ppxscal/embedding_network huggingface dataset:
Connections: integrated first year engineering education at the Colorado School of Mines
Authors: R. L. Miller, B. M. Olds
Venue: Proceedings of the Frontiers in Education Conference, on 1995. Proceedings., 1995 - Volume 02 (1995)

We are developing and implementing the Connections program, an integrated series of active learning based courses and seminars which will allow first year engineering students to develop significant connections among their studies in humanities, social and physical sciences, and engineering. By connecting first year courses via a series of interdisciplinary modules and developing the connections further in a seminar series, we allow students to discover the relationships among the humanities, science, and engineering disciplines they are studying. The result is students who are beginning to construct the "big picture" of engineering as a human enterprise, thereby appreciating the importance of liberal learning in their education, their profession, and their lives. The paper describes the Connections structure including details of the Connections seminar and examples of Connections modules. We also report preliminary evaluation results from Connections pilot courses taught during the 1994-95 academic year.
An Adaptive Real-Time Routing Scheme for Wireless Sensor Networks
Authors: Han Peng, Zhou Xi, Li Ying, Chen Xun, Gao Chuanshan
Venue: Proceedings of the 21st International Conference on Advanced Information Networking and Applications Workshops - Volume 02 (2007)

Wireless sensor networks may have to support many kinds of applications, some of which may have to satisfy strict requirements for data transfer delay while others do not. Thus, it is necessary to design routing schemes that can provide adaptive real-time data transmission services. On the other hand, energy consumption is one of the most important criteria for routing schemes. This paper aims to explore the routing schemes that can satisfy the real-time transmission applications and also save energy. We achieve this target by designing an adaptive real-time routing scheme (ARP). This scheme provides different real-time levels for different applications and dynamically adjusts the transmission rate of data packets during the end-to-end transmission.
Extending acid semantics to the file system via ptrace
Authors: Erez Zadok
Venue:  (2006)

An organization's data is often its most valuable asset, but today's file systems provide few facilities to ensure its safety. Databases, on the other hand, have long provided safety mechanisms in the form of transactions. Transactions are useful because they provide atomicity, consistency, isolation, and durability (ACID). Although many applications could make use of these semantics, databases have a wide variety of non-standard interfaces. As a result, applications currently perform elaborate error handling by themselves to ensure atomicity and consistency, because it is easier than using a DBMS. A transaction-oriented programming model eliminates such complex error-handling code, because failed operations can simply be aborted without side effects. We have designed a file system that exports ACID transactions to user-level applications, while preserving the ubiquitous and convenient POSIX file-system interface, In our prototype ACID file system, called Amino, updated applications can group arbitrary sequences of system calls within a transaction. Unmodified applications operate without any changes, but each system call is protected by a transaction. Amino stores all of its meta-data and data in Berkeley DB, a user-level open-source embedded database. Berkeley DB provides an easy-to-use record-management API, an efficient B-tree access manager, caching, and ACID transactions. We developed Amino entirely in user space by intercepting system calls using the standard ptrace API, because developing Amino in the kernel would have required complex kernel changes. For example, the kernel's file system interfaces are intertwined with caches, thus preventing a DBMS from providing proper locking to ensure isolation. Additionally, user-level development proceeds more quickly than kernel development because more debugging- and development tools are available. We show that our ptrace monitor can be used to develop a variety of user-level file systems with less complexity than other user-level file system approaches. Our performance evaluation shows that for general purpose benchmarks Amino has acceptable overheads (22.6--84.7%), and in some cases even exceeds the performance of Ext3.
Robust multi-view feature matching from multiple unordered views
Authors: Jian Yao, Wai-Kuen Cham
Venue: Pattern Recognition (2007)

This paper explores the problem of multi-view feature matching from an unordered set of widely separated views. A set of local invariant features is extracted independently from each view. First we propose a new view-ordering algorithm that organizes all the unordered views into clusters of related (i.e. the same scene) views by efficiently computing the view-similarity values of all view pairs by reasonably selecting part of extracted features to match. Second a robust two-view matching algorithm is developed to find initial matches, then detect the outliers and finally incrementally find more reliable feature matches under the epipolar constraint between two views from dense to sparse based on an assumption that changes of both motion and feature characteristics of one match are consistent with those of neighbors. Third we establish the reliable multi-view matches across related views by reconstructing missing matches in a neighboring triple of views and efficiently determining the states of matches between view pairs. Finally, the reliable multi-view matches thus obtained are used to automatically track all the views by using a self-calibration method. The proposed methods were tested on several sets of real images. Experimental results show that it is efficient and can track a large set of multi-view feature matches across multiple widely separated views.
Exploiting Narrow Accelerators with Data-Centric Subgraph Mapping
Authors: Amir Hormati, Nathan Clark, Scott Mahlke
Venue: Proceedings of the International Symposium on Code Generation and Optimization (2007)

