ppxscal/embedding_network huggingface dataset:
External memory page remapping for embedded multimedia systems
Authors: Ke Ning, David Kaeli
Venue: ACM SIGPLAN Notices (2007)

As memory speeds and bus capacitances continue to rise, external memory bus power will make up an increasing portion of the total system power budget for system-on-a-chip embedded systems. Both hardware and software approaches can be explored to balance the power/performance tradeoff associated with the external memory. In this paper we present a hardware-based, programmable external memory page remapping mechanism which can significantly improve performance and decrease the power budget due to external memory bus accesses. Our approach was developed by studying common data access patterns present in embedded multimedia applications. In the paper, we evaluate a mechanism that can perform page remapping of external memory. We also develop an efficient algorithm to map application data and instruction memory into external memory pages. We employ graph-coloring techniques to guide the page mapping procedure. The objective is to avoid page misses by remapping conflicting pages to different memory banks (i.e., by assigning them different colors). Our algorithm can significantly reduce the memory page miss rate by 70-80% on average. For a 4-bank SDRAM memory system, we reduced external memory access time by 12.6%. The proposed algorithm can reduce power consumption in majority of the benchmarks, averaged by 13.2% of power reduction. Combining the effects of both power and delay, our algorithm can benefit significantly to the total energy cost.
Construction of a Webportal and User Management Framework for Grid
Authors: Lichun Zhu, Robert D. Kent, Akshai Aggarwal, Peiris Viranthi, Quazi Rahman, Tarik Elamsy, Ositadimma Ejelike
Venue: Proceedings of the 21st International Symposium on High Performance Computing Systems and Applications (2007)

User management is a vital problem to be solved when constructing a webportal for accessing grid resources. Most current approaches treat web and grid users separately. This is inconvenient to the system users. This paper presents a user management framework that combines the two kinds of user management. It also supports Single Sign- On and federated identity service through integration of different technologies such as Shibboleth, MyProxy and PURSe portlets.
FLIPC: a low latency messaging system for distributed real time environments
Authors: David L. Black, Randall D. Smith, Steven J. Sears, Randall W. Dean
Venue: Proceedings of the 1996 annual conference on USENIX Annual Technical Conference (1996)

FLIPC is a new messaging system intended to support distributed real time applications on high performance communication hardware. Application messaging systems designed for high performance computing environments are not well suited to other environments because they lack support for the complex application structures involving multiple processes, threads, and classes of message traffic found in environments such as distributed real time. These messaging systems also have not been optimized for medium size messages found in important classes of real time applications. FLIPC includes additional features to support applications outside the high performance computing domain. For medium size messages, our system significantly outperforms other messaging systems on the Intel Paragon. An explicit design focus on programmable communication hardware and the resulting use of wait-free synchronization was a key factor in achieving this level of performance. The implementation of FLIPC was accelerated by our use of PC clusters connected by ethernet or by a SCSI bus as development platforms to reduce the need for Paragon time.
Provably secure chipcard personalization, or, how to fool malicious insiders
Authors: Helena Handschuh, David Naccache, Pascal Paillier, Christophe Tymen
Venue: Proceedings of the 5th conference on Smart Card Research and Advanced Application Conference - Volume 5 (2002)

We present 'malicious insider attacks' on chip-card personalization processes and suggest an improved way to securely generate secret-keys shared between an issuer and the user's smart card. Our procedure which results in a situation where even the card manufacturer producing the card cannot determine the value of the secret-keys that he personalizes into the card, uses public key techniques to provide integrity and privacy of the generated keys with respect to the complete initialisation chain. Our solution, which provides a noninteractive alternative to authenticated key agreement protocols, achieves provable security in the random oracle model under standard complexity assumptions. Our mechanism also features a certain genericity and, when coupled to a cryptosystem with fast encryption like RSA, allows low-cost intrusion-secure secret key generation.
2007 Special Issue: Nonlinear principal component analysis of noisy data
Authors: William W. Hsieh
Venue: Neural Networks (2007)

With very noisy data, having plentiful samples eliminates overfitting in nonlinear regression, but not in nonlinear principal component analysis (NLPCA). To overcome this problem in NLPCA, a new information criterion (IC) is proposed for selecting the best model among multiple models with different complexity and regularization (i.e. weight penalty). This IC gauges the inconsistency I between the nonlinear principal components (u and u@?) for every data point x and its nearest neighbour x@?, with I=1-correlation(u,u@?), where I tends to increase with overfitted solutions. Tests were performed using autoassociative neural networks for NLPCA on synthetic and real climate data (tropical Pacific sea surface temperatures and equatorial stratospheric winds), with the IC performing well in model selection and in deciding between an open curve or a closed curve solution.
Building an application-aware IPsec policy system
Authors: Heng Yin, Haining Wang
Venue: Proceedings of the 14th conference on USENIX Security Symposium - Volume 14 (2005)

