ppxscal/embedding_network huggingface dataset:
Scalable Content-Based Publish/Subscribe Services over Structured Peer-to-Peer Networks
Authors: Xiaoyu Yang, Yingwu Zhu, Yiming Hu
Venue: Proceedings of the 15th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (2007)

The scalability has remained a challenge in the design of distributed publish/subscribe systems. In this paper we propose a novel solution to address this problem in contentbased pub/sub systems on top of Distributed Hash Table. The main objective is to ensure an appropriate amount of rendezvous point nodes in the system, as well as maintain an even load distribution among them. An attribute-vector based publish/subscribe scheme and related load balancing mechanisms (ID space partitioning, attribute grouping, dynamic ID space split-merge) are proposed to achieve this goal. The experimental results show that our approaches can achieve a good scalability by efficiently distribute/ balance load among an adaptive quantity of rendezvous point nodes, while retaining very small overhead and latency.
A multi-expert approach for wavelet-based face detection
Authors: Loris Nanni, Alessandra Lumini
Venue: Pattern Recognition Letters (2007)

In this work we present an upright frontal face detection system based on the multi-resolution analysis of the face. The images are decomposed into frequency sub-bands with different levels decomposition using different wavelets. We propose to use a multi-matcher where each matcher (a Radial Basis Function Support Vector Machine) is trained using a different set of features (a given sub-band or the gray values) projected onto a lower subspace by Laplacian Eigenmaps, the matchers are combined using the ''Sum Rule''. The matcher selection is performed by running Sequential Forward Floating Selection. To speed up the detection, an eye detector is used to find the position of the most probable face. Among these sub-windows only the sub-windows that are classified, by the matcher trained using gray values, as ''face'' are classified by the multi-matcher.
Dataflow Graph Optimization for Dataflow Architectures a Dataflow Otimizing Compiler
Authors: Sholin Kyo, Shin'ichiro Okazaki, Masanori Mizoguchi
Venue: Proceedings of the 1993 International Conference on Parallel Processing - Volume 02 (1993)

In general, datafiow graph for which it is difficult to optimize quality are those used for branches (conditionals) and loops. Although a number of dataflow graph transformation schemes have taken these into accounts, the quality of graphs been produced was not compared with that of hand-written optimized graphs.
Compensating of room acoustic transfer functions affected by change of room temperature
Authors: M. Omura
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 02 (1999)

This paper proposes an efficient compensation method using a first-order approximation of time axis scaling for the variations of the room acoustic transfer function. The time axis scaling model is based on the fact that the change of the sound velocity due to the change of room temperature is a dominant factor for the variations of room impulse response affected by environmental conditions. In this paper, the effectiveness of the compensation method is evaluated using room impulse responses measured in the real environment. As the results, it is clarified that the variations of room impulse response can be modeled by the first-order approximated time axis scaling when the successive re-estimation is performed every small change of temperature. Furthermore, it is shown that the compensation method applied to an inverse filtering based dereverberation approach improves the intelligibility and speech recognition rates dramatically.
Adaptive paraunitary filter banks for contrast-based multichannel blind deconvolution
Authors: X. Sun
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 05 (2001)

We present novel algorithms for multichannel blind deconvolution under output whitening constraints. The algorithms are inspired by recently-developed procedures for gradient adaptive paraunitary filter banks. Several algorithms are developed, including one algorithm that successfully deconvolves mixtures of arbitrary non-zero kurtosis source signals. We provide detailed local stability analyses of the proposed methods to verify their capabilities. Simulations show that the methods successfully deconvolve spatio-temporal mixtures of statistically independent source signals.
Activity Recognition using Dynamic Bayesian Networks with Automatic State Selection
Authors: Justin Muncaster, Yunqian Ma
Venue: Proceedings of the IEEE Workshop on Motion and Video Computing (2007)

Applying advanced video technology to understand activity and intent is becoming increasingly important for intelligent video surveillance. We present a general model of a d-level dynamic Bayesian network to perform complex event recognition. The levels of the network are constrained to enforce state hierarchy while the dth level models the duration of simplest event. Moreover, in this paper we propose to use the deterministic annealing clustering method to automatically discover the states for the observable levels. We used real world data sets to show the effectiveness of our proposed method.
Speech recognition and enhancement by a nonstationary AR HMM with gain adaptation under unknown noise
Authors: G. Ruske
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 01 (1999)

A gain-adapted speech recognition in unknown noise is developed in time domain. The noise is assumed to be the colored noise. The nonstationary autoregressive (NAR) hidden Markov model (HMM) used to model clean speeches. The nonstationary AR is modeled by polynomial functions with a linear combination of M known basis functions. Enhancement using multiple Kalman filters is performed for the gain contour of speech and estimation of noise model when only the noisy signal is available.
Concept Pre-digestion Method for Image Relevance Reinforcement Learning
Authors: Sudhakara P. Reddy, Raju S. Bapi, Chakravarthy Bhagvati, B. L. Deekshatulu
Venue: Proceedings of the International Conference on Computing: Theory and Applications (2007)