The demand for high performance has driven acyclic computation accelerators into extensive use in modern embedded and desktop architectures. Accelerators that are ideal from a software perspective, are difficult or impossible to integrate in many modern architectures, though, due to area and timing requirements. This reality is coupled with the observation that many application domains under-utilize accelerator hardware, because of the narrow data they operate on and the nature of their computation. In this work, we take advantage of these facts to design accelerators capable of executing in modern architectures by narrowing datapath width and reducing interconnect. Novel compiler techniques are developed in order to generate highquality code for the reduced-cost accelerators and prevent performance loss to the extent possible. First, data width profiling is used to statistically determine how wide program data will be at run time. This information is used by the subgraph mapping algorithm to optimally select subgraphs for execution on targeted narrow accelerators. Overall, our data-centric compilation techniques achieve on average 6.5%, and up to 12%, speed up over previous subgraph mapping algorithms for 8-bit accelerators. We also show that, with appropriate compiler support, the increase in the total number of execution cycles in reduced-interconnect accelerators is less than 1% of the fully-connected accelerator.
Detection of Microcalcifications in Mammographies Based on Linear Pixel Prediction and Support-Vector Machines
Authors: F. Martinez-Alvarez, A. Troncoso, J. C. Riquelme, J. S. Aguilar-Ruiz
Venue: Proceedings of the Twentieth IEEE International Symposium on Computer-Based Medical Systems (2007)

Breast cancer is one of the diseases causing the largest number of deaths among women. Its early detection has been proved to be the most effective way to combat it. This work is focused on developing an integral tool able to detect microcalcifications in mammographies, since the presence of these particles is a clear symptom of an incipient cancer. The proposed approach combines two techniques successfully used in other areas separately, such as linear pixel prediction and support-vector machines, in order to obtain almost perfect prediction accuracy. Moreover, a filter has been designed with the aim of decrease the processing time. The result verges on 96% of hits, improving previous works by 6%, on average.
A new mobile payment scheme for roaming services
Authors: Ren-Junn Hwang, Sheng-Hua Shiau, Ding-Far Jan
Venue: Electronic Commerce Research and Applications (2007)

Due to the advance of mobile network technologies, mobile personal devices are used to perform electronic payment. This paper proposes a new on-line payment scheme for mobile network. The proposed scheme is not only performed in the home domain, but also can be performed in visited domain. Our scheme provides consumer anonymity, authentication, non-repudiation and data integrity properties. The consumer can make transaction with shop, vendor machine and WAP site based on our scheme. Our scheme only includes symmetric encryption and one-way hash function, it takes lower computation cost and is more suitable for mobile device.
Minority vote: at-least-N voting improves recall for extracting relations
Authors: Nanda Kambhatla
Venue: Proceedings of the COLING/ACL on Main conference poster sessions (2006)

Several NLP tasks are characterized by asymmetric data where one class label NONE, signifying the absence of any structure (named entity, coreference, relation, etc.) dominates all other classes. Classifiers built on such data typically have a higher precision and a lower recall and tend to overproduce the NONE class. We present a novel scheme for voting among a committee of classifiers that can significantly boost the recall in such situations. We demonstrate results showing up to a 16% relative improvement in ACE value for the 2004 ACE relation extraction task for English, Arabic and Chinese.
Performance evaluation of non-Gaussian channel estimation techniques on ultrawideband impulse radio channels: Research Articles
Authors: Richard J. Barton, Manoj Daniel
Venue: International Journal of Communication Systems (2007)

We study the problem of adaptive channel estimation for a multipath channel on an ultrawideband (UWB) impulse radio (IR) system. The purpose of the work is to demonstrate that the statistical characteristics of the UWB-IR environment are strongly non-Gaussian and that as a result, non-Gaussian signal processing techniques are both efficient and powerful in a UWB-IR environment. The multipath channel estimation problem has been chosen as an illustrative example because UWB-IR systems often operate in complex multipath environments. We study both blind and training-based estimation techniques and demonstrate that even simple non-Gaussian strategies can achieve significant performance improvement when compared to more common second-order estimation techniques. Copyright &copy; 2006 John Wiley & Sons, Ltd.
A compact modular architecture for high-speed binary sorting
Authors: I. Hatirnaz
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 06 (2000)