As a security mechanism at the network-layer, the IP security protocol (IPsec) has been available for years, but its usage is limited to Virtual Private Networks (VPNs). The end-to-end security services provided by IPsec have not been widely used. To bring the IPsec services into wide usage, a standard IPsec API is a potential solution. However, the realization of a user-friendly IPsec API involves many modifications on the current IPsec and Internet Key Exchange (IKE) implementations. An alternative approach is to configure application-specific IPsec policies, but the current IPsec policy system lacks the knowledge of the context of applications running at upper layers, making it infeasible to configure application-specific policies in practice. In this paper, we propose an application-aware IPsec policy system on the existing IPsec/IKE infrastructure, in which a socket monitor running in the application context reports the socket activities to the application policy engine. In turn, the engine translates the application policies into the underlying security policies, and then writes them into the IPsec Security Policy Database (SPD) via the existing IPsec policy management interface. We implement a prototype in Linux (Kernel 2.6) and evaluate it in our testbed. The experimental results show that the overhead of policy translation is insignificant, and the overall system performance of the enhanced IPsec is comparable to those of security mechanisms at upper layers. Configured with the application-aware IPsec policies, both secured applications at upper layers and legacy applications can transparently obtain IP security enhancements.
An empirical study of programmer learning during incremental software development
Authors: Shaochun Xu, V. Rajlich, A. Marcus
Venue: Proceedings of the Fourth IEEE International Conference on Cognitive Informatics (2005)

The paper presents a case study that investigates programmer learning during incremental program development. Dialog based protocol and protocol analysis are used to explore the learning from the point of view of self-directed learning theory. The replicated case study confirmed that the Bloom's levels of cognitive domain and the cognitive activities of absorption, denial, reorganization, and expulsion characterize the programmer learning and give insight into the differences between experts and intermediate level programmers.
Computer use and the gender gap: The issue of access, use, motivation, and performance
Authors: Margarete Imhof, Regina Vollmeyer, Constanze Beierlein
Venue: Computers in Human Behavior (2007)

Since the beginning of computerization, it has been of interest whether there are differential effects on computer behavior, in particular in terms of computer access, computer use, and motivational variables, such as computer self-efficacy. The current research addresses the questions if the gender-related differences in this respect persist to the present day and if there is also a difference in actual performance characteristics. A sample of 48 university students (23 male) was administered a technology self-efficacy questionnaire, a survey on computer access, recorded a user diary, and turned in a computer task. Results show that the gender gap is closing as far as computer access and self-efficacy are concerned. Also, female and male students report comparable amounts of computer usage for their studies. User behavior appears to be gender-specific as males spend more time at the computer for personal purposes. There is also some evidence that male students outperform female students at a computer task (remastering of Power-Point slides). Conclusions for creating computer-based learning environments are discussed.
Program explorer: a program visualizer for C++
Authors: Danny B. Lange, Yuichi Nakamura
Venue: Proceedings of the USENIX Conference on Object-Oriented Technologies on USENIX Conference on Object-Oriented Technologies (COOTS) (1995)

Despite the obvious advantages of using object-oriented (O-O) program visualizers in system understanding and debugging, they are still rarely found in the programmers's tool box. One reason for this that such visualizers often fail because of their inability to handle problems of a realistic scale. In our research, we have addressed the scalability problem by integrating static and dynamic program information to produce abstract and yet accurate views of complex O-O systems that often provide more useful information than can be obtained by reading the source code. This is the approach we followed in designing Program Explorer, a research prototype for C++ program visualization, which has been used to examine large O-O systems such as Stanford's Interviews library and Taligent's CommonPoint frameworks.
An End-To-End Approach to Distributed Policy Language Implementation
Authors: Tom Chothia, Dominic Duggan, Ye Wu
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2007)

Language-based security approaches to access control and information flow control must at some point rely on a language for expressing policies. However there will in general be several choices for the correct policy language for any given application, and several choices for the implementation of a policy language in a given domain. This article considers an approach to implementing the policy language at the application level, relying on trusted cryptographic libraries whose interface security guarantees are used to verify the correctness of the policy language implementation.
Recursive blind estimation and equalization of time-varying channel based on parametric model
Authors: Zheng Yuanjin
Venue: Proceedings of the The 8th International Conference on Communication Systems - Volume 01 (2002)

