ppxscal/embedding_network huggingface dataset:
Data structures for limited oblivious execution of programs while preserving locality of reference
Authors: Avinash V. Varadarajan, Ramarathnam Venkatesan, C. Pandu Rangan
Venue: Proceedings of the 2007 ACM workshop on Digital Rights Management (2007)

We introduce a data structure for program execution under a limited oblivious execution model. For fully oblivious execution along the lines of Goldreich and Ostrovsky [2], one transforms a given program into a one that has totally random looking execution, based on some cryptographic assumptions and the existence of secure hardware. Totally random memory access patterns do not respect the locality of reference in programs to which the programs generally owe their efficiency. We propose a model that limits the obliviousness so as to enable efficient execution of the program; here the adversary marks a variable and tries to produce a list of candidate locations where it may be stored in after $T$-steps ofexecution. We propose a randomized algorithm based on splay trees,and prove a lower bound on such lists.
High Performance MPI over iWARP: Early Experiences
Authors: S. Narravula, A. Mamidala, A. Vishnu, G. Santhanaraman, D. K. Panda
Venue: Proceedings of the 2007 International Conference on Parallel Processing (2007)

Modern interconnects and corresponding high performance MPIs have been feeding the surge in the popularity of compute clusters and computing applications. Recently with the introduction of the iWARP (Internet Wide Area RDMA Protocol) standard, RDMA and zero-copy data transfer capabilities have been introduced and standardized for Ethernet networks. While traditional Ethernet networks had largely been limited to the traditional kernel based TCP/IP stacks and hence their limitations, iWARP capabilities of the newer GigE and 10 GigE adapters have broken this barrier and thereby exposing the available potential performance. In order to enable applications to harness the performance benefits of iWARP and to study the quantitative extent of such improvements, we present MPI-iWARP, a high performance MPI implementation over the Open Fabrics verbs. Our preliminary results with Chelsio T3B adapters show an improvement of up to 37% in bandwidth, 75% in latency and 80% in MPI allreduce as compared to MPICH2 over TCP/IP. To the best of our knowledge, this is the first design, implementation and evaluation of a high performance MPI over the iWARP standard.
Knowledge-based modelling of voting protocols
Authors: A. Baskar, R. Ramanujam, S. P. Suresh
Venue: Proceedings of the 11th conference on Theoretical aspects of rationality and knowledge (2007)

We contend that reasoning about knowledge is both natural and pragmatic for verification of electronic voting protocols. We present a model in which desirable properties of elections are naturally expressed using standard knowledge operators, and show that the associated logic is decidable (under reasonable assumptions of bounded agents and nonces).
Omni-directional Vision Localization Based on Particle Filter
Authors: Zuoliang Cao, Shiyu Liu, Juha Roning
Venue: Proceedings of the Fourth International Conference on Image and Graphics (2007)

Omni-directional vision navigation appears definite significant since its advantage of panoramic sight with a single compact visual scene. This unique guidance technique involves target recognition, vision tracking, object positioning, path programming. An algorithm for omni-vision based global localization which utilizes two overhead features as beacon pattern is proposed in this paper. An approach for geometric restoration of omni-vision images has to be considered since an inherent distortion exists. The localization of the robot can be achieved by geometric computation. Dynamic localization employs a beacon tracker to follow the landmarks in real time during the arbitrary movement of the vehicle. Particle filter (PF) has been shown to be successful for several nonlinear estimation problems. A beacon tracker based on Particle Filter which offers a probabilistic framework for dynamic state estimation in visual tracking has been developed. We have implemented the tracking and localization system and demonstrated the relevant of the algorithm.
An Empirical Study of a Syntactic Complexity Family
Authors: V. R. Basili
Venue: IEEE Transactions on Software Engineering (1983)

A family of syntactic complexity metrics is defined that generates several metrics commonly occurring in the literature. The paper uses the family to answer some questions about the relationship of these metrics to error-proneness and to each other. Two derived metrics are applied; slope which measures the relative skills of programmers at handling a given level of complexity and r square which is indirectly related to the consistency of performance of the programmer or team. The study suggests that individual differences have a large effect on the significance of results where many individuals are used. When an individual is isolated, better results are obtainable. The metrics can also be used to differentiate between projects on which a methodology was used and those on which it was not.
On-Line Periodic Self-Testing of High-Speed Floating-Point Units in Microprocessors
Authors: G. Xenoulis, M. Psarakis, D. Gizopoulos, A. Paschalis
Venue: Proceedings of the 22nd IEEE International Symposium on Defect and Fault-Tolerance in VLSI Systems (2007)

