Downloads & Free Reading Options - Results

John Hand, EPRSC (Engineering and Physical Sciences Research Council) http://www.epsrc.ac.uk/default.htm on their Digital Economy Programme.Part of Wealth of Networks 2008 conference, 24 July 2008, Imperial College Internet Centre http://www.internetcentre.imperial.ac.uk/  

USA

The Internet and its current information culture of preserving all kinds of data cause severe problems with privacy. Most of today's Internet users, especially teenagers, publish various kinds of sensitive information, yet without recognizing that revealing this information might be detrimental to their future life and career. Unflattering images that can be openly accessed now and in the future, e.g., by potential employers, constitute a particularly important such privacy concern. We have developed a novel, fast, and scalable system called X-pire! that allows users to set an expiration date for images in social networks (e.g., Facebook and Flickr) and on static websites, without requiring any form of additional interaction with these web pages. Once the expiration date is reached, the images become unavailable. Moreover, the publishing user can dynamically prolong or shorten the expiration dates of his images later, and even enforce instantaneous expiration. Rendering the approach possible for social networks crucially required us to develop a novel technique for embedding encrypted information within JPEG files in a way that survives JPEG compression, even for highly optimized implementations of JPEG post-processing with their various idiosyncrasies as commonly used in such networks. We have implemented our system and conducted performance measurements to demonstrate its robustness and efficiency.

For every Gaussian relay network with a single source-destination pair, it is known that there exists a corresponding deterministic network called the discrete superposition network that approximates its capacity uniformly over all SNR's to within a bounded number of bits. The next step in this program of rigorous approximation is to determine whether coding schemes for discrete superposition models can be lifted to Gaussian relay networks with a bounded rate loss independent of SNR. We establish precisely this property and show that the superposition model can thus serve as a strong surrogate for designing codes for Gaussian relay networks. We show that a code for a Gaussian relay network, with a single source-destination pair and multiple relay nodes, can be designed from any code for the corresponding discrete superposition network simply by pruning it. In comparison to the rate of the discrete superposition network's code, the rate of the Gaussian network's code only reduces at most by a constant that is a function only of the number of nodes in the network and independent of channel gains. This result is also applicable for coding schemes for MIMO Gaussian relay networks, with the reduction depending additionally on the number of antennas. Hence, the discrete superposition model can serve as a digital interface for operating Gaussian relay networks.

For every Gaussian relay network with a single source-destination pair, it is known that there exists a corresponding deterministic network called the discrete superposition network that approximates its capacity uniformly over all SNR's to within a bounded number of bits. The next step in this program of rigorous approximation is to determine whether coding schemes for discrete superposition models can be lifted to Gaussian relay networks with a bounded rate loss independent of SNR. We establish precisely this property and show that the superposition model can thus serve as a strong surrogate for designing codes for Gaussian relay networks. We show that a code for a Gaussian relay network, with a single source-destination pair and multiple relay nodes, can be designed from any code for the corresponding discrete superposition network simply by pruning it. In comparison to the rate of the discrete superposition network's code, the rate of the Gaussian network's code only reduces at most by a constant that is a function only of the number of nodes in the network and independent of channel gains. This result is also applicable for coding schemes for MIMO Gaussian relay networks, with the reduction depending additionally on the number of antennas. Hence, the discrete superposition model can serve as a digital interface for operating Gaussian relay networks.

For every Gaussian relay network with a single source-destination pair, it is known that there exists a corresponding deterministic network called the discrete superposition network that approximates its capacity uniformly over all SNR's to within a bounded number of bits. The next step in this program of rigorous approximation is to determine whether coding schemes for discrete superposition models can be lifted to Gaussian relay networks with a bounded rate loss independent of SNR. We establish precisely this property and show that the superposition model can thus serve as a strong surrogate for designing codes for Gaussian relay networks. We show that a code for a Gaussian relay network, with a single source-destination pair and multiple relay nodes, can be designed from any code for the corresponding discrete superposition network simply by pruning it. In comparison to the rate of the discrete superposition network's code, the rate of the Gaussian network's code only reduces at most by a constant that is a function only of the number of nodes in the network and independent of channel gains. This result is also applicable for coding schemes for MIMO Gaussian relay networks, with the reduction depending additionally on the number of antennas. Hence, the discrete superposition model can serve as a digital interface for operating Gaussian relay networks.

For every Gaussian relay network with a single source-destination pair, it is known that there exists a corresponding deterministic network called the discrete superposition network that approximates its capacity uniformly over all SNR's to within a bounded number of bits. The next step in this program of rigorous approximation is to determine whether coding schemes for discrete superposition models can be lifted to Gaussian relay networks with a bounded rate loss independent of SNR. We establish precisely this property and show that the superposition model can thus serve as a strong surrogate for designing codes for Gaussian relay networks. We show that a code for a Gaussian relay network, with a single source-destination pair and multiple relay nodes, can be designed from any code for the corresponding discrete superposition network simply by pruning it. In comparison to the rate of the discrete superposition network's code, the rate of the Gaussian network's code only reduces at most by a constant that is a function only of the number of nodes in the network and independent of channel gains. This result is also applicable for coding schemes for MIMO Gaussian relay networks, with the reduction depending additionally on the number of antennas. Hence, the discrete superposition model can serve as a digital interface for operating Gaussian relay networks.

For every Gaussian relay network with a single source-destination pair, it is known that there exists a corresponding deterministic network called the discrete superposition network that approximates its capacity uniformly over all SNR's to within a bounded number of bits. The next step in this program of rigorous approximation is to determine whether coding schemes for discrete superposition models can be lifted to Gaussian relay networks with a bounded rate loss independent of SNR. We establish precisely this property and show that the superposition model can thus serve as a strong surrogate for designing codes for Gaussian relay networks. We show that a code for a Gaussian relay network, with a single source-destination pair and multiple relay nodes, can be designed from any code for the corresponding discrete superposition network simply by pruning it. In comparison to the rate of the discrete superposition network's code, the rate of the Gaussian network's code only reduces at most by a constant that is a function only of the number of nodes in the network and independent of channel gains. This result is also applicable for coding schemes for MIMO Gaussian relay networks, with the reduction depending additionally on the number of antennas. Hence, the discrete superposition model can serve as a digital interface for operating Gaussian relay networks.

