ppxscal/embedding_network huggingface dataset:
High-level Synthesis for Highly Concurrent Hardware Systems
Authors: Sunan Tugsinavisut, Roger Su, Peter A. Beerel
Venue: Proceedings of the Sixth International Conference on Application of Concurrency to System Design (2006)

This paper presents new approaches for high-level synthesis of highly concurrent hardware systems modeled with timed marked graphs. Unlike control data flow graphs (CDFGs) used in most high-level synthesis works, timed marked graphs can easily express highly concurrent hardware systems, including those with pipelined and multithreading behaviors. We first propose both exact and heuristic scheduling and allocation algorithms without considering binding. These algorithms, however, do not allow the cost associated with binding to be included. Thus, we propose concurrent scheduling and binding algorithms that include control complexity. Lastly, we describe and compare experimental results on a variety of digital signal processing (DSP) applications.
Achieving cooperation in multihop wireless networks of selfish nodes
Authors: Fabio Milan, Juan José Jaramillo, R. Srikant
Venue: Proceeding from the 2006 workshop on Game theory for communications and networks (2006)

In a multihop wireless network, routing a packet from source to destination requires cooperation among nodes. If nodes are selfish, reputation-based mechanisms can be used to sustain cooperation without resorting to a central authority. Within a hop-by-hop reputation-based mechanism, every node listens to its relaying neighbors, and the misbehaving ones are punished by dropping a fraction of their packets, according to a Tit-for-tat strategy. Packet collisions may prevent a node from recognizing a correct transmission, distorting the evaluated reputation. Therefore, even if all the nodes are willing to cooperate, the retaliation triggered by a perceived defection may eventually lead to zero throughput. A classical solution to this problem is to add a tolerance threshold to the pure Tit-for-tat strategy, so that a limited number of defections will not be punished. In this paper, we propose a game-theoretic model to study the impact of collisions on a hop-by-hop reputation-based mechanism for regular networks with uniform random traffic. Our results show that the Nash Equilibrium of a Generous Tit-for-tat strategy is cooperative for any admissible load, if the nodes are sufficiently far-sighted, or equivalently if the value for a packet to the nodes is sufficiently high with respect to the transmission cost. We also study two more severe punishment schemes, namely One-step Trigger and Grim Trigger, that can achieve cooperation under milder conditions.
Comparisons of K-Anonymization and Randomization Schemes under Linking Attacks
Authors: Zhouxuan Teng, Wenliang Du
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

Recently K-anonymity has gained popularity as a privacy quantification against linking attacks, in which attackers try to identify a record with values of some identifying attributes. If attacks succeed, the identity of the record will be revealed and potential confidential information contained in other attributes of the record will be disclosed. K-anonymity counters this attack by requiring that each record must be indistinguishable from at least K -1 other records with respect to the identifying attributes. Randomization can also be used for protection against linking attacks. In this paper, we compare the performance of K-anonymization and randomization schemes under linking attacks. We present a new privacy definition that can be applied to both k-anonymization and randomization. We compare these two schemes in terms of both utility and risks of privacy disclosure, and we promote to use R-U confidentiality map for such comparisons. We also compare various randomization schemes.
Building Blocks for a Smart Space for Learning^TM
Authors: Bernd Simon, Stefan Sobernig, Fridolin Wild, Sandra Aguirre, Stefan Brantner, Peter Dolog, Gustaf Neumann, Gernot Huber, Tomaz Klobucar, Sascha Markus, Zoltan Miklos, Wolfgang Nejdl, Daniel Olmedilla, Joaquin Salvachua, Michael Sintek, Thomas Zillinger
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

This case study summarizes the demonstration of a semantic network of interoperable educational systems referred to as Smart Space for Learning^TM. We started connecting several educational nodes in projects such as Elena, Prolearn, and Icamp. Integration was achieved by using the interaction standard SQI, common schemas for querying and results presentation, and query exchange language, e.g. QEL. The paper particularly focuses on how heterogeneous nodes can be made interoperable by reusing generalizations of mediating components -building blocks for a Smart Space for Learning^TM.
Identifying Multi-Word Terms by Text-Segments
Authors: Jisong Chen, Chung-Hsing Yeh, Rowena Chau
Venue: Proceedings of the Seventh International Conference on Web-Age Information Management Workshops (2006)

Traditional statistical approaches for identifying multi-word terms have to handle a large amount of noisy data and are extremely time consuming. This paper presents a new statistical approach for identifying multiword terms based on the co-related text-segments existing in a group of documents. The approach involves three stages: (a) using a short predefined stoplist as an initial input to segment a set of text documents into text-segments, (b) calculating the segment-weights of all text-segments, and (c) applying the short text-segments to segment the longer text-segments based on the weight values. The newly generated text-segments then segment each other again until all text-segments cannot be further divided. The resultant text-segments are identified as terms based on a specified threshold. The initial experimental result on a set of traditional Chinese documents shows that this approach can achieve a minimum of 76.39% of recall rate and a minimum of 91.05% of precision rate on retrieving multiple occurrences terms, including 18.30% of new identified terms. The approach can be applied to identify multi-word terms in any languages.
Improving Intrusion Detection Performance Using Rough Set Theory and Association Rule Mining
Authors: Wang Xuren, He Famei
Venue: Proceedings of the 2006 International Conference on Hybrid Information Technology - Volume 02 (2006)

