for analyzing individual and aggregate mobility patterns, dynamic urban landscapes, and detecting spatial communities in interaction networks.
4) Preliminary results suggest distance still constrains human interactions and mobility, and that a relationship exists between communication technologies and physical movements.
IEEE-ROBIO-2013-115-120
I'm sorry, I don't have control of the wheelchair motors. Please use the joystick or remote control.
User: Navigate to the kitchen.
A boring presentation about social mobile communication patterns and opportun...
This document provides an outline and summary of a survey on social communication patterns and opportunistic forwarding in mobile networks. It begins with an introduction on opportunistic networking in infrastructureless environments. It then outlines key areas covered in the survey, including useful knowledge on social behavior patterns, how social patterns can impact opportunistic forwarding, and how social information can be exploited to enhance network performance. The document evaluates the state of the art in research on this topic and concludes with directions for future work, such as considering power consumption and marketing-oriented social behaviors.
City Data Dating: emerging affinities between diverse urban datasets
Cities are complex environments in which digital technologies are more and more pervasive; this digitization of the urban space has led to a rich ecosystem of data producers and data consumers. Moreover, heterogeneous sources differ in terms of data complexity, spatio-temporal resolution and curation/maintenance costs. Do those diverse urban sources reflect the same picture of the city? Do distinct perspectives share some commonalities?
We present our data analytics empirical experiments on a set of urban sources related to the city of Milano; our investigation is aimed at discovering “affinities” between datasets by means of different quantitative and qualitative correlation analyses. We also explore the influence of spatial resolution and data complexity on the dependence strength between heterogeneous urban sources, to pave the way to a meaningful information fusion.
Similar to Bhanu new ppt (20)
Sampling of User Behavior Using Online Social Network
Sampling of User Behavior Using Online Social Network
DeepCrowd A Deep Model for Large-Scale Citywide Crowd Density and Flow Predic...
DeepCrowd A Deep Model for Large-Scale Citywide Crowd Density and Flow Predic...
Social and Spatial Clustering of People at Humanity’s Largest Gathering
Social and Spatial Clustering of People at Humanity’s Largest Gathering
Application Of Android Enabled Mobile Device For Personal Information Systems
Application Of Android Enabled Mobile Device For Personal Information Systems
Studying perceptions of urban space and neighbourhood with moblogging
Studying perceptions of urban space and neighbourhood with moblogging
Service rating prediction by exploring social mobile users’ geographical loca...
Service rating prediction by exploring social mobile users’ geographical loca...
Travel Recommendation Approach using Collaboration Filter in Social Networking
Travel Recommendation Approach using Collaboration Filter in Social Networking
An updated look at social network extraction system a personal data analysis ...
An updated look at social network extraction system a personal data analysis ...
Human mobility,urban structure analysis,and spatial community detection from ...
Human mobility,urban structure analysis,and spatial community detection from ...
A boring presentation about social mobile communication patterns and opportun...
A boring presentation about social mobile communication patterns and opportun...
City Data Dating: emerging affinities between diverse urban datasets
City Data Dating: emerging affinities between diverse urban datasets
Recently uploaded
Vitthal Shirke Java Microservices Resume.pdf
Software Engineering, Software Consulting, Tech Lead, Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Transaction, Spring MVC, OpenShift Cloud Platform, Kafka, REST, SOAP, LLD & HLD.
8 Best Automated Android App Testing Tool and Framework in 2024.pdf
Regarding mobile operating systems, two major players dominate our thoughts: Android and iPhone. With Android leading the market, software development companies are focused on delivering apps compatible with this OS. Ensuring an app's functionality across various Android devices, OS versions, and hardware specifications is critical, making Android app testing essential.
Revolutionizing Visual Effects Mastering AI Face Swaps.pdf
The quest for the best AI face swap solution is marked by an amalgamation of technological prowess and artistic finesse, where cutting-edge algorithms seamlessly replace faces in images or videos with striking realism. Leveraging advanced deep learning techniques, the best AI face swap tools meticulously analyze facial features, lighting conditions, and expressions to execute flawless transformations, ensuring natural-looking results that blur the line between reality and illusion, captivating users with their ingenuity and sophistication.
