From Print to Pixel: Visual Media and The Fate of Nonviolent Social Movement Activism

In order to be heard or seen, nonviolent social movements (NVSMs) require an audience. News images of nonviolent protests become the means through which awareness of social movements is created. Comparative historical and semiotic analysis of journalistic images demonstrates that violence is a prominent theme within news coverage of nonviolent struggles. Four types of violence within nonviolence are identified: state violence, third-party violence, self-inflicted violence and symbolic violence. The examination of news images of these four types of violence showed the different ways in which challengers and the state contest power in the public domain through the media, in both text and images. Various actors (the state, social movements, journalists, the audience) use news images to historicize and construct their narratives of unfolding events, as well as make transhistorical claims. In this process, they deliberately employ news images to advocate for their causes, align themselves with previous heroes of civil disobedience and play on the popular understandings of good and evil. While this project focuses on different types of media, they have affected their audiences in similar ways, providing the space not only to the state within which they emerged, but also to those who seek to reform the state, like all of the movements in this study did. The media are the environment within which images circulate and as such they influence who images reach and, to a lesser extent, what effect they may have on the viewers. The power of images lies in both their universality that connects them with their genealogical predecessors and their singularity that underscores the specific conditions in which they emerge, making the ultimate outcome of the protests uncertain. The dissertation contributes to the research on social movements, mass communication, conflict and social change. It also raises the question of how images can be analyzed and incorporated into sociological research

Analysis of Trade-offs in Fault-Tolerant Distributed Computing and Replicated Databases

This paper examines fundamental trade-offs in fault-tolerant distributed systems and replicated databases built over the Internet. We discuss interplays between consistency, availability, and latency which are in the very nature of globally distributed computer systems and also analyse their interconnection with durability and energy efficiency. In this paper we put forward an idea that consistency, availability, latency, durability and other properties need to be viewed as more continuous than binary in contrast to the well-known CAP/PACELC theorems. We compare different consistency models and highlight the role of the application timeout, replication factor and other settings that essentially determine the interplay between above properties. Our findings may be of interest to software engineers and system architects who develop Internet-scale distributed computer systems and cloud solutions

From Analysing Operating System Vulnerabilities to Designing Multiversion Intrusion-Tolerant Architectures

This paper analyses security problems of modern computer systems caused by vulnerabilities in their operating systems. Our scrutiny of widely used enterprise operating systems focuses on their vulnerabilities by examining the statistical data available on how vulnerabilities in these systems are disclosed and eliminated, and by assessing their criticality. This is done by using statistics from both the National Vulnerabilities database (NVD) and the Common Vulnerabilities and Exposures system (CVE). The specific technical areas the paper covers are the quantitative assessment of forever-day vulnerabilities, estimation of days-of-grey-risk, the analysis of the vulnerabilities severity and their distributions by attack vector and impact on security properties. In addition, the study aims to explore those vulnerabilities that have been found across a diverse range of operating systems. This leads us to analysing how different intrusion-tolerant architectures deploying the operating system diversity impact availability, integrity and confidentiality

Exploring Timeout As A Performance And Availability Factor Of Distributed Replicated Database Systems

A concept of distributed replicated data storages like Cassandra, HBase, MongoDB has been proposed to effectively manage the Big Data sets whose volume, velocity, and variability are difficult to deal with by using the traditional Relational Database Management Systems. Trade-offs between consistency, availability, partition tolerance, and latency are intrinsic to such systems. Although relations between these properties have been previously identified by the well-known CAP theorem in qualitative terms, it is still necessary to quantify how different consistency and timeout settings affect system latency. The paper reports results of Cassandra's performance evaluation using the YCSB benchmark and experimentally demonstrates how to read latency depends on the consistency settings and the current database workload. These results clearly show that stronger data consistency increases system latency, which is in line with the qualitative implication of the CAP theorem. Moreover, Cassandra latency and its variation considerably depend on the system workload. The distributed nature of such a system does not always guarantee that the client receives a response from the database within a finite time. If this happens, it causes so-called timing failures when the response is received too late or is not received at all. In the paper, we also consider the role of the application timeout which is the fundamental part of all distributed fault tolerance mechanisms working over the Internet and used as the main error detection mechanism here. The role of the application timeout as the main determinant in the interplay between system availability and responsiveness is also examined in the paper. It is quantitatively shown how different timeout settings could affect system availability and the average servicing and waiting time. Although many modern distributed systems including Cassandra use static timeouts it was shown that the most promising approach is to set timeouts dynamically at run time to balance performance, availability and improve the efficiency of the fault-tolerance mechanisms

