Estimating the compression quality of an image by analysing blocking artefacts

Abstract: Determining the compression quality of an image is important for photo forensics and image enhancement algorithms. Unfortunately, there are a number of issues involved in determining the compression quality of an image from its metadata or quantization tables. A compression quality estimation algorithm based on visual inspection of detected compression artefacts is presented. This method detects and extracts feature samples around compression block corners. These feature samples are then pre-filtered to enhance the discontinuities produced by compression artefacts. The feature samples are then classified using a constricted Neural Network. The local quality estimations are then combined using robust statistics to estimate the maximum likelihood compression quality. This method was shown to accurately estimate the compression quality of an image without prior knowledge of the original uncompressed image

ISC/OSI Journal Authors Survey Report

On behalf of the Joint Information Systems Committee (JISC) and the Open Society Institute (OSI) a survey of journal authors has been carried out by Key Perspectives Ltd. The terms of reference were to poll a cohort of authors who had published on an open access basis and another cohort of authors who had published their work in conventional journals without making the article available on open access. The survey’s aims were to investigate the authors’ awareness of new open access possibilities, the ease of identification of and submission to open access outlets, their experiences of publishing their work in this way, their concerns about any implications open access publishing may have upon their careers, and the reasons why (or not) they chose to publish through an open access outlet

ETDB-Caltech: a blockchain-based distributed public database for electron tomography

Three-dimensional electron microscopy techniques like electron tomography provide valuable insights into cellular structures, and present significant challenges for data storage and dissemination. Here we explored a novel method to publicly release more than 11,000 such datasets, more than 30 TB in total, collected by our group. Our method, based on a peer-to-peer file sharing network built around a blockchain ledger, offers a distributed solution to data storage. In addition, we offer a user-friendly browser-based interface, https://etdb.caltech.edu, for anyone interested to explore and download our data. We discuss the relative advantages and disadvantages of this system and provide tools for other groups to mine our data and/or use the same approach to share their own imaging datasets

Music genre classification based on dynamical models

This paper studies several alternatives to extract dynamical features from hidden Markov Models (HMMs) that are meaningful for music genre supervised classification. Songs are modelled using a three scale approach: a first stage of short term (milliseconds) features, followed by two layers of dynamical models: a multivariate AR that provides mid term (seconds) features for each song followed by an HMM stage that captures long term (song) features shared among similar songs. We study from an empirical point of view which features are relevant for the genre classification task. Experiments on a database including pieces of heavy metal, punk, classical and reggae music illustrate the advantages of each set of features

Scaffolding reflective inquiry - enabling why-questioning while e-learning

This paper presents some theoretical and interdisciplinary perspectives that might inform the design and development of information and communications technology (ICT) tools to support reflective inquiry during e-learning. The role of why-questioning provides the focus of discussion and is guided by literature that spans critical thinking, inquiry-based and problem-based learning, storytelling, sense-making, and reflective practice, as well as knowledge management, information science, computational linguistics and automated question generation. It is argued that there exists broad scope for the development of ICT scaffolding targeted at supporting reflective inquiry duringe-learning. Evidence suggests that wiki-based learning tasks, digital storytelling, and e-portfolio tools demonstrate the value of accommodating reflective practice and explanatory content in supporting learning; however, it is also argued that the scope for ICT tools that directly support why-questioning as a key aspect of reflective inquiry is a frontier ready for development

Design and Implementation of Views: Isolated Perspectives of a File System

We present Views, a file system architecture that provides isolation between system components for the purposes of access control, regulatory compliance, and sandboxing. Views allows for discrete I/O entities, such as users, groups, or processes, to have a logically complete yet fully isolated perspective (view) of the file system. This ensures that each entity’s file system activities only modify that entity’s view of the file system, but in a transparent fashion that does not limit or restrict the entity’s functionality. Views can therefore be used to monitor system activity based on user accounts for access control (as required by federal regulations such as HIPAA), provide a reliable sandbox for arbitrary applications without inducing any noticeable loss in performance, and enable traditional snapshotting functionality by manipulating and transplanting views as snapshots in time. Views’ architecture is designed to be file system independent, extremely easy to use and manage, and flexible in defining isolation and sharing polices. Our implementation of Views is built on ext3cow, which additionally provides versioning capabilities to all entities. Benchmarking results show that the performance of Views is nearly identical to other traditional file systems such as ext3

Analysis of Knowledge Management and E-Learning Integration Models

AbstractThe development of knowledge management (KM) and e-learning (EL) naturally brings both disciplines closer and encourages integration. There are several models that offer possible ways of such integration. With the goal to develop practically applicable integration solution for specific organization, existing integration models are analysed in this paper. The main criterion for analysis is application of integration model in the enterprise. Model analysis shows several different theoretical approaches for integration that are tied to specific goals and needs of organization. The more general approach is to base integration on common ground, which is identified as learning

Design and Implementation of Views: Isolated Perspectives of a File System for Regulatory Compliance

We present Views, a file system architecture designed to meet the role-based access control (RBAC) requirement of federal regulations, such as those in HIPAA. Views allows for discrete IO entities, such as users, groups or processes, to have a logically complete but isolated perspective of the file system. Entities may perform IO using the standard system call interface without affecting the views of other entities. Views is designed to be file system independent, extremely easy to use and manage, and flexible in defining isolation and sharing polices. Our implementation of Views is built on ext3cow, which additionally provides versioning capabilities to all entities. Preliminary results show the performance of Views is comparable with other traditional disk file systems.The Johns Hopkins Universit

Designing Light Filters to Detect Skin Using a Low-powered Sensor

Detection of nudity in photos and videos, especially prior to uploading to the internet, is vital to solving many problems related to adolescent sexting, the distribution of child pornography, and cyber-bullying. The problem with using nudity detection algorithms as a means to combat these problems is that: 1) it implies that a digitized nude photo of a minor already exists (i.e., child pornography), and 2) there are real ethical and legal concerns around the distribution and processing of child pornography. Once a camera captures an image, that image is no longer secure. Therefore, we need to develop new privacy-preserving solutions that prevent the digital capture of nude imagery of minors. My research takes a first step in trying to accomplish this long-term goal: In this thesis, I examine the feasibility of using a low-powered sensor to detect skin dominance (defined as an image comprised of 50% or more of human skin tone) in a visual scene. By designing four custom light filters to enhance the digital information extracted from 300 scenes captured with the sensor (without digitizing high-fidelity visual features), I was able to accurately detect a skin dominant scene with 83.7% accuracy, 83% precision, and 85% recall. The long-term goal to be achieved in the future is to design a low-powered vision sensor that can be mounted on a digital camera lens on a teen\u27s mobile device to detect and/or prevent the capture of nude imagery. Thus, I discuss the limitations of this work toward this larger goal, as well as future research directions