Web:- https://undressbaby.com/
AI Fusion Buddy Review: Brand New, Groundbreaking Gemini-Powered AI App
AI Fusion Buddy Review: Brand New, Groundbreaking Gemini-Powered AI App
👉👉 Click Here To Get More Info 👇👇
https://sumonreview.com/ai-fusion-buddy-review
AI Fusion Buddy Review: Key Features
✅Create Stunning AI App Suite Fully Powered By Google's Latest AI technology, Gemini
✅Use Gemini to Build high-converting Converting Sales Video Scripts, ad copies, Trending Articles, blogs, etc.100% unique!
✅Create Ultra-HD graphics with a single keyword or phrase that commands 10x eyeballs!
✅Fully automated AI articles bulk generation!
✅Auto-post or schedule stunning AI content across all your accounts at once—WordPress, Facebook, LinkedIn, Blogger, and more.
✅With one keyword or URL, generate complete websites, landing pages, and more…
✅Automatically create & sell AI content, graphics, websites, landing pages, & all that gets you paid non-stop 24*7.
✅Pre-built High-Converting 100+ website Templates and 2000+ graphic templates logos, banners, and thumbnail images in Trending Niches.
✅Say goodbye to wasting time logging into multiple Chat GPT & AI Apps once & for all!
✅Save over $5000 per year and kick out dependency on third parties completely!
✅Brand New App: Not available anywhere else!
✅ Beginner-friendly!
✅ZERO upfront cost or any extra expenses
✅Risk-Free: 30-Day Money-Back Guarantee!
✅Commercial License included!
See My Other Reviews Article:
(1) AI Genie Review: https://sumonreview.com/ai-genie-review
(2) SocioWave Review: https://sumonreview.com/sociowave-review
(3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review
(4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review
#AIFusionBuddyReview,
#AIFusionBuddyFeatures,
#AIFusionBuddyPricing,
#AIFusionBuddyProsandCons,
#AIFusionBuddyTutorial,
#AIFusionBuddyUserExperience
#AIFusionBuddyforBeginners,
#AIFusionBuddyBenefits,
#AIFusionBuddyComparison,
#AIFusionBuddyInstallation,
#AIFusionBuddyRefundPolicy,
#AIFusionBuddyDemo,
#AIFusionBuddyMaintenanceFees,
#AIFusionBuddyNewbieFriendly,
#WhatIsAIFusionBuddy?,
#HowDoesAIFusionBuddyWorks
openEuler Case Study - The Journey to Supply Chain Security
openEuler Case Study - The Journey to Supply Chain Security
Why Choose Odoo 17 Community & How it differs from Odoo 17 Enterprise Edition
Why Choose Odoo 17 Community & How it differs from Odoo 17 Enterprise EditionEnvertis Software Solutions
Odoo ERP software
Odoo ERP software, a leading open-source software for Enterprise Resource Planning (ERP) and business management, has recently launched its latest version, Odoo 17 Community Edition. This update introduces a range of new features and enhancements designed to streamline business operations and support growth.
The Odoo Community serves as a cost-free edition within the Odoo suite of ERP systems. Tailored to accommodate the standard needs of business operations, it provides a robust platform suitable for organisations of different sizes and business sectors. Within the Odoo Community Edition, users can access a variety of essential features and services essential for managing day-to-day tasks efficiently.
This blog presents a detailed overview of the features available within the Odoo 17 Community edition, and the differences between Odoo 17 community and enterprise editions, aiming to equip you with the necessary information to make an informed decision about its suitability for your business.Introducing Crescat - Event Management Software for Venues, Festivals and Eve...
Crescat is industry-trusted event management software, built by event professionals for event professionals. Founded in 2017, we have three key products tailored for the live event industry.
Crescat Event for concert promoters and event agencies. Crescat Venue for music venues, conference centers, wedding venues, concert halls and more. And Crescat Festival for festivals, conferences and complex events.
With a wide range of popular features such as event scheduling, shift management, volunteer and crew coordination, artist booking and much more, Crescat is designed for customisation and ease-of-use.