Performance evaluation of various deployment scenarios of the 3-replicated Cassandra NoSQL cluster on AWS

A concept of distributed replicated NoSQL data storages Cassandra-like, HBase, MongoDB has been proposed to effectively manage Big Data set whose volume, velocity and variability are difficult to deal with by using the traditional Relational Database Management Systems. Tradeoffs between consistency, availability, partition tolerance and latency is intrinsic to such systems. Although relations between these properties have been previously identified by the well-known CAP and PACELC theorems in qualitative terms, it is still necessary to quantify how different consistency settings, deployment patterns and other properties affect system performance.This experience report analysis performance of the Cassandra NoSQL database cluster and studies the tradeoff between data consistency guaranties and performance in distributed data storages. The primary focus is on investigating the quantitative interplay between Cassandra response time, throughput and its consistency settings considering different single- and multi-region deployment scenarios. The study uses the YCSB benchmarking framework and reports the results of the read and write performance tests of the three-replicated Cassandra cluster deployed in the Amazon AWS. In this paper, we also put forward a notation which can be used to formally describe distributed deployment of Cassandra cluster and its nodes relative to each other and to a client application. We present quantitative results showing how different consistency settings and deployment patterns affect Cassandra performance under different workloads. In particular, our experiments show that strong consistency costs up to 22 % of performance in case of the centralized Cassandra cluster deployment and can cause a 600 % increase in the read/write requests if Cassandra replicas and its clients are globally distributed across different AWS Regions

Metal-insulator transition induced by 16O -18O oxygen isotope exchange in colossal negative magnetoresistance manganites

The effect of 16O-18O isotope exchange on the electric resistivity was studied for (La(1-y)Pr(y))0.7Ca0.3MnO3 ceramic samples. Depending on y, this mixed perovskite exhibited different types of low-temperature behavior ranging from ferromagnetic metal (FM) to charge ordered (CO) antiferromagnetic insulator. It was found that at y=0.75, the substitution of 16O by 18O results in the reversible transition from a FM to a CO insulator at zero magnetic field. The applied magnetic field (H >= 2 T) transformed the sample with 18O again to the metallic state and caused the increase in the FM transition temperature Tc of the 16O sample. As a result, the isotope shift of Tc at H = 2 T was as high as 63 K. Such unique sensitivity of the system to oxygen isotope exchange, giving rise even to the metal-insulator transition, is discussed in terms of the isotope dependence of the effective electron bandwidth which shifts the balance between the CO and FM phases.Comment: 5 pages (RevTeX), 2 eps figures included, to appear in J. Appl. Phys. 83, (1998

Improving the Accuracy of Software Reliability Modeling by Predicting the Number of Secondary Software Defects

Reliability assessment and prediction of the number of faults/defects is an important part of the software engineering process. Many software reliability models assume that all detected are removed with certainty and no new faults are introduced. However, the introduction of secondary faults during software updates has become quite common in software development practice, which can be explained by the enormous complexity of modern computer applications. In the paper we consider different scenarios of introducing secondary faults and how to predict number of such faults. Finally, we discuss how different SRGMs like Jelinski-Moranda, Exponential, Schick-Wolverton, Musa and Lipov models can be modified to account secondary faults in order to improve accuracy of software reliability prediction. We use an industrial case study to demonstrate applicability of the proposed approach. Our results show that considering secondary faults helped to considerably improve accuracy of software failure rate prediction