5741503
A new scheme on privacy-preserving data classification
We address privacy-preserving classification problem in a distributed system. Randomization has been the approach proposed to preserve privacy in such scenario. However, this approach is now proven to be insecure as it has been discovered that some privacy intrusion techniques can be used to reconstruct private information from the randomized data tuples. We introduce an algebraic-technique-based scheme. Compared to the randomization approach, our new scheme can build classifiers more accurately but disclose less private information. Furthermore, our new scheme can be readily integrated as a middleware with existing systems.
6827646
Design and implementation of QoS-provisioning system for voice over IP
In this paper, we address issues in implementing voice over IP (VoIP) services in packet switching networks. VoIP has been identified as a critical real-time application in the network QoS research community and has been implemented in commercial products. To provide competent quality of service for VoIP systems comparable to traditional PSTN systems, a call admission control (CAC) mechanism has to be introduced to prevent packet loss and over-queuing. Several well-designed CAC mechanisms, such as the site-utilization-based CAC-and the link-utilization-based CAC mechanisms have been in place. However, the existing commercial VoIP systems have not been able to adequately apply and support these CAC mechanisms and, hence, have been unable to provide QoS guarantees to voice over IP networks. We have designed and implemented a QoS-provisioning system that can be seamlessly integrated with the existing VoIP systems to overcome their weakness in offering QoS guarantees. A practical implementation of our QoS-provisioning system has been realized.
8639082
Delay Analysis in Temperature-Constrained Hard Real-Time Systems with General Task Arrivals
In this paper, we study temperature-constrained hard real-time systems, where real-time guarantees must be met without exceeding safe temperature levels within the processor. Dynamic speed scaling is one of the major techniques to manage power so as to maintain safe temperature levels. As example, we adopt a simple reactive speed control technique in our work. We design a methodology to perform delay analysis for general task arrivals under reactive speed control with first-in-first-out (FIFO) scheduling and static-priority (SP) scheduling. As a special case, we obtain a close-form delay formula for the leaky-bucket task arrival model. Our data show how simple reactive speed control can decrease the delay of tasks compared with any constant-speed scheme
26802568
Isotropic processing for gradient estimation
This paper concerns the influence of edge direction on the estimation of edge contrast and orientation. We show that the gradient estimated using radial filters is not affected by edge orientation. For non-radial filters the gradient can be affected by edge orientation. For instance, we find that the estimated edge orientation using a non-radial filter may be biased, even if the signal is noise-free. However, there are non-radial filters for which gradient is unaffected by edge orientation as in the case of radial filters. The properties of these functions are given in this paper. The results are illustrated by the study of the Canny, Deriche, and Shen & Castan detectors. We take into account discretization errors. These results give a clear indication of the effect of the rotation invariance property of an edge detector on its response, thus providing a more precise meaning for this property in edge detection.
6812524
Stochastic Analysis of Lexical and Semantic Enhanced Structural Language Model
In this paper, we present a directed Markov random field model that integrates trigram models, structural language models (SLM) and probabilistic latent semantic analysis (PLSA) for the purpose of statistical language modeling. The SLM is essentially a generalization of shift-reduce probabilistic push-down automata thus more complex and powerful than probabilistic context free grammars (PCFGs). The added context-sensitiveness due to trigrams and PLSAs and violation of tree structure in the topology of the underlying random field model make the inference and parameter estimation problems plausibly intractable, however the analysis of the behavior of the lexical and semantic enhanced structural language model leads to a generalized inside-outside algorithm and thus to rigorous exact EM type re-estimation of the composite language model parameters.
11079160
An Anonymous Endorsement System
The expression of one’s opinion through endorsement is one of the simplest methods of democratic participation. The result of an endorsement can be used to evaluate whether a certain subject should deserve a higher attention. In some cases, the endorsers desire privacy protection. However, conventional paper-based endorsement systems provide neither convenience nor well privacy protection for the endorsers. In addition, current electronic anonymous voting schemes are unsuitable for anonymous endorsement. This motivates us to develop an anonymous endorsement system that can be realized on computer networks. The proposed system satisfies completeness, soundness, privacy, unreusability, eligibility, and verifiability. In practice, the proposed system can be integrated with the conventional paper-based endorsement system.
16153164
Rapid Benchmarking for Semantic Web Knowledge Base Systems
We present a method for rapid development of benchmarks for Semantic Web knowledge base systems. At the core, we have a synthetic data generation approach for OWL that is scalable and models the real world data. The data-generation algorithm learns from real domain documents and generates benchmark data based on the extracted properties relevant for benchmarking. We believe that this is important because relative performance of systems will vary depending on the structure of the ontology and data used. However, due to the novelty of the Semantic Web, we rarely have sufficient data for benchmarking. Our approach helps overcome the problem of having insufficient real world data for benchmarking and allows us to develop benchmarks for a variety of domains and applications in a very time efficient manner. Based on our method, we have created a new Lehigh BibTeX Benchmark and conducted an experiment on four Semantic Web knowledge base systems. We have verified our hypothesis about the need for representative data by comparing the experimental result to that of our previous Lehigh University Benchmark. The difference in both experiments has demonstrated the influence of ontology and data on the capability and performance of the systems and thus the need of using a representative benchmark for the intended application of the systems.
9413098
A rotation invariant printed Chinese character recognition system
Abstract In this paper, we present an approach to construct an optical character recognition (OCR) system for recognizing rotated printed Chinese characters. Our system includes preprocessing, feature extraction, candidates selection, and target character recognition. The proposed system has a three-stage structure designed mainly to reduce the time complexity in the recognition process. Our goal is to recognize the complete set of frequently used 13 053 printed Chinese characters with arbitrary orientations. The overall recognition rate of our system reaches 97.4%.