For every Gaussian relay network with a single source-destination pair, it is known that there exists a corresponding deterministic network called the discrete superposition network that approximates its capacity uniformly over all SNR's to within a bounded number of bits. The next step in this program of rigorous approximation is to determine whether coding schemes for discrete superposition models can be lifted to Gaussian relay networks with a bounded rate loss independent of SNR. We establish precisely this property and show that the superposition model can thus serve as a strong surrogate for designing codes for Gaussian relay networks. We show that a code for a Gaussian relay network, with a single source-destination pair and multiple relay nodes, can be designed from any code for the corresponding discrete superposition network simply by pruning it. In comparison to the rate of the discrete superposition network's code, the rate of the Gaussian network's code only reduces at most by a constant that is a function only of the number of nodes in the network and independent of channel gains. This result is also applicable for coding schemes for MIMO Gaussian relay networks, with the reduction depending additionally on the number of antennas. Hence, the discrete superposition model can serve as a digital interface for operating Gaussian relay networks.

For every Gaussian relay network with a single source-destination pair, it is known that there exists a corresponding deterministic network called the discrete superposition network that approximates its capacity uniformly over all SNR's to within a bounded number of bits. The next step in this program of rigorous approximation is to determine whether coding schemes for discrete superposition models can be lifted to Gaussian relay networks with a bounded rate loss independent of SNR. We establish precisely this property and show that the superposition model can thus serve as a strong surrogate for designing codes for Gaussian relay networks. We show that a code for a Gaussian relay network, with a single source-destination pair and multiple relay nodes, can be designed from any code for the corresponding discrete superposition network simply by pruning it. In comparison to the rate of the discrete superposition network's code, the rate of the Gaussian network's code only reduces at most by a constant that is a function only of the number of nodes in the network and independent of channel gains. This result is also applicable for coding schemes for MIMO Gaussian relay networks, with the reduction depending additionally on the number of antennas. Hence, the discrete superposition model can serve as a digital interface for operating Gaussian relay networks.

This item represents a case in PACER, the U.S. Government's website for federal case data. If you wish to see the entire case, please consult PACER directly.

Face detection is a critical function of security (secure witness face in the video) who appear in a scene and are frequently captured by the camera. Recognition of people from their faces in images has recently piqued the scientific community, partly due to application concerns, but also for the difficulty this characterizes for the algorithms of artificial vision. The idea for this research stems from a broad interest in courtroom witness face detection. The goal of this work is to detect and track the face of a witness in court. In this work, a Viola-Jones method is used to extract human faces and then a particular transformation is applied to crop the image. Witness and non-witness images are classified using convolutional neural networks (CNN). The Kanade-Lucas-Tomasi (KLT) algorithm was utilized to track the witness face using trained features. In this model, the two methods were combined in one model to take the advantage of each method in terms of speed and reduce the amount of space required to implement CNN and detection accuracy. After the test, the results of the proposed model showed that it was 99.5% percent accurate when executed in real-time and with adequate lighting. 

In order to promote public education and public safety, equal justice for all, a better informed citizenry, the rule of law, world trade and world peace, this legal document is hereby made available on a noncommercial basis, as it is the right of all humans to know and speak the laws that govern them. (For more information: 12 Tables of Code ) Name of Standards Organization: Bureau of Indian Standards (BIS) Division Name: Electronics and Information Technology Section Name: Wires, Cables, Waveguides and Accessories (LITD 6) Designator of Legally Binding Document: IS/IEC 62255-4 Title of Legally Binding Document: Multicore and Symmetrical Pair/Quad Cables for Broadband Digital Communications (High Bit Rate Digital Access Telecommunication Networks) - Outside Plant Cables, Part 4: Aerial Drop Cables - Sectional Specification Number of Amendments: Equivalence: IEC 62255-4:2006 Superceding: Superceded by: LEGALLY BINDING DOCUMENT Step Out From the Old to the New --Jawaharlal Nehru Invent a new India using knowledge. --Satyanarayan Gangaram Pitroda

Digital Equipment Corporation, Cambridge Research Laboratory Technical Report Series Counting Networks

Digital Equipment Corporation, Cambridge Research Laboratory Technical Report Series Counting Networks

Slides from a seminar that Carl Malamud gave in the mid-1980s.

Slides from a seminar that Carl Malamud gave in the mid-1980s.

Slides from a seminar that Carl Malamud gave in the mid-1980s.

Slides from a seminar that Carl Malamud gave in the mid-1980s.

Slides from a seminar that Carl Malamud gave in the mid-1980s.

How black Americans use digital networks to organize and cultivate solidarity Unrest gripped Ferguson, Missouri, after Mike Brown, an unarmed black teenager, was shot and killed by Officer Darren Wilson in August 2014. Many black Americans turned to their digital and social media networks to circulate information, cultivate solidarity, and organize during that tumultuous moment. While Ferguson and the subsequent protests made black digital networks visible to mainstream media, these networks did not coalesce overnight. They were built and maintained over years through common, everyday use. Beyond Hashtags explores these everyday practices and their relationship to larger social issues through an in-depth analysis of a trans-platform network of black American digital and social media users and content creators. In the crucial years leading up to the emergence of the Movement for Black Lives, black Americans used digital networks not only to cope with day-to-day experiences of racism, but also as an incubator for the debates that have since exploded onto the national stage. Beyond Hashtags tells the story of an influential subsection of these networks, an assemblage of podcasting, independent media, Instagram, Vine, Facebook, and the network of Twitter users that has come to be known as “Black Twitter.” Florini looks at how black Americans use these technologies often simultaneously to create a space to reassert their racial identities, forge community, organize politically, and create alternative media representations and news sources. Beyond Hashtags demonstrates how much insight marginalized users have into technology.

Neural networks tend to fall into two general categories: (1) software simulations, or (2) custom hardware that must be trained. The scope of this project is the merger of these two classifications into a system whereby a software model of a network is trained to perform a specific task and the results used to synthesize a standard cell realization of the network using automated tools.

This paper summarizes initial field-test results from data analytics used in the work of the Assessment and Teaching of 21st Century Skills (ATC21S) project, on the "ICT Literacy--Learning in digital networks" learning progression. This project, sponsored by Cisco, Intel and Microsoft, aims to help educators around the world enable students with the skills to succeed in future career and college goals. The paper begins with describing some expansions to a common definition of learning analytics, then includes a review of the literature on ICT literacy, including the specific development that led to the ATC21S effort. This is followed by a description of the development of a "learning progression" for this project, as well as the logic behind the instrument construction and data analytics, along with examples of each. Data were collected in a demonstration digital environment in four countries: Australia, Finland, Singapore and the U.S. The results indicate that the new constructs developed by the project, and the novel item forms and analytics that were employed, are indeed capable of being employed in a large-scale digital environment. The paper concludes with a discussion of the next steps for this effort.