Relevance feedback (RF) is commonly used to improve the performance of CBIR system by allowing incorporation of user feedback iteratively. Recently, a method called image relevance reinforcement learning (IRRL) has been proposed for integrating several existing RF techniques as well as for exploiting RF sessions of multiple users. The precision obtained at the end of every iteration is used was a reward signal in the Q-learning based reinforcement learning (RL) approach. The objective of learning in IRRL is to estimate the optimal RF technique to be applied for a given query at a specific iteration. The main drawback of IRRL is its prohibitive learning time and storage requirement. We propose a way of addressing these difficulties by performing `pre-digestion' of concepts before applying IRRL. Experimental results on two databases of images demonstrated the viability of the proposed approach.
A successful undergraduate design center
Authors: J. C. Sutton
Venue: Proceedings of the Frontiers in Education Conference on 1995. Proceedings., 1995 vol 1. - Volume 01 (1995)

The Department of Electrical and Computer Engineering (ECE) at North Carolina State University formed an ECE Undergraduate Design Center (UDC) in 1990. The initial funding for the center came from the National Science Foundation (NSF). Beginning in 1991, funding for the center started to come from industry, and the center is currently 100% industry funded. In its first four years, senior ECE students working in reams at the center have completed more than 400 semester long projects. From the industrial perspective, many of these projects have saved companies time or money. From the educational perspective, these undergraduate students have been given the opportunity to work on "real world" projects with engineers from industry and gain valuable experience that would otherwise not be possible. Most of the activities of the UDC evolve around the four credit hour senior design capstone course that is required for all ECE seniors. In the classroom, the capstone course focuses on time-management, team-work, communication skills and open-ended design. Students are expected to take this classroom knowledge and apply it to their actual projects. While working on their projects students interact with engineers from sponsoring companies and with ECE faculty who are familiar with the technology that their particular project focuses on.
Automatic Acquisition of Translation Knowledge Using Structural Matching Between Parse Trees
Authors: Werner Winiwarter
Venue: Proceedings of the First International Conference on the Digital Society (2007)

In this paper we present a rule-based formalism for the representation, acquisition, and application of translation knowledge. The formalism is being used successfully in a Japanese-English machine translation system. The translation knowledge is learnt automatically from a parallel corpus using structural matching between the parse trees of translation examples. We have developed a comfortable user interface, which makes it possible to invoke the translation functionality directly from MS Word. The user can customize the translation knowledge by simply correcting translation results in MS Word. Our system is mainly intended for language students, therefore, we also offer the display of detailed information about linguistic and translation knowledge, in particular token lists, parse trees, translation rules, and a single step trace mode to provide a better understanding of the translation process.
Scalable Distributed Organizations for Ultra-Large-Scale Software
Authors: Daniel J. Paulish
Venue: Proceedings of the International Workshop on Software Technologies for Ultra-Large-Scale Systems (2007)

Achieving ultra-large-scale software systems will necessarily require new organizational structures and processes. This position paper suggests an approach in which large systems are decomposed into smaller components that can be implemented by small teams. A collection of small development teams is then organized such that communications are profiled and controlled as reflected by the system architecture. Although such organization structures are far from optimal, they can help us achieve a next step and gain insights for implementing future ultra-large-scale software systems.
A Bottom-Up Approach to Task Scheduling on Distributed Memory Multiprocessors
Authors: Neelima Mehdiratta, Kanad Ghose
Venue: Proceedings of the 1994 International Conference on Parallel Processing - Volume 02 (1994)

This paper presents a new approach to statically schedule parallel programs modeled as Directed Acyclic Graphs (DAGs) on various distributed memory multi-processor topologies represented as processor graphs to reduce the overall execution time of the program. The scheduler factors in the processor topology, communication delays and delays due to channel conflicts for scheduling. Our scheme differs dramatically from existing schedulers in that tasks of the DAG are scheduled bottom up. Experimental results presentedfor message switched systems using the hypercube and torus topologies show the effectiveness of our scheme. Our scheme can also be adapted for other topologies and routing schemes such as wormhole routing and circuit switching.
A comparison of OS extension technologies
Authors: Christopher Small, Margo Seltzer
Venue: Proceedings of the 1996 annual conference on USENIX Annual Technical Conference (1996)

