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Articles 1 - 22 of 22
Full-Text Articles in Engineering
Adaptive Weighing Of Context Models For Lossless Data Compression, Matthew V. Mahoney
Adaptive Weighing Of Context Models For Lossless Data Compression, Matthew V. Mahoney
Electrical Engineering and Computer Science Faculty Publications
Until recently the state of the art in lossless data compression was prediction by partial match (PPM). A PPM model estimates the next-symbol probability distribution by combining statistics from the longest matching contiguous contexts in which each symbol value is found. We introduce a context mixing model which improves on PPM by allowing contexts which are arbitrary functions of the history. Each model independently estimates a probability and confidence that the next bit of data will be 0 or 1. Predictions are combined by weighted averaging. After a bit is arithmetic coded, the weights are adjusted along the cost gradient …
Secure Combinatorial Optimization Using Dfs-Based Variable Elimination, Marius C. Silaghi, Adrian Petcu, Boi Faltings
Secure Combinatorial Optimization Using Dfs-Based Variable Elimination, Marius C. Silaghi, Adrian Petcu, Boi Faltings
Electrical Engineering and Computer Science Faculty Publications
It is known that, in general, Constraint Optimization Problems (COP) are NP-hard. Existing arithmetic circuits for secure protocols solving such problems are exponential in the number of variables, $n$. Recently a combinatorial optimization algorithm was proposed whose cost is exponential only in a parameter of the Depth First Search tree (DFS) of the constraint graph, smaller than $n$. We show how to construct an arithmetic circuit with this property and solving any COP. For forest constraint graphs, this leads to a linear cost secure solver.
A Chain-Type Wireless Sensor Network For Monitoring Long Range Infrastructures, Chang Wen Chen, Yu Wang, Ivica Kostanic
A Chain-Type Wireless Sensor Network For Monitoring Long Range Infrastructures, Chang Wen Chen, Yu Wang, Ivica Kostanic
Electrical Engineering and Computer Science Faculty Publications
We present in this paper an investigation on a special class of wireless sensor networks for monitoring critical infrastructures that may extend for hundreds of miles in distances. Such networks are fundamentally different from traditional sensor networks in that the sensor nodes in this class of networks are deployed along narrowly elongated geographical areas and form a chain-type topology. Based on careful analysis of existing sensor network architectures, we first demonstrate the needs to develop new architecture and networking protocols to match the unique topology of chain-type sensor networks. We then propose hierarchical network architecture that consists of clusters of …
An Energy-Efficient Media Access Control Protocol For Chain-Type Wireless Sensor Networks, Yu Wang, Chang Wen Chen
An Energy-Efficient Media Access Control Protocol For Chain-Type Wireless Sensor Networks, Yu Wang, Chang Wen Chen
Electrical Engineering and Computer Science Faculty Publications
We present in this paper an energy efficient media access control (MAC) protocol for chain-type wireless sensor networks. The chain-type sensor networks are fundamentally different from traditional sensor networks in that the sensor nodes in this class of networks are deployed along narrow and elongated geographical areas and form a chain-type topology. Recently, we have successfully developed hierarchical network architecture, sensor deployment strategy, and corresponding network initialization and operation protocols for this class of sensor networks. In this paper, we present a novel TDMA scheduling protocol that takes full advantages of the available channel reuse inherent in the chain-type sensor …
Application-Specific Routing Scheme For Indoor Wireless Localization Systems, Tamas Kasza, Chang Wen Chen
Application-Specific Routing Scheme For Indoor Wireless Localization Systems, Tamas Kasza, Chang Wen Chen
Electrical Engineering and Computer Science Faculty Publications
The proposed research focuses on the communication in an RF-based indoor wireless localization system. In such a system, wireless badges attached to people or devices report positions to wireless gateway units. Badges have very limited communication, energy, as well as processing capabilities. However, gateways are significantly less constrained by battery than the badges. Wireless gateway units route collected badge information hop-by-hop towards one central unit of the system. We assume that each gateway unit has one transceiver antenna and is able to determine its own relative position in the system. The goal of this research is to develop an application-specific …
Multilevel Fusion Using Enhanced Feature Detection, Trond M. Ostrem, Samuel Peter Kozaitis
Multilevel Fusion Using Enhanced Feature Detection, Trond M. Ostrem, Samuel Peter Kozaitis
Electrical Engineering and Computer Science Faculty Publications
We combined images from different sensors based on the magnitude of multiscale products of the wavelet transform. Using the product of nondownsampled wavelet coefficients across scales, we formed a fusion rule between two images. In this way, the products represented features than were related to contrast. Therefore, using our approach allowed us to enhance the contrast of two images using a pixel-level fusion approach. In experiments, our approach compared favorably to using only a single level, or other methods using subjective tests.