This paper summarizes initial field-test results from data analytics used in the work of the Assessment and Teaching of 21st Century Skills (ATC21S) project, on the "ICT Literacy--Learning in digital networks" learning progression. This project, sponsored by Cisco, Intel and Microsoft, aims to help educators around the world enable students with the skills to succeed in future career and college goals. The paper begins with describing some expansions to a common definition of learning analytics, then includes a review of the literature on ICT literacy, including the specific development that led to the ATC21S effort. This is followed by a description of the development of a "learning progression" for this project, as well as the logic behind the instrument construction and data analytics, along with examples of each. Data were collected in a demonstration digital environment in four countries: Australia, Finland, Singapore and the U.S. The results indicate that the new constructs developed by the project, and the novel item forms and analytics that were employed, are indeed capable of being employed in a large-scale digital environment. The paper concludes with a discussion of the next steps for this effort.

This paper summarizes initial field-test results from data analytics used in the work of the Assessment and Teaching of 21st Century Skills (ATC21S) project, on the "ICT Literacy--Learning in digital networks" learning progression. This project, sponsored by Cisco, Intel and Microsoft, aims to help educators around the world enable students with the skills to succeed in future career and college goals. The paper begins with describing some expansions to a common definition of learning analytics, then includes a review of the literature on ICT literacy, including the specific development that led to the ATC21S effort. This is followed by a description of the development of a "learning progression" for this project, as well as the logic behind the instrument construction and data analytics, along with examples of each. Data were collected in a demonstration digital environment in four countries: Australia, Finland, Singapore and the U.S. The results indicate that the new constructs developed by the project, and the novel item forms and analytics that were employed, are indeed capable of being employed in a large-scale digital environment. The paper concludes with a discussion of the next steps for this effort.

This paper summarizes initial field-test results from data analytics used in the work of the Assessment and Teaching of 21st Century Skills (ATC21S) project, on the "ICT Literacy--Learning in digital networks" learning progression. This project, sponsored by Cisco, Intel and Microsoft, aims to help educators around the world enable students with the skills to succeed in future career and college goals. The paper begins with describing some expansions to a common definition of learning analytics, then includes a review of the literature on ICT literacy, including the specific development that led to the ATC21S effort. This is followed by a description of the development of a "learning progression" for this project, as well as the logic behind the instrument construction and data analytics, along with examples of each. Data were collected in a demonstration digital environment in four countries: Australia, Finland, Singapore and the U.S. The results indicate that the new constructs developed by the project, and the novel item forms and analytics that were employed, are indeed capable of being employed in a large-scale digital environment. The paper concludes with a discussion of the next steps for this effort.

Lecture presented by Peter G. Klein at the Mises Institute Brasil's 2nd Austrian School of Economics seminar on April 10, 2011.

The emergence of new digital technologies has allowed the study of human behaviour at a scale and at level of granularity that were unthinkable just a decade ago. In particular, by analysing the digital traces left by people interacting in the online and offline worlds, we are able to trace the spreading of knowledge and ideas at both local and global scales. In this article we will discuss how these digital traces can be used to map knowledge across the world, outlining both the limitations and the challenges in performing this type of analysis. We will focus on data collected from social media platforms, large-scale digital repositories and mobile data. Finally, we will provide an overview of the tools that are available to scholars and practitioners for understanding these processes using these emerging forms of data.

The overwhelming success of the web 2.0, with online social networks as key actors, has induced a paradigm shift in the nature of human interactions. The user-driven character of these services for the first time has allowed researchers to quantify large-scale social patterns. However, the mechanisms that determine the fate of networks at a system level are still poorly understood. For instance, the simultaneous existence of numerous digital services naturally raises the question under which conditions these services can coexist. In analogy to population dynamics, the digital world is forming a complex ecosystem of interacting networks whose fitnesses depend on their ability to attract and maintain users' attention, which constitutes a limited resource. In this paper, we introduce an ecological theory of the digital world which exhibits a stable coexistence of several networks as well as the domination of a single one, in contrast to the principle of competitive exclusion. Interestingly, our model also predicts that the most probable outcome is the coexistence of a moderate number of services, in agreement with empirical observations.

The overwhelming success of the web 2.0, with online social networks as key actors, has induced a paradigm shift in the nature of human interactions. The user-driven character of these services for the first time has allowed researchers to quantify large-scale social patterns. However, the mechanisms that determine the fate of networks at a system level are still poorly understood. For instance, the simultaneous existence of numerous digital services naturally raises the question under which conditions these services can coexist. In analogy to population dynamics, the digital world is forming a complex ecosystem of interacting networks whose fitnesses depend on their ability to attract and maintain users' attention, which constitutes a limited resource. In this paper, we introduce an ecological theory of the digital world which exhibits a stable coexistence of several networks as well as the domination of a single one, in contrast to the principle of competitive exclusion. Interestingly, our model also predicts that the most probable outcome is the coexistence of a moderate number of services, in agreement with empirical observations.

EXECUTIVE SUMMARY  In December 2023, the Network Contagion Research Institute (NCRI) published an initial report that found a strong possibility of content on TikTok being either amplified or suppressed based on its alignment with the interests of the Chinese Government. The report concluded with a warning: “should future research find that TikTok users exhibit attitudes and assessments of world events aligned with these information distortions, democracies will need to consider appropriate countermeasures to protect information integrity and mitigate potential real-world impacts.” These findings underscored the urgency of investigating the specific mechanisms and broader implications of potential algorithmic manipulations. While our initial study shed light on the potential for content manipulation on TikTok, it did not explore whether specific moderation algorithms or practices are used to suppress topics sensitive to the Chinese Communist Party (CCP). Moreover, it did not compare the nature and impact of pro- and anti-CCP content across other major social media platforms like Instagram and YouTube. This current report addresses these gaps by providing a more comprehensive analysis of TikTok's moderation practices, examining the nature and prevalence of CCP-sensitive content, and evaluating how different platforms handle such content. Furthermore, this study explores the association between social media platform usage and pro-CCP attitudes among users. By combining user journey data, survey research, and cross-platform comparisons, we uncover the extent to which TikTok and other platforms may influence user perceptions and behaviors in favor of the CCP.  The publication of this research precedes the delivery of oral arguments for TikTok Inc. and ByteDance Ltd. v. Merrick B. Garland, a federal court case that has subjected the TikTok algorithm to intensive new scrutiny. As detailed in the DOJ’s response to TikTok’s lawsuit, “covert content manipulation” is an area of legal interest for the DOJ, not to mention its relevance to the broader U.S. intelligence and national security community. That said, within the DOJ response it is noted that definitively proving covert content manipulation by the Chinese government remains a challenge. As FBI Director Wray testified to in multiple hearings, “[t]his sort of manipulation of the algorithm would be difficult to detect…" 1 This research gap sets the stage for our findings, which, while not definitive proof of state orchestration, present compelling and strong circumstantial evidence of TikTok’s covert content manipulation.