On-line periodic testing of microprocessors is a viable low-cost alternative for a wide variety of embedded systems which cannot afford hardware or software redundancy techniques but necessitate the detection of intermittent or permanent faults. Low-cost, on-line periodic testing has been pre- viously applied to the integer datapaths of microprocessors but not to their high-performance real number processing counterparts consisting of sophisticated high-speed floating-point (FP) units. In this paper, we present, an effective on-line periodic self-testing methodology for high-speed FP units and demonstrate it on high-speed FP adders/subtractors of both single and double preci- sion. The proposed self-test code development methodology leads to compact self-test routines that exploit the integer part of the processors instruction set architecture to apply test sets to the FP sub- system periodically. The periodic self-test routines exhibit very low memory storage requirements along with a very small number of memory references which are both fundamental requirements for on-line periodic testing. A comprehensive set of experiments on both single and double precision FP units including pipelined versions, and on a RISC processor with a complete FP unit demon- strate the efficacy of the methodology in terms of very high fault coverage and low memory footprint thus rendering the proposed methodology highly appropriate for on-line periodic testing.
Routing Queries through a Peer-to-Peer InfoBeacons Network Using Information Retrieval Techniques
Authors: Sangeetha Seshadri, Brian F. Cooper
Venue: IEEE Transactions on Parallel and Distributed Systems (2007)

In the InfoBeacons system, a peer-to-peer network of beacons cooperates to route queries to the best information sources. Many internet sources are unwilling to provide more cooperation than simple searching to aid in the query routing.We adapt techniques from information retrieval to deal with this lack of cooperation. In particular, beacons determine how to route queries based on information cached from sources’ responses to queries. In this paper, we examine alternative architectures for routing queries between beacons and to data sources. We also examine how to improve the routing by probing sources in an informed way to learn about their content. Results of experiments using a beacon network to search 2,500 information sources demonstrates the effectiveness of our system; for example, our techniques require contacting up to 71 percent fewer sources than existing peer-to-peer random walk techniques.
Entropy-Based Epistasy Search in SNP Case-Control Studies
Authors: Amir Manzour, Mohammad Saraee
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 03 (2007)

The purpose of gene mapping is to identify the causal genetic regions of a specific phenotype mainly a complex disease. Most complex diseases are believed to have multiple contributing loci often having subtle patterns which make them fairly difficult to find in large datasets. We present and discuss a new criterion called conditional mutual information for association mapping and compare it to the previous criterion which is mutual information from different aspects. Furthermore, algorithms are proposed to find relevance chains. The proposed algorithms are especially in favor of diseases having almost equally contributing regions known as being epistatic. These algorithms are applied to both simulated and real data. The real data represents the genotype-phenotype values for AMD disease. Proposed relevance-chain algorithms have detected some highly associated markers with AMD. C# source files for relevance- chains algorithm are freely available at https://www.sharemation.com/amanzour.
Image with Less InformationWatermarking Algorithm Based on DWT
Authors: Hou Yingkun, Zhu Xiangcai, Zhu Lili, Liu Mingxia
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 03 (2007)

In this paper two definitions which are respectively called white image and pseudo-binary image are given through certain mapping relations,we propose a white image and pseudo-binary image watermarking algorithm based on discrete wavelet transform(DWT).This algorithm directly embeds binary image watermarks into wavelet transformation domain of the white digital image and pseudo-binary image, inserted watermark realized the watermark information strong robustness under the guarantee of the highly transparent premise.Moreover,the algorithm is also suitable for the common text image watermark. The experimental results show that this algorithm is feasible.
SPANBRE: An Efficient Hierarchical Clustering Algorithm for Spatial Data with Neighborhood Relations
Authors: Yaqin Wang, Yue Chen, Minggui Qin, Yangyong Zhu
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 03 (2007)

Due to the attributes of the neighbors are always similar or associated to each other, we address the problem of discovering spatial relationships in spatial data through the identification of clusters based on spatial neighborhood relations. We present an efficient clustering algorithm called SPANBRE that generates high quality clusters in O(nlogn) time and in O(n2) message complexity. SPANBRE is kind of agglomerative hierarchical method. By using a sequence data structure, SPANBRE avoids the complex spatial join operation. SPANBRE also execute an optimization strategy for clustering splitting and merging to achieve high clustering quality. The experimental results on traffic flow data sets show that the clustering quality and the algorithm efficiency of SPANBRE are superior to other alternative techniques.
On Paper
Authors: Diomidis Spinellis
Venue: IEEE Software (2007)

Paper as a tool for expressing our thoughts offers superb usability and versatility, letting us mix various notations and multiple levels of abstraction. This makes it easier to pour out our thoughts on it. In contrast to software tools, paper doesn't provide feedback and won't interrupt us with various notifications. This gives us a chance to meditate on our design in a state of flow.
Using the Augmented Data Manipulator Network in PASM
Authors: H. J. Siegel
Venue: Computer (1981)