Secure Stochastic Multi-Party Computation For Combinatorial Problems, Marius C. Silaghi, Gerhard Friedrich
Secure Stochastic Multi-Party Computation For Combinatorial Problems, Marius C. Silaghi, Gerhard Friedrich
Electrical Engineering and Computer Science Faculty Publications
High levels of security often imply that the computation time should be independent of the value of involved secrets. When the expected answer of the solver is either a solution or "unsatisfiable", then the previous assumption leads to algorithms that take always the computation time of the worst case. This is particularly disturbing for NP-hard combinatorial problems. Here we start from the observation that sometimes (specially for hard problems) users find it acceptable to receive as answer either a solution, the answer "unsatisfiable" or a failure with meaning "don't know". More exactly users accept "incomplete" solvers. For certain problems privacy …
Iterative Segmentation In Keyword Spotting: Relation To Fractional Programming, Marius C. Silaghi
Iterative Segmentation In Keyword Spotting: Relation To Fractional Programming, Marius C. Silaghi
Electrical Engineering and Computer Science Faculty Publications
This paper addresses the problem of detecting keywords in unconstrained speech. The proposed algorithms search for the speech segment maximizing the average observation probability along the most likely path in the hypothesized keyword model. As known, this approach (sometimes referred to as sliding model method) requires a relaxation of the begin/endpoints of the Viterbi matching, as well as a time normalization of the resulting score. This makes solutions complex (i.e., LN2/2 basic operations for keyword HMM models with L states and utterances with N frames). We present here two alternative (quite simple and efficient) solutions to this problem. a) First …
Personalized Ranking Of Search Results With Implicitly Learned User Interest Hierarchies, Hyoung-Rae Kim, Philip K. Chan
Personalized Ranking Of Search Results With Implicitly Learned User Interest Hierarchies, Hyoung-Rae Kim, Philip K. Chan
Electrical Engineering and Computer Science Faculty Publications
Web search engines are usually designed to serve all users, without considering the interests of individual users. Personalized web search incorporates an individual user's interests when deciding relevant results to return. We propose to learn a user profile, called a user interest hierarchy (UIH), from web pages that are of interest to the user. The user's interest in web pages will be determined implicitly, without directly asking the user. Using the implicitly learned UIH, we study methods that rank the results from a search engine. Experimental results indicate that our personalized ranking methods, when used with a popular search engine, …
Disparity Determination Using Multilevel Products, Michel Ouendeno, Samuel Peter Kozaitis
Disparity Determination Using Multilevel Products, Michel Ouendeno, Samuel Peter Kozaitis
Electrical Engineering and Computer Science Faculty Publications
We determined the overall disparity from stereo images using multiscale products of disparity values. Using the wavelet transform, we used a multiresolution analysis to calculate disparity values from stereo images at different scales. Forming the product of disparities and rescaling resulted in a disparity map that was directly related to depth. Using a multiresolution approach allowed us to more accurately determine disparity by examining the consistency of results through different scales. Using this approach could form the basis of an effective method for depth estimation.
Product-Based Multiresolution Image Fusion, Trond M. Ostrem, Samuel Peter Kozaitis
Product-Based Multiresolution Image Fusion, Trond M. Ostrem, Samuel Peter Kozaitis
Electrical Engineering and Computer Science Faculty Publications
We combined images from different sensors that were enhanced by multiscale products of the wavelet coefficients. Using the wavelet transform, we used a multiresolution analysis to form products of coefficients across scales. Then, a fusion rule was applied to the product images to determine how the original images could be combined. Using this approach, we were able to decrease the sensitivity of the fusion process to noise.