EXECUTIVE SUMMARY  In December 2023, the Network Contagion Research Institute (NCRI) published an initial report that found a strong possibility of content on TikTok being either amplified or suppressed based on its alignment with the interests of the Chinese Government. The report concluded with a warning: “should future research find that TikTok users exhibit attitudes and assessments of world events aligned with these information distortions, democracies will need to consider appropriate countermeasures to protect information integrity and mitigate potential real-world impacts.” These findings underscored the urgency of investigating the specific mechanisms and broader implications of potential algorithmic manipulations. While our initial study shed light on the potential for content manipulation on TikTok, it did not explore whether specific moderation algorithms or practices are used to suppress topics sensitive to the Chinese Communist Party (CCP). Moreover, it did not compare the nature and impact of pro- and anti-CCP content across other major social media platforms like Instagram and YouTube. This current report addresses these gaps by providing a more comprehensive analysis of TikTok's moderation practices, examining the nature and prevalence of CCP-sensitive content, and evaluating how different platforms handle such content. Furthermore, this study explores the association between social media platform usage and pro-CCP attitudes among users. By combining user journey data, survey research, and cross-platform comparisons, we uncover the extent to which TikTok and other platforms may influence user perceptions and behaviors in favor of the CCP.  The publication of this research precedes the delivery of oral arguments for TikTok Inc. and ByteDance Ltd. v. Merrick B. Garland, a federal court case that has subjected the TikTok algorithm to intensive new scrutiny. As detailed in the DOJ’s response to TikTok’s lawsuit, “covert content manipulation” is an area of legal interest for the DOJ, not to mention its relevance to the broader U.S. intelligence and national security community. That said, within the DOJ response it is noted that definitively proving covert content manipulation by the Chinese government remains a challenge. As FBI Director Wray testified to in multiple hearings, “[t]his sort of manipulation of the algorithm would be difficult to detect…" 1 This research gap sets the stage for our findings, which, while not definitive proof of state orchestration, present compelling and strong circumstantial evidence of TikTok’s covert content manipulation.

EXECUTIVE SUMMARY  In December 2023, the Network Contagion Research Institute (NCRI) published an initial report that found a strong possibility of content on TikTok being either amplified or suppressed based on its alignment with the interests of the Chinese Government. The report concluded with a warning: “should future research find that TikTok users exhibit attitudes and assessments of world events aligned with these information distortions, democracies will need to consider appropriate countermeasures to protect information integrity and mitigate potential real-world impacts.” These findings underscored the urgency of investigating the specific mechanisms and broader implications of potential algorithmic manipulations. While our initial study shed light on the potential for content manipulation on TikTok, it did not explore whether specific moderation algorithms or practices are used to suppress topics sensitive to the Chinese Communist Party (CCP). Moreover, it did not compare the nature and impact of pro- and anti-CCP content across other major social media platforms like Instagram and YouTube. This current report addresses these gaps by providing a more comprehensive analysis of TikTok's moderation practices, examining the nature and prevalence of CCP-sensitive content, and evaluating how different platforms handle such content. Furthermore, this study explores the association between social media platform usage and pro-CCP attitudes among users. By combining user journey data, survey research, and cross-platform comparisons, we uncover the extent to which TikTok and other platforms may influence user perceptions and behaviors in favor of the CCP.  The publication of this research precedes the delivery of oral arguments for TikTok Inc. and ByteDance Ltd. v. Merrick B. Garland, a federal court case that has subjected the TikTok algorithm to intensive new scrutiny. As detailed in the DOJ’s response to TikTok’s lawsuit, “covert content manipulation” is an area of legal interest for the DOJ, not to mention its relevance to the broader U.S. intelligence and national security community. That said, within the DOJ response it is noted that definitively proving covert content manipulation by the Chinese government remains a challenge. As FBI Director Wray testified to in multiple hearings, “[t]his sort of manipulation of the algorithm would be difficult to detect…" 1 This research gap sets the stage for our findings, which, while not definitive proof of state orchestration, present compelling and strong circumstantial evidence of TikTok’s covert content manipulation.

EXECUTIVE SUMMARY  In December 2023, the Network Contagion Research Institute (NCRI) published an initial report that found a strong possibility of content on TikTok being either amplified or suppressed based on its alignment with the interests of the Chinese Government. The report concluded with a warning: “should future research find that TikTok users exhibit attitudes and assessments of world events aligned with these information distortions, democracies will need to consider appropriate countermeasures to protect information integrity and mitigate potential real-world impacts.” These findings underscored the urgency of investigating the specific mechanisms and broader implications of potential algorithmic manipulations. While our initial study shed light on the potential for content manipulation on TikTok, it did not explore whether specific moderation algorithms or practices are used to suppress topics sensitive to the Chinese Communist Party (CCP). Moreover, it did not compare the nature and impact of pro- and anti-CCP content across other major social media platforms like Instagram and YouTube. This current report addresses these gaps by providing a more comprehensive analysis of TikTok's moderation practices, examining the nature and prevalence of CCP-sensitive content, and evaluating how different platforms handle such content. Furthermore, this study explores the association between social media platform usage and pro-CCP attitudes among users. By combining user journey data, survey research, and cross-platform comparisons, we uncover the extent to which TikTok and other platforms may influence user perceptions and behaviors in favor of the CCP.  The publication of this research precedes the delivery of oral arguments for TikTok Inc. and ByteDance Ltd. v. Merrick B. Garland, a federal court case that has subjected the TikTok algorithm to intensive new scrutiny. As detailed in the DOJ’s response to TikTok’s lawsuit, “covert content manipulation” is an area of legal interest for the DOJ, not to mention its relevance to the broader U.S. intelligence and national security community. That said, within the DOJ response it is noted that definitively proving covert content manipulation by the Chinese government remains a challenge. As FBI Director Wray testified to in multiple hearings, “[t]his sort of manipulation of the algorithm would be difficult to detect…" 1 This research gap sets the stage for our findings, which, while not definitive proof of state orchestration, present compelling and strong circumstantial evidence of TikTok’s covert content manipulation.