The ADM network, with its multiple paths between given inputs and outputs, could bring fast, cost-effective communications to PASM and other distributed/parallel systems.
Development of Single Sign-On System with Hardware Token and Key Management Server
Authors: Daiki Nobayashi, Yutaka Nakamura, Takeshi Ikenaga, Yoshiaki Hori
Venue: Proceedings of the Second International Conference on Systems and Networks Communications (2007)

With the growth of the Internet, various types of services, such as World Wide Web (WWW), File Transfer Protocol (FTP), remote login, etc., are widely expanded. Consequently it is difficult for users to manage all the authentication information, e.g., user ID/Password pairs, keys, and certificates, since the authentication information has been increased to use those services. Therefore, Single Sign-On (SSO) system, which makes all the services available for a user by only one-time authentication, has been developed. However, existing systems cannot provide all the SSO services for any kinds of services on the Internet even if the service provider deploys the SSO server. Therefore, in this paper, we propose a new SSO system with hardware token and key management server to improve the safety and the convenience. Furthermore, we implement the proposed system, and show its effectiveness through evaluation. In addition, adding any functions for this system provide various conveniences to us. As one example, we add high trust connection function for a Web server, and show its the effectiveness through evaluation by implementing it.
Study on Linked List-based Algorithm for Metarule-guided Mining of Multidimensional Quantitative Association Rules
Authors: Jinze Li, Xiaojun Ye
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 01 (2007)

Grid-based algorithms for quantitative association rule mining are high efficient, but they are fundamentally low dimension oriented. This paper extends the grid-based concept and proposes a metarule-guided generalized linked list-based algorithm aimed to mine multidimensional quantitative association rules from relational databases. Based on the metarule, the algorithm stores data tuples into the linked lists and mining is acted upon these linked lists. Experimental results show that our solution is size and dimensions scalable linearly. A math model is also introduced to endow the association rules with some prediction functions, which can be considered as an extension to the classification functions of association rules.
A Distributed Connectivity Restoration Algorithm in Wireless Sensor and Actor Networks
Authors: Ameer Ahmed Abbasi, Kemal Akkaya, Mohamed Younis
Venue: Proceedings of the 32nd IEEE Conference on Local Computer Networks (2007)

There has been an increased interest in applications of wireless sensor and actor networks (WSANs) in recent years. In such applications, a set of mobile actor nodes are deployed in addition to sensors in order to collect sensors' data and perform specific tasks in response to detected events/objects. In most scenarios actors have to respond collectively which requires an inter-actor coordination. Therefore, maintaining a connected inter-actor network is crucial to the effectiveness of WSANs. However, WSANs often operate unattended in harsh environments where actors can easily fail or get damaged. Due to such failures an actor will be unable to communicate with its neighbors which may lead to partitioning the inter-actor network. In this paper we present DARA; a Distributed Actor Recovery Algorithm, which opts to efficiently restore the connectivity of the inter-actor network that has been affected by the failure of an actor. The idea is to identify the least set of actors that should be repositioned in order to establish connectivity among disjoint network partitions. DARA strives to localize the scope of the recovery process and minimize the movement overhead imposed on the involved actors. The effectiveness of DARA is validated through simulation experiments.
Computor Simulation of Narrowband Systems
Authors: R. A. Manske
Venue: IEEE Transactions on Computers (1968)

Abstract Any narrowband signal can be represented by two low-frequency functions, containing only frequencies lower than the bandwidth, which represent the envelopes of the in-phase (cosine) and quadrature ( sine) components of the carrier frequency. To obtain the transient response of a narrowband system efficiently by computer simulation, the system can be represented by a low-frequency equivalent system, avoiding time-consuming direct simulation of carrier frequencies. This paper presents techniques by which a wide variety of narrowband systems, expressible mathematically as block diagrams, can be converted into block diagrams consisting only of low-frequency functions. The resulting low-frequency equivalent systems can be simulated on either an analog or digital computer by well-known techniques. Although the low-frequency equivalent representation presented here includes an extension of the bandpass low-pass analogy, it is not subject to many of the restrictions normally applied to this analogy. It is not necessary that the modulation be simple AM, that the filtering be symmetrical, or that only the envelope velope of the output be of interest.
Graphic Design for Computer Graphics
Authors: Aaron Marcus
Venue: IEEE Computer Graphics and Applications (1983)

In concentrating on developing the computer's internal electronic communicative abilities, we have neglected the interface between the machine's display surface and the human viewer.
Detecting change in data streams
Authors: Daniel Kifer, Shai Ben-David, Johannes Gehrke
Venue: Proceedings of the Thirtieth international conference on Very large data bases - Volume 30 (2004)