Trajectory Boundary Modeling Of Time Series For Anomaly Detection, Matthew V. Mahoney, Philip K. Chan
Trajectory Boundary Modeling Of Time Series For Anomaly Detection, Matthew V. Mahoney, Philip K. Chan
Electrical Engineering and Computer Science Faculty Publications
We address the problem of online detection of unanticipated modes of mechanical failure given a small set of time series under normal conditions, with the requirement that the anomaly detection model be manually verifiable and modifiable. We specify a set of time series features, which are linear combinations of the current and past values, and model the allowed feature values by a sequence of minimal bounding boxes containing all of the training trajectories. The model can be constructed in O(n log n) time. If there are at most three features, the model can be displayed graphically for verification, otherwise a …
Visualization Of Medical Images Over Mobile Wireless Handheld Devices, Min Wu, Khurana Ashish, Nadar Mariappan, Chang Wen Chen
Visualization Of Medical Images Over Mobile Wireless Handheld Devices, Min Wu, Khurana Ashish, Nadar Mariappan, Chang Wen Chen
Electrical Engineering and Computer Science Faculty Publications
With the novel advances in wireless communication and personal mobile handheld devices, a newly emerging technology of medical visualization on mobile handheld is believed to provide advance service for physicians, especially in image-based diagnosis. In this paper, we have implemented a real time easy-to-use 3D volume visualization system on mobile handheld devices. The doctors could use their wireless handheld devices, such as Pocket PC or PDA, interactively access medical image at anytime and anywhere in the hospital building. System architecture, technical problems and solutions are discussed. Experimental results are clear enough to show this system to be practical for clinic …
A Novel Multiple Description Scalable Coding Scheme For Mobile Wireless Video Transmission, Haifeng Zheng, Lun Yu, Chang Wen Chen
A Novel Multiple Description Scalable Coding Scheme For Mobile Wireless Video Transmission, Haifeng Zheng, Lun Yu, Chang Wen Chen
Electrical Engineering and Computer Science Faculty Publications
We proposed in this paper a novel multiple description scalable coding (MDSC) scheme based on in-band motion compensation temporal filtering (IBMCTF) technique in order to achieve high video coding performance and robust video transmission. The input video sequence is first split into equal-sized groups of frames (GOFs). Within a GOF, each frame is hierarchically decomposed by discrete wavelet transform. Since there is a direct relationship between wavelet coefficients and what they represent in the image content after wavelet decomposition, we are able to reorganize the spatial orientation trees to generate multiple bit-streams and employed SPIHT algorithm to achieve high coding …
Zero-Knowledge Proofs For Mix-Nets Of Secret Shares And A Version Of Elgamal With Modular Homomorphism, Marius C. Silaghi
Zero-Knowledge Proofs For Mix-Nets Of Secret Shares And A Version Of Elgamal With Modular Homomorphism, Marius C. Silaghi
Electrical Engineering and Computer Science Faculty Publications
Mix-nets can be used to shuffle vectors of shared secrets. This operation can be an important building block for solving combinatorial problems where constraints are secret to different participants. A main contribution of this paper is to show how participants in the mix-net can provide Zero-Knowledge proofs to convince each other that they do not tamper with the shuffled secrets, and that inverse permutations are correctly applied. The approach is related to the proof of knowing an isomorphism between large graphs. We also make a detailed review and comparison with rationales and analysis of Chaum's and Merritt's mix-nets. Mix-nets offer …
Learning Rules For Time Series Anomaly Detection, Matthew V. Mahoney, Philip K. Chan
Learning Rules For Time Series Anomaly Detection, Matthew V. Mahoney, Philip K. Chan
Electrical Engineering and Computer Science Faculty Publications
We describe a multi-dimensional time series anomaly detection method in which each point in a test series is required to match the value, slope, and curvature of a point seen in training (with an optional sequential constraint), and a method of generating a model in the form of concise, human-comprehensible, and editable rules. Training time complexity is O(n log n), and testing is O(n). The method generalizes to multiple training series by allowing test points to fall within the range bounded by the training data. We use this approach to detect test failures in Marotta fuel control valves used on …
Implicit Indicators For Interesting Web Pages, Hyoung-Rae Kim, Philip K. Chan
Implicit Indicators For Interesting Web Pages, Hyoung-Rae Kim, Philip K. Chan
Electrical Engineering and Computer Science Faculty Publications