EXECUTIVE SUMMARY  In December 2023, the Network Contagion Research Institute (NCRI) published an initial report that found a strong possibility of content on TikTok being either amplified or suppressed based on its alignment with the interests of the Chinese Government. The report concluded with a warning: “should future research find that TikTok users exhibit attitudes and assessments of world events aligned with these information distortions, democracies will need to consider appropriate countermeasures to protect information integrity and mitigate potential real-world impacts.” These findings underscored the urgency of investigating the specific mechanisms and broader implications of potential algorithmic manipulations. While our initial study shed light on the potential for content manipulation on TikTok, it did not explore whether specific moderation algorithms or practices are used to suppress topics sensitive to the Chinese Communist Party (CCP). Moreover, it did not compare the nature and impact of pro- and anti-CCP content across other major social media platforms like Instagram and YouTube. This current report addresses these gaps by providing a more comprehensive analysis of TikTok's moderation practices, examining the nature and prevalence of CCP-sensitive content, and evaluating how different platforms handle such content. Furthermore, this study explores the association between social media platform usage and pro-CCP attitudes among users. By combining user journey data, survey research, and cross-platform comparisons, we uncover the extent to which TikTok and other platforms may influence user perceptions and behaviors in favor of the CCP.  The publication of this research precedes the delivery of oral arguments for TikTok Inc. and ByteDance Ltd. v. Merrick B. Garland, a federal court case that has subjected the TikTok algorithm to intensive new scrutiny. As detailed in the DOJ’s response to TikTok’s lawsuit, “covert content manipulation” is an area of legal interest for the DOJ, not to mention its relevance to the broader U.S. intelligence and national security community. That said, within the DOJ response it is noted that definitively proving covert content manipulation by the Chinese government remains a challenge. As FBI Director Wray testified to in multiple hearings, “[t]his sort of manipulation of the algorithm would be difficult to detect…" 1 This research gap sets the stage for our findings, which, while not definitive proof of state orchestration, present compelling and strong circumstantial evidence of TikTok’s covert content manipulation.

EXECUTIVE SUMMARY  In December 2023, the Network Contagion Research Institute (NCRI) published an initial report that found a strong possibility of content on TikTok being either amplified or suppressed based on its alignment with the interests of the Chinese Government. The report concluded with a warning: “should future research find that TikTok users exhibit attitudes and assessments of world events aligned with these information distortions, democracies will need to consider appropriate countermeasures to protect information integrity and mitigate potential real-world impacts.” These findings underscored the urgency of investigating the specific mechanisms and broader implications of potential algorithmic manipulations. While our initial study shed light on the potential for content manipulation on TikTok, it did not explore whether specific moderation algorithms or practices are used to suppress topics sensitive to the Chinese Communist Party (CCP). Moreover, it did not compare the nature and impact of pro- and anti-CCP content across other major social media platforms like Instagram and YouTube. This current report addresses these gaps by providing a more comprehensive analysis of TikTok's moderation practices, examining the nature and prevalence of CCP-sensitive content, and evaluating how different platforms handle such content. Furthermore, this study explores the association between social media platform usage and pro-CCP attitudes among users. By combining user journey data, survey research, and cross-platform comparisons, we uncover the extent to which TikTok and other platforms may influence user perceptions and behaviors in favor of the CCP.  The publication of this research precedes the delivery of oral arguments for TikTok Inc. and ByteDance Ltd. v. Merrick B. Garland, a federal court case that has subjected the TikTok algorithm to intensive new scrutiny. As detailed in the DOJ’s response to TikTok’s lawsuit, “covert content manipulation” is an area of legal interest for the DOJ, not to mention its relevance to the broader U.S. intelligence and national security community. That said, within the DOJ response it is noted that definitively proving covert content manipulation by the Chinese government remains a challenge. As FBI Director Wray testified to in multiple hearings, “[t]his sort of manipulation of the algorithm would be difficult to detect…" 1 This research gap sets the stage for our findings, which, while not definitive proof of state orchestration, present compelling and strong circumstantial evidence of TikTok’s covert content manipulation.

EXECUTIVE SUMMARY  In December 2023, the Network Contagion Research Institute (NCRI) published an initial report that found a strong possibility of content on TikTok being either amplified or suppressed based on its alignment with the interests of the Chinese Government. The report concluded with a warning: “should future research find that TikTok users exhibit attitudes and assessments of world events aligned with these information distortions, democracies will need to consider appropriate countermeasures to protect information integrity and mitigate potential real-world impacts.” These findings underscored the urgency of investigating the specific mechanisms and broader implications of potential algorithmic manipulations. While our initial study shed light on the potential for content manipulation on TikTok, it did not explore whether specific moderation algorithms or practices are used to suppress topics sensitive to the Chinese Communist Party (CCP). Moreover, it did not compare the nature and impact of pro- and anti-CCP content across other major social media platforms like Instagram and YouTube. This current report addresses these gaps by providing a more comprehensive analysis of TikTok's moderation practices, examining the nature and prevalence of CCP-sensitive content, and evaluating how different platforms handle such content. Furthermore, this study explores the association between social media platform usage and pro-CCP attitudes among users. By combining user journey data, survey research, and cross-platform comparisons, we uncover the extent to which TikTok and other platforms may influence user perceptions and behaviors in favor of the CCP.  The publication of this research precedes the delivery of oral arguments for TikTok Inc. and ByteDance Ltd. v. Merrick B. Garland, a federal court case that has subjected the TikTok algorithm to intensive new scrutiny. As detailed in the DOJ’s response to TikTok’s lawsuit, “covert content manipulation” is an area of legal interest for the DOJ, not to mention its relevance to the broader U.S. intelligence and national security community. That said, within the DOJ response it is noted that definitively proving covert content manipulation by the Chinese government remains a challenge. As FBI Director Wray testified to in multiple hearings, “[t]his sort of manipulation of the algorithm would be difficult to detect…" 1 This research gap sets the stage for our findings, which, while not definitive proof of state orchestration, present compelling and strong circumstantial evidence of TikTok’s covert content manipulation.

EXECUTIVE SUMMARY  In December 2023, the Network Contagion Research Institute (NCRI) published an initial report that found a strong possibility of content on TikTok being either amplified or suppressed based on its alignment with the interests of the Chinese Government. The report concluded with a warning: “should future research find that TikTok users exhibit attitudes and assessments of world events aligned with these information distortions, democracies will need to consider appropriate countermeasures to protect information integrity and mitigate potential real-world impacts.” These findings underscored the urgency of investigating the specific mechanisms and broader implications of potential algorithmic manipulations. While our initial study shed light on the potential for content manipulation on TikTok, it did not explore whether specific moderation algorithms or practices are used to suppress topics sensitive to the Chinese Communist Party (CCP). Moreover, it did not compare the nature and impact of pro- and anti-CCP content across other major social media platforms like Instagram and YouTube. This current report addresses these gaps by providing a more comprehensive analysis of TikTok's moderation practices, examining the nature and prevalence of CCP-sensitive content, and evaluating how different platforms handle such content. Furthermore, this study explores the association between social media platform usage and pro-CCP attitudes among users. By combining user journey data, survey research, and cross-platform comparisons, we uncover the extent to which TikTok and other platforms may influence user perceptions and behaviors in favor of the CCP.  The publication of this research precedes the delivery of oral arguments for TikTok Inc. and ByteDance Ltd. v. Merrick B. Garland, a federal court case that has subjected the TikTok algorithm to intensive new scrutiny. As detailed in the DOJ’s response to TikTok’s lawsuit, “covert content manipulation” is an area of legal interest for the DOJ, not to mention its relevance to the broader U.S. intelligence and national security community. That said, within the DOJ response it is noted that definitively proving covert content manipulation by the Chinese government remains a challenge. As FBI Director Wray testified to in multiple hearings, “[t]his sort of manipulation of the algorithm would be difficult to detect…" 1 This research gap sets the stage for our findings, which, while not definitive proof of state orchestration, present compelling and strong circumstantial evidence of TikTok’s covert content manipulation.