This paper proposes a new technique for recursive blind equalization of a time-varying IIR communication channel to obtain simultaneous estimation of channel impulse response and input symbols. The received sequences are represented as the output of a noisy non-Gaussian time-varying parametric model. A pseudo maximum likelihood estimation algorithm is proposed for the identification of channel parameters. The blind equalization is implemented by three algorithms: the recursive channel estimation algorithm, the Gaussian-mixture parameter estimation algorithm and the standard Kalman filtering algorithm. The equalization results are good even on low SNR received sequence and fast fading channel. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
2007 Special Issue: Automatic speech recognition using a predictive echo state network classifier
Authors: Mark D. Skowronski, John G. Harris
Venue: Neural Networks (2007)

We have combined an echo state network (ESN) with a competitive state machine framework to create a classification engine called the predictive ESN classifier. We derive the expressions for training the predictive ESN classifier and show that the model was significantly more noise robust compared to a hidden Markov model in noisy speech classification experiments by 8+/-1 dB signal-to-noise ratio. The simple training algorithm and noise robustness of the predictive ESN classifier make it an attractive classification engine for automatic speech recognition.
Anypoint: extensible transport switching on the edge
Authors: Kenneth G. Yocum, Darrell C. Anderson, Jeffrey S. Chase, Amin M. Vahdat
Venue: Proceedings of the 4th conference on USENIX Symposium on Internet Technologies and Systems - Volume 4 (2003)

Anypoint is a new model for one-to-many communication with ensemble sites-aggregations of end nodes that appear to the external Internet as a unified site. Policies for routing Any-point traffic are defined by application-layer plugins residing in extensible routers at the ensemble edge. Anypoint's switching functions operate at the transport layer at the granularity of transport frames. Communication over an Anypoint connection preserves end-to-end transport rate control, partial ordering, and reliable delivery. Experimental results from a host-based Anypoint prototype and an NFS storage router application show that Anypoint is a powerful technique for virtualizing and extending cluster services, and is amenable to implementation in high-speed switches. The Anypoint prototype improves storage router throughput by 29% relative to a TCP proxy.
Understanding the design space of referencing in collaborative augmented reality environments
Authors: Jeffrey W. Chastine, Kristine Nagel, Ying Zhu, Luca Yearsovich
Venue: Proceedings of Graphics Interface 2007 (2007)

For collaborative environments to be successful, it is critical that participants have the ability to generate effective references. Given the heterogeneity of the objects and the myriad of possible scenarios for collaborative augmented reality environments, generating meaningful references within them can be difficult. Participants in co-located physical spaces benefit from non-verbal communication, such as eye gaze, pointing and body movement; however, when geographically separated, this form of communication must be synthesized using computer-mediated techniques. We have conducted an exploratory study using a collaborative building task of constructing both physical and virtual models to better understand inter-referential awareness -- or the ability for one participant to refer to a set of objects, and for that reference to be understood. Our contributions are not necessarily in presenting novel techniques, but in narrowing the design space for referencing in collaborative augmented reality. This study suggests collaborative reference preferences are heavily dependent on the context of the workspace.
Improving the suitability of imperfect transcriptions for information retrieval from spoken documents
Authors: M. Siegler
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 01 (1999)

There has been a considerable focus on information retrieval for multimedia databases. When speech is used as the source material for multimedia indexing, the effect of transcriber error on retrieval effectiveness must be considered. This paper describes a method for measuring the relevance of documents to queries when information about the probability of word transcription error is available. To support the use of this technique, a method is presented for estimating word error probability in speech recognition engines that use word graphs (lattices). An information retrieval experiment using this technique on a large corpus of spoken documents is discussed. The method was able to reduce the difference in retrieval effectiveness between reference texts and hypothesized texts by 13-38 % depending on the size of the document set.
Translating Mobile Ambients into P Systems
Authors: Aman Bogdan, Gabriel Ciobanu
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2007)

We present a translation of the mobile ambients without communication and replication into P systems with mobile membranes. We introduce a set of developmental rules over membranes, and describe the correspondence between the behaviour of an ambient and the evolution of its translated membrane system. We give an operational correspondence result between the mobile ambients and P systems.
Learning from data streams using transductive inference and martingale
Authors: Harry Wechsler
Venue:  (2006)