A new algorithm and a new modular architecture are presented for the realization of high-speed binary sorting engines, based on efficient rank ordering. Capacitive threshold logic (CTL) gates are utilized for the implementation of the multi-input programmable majority (voting) functions required in the architecture. The overall complexity of the proposed bit-serial architecture increases linearly with the number of input vectors to be sorted (window size=m) and with the bit-length of the input vectors (word size=n), and the sorter architecture can be easily expanded to accommodate large vector sets. Detailed simulations indicate that the sorter structure can operate at sampling clock rates of up to 50 MHz, where the throughput is boosted by fine-grain pipelining. It is demonstrated that the proposed sorting engine is capable of producing a fully sorted output vector set in (m+n-1) clock cycles.
T-PaD: Tactile Pattern Display through Variable Friction Reduction
Authors: Laura Winfield, John Glassmire, J. Edward Colgate, Michael Peshkin
Venue: Proceedings of the Second Joint EuroHaptics Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (2007)

In this paper we discuss the theory, design and construction of a haptic display for creating texture sensations through variations in surface friction. Ultrasonic frequency, low amplitude vibrations between two flat plates have been shown to create a squeeze film of air between the two plate surfaces thereby reducing the friction [1][2]. We show that a reduction of friction will also occur between a human finger and a vibrating plate. Thus, a vibrating plate can serve as a haptic interface. The amplitude of vibration can also be correlated to the amount of friction reduction between the plate and the finger. Varying the surface friction between the finger and the haptic interface is a way of indirectly controlling shear forces on the finger during active exploration. Using finger position and velocity feedback on the display allows for the creation of spatial texture sensations.
An expert system approach based on principal component analysis and adaptive neuro-fuzzy inference system to diagnosis of diabetes disease
Authors: Kemal Polat, Salih Güneş
Venue: Digital Signal Processing (2007)

Diabetes occurs when a body is unable to produce or respond properly to insulin which is needed to regulate glucose (sugar). Besides contributing to heart disease, diabetes also increases the risks of developing kidney disease, blindness, nerve damage, and blood vessel damage. In this paper, we have detected on diabetes disease, which is a very common and important disease using principal component analysis (PCA) and adaptive neuro-fuzzy inference system (ANFIS). The aim of this study is to improve the diagnostic accuracy of diabetes disease combining PCA and ANFIS. The proposed system has two stages. In the first stage, dimension of diabetes disease dataset that has 8 features is reduced to 4 features using principal component analysis. In the second stage, diagnosis of diabetes disease is conducted via adaptive neuro-fuzzy inference system classifier. We took the diabetes disease dataset used in our study from the UCI (from Department of Information and Computer Science, University of California) Machine Learning Database. The obtained classification accuracy of our system was 89.47% and it was very promising with regard to the other classification applications in literature for this problem.
Delay estimation using sinusoidal signals
Authors: H. C. So
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 05 (2000)

The problem of estimating the difference in arrival times of a noisy sinusoid received at two spatially separated sensors is considered. Given the sinusoidal frequency, a simple delay estimator using the phase difference of the discrete time Fourier transforms (DTFTs) of the received signals is devised. With the use of a periodogram, the algorithm is extended to estimate the delay when the frequency is unknown. The minimum achievable delay variances for the cases of known/unknown frequencies and constant/rectangular envelopes are also given. The effectiveness of the method is demonstrated by comparing with the performance bounds for different frequencies, envelopes and noise conditions.
Non-uniform filterbank bandwidth allocation for system modeling subband adaptive filters
Authors: J. D. Griesbach
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 03 (1999)

Subband adaptive filters have been used extensively in system modeling configurations to model unknown systems with large impulse responses. This paper illustrates the advantages of a non-uniform subband adaptive filter over a uniform subband adaptive filter while giving insight to subband bandwidth allocations for system modeling configurations. By implementing small subbands which isolate the transition regions in the unknown system, while using larger subbands for other, more spectrally flat regions, one can minimize convergence time and lower misadjustment.
On the Assessment of the Interaction Quality of Users with Cerebral Palsy
Authors: C. Mauri, T. Granollers, A. Solanas
Venue: Proceedings of the The Second International Conference on Availability, Reliability and Security (2007)