Intrusion Detection System has some defects, such as signatures being generated manually, updating attack signatures difficultly and doing nothing in front of ultra data set. This paper presents a hybrid approaches for modeling IDS. Association rule mining and Rough set theory are combined as a hierarchical hybrid intelligent system model. The hybrid intrusion detection model combines association rule mining and rough set theory to improve detection accuracy and reduce false alarm, unreal alarm and computational complexity. Empirical results illustrate that the hybrid intrusion detection model can detect intrusion more accurately.
Image processing for teaching: transforming a scientific research tool into an educational technology
Authors: Richard Greenberg
Venue: Proceedings of the 1996 international conference on Learning sciences (1996)

The Image Processing for Teaching (IPT) project provides a powerful medium to excite students about science and mathematics, including children whose needs have not been met by traditional ways of teaching these subjects. It offers to all students open-ended opportunities for exploration, discovery, and quantitative analysis.
Stable and Accurate Network Coordinates
Authors: Jonathan Ledlie, Peter Pietzuch, Margo Seltzer
Venue: Proceedings of the 26th IEEE International Conference on Distributed Computing Systems (2006)

Network coordinates provide a scalable way to estimate latencies among large numbers of hosts. While there are several algorithms for producing coordinates, none account for the fact that nodes observe a stream of distinct observations that may vary by as much as three orders-ofmagnitude. With such variable data, coordinate systems are prone to high error and instability in live deployments. In addition, dynamics such as triangle violations can lead to coordinate oscillations, producing further instability and making it difficult for applications to know when their coordinates have truly changed. Because simulation results demonstrate that network coordinates are capable of providing low cost and sufficiently accurate answers to common queries, it is vital that we develop the ability to obtain similar results in practice. We propose two filters which combined to improve network coordinate accuracy by 54% and coordinate stability by 96% when run on a real, largescale network.
Measurement-based optimal routing on overlay architectures for unicast sessions
Authors: Tuna Güven, Richard J. La, Mark A. Shayman, Bobby Bhattacharjee
Venue: Computer Networks: The International Journal of Computer and Telecommunications Networking (2006)

We propose a measurement-based routing algorithm to load-balance intradomain traffic along multiple paths for multiple unicast sources. Multiple paths are established using overlay nodes. The distributed algorithm is derived from simultaneous perturbation stochastic approximation (SPSA) and does not assume that the gradient of an analytical cost function is known. Instead, we rely on (potentially) noisy estimates from local measurements. Using the analytical model presented in the paper, we first show the almost sure convergence of the algorithm to the optimal solution under a decreasing step size policy (as with a standard SPSA model). Motivated by practical concerns, we next consider the constant step size case, for which we establish weak convergence. We provide simulation results to demonstrate the advantages of our proposed algorithm under various network scenarios, and also present a comparative study with MATE (an existing optimal routing algorithm).
An experimental study on forecasting using TES processes
Authors: Abdullah S. Karaman, Tayfur Altiok
Venue: Proceedings of the 36th conference on Winter simulation (2004)

Forecasting is of prime importance for accuracy in decision making. For data sets containing high autocorrelations, failure to account for temporal dependence will result in poor forecasting. TES (Transform-Expand-Sample) is a class of stochastic processes to model empirical autocorrelated time series and is used in Monte Carlo simulation. Its merit is to simultaneously capture both the empirical distribution function and the autocorrelation function. The transition structure of TES processes can be utilized to calculate forecasts for future periods. In this paper, we utilize phase-type random variables as the innovation density in TES model fitting methodology, and we investigate the forecasting performance of TES processes compared to traditional auto regressive integrated moving-average models. We find that TES models yield forecasts as accurate as time series models.
Integrated Textbook: Augmenting Paper Textbooks with Digital Learning Support Using Digital Pens
Authors: Chia-Hao Chuang, Po-Yao Chao, Hsiao-Kuang Wu, Gwo-Dong Chen
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

Although quality of display devices is good right now, most textbooks are still printed on papers. At the same time, most learning support and e-learning courseware are built with the assumption that the student only read information displayed on the screen. In this paper, we present an environment that provides learning support via computers, digital devices and network when a student studies a course by reading paper textbooks with a digital pen. The learning support is organized based on the knowledge unit of the location positioning by the digital pen in the textbook. The support includes term explanation, related discussions, underline, and annotation. These studying actions and results on papers will be stored in the computer as well for later use. Initial experiment result on using the system shows that students feel beneficial to their study.
Parameter Estimation of DSSS Signals with Modified Fourth-Order Cumulants
Authors: Xiao-Ming Zhang, Zhong-Zhao Zhang
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1 (2006)