EXECUTIVE SUMMARY  In December 2023, the Network Contagion Research Institute (NCRI) published an initial report that found a strong possibility of content on TikTok being either amplified or suppressed based on its alignment with the interests of the Chinese Government. The report concluded with a warning: “should future research find that TikTok users exhibit attitudes and assessments of world events aligned with these information distortions, democracies will need to consider appropriate countermeasures to protect information integrity and mitigate potential real-world impacts.” These findings underscored the urgency of investigating the specific mechanisms and broader implications of potential algorithmic manipulations. While our initial study shed light on the potential for content manipulation on TikTok, it did not explore whether specific moderation algorithms or practices are used to suppress topics sensitive to the Chinese Communist Party (CCP). Moreover, it did not compare the nature and impact of pro- and anti-CCP content across other major social media platforms like Instagram and YouTube. This current report addresses these gaps by providing a more comprehensive analysis of TikTok's moderation practices, examining the nature and prevalence of CCP-sensitive content, and evaluating how different platforms handle such content. Furthermore, this study explores the association between social media platform usage and pro-CCP attitudes among users. By combining user journey data, survey research, and cross-platform comparisons, we uncover the extent to which TikTok and other platforms may influence user perceptions and behaviors in favor of the CCP.  The publication of this research precedes the delivery of oral arguments for TikTok Inc. and ByteDance Ltd. v. Merrick B. Garland, a federal court case that has subjected the TikTok algorithm to intensive new scrutiny. As detailed in the DOJ’s response to TikTok’s lawsuit, “covert content manipulation” is an area of legal interest for the DOJ, not to mention its relevance to the broader U.S. intelligence and national security community. That said, within the DOJ response it is noted that definitively proving covert content manipulation by the Chinese government remains a challenge. As FBI Director Wray testified to in multiple hearings, “[t]his sort of manipulation of the algorithm would be difficult to detect…" 1 This research gap sets the stage for our findings, which, while not definitive proof of state orchestration, present compelling and strong circumstantial evidence of TikTok’s covert content manipulation.

EXECUTIVE SUMMARY  In December 2023, the Network Contagion Research Institute (NCRI) published an initial report that found a strong possibility of content on TikTok being either amplified or suppressed based on its alignment with the interests of the Chinese Government. The report concluded with a warning: “should future research find that TikTok users exhibit attitudes and assessments of world events aligned with these information distortions, democracies will need to consider appropriate countermeasures to protect information integrity and mitigate potential real-world impacts.” These findings underscored the urgency of investigating the specific mechanisms and broader implications of potential algorithmic manipulations. While our initial study shed light on the potential for content manipulation on TikTok, it did not explore whether specific moderation algorithms or practices are used to suppress topics sensitive to the Chinese Communist Party (CCP). Moreover, it did not compare the nature and impact of pro- and anti-CCP content across other major social media platforms like Instagram and YouTube. This current report addresses these gaps by providing a more comprehensive analysis of TikTok's moderation practices, examining the nature and prevalence of CCP-sensitive content, and evaluating how different platforms handle such content. Furthermore, this study explores the association between social media platform usage and pro-CCP attitudes among users. By combining user journey data, survey research, and cross-platform comparisons, we uncover the extent to which TikTok and other platforms may influence user perceptions and behaviors in favor of the CCP.  The publication of this research precedes the delivery of oral arguments for TikTok Inc. and ByteDance Ltd. v. Merrick B. Garland, a federal court case that has subjected the TikTok algorithm to intensive new scrutiny. As detailed in the DOJ’s response to TikTok’s lawsuit, “covert content manipulation” is an area of legal interest for the DOJ, not to mention its relevance to the broader U.S. intelligence and national security community. That said, within the DOJ response it is noted that definitively proving covert content manipulation by the Chinese government remains a challenge. As FBI Director Wray testified to in multiple hearings, “[t]his sort of manipulation of the algorithm would be difficult to detect…" 1 This research gap sets the stage for our findings, which, while not definitive proof of state orchestration, present compelling and strong circumstantial evidence of TikTok’s covert content manipulation.

EXECUTIVE SUMMARY  In December 2023, the Network Contagion Research Institute (NCRI) published an initial report that found a strong possibility of content on TikTok being either amplified or suppressed based on its alignment with the interests of the Chinese Government. The report concluded with a warning: “should future research find that TikTok users exhibit attitudes and assessments of world events aligned with these information distortions, democracies will need to consider appropriate countermeasures to protect information integrity and mitigate potential real-world impacts.” These findings underscored the urgency of investigating the specific mechanisms and broader implications of potential algorithmic manipulations. While our initial study shed light on the potential for content manipulation on TikTok, it did not explore whether specific moderation algorithms or practices are used to suppress topics sensitive to the Chinese Communist Party (CCP). Moreover, it did not compare the nature and impact of pro- and anti-CCP content across other major social media platforms like Instagram and YouTube. This current report addresses these gaps by providing a more comprehensive analysis of TikTok's moderation practices, examining the nature and prevalence of CCP-sensitive content, and evaluating how different platforms handle such content. Furthermore, this study explores the association between social media platform usage and pro-CCP attitudes among users. By combining user journey data, survey research, and cross-platform comparisons, we uncover the extent to which TikTok and other platforms may influence user perceptions and behaviors in favor of the CCP.  The publication of this research precedes the delivery of oral arguments for TikTok Inc. and ByteDance Ltd. v. Merrick B. Garland, a federal court case that has subjected the TikTok algorithm to intensive new scrutiny. As detailed in the DOJ’s response to TikTok’s lawsuit, “covert content manipulation” is an area of legal interest for the DOJ, not to mention its relevance to the broader U.S. intelligence and national security community. That said, within the DOJ response it is noted that definitively proving covert content manipulation by the Chinese government remains a challenge. As FBI Director Wray testified to in multiple hearings, “[t]his sort of manipulation of the algorithm would be difficult to detect…" 1 This research gap sets the stage for our findings, which, while not definitive proof of state orchestration, present compelling and strong circumstantial evidence of TikTok’s covert content manipulation.