Streaming data, is ubiquitous, e.g., data generated from wireless sensor networks, web logs and click streams, ATM transactions, phone call records, and multimedia video data. One seeks to discover knowledge and to extract interesting patterns from the data stream. Such knowledge can be extremely useful for commercial, military, and home-land security purposes, among others. To ensure that what is learned is useful, one seeks to describe the data generating process using the best available model. This corresponds to model selection. Two questions that affect the model selection problem in an online data streaming setting are explored: those of contents ("what") and time ("when"): (1) What are the data points needed to build a good predictive model? (2) When does the data generation model change? These questions correspond to the active learning problem and change detection problem, respectively. The active learning problem involves the selection of informative but yet unlabeled data points to label. The solution to this problem aims to label a small [minimum] number of data points to build a good model. The change detection problem involves the recognition of deviation from the existing data generation model. The solution to this problem aims to detect the change as fast as possible. In this dissertation, an active learning strategy based on transductive inference and a change detection strategy using martingale are proposed. The contributions of this dissertation are as follows: (1) An active learning strategy based on transductive inference is proposed and justified. The active learning strategy is empirically shown to be feasible and compares favorably with other stream-based active learning strategies. (2) Change detection in data streams based on testing the exchangeability condition using martingale is proposed. The feasibility of the three proposed martingale tests for change detection is shown empirically on both labeled and unlabeled data points. The advantages of our novel one-pass incremental martingale change detection method are: it (i) does not require a sliding window on the data stream, (ii) does not require monitoring the explicit performance (e.g. classification error) as data points are streaming, and (iii) works well for high-dimensional data streams. The change detection method is used to implement (i) an online adaptive learning algorithm for labeled data streams, which compares favorably with a sliding window method; and (ii) a single-pass videoshot change detector for unlabeled video streams, which compares favorably to some standard off-line methods.
Improving the effectiveness of undergraduate teaching by integrating a historical perspective
Authors: M. M. Morcos
Venue: Proceedings of the 28th Annual Frontiers in Education - Volume 03 (1998)

Summary form only given. It is universally acknowledged that if the students like the instructor (and, of course, the way the material is taught and presented), they like the course and become enthusiastic to learn more from the teacher. There are many techniques on lecturing available in the literature, e.g. learn the students' names and use them; put long derivations in handouts (leave gaps) and spend most of the class time on teaching, don't write with the right hand and erase with the left; etc. One important technique is story telling. Students love stories, and a good teacher is a good story teller. However, there is seldom enough time to tell stories during the lecture period and at the same time cover the required course material. However, the history of the profession can be taught in a story-telling format. The best way to do that is to give the students some information about the pioneers in the field of the designated course. These individuals spent most of their lives trying to discover the secrets of that engineering field. These historical case studies can provide technical information, historical perspective, and motivation. One pioneer has been selected, by way of an example, whose contributions have led to the evolution of electrical engineering: Michael Faraday.
Texture features for DCT-coded image retrieval and classification
Authors: Yu-Len Huang
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 06 (1999)

The multiresolution wavelet transform has been shown to be an effective technique and achieved very good performance for texture analysis. However, a large number of images are compressed by methods based on the discrete cosine transform (DCT). Hence, the image decompression of the inverse DCT is needed to obtain the texture features based on the wavelet transform for the DCT-coded image. This paper proposes the use of the multiresolution reordered features for texture analysis. The proposed features are directly generated by using the DCT coefficients from the DCT-coded image. Comparisons with the subband-energy features extracted from the wavelet transform, conventional DCT using the Brodatz (1966) texture database indicate that the proposed method provides the best texture pattern retrieval accuracy and obtains a much better correct classification rate. The proposed DCT based features are expected to be very useful and efficient for texture pattern retrieval and classification in large DCT-coded image databases.
Directional processing of line-drawing images based on adaptive morphological operations
Authors: G. Agam
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 04 (1996)

Directional information has a strong meaning in line-drawing images. Therefore, the proposed approach for line-drawing images processing is based on a directional decomposition of the input image into a set of images each containing line segments in a respective range of directions. The directional information is then processed by using newly defined directional morphological operators, called tube-directional, that have accurate selectivity and controllable strictness. When using morphological operators, adaptation to a specific task is achieved only globally by setting the structure of the morphological kernel. The concept of one global adjustment for many local operations is some how conflicting. In the proposed approach the parameters of the tube-directional morphological operators are determined locally for each element of the processed image.