The current trend in operating systems research is to allow applications to dynamically extend the kernel to improve application performance or extend functionality, but the most effective approach to extensibility remains unclear. Some systems use safe languages to permit code to be downloaded directly into the kernel; other systems provide in-kernel interpreters to execute extension code; still others use software techniques to ensure the safety of kernel extensions. The key characteristics that distinguish these systems are the philosophy behind extensibility and the technology used to implement extensibility. This paper presents a taxonomy of the types of extensions that might be desirable in an extensible operating system, evaluates the performance cost of various extension technologies currently being employed, and compares the cost of adding a kernel extension to the benefit of having the extension in the kernel. Our results show that compiled technologies (e.g. Modula-3 and software fault isolation) are good candidates for implementing general-purpose kernel extensions, but that the overhead of interpreted languages is sufficiently high that they are inappropriate for this use.
A new edge-adaptive demosaicing algorithm for color filter arrays
Authors: Chi-Yi Tsai, Kai-Tai Song
Venue: Image and Vision Computing (2007)

A novel edge-adaptive demosaicing algorithm (EADA) is proposed in this paper to effectively reduce color artifacts in demosaiced images from a color filter array (CFA). The proposed algorithm aims to reduce the aliasing error in red and blue channels by exploiting high-frequency information of the green channel. To achieve this, color-difference based edge-adaptive filtering and post-processing schemes are designed to reproduce the color values by exploiting the green channel information. For green channel interpolation, any of the existing image interpolation methods can be used and combined with the proposed algorithm. Moreover, a new adaptive interpolation method is presented for reconstructing the green channel from CFA samples. We have compared this technique with two recently proposed demosaicing techniques: Gunturk's and Lu's methods. The experimental results show that EADA outperforms both of them in both PSNR values and CIELAB @DE"a"b^* measures.
Large Area Sensor Skin based on Two-Dimensional Signal Transmission Technology
Authors: Hiromasa Chigusa, Yasutoshi Makino, Hiroyuki Shinoda
Venue: Proceedings of the Second Joint EuroHaptics Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (2007)

In this paper, we propose a stretchable large area sensor skin based on Two-Dimensional Signal Transmission (2DST) technology. A small tactile sensor chip with stable non-contact connectors (Resonant Proximity Connector: RPC) to a 2DST sheet is developed. The sensor nodes communicate by microwave that propagates in a two-dimensional sheet. Sensor nodes connect to the 2DST sheet via RPCs without electrical contact anywhere on the sheet and also receive the power for operation from the microwave in the sheet. RPC is a spiral electrode whose total length is a quarter of the electromagnetic wavelength. The induced resonance around the electrode reduces the impedance between the connector and 2DST sheet, which allows sensor chips to connect to the 2DST sheet stably. Simulation results on spiral RPCs show that the concept is effective. We produce an on-off type tactile sensor element which consists of a RFID-tag and RPC, and experimentally confirm that the sensor element works in a stretchable 2DST sheet.
The design and performance of MedJava: a distributed electronic medical imaging system developed with java applets and web tools
Authors: Prashant Jain, Seth Widoff, Douglas C. Schmidt
Venue: Proceedings of the 4th conference on USENIX Conference on Object-Oriented Technologies and Systems - Volume 4 (1998)

The Java programming language has gained substantial popularity in the past two years. Java's networking features, along with the growing number of Web browsers that execute Java applets, facilitate Internet programming. Despite the popularity of Java, however, there are many concerns about its efficiency. In particular, networking and computation performance are key concerns when considering the use of Java to develop performance-sensitive distributed applications. This paper makes three contributions to the study of Java for performance-sensitive distributed applications. First, we describe an architecture using Java and the Web to develop Med-Java, which is a distributed electronic medical imaging system with stringent networking and computation requirements. Second, we present benchmarks of MedJava image processing and compare the results to the performance of xv, which is an equivalent image processing application written in C. Finally, we present performance benchmarks using Java as a transport interface to exchange large medical images over high-speed ATM networks. For computationally intensive algorithms, such as image filters, hand-optimized Java code, coupled with use of a JIT compiler, can sometimes compensate for the lack of compile-time optimization and yield performance commensurate with identical compiled C code. With rigorous compile-time optimizations employed, C compilers still tend to generate more efficient code. However, with the advent of highly optimizing Java compilers, it should be feasible to use Java for the performance-sensitive distributed applications where C and C++ are currently used.
Transportation Quality Monitor Using Sensor Active RFID
Authors: Kohei Mizuno, Masashi Shimizu
Venue: Proceedings of the 2007 International Symposium on Applications and the Internet Workshops (2007)