A user's interest in a web page can be estimated by unobtrusively (implicitly) observing his or her behaviour rather than asking for feedback directly (explicitly). Implicit methods are naturally less accurate than explicit methods, but they do not waste a user's time or effort. Implicit indicators of a user's interests can also be used to create models that change with a user's interests over time. Research has shown that a user's behavior is related to his/her interest in a web page. We evaluate previously studied implicit indicators and examine the time spent on a page in more detail. For example, …
Publicly Verifiable Private Credentials - A Technique For Privately Signing Citizen Initiatives, Kishore R. Kattamuri, Marius C. Silaghi
Publicly Verifiable Private Credentials - A Technique For Privately Signing Citizen Initiatives, Kishore R. Kattamuri, Marius C. Silaghi
Electrical Engineering and Computer Science Faculty Publications
Besides voting, another way of practicing democracy is by signing popular / citizen initiatives or optional referendums of certain types. We address the problems related to the electronic remote signing of support for referendums and popular initiatives (e-referendums). We propose, publicly verifiable private credentials (PVPCs) , a type of certified pseudonym digital signatures for which one can publicly prove that only eligible users (belonging to a specified group) got them and that no user got two of them. They can be used to sign citizen initiatives. Our technique generates PVPCs that can be publicly proven to belong to an unknown …
Supporting Debates Over Citizen Initiatives, Kishore R. Kattamuri, Marius C. Silaghi
Supporting Debates Over Citizen Initiatives, Kishore R. Kattamuri, Marius C. Silaghi
Electrical Engineering and Computer Science Faculty Publications
Popular / citizen initiatives provide a way for the inclusion of constitutional or statutory proposals on the ballot (e.g., at an election) if enough signatures are collected in support of the proposal. Once citizens are enabled to digitally sign such initiatives remotely, the next challenge will be to provide support for verified eligible citizens to debate on running initiatives. Intelligent ways of structuring information for easy access and cooperation is a major research interest in computer science, with results like WWW, Semantic Web, Forums, Blogs, Slashdot. We propose here a new interaction paradigm for debates in the setting where participants …
Multiple Description Distributed Image Coding With Side Information For Mobile Wireless Transmission, Min Wu, Daewon Song, Chang Wen Chen
Multiple Description Distributed Image Coding With Side Information For Mobile Wireless Transmission, Min Wu, Daewon Song, Chang Wen Chen
Electrical Engineering and Computer Science Faculty Publications
Multiple description coding (MDC) is a source coding technique that involves coding the source information into multiple descriptions, and then transmitting them over different channels in packet network or error-prone wireless environment to achieve graceful degradation if parts of descriptions are lost at the receiver. In this paper, we proposed a multiple description distributed wavelet zero tree image coding system for mobile wireless transmission. We provide two innovations to achieve an excellent error resilient capability. First, when MDC is applied to wavelet subband based image coding, it is possible to introduce correlation between the descriptions in each subband. We consider …
Constant Quality Constrained Bit Allocation For Leaky Prediction Based Fgs Video Streaming, Jianhua Wu, Jianfei Cai, Chang Wen Chen
Constant Quality Constrained Bit Allocation For Leaky Prediction Based Fgs Video Streaming, Jianhua Wu, Jianfei Cai, Chang Wen Chen
Electrical Engineering and Computer Science Faculty Publications
Leaky prediction based FGS (Fine Granularity Scalability) can achieve better coding efficiency than the baseline FGS. However, for leaky prediction based FGS (L-FGS), constant quality constrained bit allocation, i.e., how to optimally allocate bits given the current channel bandwidth, is still an open problem. In this paper, based on the accurate R-D (Rate-Distortion) model developed in our previous work, we propose a constant quality constrained bit allocation scheme for L-FGS. The proposed scheme is a combination of offline and online processes. During the offline stage, we perform the L-FGS encoding and collect the necessary feature information. At the online stage, …
Robust Video Transmission Based On Multiple Description Scalable Coding With Erec, Haifeng Zheng, Lun Yu, Chang Wen Chen
Robust Video Transmission Based On Multiple Description Scalable Coding With Erec, Haifeng Zheng, Lun Yu, Chang Wen Chen
Electrical Engineering and Computer Science Faculty Publications
This paper presents a multiple description scalable video coding scheme based on overcomplete motion compensated temporal filtering, named MD-OMCTF, for robust video transmission over wireless and packet loss networks. The intrinsic nature of the structure of OMCTF and embedded coding with modified SPIHT algorithm enable us to provide fully scalable properties for the proposed scheme. We show that multiple description coding is very effective in combating with channel failures in both Internet and wireless video. The integration of MD with OMCTF allows us to achieve both loss resilience and complete scalability. In order to further improve error-resilience to channel bit …