Over 125,000 events have been planned in Crescat and with hundreds of customers of all shapes and sizes, from boutique event agencies through to international concert promoters, Crescat is rigged for success. What's more, we highly value feedback from our users and we are constantly improving our software with updates, new features and improvements.
If you plan events, run a venue or produce festivals and you're looking for ways to make your life easier, then we have a solution for you. Try our software for free or schedule a no-obligation demo with one of our product specialists today at crescat.io
Fundamentals of Programming and Language Processors
Fundamentals of Programming and Language Processors
How to write a program in any programming language
How to write a program in any programming language
Using Query Store in Azure PostgreSQL to Understand Query Performance
Microsoft has added an excellent new extension in PostgreSQL on their Azure Platform. This session, presented at Posette 2024, covers what Query Store is and the types of information you can get out of it.
What is Augmented Reality Image Tracking
Augmented Reality (AR) Image Tracking is a technology that enables AR applications to recognize and track images in the real world, overlaying digital content onto them. This enhances the user's interaction with their environment by providing additional information and interactive elements directly tied to physical images.
OpenMetadata Community Meeting - 5th June 2024
The OpenMetadata Community Meeting was held on June 5th, 2024. In this meeting, we discussed about the data quality capabilities that are integrated with the Incident Manager, providing a complete solution to handle your data observability needs. Watch the end-to-end demo of the data quality features.
* How to run your own data quality framework
* What is the performance impact of running data quality frameworks
* How to run the test cases in your own ETL pipelines
* How the Incident Manager is integrated
* Get notified with alerts when test cases fail
Watch the meeting recording here - https://www.youtube.com/watch?v=UbNOje0kf6E
Essentials of Automations: The Art of Triggers and Actions in FME
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Microservice Teams - How the cloud changes the way we work
A lot of technical challenges and complexity come with building a cloud-native and distributed architecture. The way we develop backend software has fundamentally changed in the last ten years. Managing a microservices architecture demands a lot of us to ensure observability and operational resiliency. But did you also change the way you run your development teams?
Sven will talk about Atlassian’s journey from a monolith to a multi-tenanted architecture and how it affected the way the engineering teams work. You will learn how we shifted to service ownership, moved to more autonomous teams (and its challenges), and established platform and enablement teams.
Measures in SQL (SIGMOD 2024, Santiago, Chile)
SQL has attained widespread adoption, but Business Intelligence tools still use their own higher level languages based upon a multidimensional paradigm. Composable calculations are what is missing from SQL, and we propose a new kind of column, called a measure, that attaches a calculation to a table. Like regular tables, tables with measures are composable and closed when used in queries.
SQL-with-measures has the power, conciseness and reusability of multidimensional languages but retains SQL semantics. Measure invocations can be expanded in place to simple, clear SQL.
To define the evaluation semantics for measures, we introduce context-sensitive expressions (a way to evaluate multidimensional expressions that is consistent with existing SQL semantics), a concept called evaluation context, and several operations for setting and modifying the evaluation context.
A talk at SIGMOD, June 9–15, 2024, Santiago, Chile
Authors: Julian Hyde (Google) and John Fremlin (Google)
https://doi.org/10.1145/3626246.3653374
Webinar On-Demand: Using Flutter for Embedded
Flutter is a popular open source, cross-platform framework developed by Google. In this webinar we'll explore Flutter and its architecture, delve into the Flutter Embedder and Flutter’s Dart language, discover how to leverage Flutter for embedded device development, learn about Automotive Grade Linux (AGL) and its consortium and understand the rationale behind AGL's choice of Flutter for next-gen IVI systems. Don’t miss this opportunity to discover whether Flutter is right for your project.
Atelier - Innover avec l’IA Générative et les graphes de connaissances
Atelier - Innover avec l’IA Générative et les graphes de connaissances
Allez au-delà du battage médiatique autour de l’IA et découvrez des techniques pratiques pour utiliser l’IA de manière responsable à travers les données de votre organisation. Explorez comment utiliser les graphes de connaissances pour augmenter la précision, la transparence et la capacité d’explication dans les systèmes d’IA générative. Vous partirez avec une expérience pratique combinant les relations entre les données et les LLM pour apporter du contexte spécifique à votre domaine et améliorer votre raisonnement.
