dARTMAP: A Neural Network for Fast Distributed Supervised Learning

Distributed coding at the hidden layer of a multi-layer perceptron (MLP) endows the network with memory compression and noise tolerance capabilities. However, an MLP typically requires slow off-line learning to avoid catastrophic forgetting in an open input environment. An adaptive resonance theory (ART) model is designed to guarantee stable memories even with fast on-line learning. However, ART stability typically requires winner-take-all coding, which may cause category proliferation in a noisy input environment. Distributed ARTMAP (dARTMAP) seeks to combine the computational advantages of MLP and ART systems in a real-time neural network for supervised learning, An implementation algorithm here describes one class of dARTMAP networks. This system incorporates elements of the unsupervised dART model as well as new features, including a content-addressable memory (CAM) rule for improved contrast control at the coding field. A dARTMAP system reduces to fuzzy ARTMAP when coding is winner-take-all. Simulations show that dARTMAP retains fuzzy ARTMAP accuracy while significantly improving memory compression.National Science Foundation (IRI-94-01659); Office of Naval Research (N00014-95-1-0409, N00014-95-0657

Use of context-awareness in mobile peer-to-peer networks

Mobile ad-hoc network are an emerging research field due to the potential range of applications that they support and for the problems they present due to their dynamic nature. Peer-to-peer is an example of a class of applications that have recently been deployed on top of ad-hoc networks. In this paper we propose an approach based on context-awareness to allow peer-to-peer applications to exploit information on the underlying network context to achieve better performance and better group organization. Information such as availability of resources, battery power, services in reach and relative distances can be used to improve the routing structures of the peer-to-peer network, thus reducing the routing overhead

Learning For Life: The Opportunity For Technology To Transform Adult Education - Part II: The Supplier Ecosystem

In fall 2014, Tyton Partners (formerly Education Growth Advisors), with support from the Joyce Foundation, conducted national research on the role and potential of instructional technology in the US adult education field. The objective was to understand the current state of the field with respect to technology readiness and the opportunities and challenges for increasing the use of technology-based instructional models within adult education. The initial publication in the series, "Part I: Interest in and Aptitude for Technology," focused on demand-side dynamics and addressed adult education administrators' and practitioners' perspectives on the role and potential of technology to support their students' needs and objectives. This second publication, "Part 2: The Supplier Ecosystem," highlights market composition and supply-side dynamics, instructional resource use, and opportunities for innovation

Smart PIN: utility-based replication and delivery of multimedia content to mobile users in wireless networks

Next generation wireless networks rely on heterogeneous connectivity technologies to support various rich media services such as personal information storage, file sharing and multimedia streaming. Due to users’ mobility and dynamic characteristics of wireless networks, data availability in collaborating devices is a critical issue. In this context Smart PIN was proposed as a personal information network which focuses on performance of delivery and cost efficiency. Smart PIN uses a novel data replication scheme based on individual and overall system utility to best balance the requirements for static data and multimedia content delivery with variable device availability due to user mobility. Simulations show improved results in comparison with other general purpose data replication schemes in terms of data availability

Broadcasting in Prefix Space: P2P Data Dissemination with Predictable Performance

A broadcast mode may augment peer-to-peer overlay networks with an efficient, scalable data replication function, but may also give rise to a virtual link layer in VPN-type solutions. We introduce a simple broadcasting mechanism that operates in the prefix space of distributed hash tables without signaling. This paper concentrates on the performance analysis of the prefix flooding scheme. Starting from simple models of recursive $k$-ary trees, we analytically derive distributions of hop counts and the replication load. Extensive simulation results are presented further on, based on an implementation within the OverSim framework. Comparisons are drawn to Scribe, taken as a general reference model for group communication according to the shared, rendezvous-point-centered distribution paradigm. The prefix flooding scheme thereby confirmed its widely predictable performance and consistently outperformed Scribe in all metrics. Reverse path selection in overlays is identified as a major cause of performance degradation.Comment: final version for ICIW'0

Multi-Stage Protection Using Pixel Selection Technique for Enhancing Steganography

Steganography and data security are extremely important for all organizations. This research introduces a novel stenographic method called multi-stage protection using the pixel selection technique (MPPST). MPPST is developed based on the features of the pixel and analysis technique to extract the pixel's characteristics and distribution of cover-image. A pixel selection technique is proposed for hiding secret messages using the feature selection method. The secret file is distributed and embedded randomly into the stego-image to make the process of the steganalysis complicated.  The attackers not only need to deter which pixel values have been selected to carry the secret file, they also must rearrange the correct sequence of pixels. MPPST generates a complex key that indicates where the encrypted elements of the binary sequence of a secret file are. The analysis stage undergoes four stages, which are the calculation of the peak signal-to-noise ratio, mean squared error, histogram analysis, and relative entropy. These four stages are used to demonstrate the characteristics of the cover image. To evaluate the proposed method, MPPST is compared to the standard technique of Least Significant Bit (LSB) and other algorithms from the literature. The experimental results show that MPPST outperforms other algorithms for all instances and achieves a significant security enhancement