Is Simpler Always Better? Consumer Evaluations of Front-of-Package Nutrition Symbols

Consumers of packaged goods products in the United States recently have faced an onslaught of front-of-package (FOP) nutrition symbols and icons, including the controversial “Smart Choices” single summary indicator. In a between-subjects experiment with 520 adult consumers, the authors compare effects of the Smart Choices (SC) icon, the more complex Traffic Light–Guideline Daily Amounts (TLGDAs) icon, and a no-FOP icon control for a nutritionally moderate food that qualifies for the SC icon. Drawing from principles of heuristic processing and halo effects, the authors predict and find that the SC icon can lead to positive (and potentially misleading) nutrient evaluations and product healthfulness when compared with the TL-GDA icon or no-FOP icon control. When the Nutrition Facts Panel is not available, the TL-GDA icon results in substantially greater nutrition accuracy scores than with the SC icon or control. The authors also find that nutrition consciousness is more likely to moderate effects related to the Nutrition Facts Panel than the FOP nutrition icon information. Implications are offered for public health officials, nutrition researchers, and food manufacturers, as the Food and Drug Administration considers FOP nutrition alternatives for use in the United States

Subband decomposition techniques for adaptive channel equalisation

In this contribution, the convergence behaviour of the adaptive linear equaliser based on subband decomposition technique is investigated. Two different subband-based linear equalisers are employed, with the aim of improving the equaliser's convergence performance. Simulation results over three channel models having different spectral characteristic are presented. Computer simulations indicate that subband-based equalisers outperform the conventional fullband linear equaliser when channel exhibit severe spectral dynamic. Convergence rate of subband equalisers are governed by the slowest subband, whereby different convergence behaviour in each individual subband is observed. Finally, the complexity of fullband and subband equalisers is discussed

Improving Malware Detection Accuracy by Extracting Icon Information

Detecting PE malware files is now commonly approached using statistical and machine learning models. While these models commonly use features extracted from the structure of PE files, we propose that icons from these files can also help better predict malware. We propose an innovative machine learning approach to extract information from icons. Our proposed approach consists of two steps: 1) extracting icon features using summary statics, histogram of gradients (HOG), and a convolutional autoencoder, 2) clustering icons based on the extracted icon features. Using publicly available data and by using machine learning experiments, we show our proposed icon clusters significantly boost the efficacy of malware prediction models. In particular, our experiments show an average accuracy increase of 10% when icon clusters are used in the prediction model.Comment: Full version. IEEE MIPR 201

ICON: It's Not Just for Corrections Anymore, Data Download, Iowa Department of Corrections, January 2010

The Iowa Correctional Offender Network (ICON) is a data collection system that was first deployed in community corrections in 2000 after two years of planning, and was integrated with the institutions in 2004. The purpose of ICON is to collect and organize the data necessary to make informed decisions

Ice Bear: The Cultural History of an Arctic Icon by Michael Engelhard

Review of Michael Engelhard\u27s Ice Bear: The Cultural History of an Arctic Icon

Implementation and performance analysis of a QoS-aware TFRC mechanism

This paper deals with the improvement of transport protocol behaviour over the DiffServ Assured Forwarding (AF)class. The Assured Service (AS) provides a minimum throughput guarantee that classical congestion control mechanisms, like window-based in TCP or equation-based in TCP-Friendly Rate Control (TFRC), are not able to use efficiently. In response, this paper proposes a performance analysis of a QoS aware congestion control mechanism, named gTFRC, which improves the delivery of continuous streams. The gTFRC (guaranteed TFRC) mechanism has been integrated into an Enhanced Transport Protocol (ETP) that allows protocol mechanisms to be dynamically managed and controlled. After comparing a ns-2 simulation and our implementation of the basic TFRC mechanism, we show that ETP/gTFRC extension is able to reach a minimum throughput guarantee whatever the flow’s RTT and target rate (TR) and the network provisioning conditions