Amenez votre ordinateur portable et nous vous guiderons sur la mise en place de votre propre pile d’IA générative, en vous fournissant des exemples pratiques et codés pour démarrer en quelques minutes.
E-commerce Development Services- Hornet Dynamics
For any business hoping to succeed in the digital age, having a strong online presence is crucial. We offer Ecommerce Development Services that are customized according to your business requirements and client preferences, enabling you to create a dynamic, safe, and user-friendly online store.
Neo4j - Product Vision and Knowledge Graphs - GraphSummit Paris
Dr. Jesús Barrasa, Head of Solutions Architecture for EMEA, Neo4j
Découvrez les dernières innovations de Neo4j, et notamment les dernières intégrations cloud et les améliorations produits qui font de Neo4j un choix essentiel pour les développeurs qui créent des applications avec des données interconnectées et de l’IA générative.
A Study of Variable-Role-based Feature Enrichment in Neural Models of Code
Understanding variable roles in code has been found to be helpful by students
in learning programming -- could variable roles help deep neural models in
performing coding tasks? We do an exploratory study.
- These are slides of the talk given at InteNSE'23: The 1st International Workshop on Interpretability and Robustness in Neural Software Engineering, co-located with the 45th International Conference on Software Engineering, ICSE 2023, Melbourne Australia
Recently uploaded (20)
8 Best Automated Android App Testing Tool and Framework in 2024.pdf
8 Best Automated Android App Testing Tool and Framework in 2024.pdf
Revolutionizing Visual Effects Mastering AI Face Swaps.pdf
Revolutionizing Visual Effects Mastering AI Face Swaps.pdf
AI Fusion Buddy Review: Brand New, Groundbreaking Gemini-Powered AI App
AI Fusion Buddy Review: Brand New, Groundbreaking Gemini-Powered AI App
openEuler Case Study - The Journey to Supply Chain Security
openEuler Case Study - The Journey to Supply Chain Security
Why Choose Odoo 17 Community & How it differs from Odoo 17 Enterprise Edition
Why Choose Odoo 17 Community & How it differs from Odoo 17 Enterprise Edition
Introducing Crescat - Event Management Software for Venues, Festivals and Eve...
Introducing Crescat - Event Management Software for Venues, Festivals and Eve...
Fundamentals of Programming and Language Processors
Fundamentals of Programming and Language Processors
How to write a program in any programming language
How to write a program in any programming language
Using Query Store in Azure PostgreSQL to Understand Query Performance
Using Query Store in Azure PostgreSQL to Understand Query Performance
Essentials of Automations: The Art of Triggers and Actions in FME
Essentials of Automations: The Art of Triggers and Actions in FME
Microservice Teams - How the cloud changes the way we work
Microservice Teams - How the cloud changes the way we work
Atelier - Innover avec l’IA Générative et les graphes de connaissances
Atelier - Innover avec l’IA Générative et les graphes de connaissances
Neo4j - Product Vision and Knowledge Graphs - GraphSummit Paris
Neo4j - Product Vision and Knowledge Graphs - GraphSummit Paris
A Study of Variable-Role-based Feature Enrichment in Neural Models of Code
A Study of Variable-Role-based Feature Enrichment in Neural Models of Code
Bhanu new ppt
- 1. Mobile cellular big data:linking cyberspace and physical world with social ecology Student name : worsu bhanuprakash Group no: 23
- 2. Data set , preprocessing and overall visualizations • What is data set? The collection of set of data from different base stations in a selected region. • What is preprocessing? This collection set of data from base stations is fine grained from the large scale traffic logs ensures our human behavior analysis and modeling is credible. • What is data visualization? The data visualization depicts the profile of normalized traffic and the number of active users in one day , which shows the active users in the day and midnight which decides the sleep patterns of humans.
- 3. Human behavior in cyberspace and physical world. • Human mobility in physical world Mobile users can be identified by checking their locations base stations which they are connected to. From this results, it can be seen that the city possesses the highest density of mobile users . Through human mobility the population of mobile users traffic can be known.
- 4. Linking with social ecology Human behavior in the cyber space and physical world can be understood with the knowledge of the social ecology. Cyber space and social ecology are interlinked each other