EXECUTIVE SUMMARY  In December 2023, the Network Contagion Research Institute (NCRI) published an initial report that found a strong possibility of content on TikTok being either amplified or suppressed based on its alignment with the interests of the Chinese Government. The report concluded with a warning: “should future research find that TikTok users exhibit attitudes and assessments of world events aligned with these information distortions, democracies will need to consider appropriate countermeasures to protect information integrity and mitigate potential real-world impacts.” These findings underscored the urgency of investigating the specific mechanisms and broader implications of potential algorithmic manipulations. While our initial study shed light on the potential for content manipulation on TikTok, it did not explore whether specific moderation algorithms or practices are used to suppress topics sensitive to the Chinese Communist Party (CCP). Moreover, it did not compare the nature and impact of pro- and anti-CCP content across other major social media platforms like Instagram and YouTube. This current report addresses these gaps by providing a more comprehensive analysis of TikTok's moderation practices, examining the nature and prevalence of CCP-sensitive content, and evaluating how different platforms handle such content. Furthermore, this study explores the association between social media platform usage and pro-CCP attitudes among users. By combining user journey data, survey research, and cross-platform comparisons, we uncover the extent to which TikTok and other platforms may influence user perceptions and behaviors in favor of the CCP.  The publication of this research precedes the delivery of oral arguments for TikTok Inc. and ByteDance Ltd. v. Merrick B. Garland, a federal court case that has subjected the TikTok algorithm to intensive new scrutiny. As detailed in the DOJ’s response to TikTok’s lawsuit, “covert content manipulation” is an area of legal interest for the DOJ, not to mention its relevance to the broader U.S. intelligence and national security community. That said, within the DOJ response it is noted that definitively proving covert content manipulation by the Chinese government remains a challenge. As FBI Director Wray testified to in multiple hearings, “[t]his sort of manipulation of the algorithm would be difficult to detect…" 1 This research gap sets the stage for our findings, which, while not definitive proof of state orchestration, present compelling and strong circumstantial evidence of TikTok’s covert content manipulation.

EXECUTIVE SUMMARY  In December 2023, the Network Contagion Research Institute (NCRI) published an initial report that found a strong possibility of content on TikTok being either amplified or suppressed based on its alignment with the interests of the Chinese Government. The report concluded with a warning: “should future research find that TikTok users exhibit attitudes and assessments of world events aligned with these information distortions, democracies will need to consider appropriate countermeasures to protect information integrity and mitigate potential real-world impacts.” These findings underscored the urgency of investigating the specific mechanisms and broader implications of potential algorithmic manipulations. While our initial study shed light on the potential for content manipulation on TikTok, it did not explore whether specific moderation algorithms or practices are used to suppress topics sensitive to the Chinese Communist Party (CCP). Moreover, it did not compare the nature and impact of pro- and anti-CCP content across other major social media platforms like Instagram and YouTube. This current report addresses these gaps by providing a more comprehensive analysis of TikTok's moderation practices, examining the nature and prevalence of CCP-sensitive content, and evaluating how different platforms handle such content. Furthermore, this study explores the association between social media platform usage and pro-CCP attitudes among users. By combining user journey data, survey research, and cross-platform comparisons, we uncover the extent to which TikTok and other platforms may influence user perceptions and behaviors in favor of the CCP.  The publication of this research precedes the delivery of oral arguments for TikTok Inc. and ByteDance Ltd. v. Merrick B. Garland, a federal court case that has subjected the TikTok algorithm to intensive new scrutiny. As detailed in the DOJ’s response to TikTok’s lawsuit, “covert content manipulation” is an area of legal interest for the DOJ, not to mention its relevance to the broader U.S. intelligence and national security community. That said, within the DOJ response it is noted that definitively proving covert content manipulation by the Chinese government remains a challenge. As FBI Director Wray testified to in multiple hearings, “[t]his sort of manipulation of the algorithm would be difficult to detect…" 1 This research gap sets the stage for our findings, which, while not definitive proof of state orchestration, present compelling and strong circumstantial evidence of TikTok’s covert content manipulation.

EXECUTIVE SUMMARY  In December 2023, the Network Contagion Research Institute (NCRI) published an initial report that found a strong possibility of content on TikTok being either amplified or suppressed based on its alignment with the interests of the Chinese Government. The report concluded with a warning: “should future research find that TikTok users exhibit attitudes and assessments of world events aligned with these information distortions, democracies will need to consider appropriate countermeasures to protect information integrity and mitigate potential real-world impacts.” These findings underscored the urgency of investigating the specific mechanisms and broader implications of potential algorithmic manipulations. While our initial study shed light on the potential for content manipulation on TikTok, it did not explore whether specific moderation algorithms or practices are used to suppress topics sensitive to the Chinese Communist Party (CCP). Moreover, it did not compare the nature and impact of pro- and anti-CCP content across other major social media platforms like Instagram and YouTube. This current report addresses these gaps by providing a more comprehensive analysis of TikTok's moderation practices, examining the nature and prevalence of CCP-sensitive content, and evaluating how different platforms handle such content. Furthermore, this study explores the association between social media platform usage and pro-CCP attitudes among users. By combining user journey data, survey research, and cross-platform comparisons, we uncover the extent to which TikTok and other platforms may influence user perceptions and behaviors in favor of the CCP.  The publication of this research precedes the delivery of oral arguments for TikTok Inc. and ByteDance Ltd. v. Merrick B. Garland, a federal court case that has subjected the TikTok algorithm to intensive new scrutiny. As detailed in the DOJ’s response to TikTok’s lawsuit, “covert content manipulation” is an area of legal interest for the DOJ, not to mention its relevance to the broader U.S. intelligence and national security community. That said, within the DOJ response it is noted that definitively proving covert content manipulation by the Chinese government remains a challenge. As FBI Director Wray testified to in multiple hearings, “[t]his sort of manipulation of the algorithm would be difficult to detect…" 1 This research gap sets the stage for our findings, which, while not definitive proof of state orchestration, present compelling and strong circumstantial evidence of TikTok’s covert content manipulation.