A number of pilot tests have been done to confirm RFID's performance at the supply chain managements. In these cases, RFID work as the bar cord systems that can connect their IDs to databases. The passive RFID system has been used in these pilot tests to meet the severe cost requirements. The result of these tests pointed out some week points of passive tags as 1)Communication range changes depend on material 2)Reader and Tags antenna pattern make null position 3)Reflection waves come from wall and ceiling make null position. The active RFID systems are expected to solve for these points. Additionally sensor capability can be loaded. We made sensor active RFID with LF (Low Frequency) module and installed these active RFIDs in an actual container to acquire movement history and the sensor data. As a result, we find our sensor active tag has the capability to acquire a movement history easily with low power consumption without GPS.
A Statistical Approach to Model-Based Robustness Testing
Authors: Miroslav Popovic, Jelena Kovacevic
Venue: Proceedings of the 14th Annual IEEE International Conference and Workshops on the Engineering of Computer-Based Systems (2007)

Recent massive research in the area of robustness testing of communication protocols have been driven by the fact that embedded systems are becoming more and more complex every day. Providing correct implementations of communication protocols is a key to successful interconnection of embedded system constituents. Test and verification is the last and the most critical phase in the production of the corresponding software artifacts. This paper contributes to the overall research effort in the area by proposing an original approach to model-based robustness testing of communication protocols. In the paper we introduce the notion of hidden FSM states and state transitions. We also show how to calculate the probabilities of detecting the existence of the hidden state transitions. Then we present our methodology of model-based robustness testing of communication protocols. The methodology is based on the special operational profiles, which are referred to as the stress operational profiles.
A new Unitary ESPRIT-based technique for direction finding
Authors: M. Haardt
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 05 (1999)

A new pseudo-noise resampling technique is proposed to mitigate the effect of outliers in Unitary ESPRIT. This scheme improves the performance of Unitary ESPRIT in unreliable situations, where the so-called reliability test has a failure. For this purpose, we exploit a pseudo-noise resampling of a failed Unitary ESPRIT estimator with a censored selection of "successful" resamplings recovering the non-failed outputs of the reliability test.
Building effective industrial relationships: the Foundation Coalition experience
Authors: J. E. Froyd
Venue: Proceedings of the Frontiers in Education Conference on 1995. Proceedings., 1995 vol 1. - Volume 01 (1995)

The focus of industrial relationships for the Foundation Coalition in its first two years has been different by design at the coalition level and the individual institutional level. At the coalition level, a National Advisory Board was formed with a broadly defined role that includes providing input relevant to the Coalition's vision and long-range strategic directions; providing input on desired student outcomes to guide curriculum development; and helping promote acceptance and support of curriculum change among the various affected constituencies. The Board has provided assistance in defining student outcomes, strategic planning, budgeting, and locating internships for Coalition students. Future plans are to involve the Board more in development efforts to obtain financial matching support from industry and private foundations. At the institutional level, industry interactions have focused on specific activities to bring industry personnel to campus and vice versa, i.e. to give students and faculty the opportunity to visit various industries. Industry visitors have been especially helpful in establishing and increasing support for the Coalition goals and programs among students and faculty at individual institutions. Some of the industry visits arranged by individual schools have been expanded when appropriate to include representation from multiple Coalition schools. The Coalition continues to attempt to expand and better utilize the industrial interactions outlined above, particularly its interactions with the National Advisory Board.
Biometric authentication revisited: understanding the impact of wolves in sheep's clothing
Authors: Lucas Ballard, Fabian Monrose, Daniel Lopresti
Venue: Proceedings of the 15th conference on USENIX Security Symposium - Volume 15 (2006)

Biometric security is a topic of rapidly growing importance, especially as it applies to user authentication and key generation. In this paper, we describe our initial steps towards developing evaluation methodologies for behavioral biometrics that take into account threat models which have largely been ignored. We argue that the pervasive assumption that forgers are minimally motivated (or, even worse, naïve), or that attacks can only be mounted through manual effort, is too optimistic and even dangerous. To illustrate our point, we analyze a handwriting-based key-generation system and show that the standard approach of evaluation significantly overestimates its security. Additionally, to overcome current labor-intensive hurdles in performing more accurate assessments of system security, we present a generative attack model based on concatenative synthesis that can provide a rapid indication of the security afforded by the system. We show that our generative attacks match or exceed the effectiveness of forgeries rendered by the skilled humans we have encountered.
Oscillation criteria for boundary value problems of high-order partial functional differential equations
Authors: Peiguang Wang, Yonghong Wu, Lou Caccetta
Venue: Journal of Computational and Applied Mathematics (2007)

In this paper, a class of boundary value problems associated with high-order partial functional differential equations with distributed deviating arguments is investigated. Some oscillation criteria of solutions to the problem are developed. Our approach is to reduce the multi-dimensional oscillation problem to a one-dimensional oscillation one by employing some integral means of solutions and introducing some parameter functions. One illustrative example is considered.