This paper is the continuation of a series of related work about experimentation of alternative ways of interaction with computers for disabled people (concretely with users suffering from cerebral palsy). In order to define an effective methodology to evaluate the usability and/or accessibility levels for this user profile, here, we start studying and evaluating (a) different interactive devices and interaction techniques that enable the use of computers for this people and, (b) existing metric techniques from human-computer interaction field. With this basis the article proposes a new evaluation method that simplifies the existing ones reducing the complexity to the minimum. This proposal is extensively explained and field research will soon be started.
A DSB-SC signal model for nonlinear regression-based quadrature receiver calibration
Authors: R. A. Green
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 03 (1999)

Advances have been made regarding quadrature receiver I/Q mismatch calibration. In particular, Green, Anderson-Sprecher and Pierre (see IEEE Transactions on Signal Processing, 1998) present a nonlinear regression (NLR)-based algorithm that utilizes a pure sinusoidal test signal for sensor calibration. This paper develops a double side-band suppressed carrier (DSB-SC) signal model for use with NLR-based calibration methods. The DSB-SC model not only provides a useful signal for calibration, it also demonstrates the model flexibility inherent to nonlinear regression techniques. Simulations illustrate the effectiveness of the DSB-SC signal model for the calibration of I/Q sensors.
Spread spectrum signaling for speech watermarking
Authors: Qiang Cheng
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03 (2001)

The technique of embedding a digital signal into an audio recording or image using techniques that render the signal imperceptible has received significant attention. Embedding an imperceptible, cryptographically secure signal, or watermark, is seen as a potential mechanism that may be used to prove ownership or detect tampering. While there has been a considerable amount of attention devoted to the techniques of spread-spectrum signaling for use in image and audio watermarking applications, there has only been a limited study for embedding data signals in speech. Speech is an uncharacteristically narrow band signal given the perceptual capabilities of the human hearing system. However, using speech analysis techniques, one may design an effective data signal that can be used to hide an arbitrary message in a speech signal. Also included are experiments demonstrating the subliminal channel capacity of the speech data embedding technique developed here.
Adaptive measures of similarity---fuzzy hamming distance---and its applications to pattern recognition problems
Authors: Anca L. Ralescu
Venue:  (2006)

Similarity measures are the basis of most of the machine learning and pattern recognition algorithms. The choice of the similarity determines the effectiveness of the algorithm in solving the specific problem. This is why finding a relevant similarity measure is an active area of research in machine learning and pattern recognition. Hamming distance is a simple and efficient similarity measure, but because it was designed to deal with binary vectors, it can not be applied to many problems that uses real-valued vectors. This thesis build upon and extends a generalization of the Hamming distance, Fuzzy Hamming distance, that can operate on real-valued vectors and maintain the same meaning as the Hamming distance: the number of different elements. To assess the effectiveness of this new measure, FHD is employed in several experiments as basis for a Content Image Retrieval system, a banknote validation system and into a conceptual spaces based, knowledge discovery system.
Generalized higher-order moments in independent component analysis
Authors: J. O. Coleman
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 01 (2000)

In independent component analysis (ICA), random-variable independence is often equated with factorization of the joint moments, expectations of products of powers. This paper shows that many nonpower functions are equally useful: if E[f(X)g(Y)] factors into E[f(X)]E[g(Y)] for every f and g from an independence class, then random variables X and Y are independent. Examples of and sufficient conditions for independence classes are presented for bounded random variables.
Statistics of stack filters with mirrored threshold decomposition
Authors: I. Shmulevich
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 06 (2000)

The output distribution formula for stack filters based on mirrored threshold decomposition is derived. This formula allows one to compute the cumulative distribution function of the output of a stack filter for a given input noise distribution. Mirrored threshold decomposition permits us to analyze the input-output characteristics of the stack filter in the binary domain. The sliding window operation of the stack filter is modeled by a deterministic finite automaton. The output distribution of the filter is obtained by interpreting the automaton as a Markov Chain whose transition probabilities depend on the probabilistic description of the binary input signal.
An Improved Approach to Passive Testing of FSM-based Systems
Authors: Hasan Ural, Zhi Xu, Fan Zhang
Venue: Proceedings of the 29th International Conference on Software Engineering Workshops (2007)

Fault detection is a fundamental part of passive testing which determines whether a system under test (SUT) is faulty by observing the input/output behavior of the SUT without interfering its normal operations. In this paper, we propose a new approach to Finite State Machine (FSM)-based passive fault detection which improves the performance of the approach in [4] and gathers more information during testing compared with the approach in [4]. The results of theoretical and experimental evaluations are reported.