Detecting changes in a data stream is an important area of research with many applications. In this paper, we present a novel method for the detection and estimation of change. In addition to providing statistical guarantees on the reliability of detected changes, our method also provides meaningful descriptions and quantification of these changes. Our approach assumes that the points in the stream are independently generated, but otherwise makes no assumptions on the nature of the generating distribution. Thus our techniques work for both continuous and discrete data. In an experimental study we demonstrate the power of our techniques.
Single-Trial Visual Evoked Potentials Estimation Using Support Vector Machine
Authors: Jinping Liu
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 02 (2007)

Exploiting the novel human-machine interaction paradigm called brain-computer interface, we developed a mental speller by constructing a virtual keyboard in a computer screen for those with neuromuscular disorders and motor disabilities. The carriers of communication between brain and computer were induced by a so-called "imitating-natural-reading" paradigm. Single-trial feature estimation should be used in this online paradigm instead of grand average that usually used in the cognitive or clinical experiments. With carefully signal preprocess and feature selection procedure, we explored the single-trial estimation of EEG using í-support vector machine in three subjects, and gained a satisfied classification accuracy of 92.6%, 88.2% and 93.5%, respectively. These results demonstrated the advantages of the inducing paradigm in the construction of our mental speller.
On-line neural training algorithm with sliding mode control and adaptive learning rate
Authors: A. Nied, S. I. Seleme,  Jr., G. G. Parma, B. R. Menezes
Venue: Neurocomputing (2007)

This paper presents a new algorithm for on-line artificial neural networks (ANN) training. The network topology is a standard multilayer perceptron (MLP) and the training algorithm is based on the theory of variable structure systems (VSS) and sliding mode control (SMC). The main feature of this novel procedure is the adaptability of the gain (learning rate), which is obtained from sliding mode surface so that system stability is guaranteed.
Overcoming registration uncertainty in image super-resolution: maximize or marginalize?
Authors: Lyndsey C. Pickup, David P. Capel, Stephen J. Roberts, Andrew Zisserman
Venue: EURASIP Journal on Advances in Signal Processing (2007)

In multiple-image super-resolution, a high-resolution image is estimated from a number of lower-resolution images. This usually involves computing the parameters of a generative imaging model (such as geometric and photometric registration, and blur) and obtaining a MAP estimate by minimizing a cost function including an appropriate prior. Two alternative approaches are examined. First, both registrations and the super-resolution image are found simultaneously using a joint MAP optimization. Second, we perform Bayesian integration over the unknown image registration parameters, deriving a cost function whose only variables of interest are the pixel values of the super-resolution image. We also introduce a scheme to learn the parameters of the image prior as part of the super-resolution algorithm. We show examples on a number of real sequences including multiple stills, digital video, and DVDs of movies.
Challenges and Directions for Semantic Communication
Authors: Volkan Rodoplu, Snehal S. Vadvalkar
Venue: Proceedings of the International Conference on Semantic Computing (2007)

This paper aims to present ideas to bridge the gap between two conflicting views of information: Shannon information, which is used to model physical layer information, and semantic information, which is used in databases, distributed systems, human-computer interaction, and in the application layer of the OSI communication stack. We introduce the notion of a semantic domain, and define the amount of semantic information relative to a semantic domain. We show that translations between semantic domains achieve a consistent picture of semantic information. We indicate where and how the conceptual divide occurs between semantic information and Shannon information. We discuss mobile devices and users and a central server, as a possible setting for the application of the concepts developed in this paper. The discussion is aimed at pointing out the need for a unified theory, and at directions for how such a theory can be pursued.
Visual languages and quality evaluation in multichannel adaptive information systems
Authors: C. Batini, E. Bertini, M. Comerio, A. Maurino, G. Santucci
Venue: Journal of Visual Languages and Computing (2007)

Multichannel Adaptive Information Systems (ISs) are becoming the new paradigm for building complex interorganization ISs based on the use of different devices, Web services, and XML specifications. Modeling Multichannel Adaptive ISs requires complex interactions between the users and the system front-end due to the different capabilities of existing devices. Unfortunately, the expressive power and effectiveness of visual languages have not been fully exploited in this new area. In this paper we address two related issues. First we propose a visual language that allows for adapting the presentation layer to different physical devices; then we describe a technique to evaluate possible tradeoffs between usability and other qualities of service in Web services design.
Mapping Real Time Operating System on Reconfigurable Instruction Cell Based Architectures
Authors: Han Wei, Mark Muir, Ioannis Nousias, Tughrul Arslan, Ahmet T. Erdogan
Venue: Proceedings of the 15th Annual IEEE Symposium on Field-Programmable Custom Computing Machines (2007)

This paper presents the porting of an RTOS Micro C/OS-II on a novel reconfigurable instruction cell based architecture which fills the gap between DSP, FPGA and ASIC with high performance, high flexibility and ANSI-C support. WiMAX physical layer program has been implemented on the target architecture with the RTOS support. A semaphore based synchronization scheme is used to improve the task independence. The research lays a foundation for further exploration of multithreading on multiple target architectures.