447865
Middleware support for embedded software with multiple QoS properties for ubiquitous computing environments
Ubiquitous application software usually has multiple QoS requirements, such as situation-awareness, real-time, and security, which make the application software development complicated. In this paper, an approach to supporting multiple QoS properties in application software using middleware is presented. Our reconfigurable context-sensitive middleware (RCSM), which provides situation-awareness support to the application software, is expanded to support more QoS by using aspect-oriented software development techniques. In the expanded RCSM, each QoS is processed through a set of aspect components. The application developers specify the QoS requirements in a specification file, which is in turn compiled to configure the corresponding aspect components. Being associated with certain application objects, the QoS aspect components enforce the QoS requirements according to the specification during run-time. In this paper, security, in addition to situation-awareness, is used as an example to illustrate our approach.
18364887
An approach to enhancing mobile applications with situation-awareness capabilities
In ubiquitous computing environments, mobile applications reside in devices that move arbitrarily and communicate with each other through wireless means. They are presented with fast changing situations, such as the location variation, service availability change, and resource fluctuation. Under these circumstances, situation-awareness is a desirable feature for mobile applications. Being situation-aware, a mobile application is capable of detecting situation changes and responding to it on-the-fly without bothering the user all the times. This paper presents an approach to enhancing mobile applications with situation-aware capabilities using middleware service.
13186882
Distributed constraint satisfaction, restricted recombination, and genetic protocols
In this paper, we present four genetic protocols for solving randomly generated distributed constraint satisfaction problems. These genetic protocols are based on an evolutionary paradigm known as a society of hill-climbers (SoHC) and are thus referred to as genetic SoHCs (GSoHCs). The difference between the SoHC and the GSoHCs is that each of the GSoHCs use a distributed restricted recombination operator. We compare the SoHC and GSoHC protocols on a test suite of 400 randomly generated distributed constraint satisfaction problems (DisCSPs) that are composed of asymmetric constraints (referred to as DisACSPs). In a second experiment, we compare the best performing GSoHC and the SoHC on an additional 1100 randomly generated DisACSPs in order to compare their performances across the phase transition. Our results show that all of the GSoHCs dramatically outperform the SoHC protocol even at the phase transition where, on average, the most difficult DisACSPs reside.
14934450
Combining Statistical and Knowledge-Based Spoken Language Understanding in Conditional Models
Spoken Language Understanding (SLU) addresses the problem of extracting semantic meaning conveyed in an utterance. The traditional knowledge-based approach to this problem is very expensive --- it requires joint expertise in natural language processing and speech recognition, and best practices in language engineering for every new domain. On the other hand, a statistical learning approach needs a large amount of annotated data for model training, which is seldom available in practical applications outside of large research labs. A generative HMM/CFG composite model, which integrates easy-to-obtain domain knowledge into a data-driven statistical learning framework, has previously been introduced to reduce data requirement. The major contribution of this paper is the investigation of integrating prior knowledge and statistical learning in a conditional model framework. We also study and compare conditional random fields (CRFs) with perceptron learning for SLU. Experimental results show that the conditional models achieve more than 20% relative reduction in slot error rate over the HMM/CFG model, which had already achieved an SLU accuracy at the same level as the best results reported on the ATIS data.
16463784
Privacy Preserving Data Generation for Database Application Performance Testing
Synthetic data plays an important role in software testing. In this paper, we initiate the study of synthetic data generation models for the purpose of application software performance testing. In particular, we will discuss models for protecting privacy in synthetic data generations. Within this model, we investigate the feasibility and techniques for privacy preserving synthetic database generation that can be used for database application performance testing. The methodologies that we will present will be useful for general privacy preserving software performance testing.
5135938
Privacy preserving database application testing
Traditionally, application software developers carry out their tests on their own local development databases. However, such local databases usually have only a small number of sample data and hence cannot simulate satisfactorily a live environment, especially in terms of performance and scalability testing. On the other hand, the idea of testing applications over live production databases is increasingly problematic in most situations primarily due to the fact that such use of live production databases has the potential to expose sensitive data to an unauthorized tester and to incorrectly update information in the underlying database. In this paper, we investigate techniques to generate mock databases for application software testing without revealing any confidential information from the live production databases. Specifically, we will design mechanisms to create the deterministic rule set R, non-deterministic rule set N R, and statistic data set S for a live production database. We will then build a security Analyzer which will process the triplet <R',N R',S'> together with security requirements (security policy) and output a new triplet <R',N R',S'> The security Analyzer will guarantee that no confidential information could be inferred from the new triplet <R',N R',S'> The mock database generated from this new triplet can simulate the live environment for testing purpose, while maintaining the privacy of data in the original database.
39368933
Improved QIM Strategies for Gaussian Watermarking
This paper revisits the problem of watermarking a Gaussian host, where the embedder and attacker are subject to mean-squared distortion constraints. The worst (nonadditive) attack and unconstrained capacity have been identified in previous work. Here we constrain the encoding function to lie in a given family of encoding functions — such as spread-spectrum or fixed-dimensional Quantization Index Modulation (QIM), with or without time-sharing, with or without external dithering. This gives rise to the notion of constrained capacity. Several such families are considered in this paper, and the one that is best under the worst attack is identified for each admissible value of the watermark-to-noise ratio (WNR) and the noise-to-host ratio (NHR). With suitable improvements, even scalar QIM can outperform any (improved) spread-spectrum scheme, for any value of WNR and NHR. The remaining gap to unconstrained capacity can be bridged using higher-dimensional lattice QIM.
21455681
A layered reference model of the brain
Based on the advances of research in cognitive informatics and related fields, this paper attempts to develop a layered reference model of the brain that explains the functional mechanisms and cognitive processes of the natural intelligence. A variety of life functions and cognitive processes have been identified in cognitive informatics, cognitive science, neuropsychology, and neurophilosophy. In order to formally and rigorously describe a comprehensive and coherent set of mental processes and their relationships, an integrated reference model of the brain is established, which encompasses 37 cognitive processes at six layers known as the sensation, memory, perception, action, meta and higher cognitive layers from bottom up. The reference model of the brain may be applied to explain a wide range of physiological, psychological, and cognitive phenomena in cognitive informatics, particularly relationships between the inherited and the acquired life functions, as well as the subconscious and conscious cognitive processes.