EXECUTIVE SUMMARY  In December 2023, the Network Contagion Research Institute (NCRI) published an initial report that found a strong possibility of content on TikTok being either amplified or suppressed based on its alignment with the interests of the Chinese Government. The report concluded with a warning: “should future research find that TikTok users exhibit attitudes and assessments of world events aligned with these information distortions, democracies will need to consider appropriate countermeasures to protect information integrity and mitigate potential real-world impacts.” These findings underscored the urgency of investigating the specific mechanisms and broader implications of potential algorithmic manipulations. While our initial study shed light on the potential for content manipulation on TikTok, it did not explore whether specific moderation algorithms or practices are used to suppress topics sensitive to the Chinese Communist Party (CCP). Moreover, it did not compare the nature and impact of pro- and anti-CCP content across other major social media platforms like Instagram and YouTube. This current report addresses these gaps by providing a more comprehensive analysis of TikTok's moderation practices, examining the nature and prevalence of CCP-sensitive content, and evaluating how different platforms handle such content. Furthermore, this study explores the association between social media platform usage and pro-CCP attitudes among users. By combining user journey data, survey research, and cross-platform comparisons, we uncover the extent to which TikTok and other platforms may influence user perceptions and behaviors in favor of the CCP.  The publication of this research precedes the delivery of oral arguments for TikTok Inc. and ByteDance Ltd. v. Merrick B. Garland, a federal court case that has subjected the TikTok algorithm to intensive new scrutiny. As detailed in the DOJ’s response to TikTok’s lawsuit, “covert content manipulation” is an area of legal interest for the DOJ, not to mention its relevance to the broader U.S. intelligence and national security community. That said, within the DOJ response it is noted that definitively proving covert content manipulation by the Chinese government remains a challenge. As FBI Director Wray testified to in multiple hearings, “[t]his sort of manipulation of the algorithm would be difficult to detect…" 1 This research gap sets the stage for our findings, which, while not definitive proof of state orchestration, present compelling and strong circumstantial evidence of TikTok’s covert content manipulation.

This is one of many short video segments which will be added to the Digital Tipping Point (DTP) archive. Thanks to Thomas King, a writer for Linux.com and LXer, for doing the rough editing for this series of interview segments! This series of 11 video segments features Brazilian entreprenuer Marcelo Marques, the prinicpal of Brazilian network security and training company 4Linux. He is also the principal of LPI Brazil, an international training and certification company. This footage was shot on the premises of Marcelo's company, called 4Linux, in Sao Paulo, Brazil. The shoot starts while the afternoon sun is declining behind Marcelo. The last few segments are a bit darker than we would have liked, but the audio is good throughout, and Marcelo is such an engaging character that you will want to stick with his interview to the end. In segment 08 (120~008), Marcelo talks about the operations of 4Linux. He says that he is good at marketing, but not so good at operations, and so he hired Rodolfo Gobbi, an executive with Ciclades, a large Brazilian company, to act as CEO of 4Linux. They hope to grow their sales 43% for 2004 over 2003. He thinks that teenagers will be a source of growth for Linux. He thinks that Linux has a coolness factor in Brazil. Teenagers hold Linux developers in high esteem. He says that Microsoft inadvertently helps his business, for example, by prosecuting its customers through the BSA and fining them lots of money. In segment 09 (120~009), Marcelo says that Microsoft is going to put up a big fight to stop Linux on the desktop. He says that Linux is already strong in other areas, like embedded Linux and servers, but the big challenge will be the desktop. This footage is our raw rough-cut footage. It lacks transitions, music, special effectsor finish rendering. It is our "source code". Please feel free to rip, mix and burn this footage consistent with our Creative Commons license as disclosed on this page. All of the segments of this set of Marcelo's interviews can be found here: http://www.archive.org/details/e-dv120_sp_32_marcelo_marques_4linux_lpi_brazil_001.ogg (segment 01) http://www.archive.org/details/e-dv120_sp_32_marcelo_marques_4linux_lpi_brazil_002.ogg (segment 02) http://www.archive.org/details/e-dv120_sp_32_marcelo_marques_4linux_lpi_brazil_003.ogg (segment 03) http://www.archive.org/details/e-dv120_sp_32_marcelo_marques_4linux_lpi_brazil_004.ogg (segment 04) http://www.archive.org/details/e-dv120_sp_32_marcelo_marques_4linux_lpi_brazil_005.ogg (segment 05) http://www.archive.org/details/e-dv120_sp_32_marcelo_marques_4linux_lpi_brazil_006.ogg (segment 06 http://www.archive.org/details/e-dv120_sp_32_marcelo_marques_4linux_lpi_brazil_007.ogg (segment 07) http://www.archive.org/details/e-dv120_sp_32_marcelo_marques_4linux_lpi_brazil_008.ogg (segment 08) http://www.archive.org/details/e-dv120_sp_32_marcelo_marques_4linux_lpi_brazil_001.ogg (segment 09) http://www.archive.org/details/e-dv121_sp_33_marcelo_marques_4linux_lpi_brazil_002.ogg (segment 10) http://www.archive.org/details/e-dv121_sp_33_marcelo_marques_4linux_lpi_brazil_002.ogg (segment 11) If you like this segment, please consider typing up a summary for it and emailing that summary to Christian Einfeldt at [email protected]. Your work will be credited and posted on this page. The DTP will be many, many films created by the global open source video community about how open source is changing their lives. We, the DTP crew, are submitting this footage for anyone to rip, mix, and burn under the Creative Commons Attribute - ShareAlike license. We welcome edits, transcriptions, graphics, music, and animation contributions to the film. Please send a link for any contributions to Christian Einfeldt at [email protected]. Or, if you would like to contribute by directly transcribing this particular video segment, you can do so by going here: http://digitaltippingpoint.com/wiki/index.php/Tape_120 and typing the audio as you hear it into the wiki. Please be sure to add the transcription for this segment under: Segment 009, marcelo Marques You can find other ways to contribute by going to our wiki front page here: http://digitaltippingpoint.com/wiki/index.php/Main_Page Thanks for viewing our video!

This item represents a case in PACER, the U.S. Government's website for federal case data. This information is uploaded quarterly. To see our most recent version please use the source url parameter, linked below. To see the canonical source for this data, please consult PACER directly.

Digital terrain modeling (DTM) is concerned with the digital storage, analysis, and display of surface configuration data (x,y,z) for topographic mapping. The field of DTM is relatively new and growing. Many methods of DTM have been studied and applied to real problems, but two are of concern here: the uniform rectangular grid (URG) and the triangulated irregular network (TIN) methods. This technical note presents preliminary evaluation methodology that will be used to compare the TIN and URG methods in the specific context of Marine Corps ground combat operations.

Digital terrain modeling (DTM) is concerned with the digital storage, analysis, and display of surface configuration data (x,y,z) for topographic mapping. The field of DTM is relatively new and growing. Many methods of DTM have been studied and applied to real problems, but two are of concern here: the uniform rectangular grid (URG) and the triangulated irregular network (TIN) methods. This technical note presents preliminary evaluation methodology that will be used to compare the TIN and URG methods in the specific context of Marine Corps ground combat operations.

A Geographic Data Structure is developed which permits the digital acquisition, storage and application of data sets of three or more dimensions, in particular topographic terrains. The Structure consists of a Triangulated Irregular Network and higher-level structures. Comparisons with systems based on regular grids reveal that the Geographic Data Structure is advantageous in terms of storage space needed, computer time, and accuracy, in the acquisition, storage and application of digital terrain.