An asymptotic estimating technique for direct sequence spread spectrum signals using modified fourth-order statistics is considered. The general higher-order cumulants may not be easily applied in signal processing with too complex computation. Based on the fourth-order cumulants with 1-D slices and adaptive linear filters, an efficient algorithm is proposed to solve this problem. In order to achieve accurate frequency estimation, the first step uses the modified fourth-order cumulants to reduce the computing complexity. While the second step employs an adaptive recursive system. The fourth-order cumulants is a function of the frequency parameters and is obtained in an iterative manner. For the case of received signals with sufficient large data samples, the estimator provides good performance in frequency estimation and the white Gaussian noise suppression. Computer simulations are included to corroborate the theoretical development with different signal-to-noise ratio conditions and iterative coefficients.
Locally Salient Feature Extraction Using ICA for Content-Based Face Image Retrieval
Authors: Guoxia Sun, Ju Liu, Jiande Sun, Shuzhong Ba
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1 (2006)

The paper focuses on face image retrieval based on higher level statistical features. The Principal Independent Content Feature (PICF) is extracted by independent component analysis (ICA) to represent facial images, and a corresponding similarity measurement is employed. The PICF method encodes face images with locally salient features from a set of training images, which operates in a reduced principal component analysis (PCA) space, and an enhanced retrieval is achieved by using the similarity measurement after the two-stage-retrieving. The simulation is performed by using the ORL database, where the face images vary in illumination, expression, pose, and scale. The results show that the PICF method using the corresponding similarity measurement has better retrieving performance than classical PCA or ICA method with the usual measurement, and the two-stage-accuracy can reach 97.5%.
Visual assistant system "HIR" for Safe Driving at an Intersection -Interlligent Intersection-
Authors: Masato KOYAMAISHI, Yasuhiro SUZUKI, Mitsuhiro WADA, Tomohiro ENDO, Toshiaki FUJII, Masayuki TANIMOTO
Venue: Proceedings of the 21st International Conference on Data Engineering Workshops (2005)

With the advance of ITS (Intelligent Transport Systems), various types of equipment such as cameras are expected to be installed as new road infrastructure. We have proposed the HIR (Human-oriented Information Restructuring) System, which utilizes information obtained from those infrastructures, such as cameras, VICS, GPS, etc. This system shows images that assist drivers and are easy to understand. This paper presents the HIR algorithm, consideration of data error and required accuracy towards realization of HIR. Furthermore, we have constructed a system that acquires in-vehicle camera position and direction. Based on our previous study, we evaluate the effectiveness of the new system architecture by conducting an experiment in the situation of turning right at an intersection. As a result, we can generate assisting images and display them on a in-car monitor.
Characterizing an equitable omission of shared resources: a DEA-based approach
Authors: Alireza Amirteimoori, Mahmoud Shafiei
Venue: Applied Mathematics and Computation (2006)

In many real applications of DEA, there are often cases in which the decision maker has to omit a fixed proportion of a shared resources from all Decision Making Units. This paper, presents a DEA-based method for omitting these shared resources from all Decision Making Units. To illustrate the method, two examples are presented.
Rearrangement of mirror elements
Authors: Hung-Yu Wang, Sheng-Hsiung Chang, Yuan-Long Jeang, Chun-Yueh Huang
Venue: Analog Integrated Circuits and Signal Processing (2006)

The rearrangement of mirror elements has been presented. By virtue of the proposed approach, new topologies realizing the same transfer function as the initial circuit can be obtained. Moreover, we may derive the circuits with improved properties than the original circuit. A practical example has been given to demonstrate the feasibility.
Basic Transformations on Virtual Hexagonal Structure
Authors: Xiangjian He, Wenjing Jia, Qiang Wu, Namho Hur, Tom Hintz, Huaqing Wang, Jinwoong Kim
Venue: Proceedings of the International Conference on Computer Graphics, Imaging and Visualisation (2006)

Hexagonal structure is different from the traditional square structure for image representation. The geometrical arrangement of pixels on hexagonal structure can be described in terms of a hexagonal grid. Hexagonal structure provides an easy way for image translation and rotation transformations. However, all the existing hardware for capturing image and for displaying image are produced based on square architecture. It has become a serious problem affecting the advanced research based on hexagonal structure. In this paper, we introduce a new virtual hexagonal structure. Based on this virtual structure, a more flexible and powerful image translation and rotation are performed. The virtual hexagonal structure retains image resolution during the process of image transformations, and does not introduce distortion. Furthermore, images can be smoothly and easily transferred between the traditional square structure and the hexagonal structure.
Using Bayesian Networks to Implement Adaptivity in Mobile Learning
Authors: Dan Yu, XinMeng Chen
Venue: Proceedings of the Second International Conference on Semantics, Knowledge, and Grid (2006)

Mobile learning technologies have the potential to revolutionize distance education by bringing the concept of anytime and anywhere to reality. However, the development of mobile learning is hampered by various technological and access related problems, including the difficulty in implementing adaptivity. In this paper, we use the Bayesian networks to determine mobile learner's styles exploring the potential of individualization of learning process for the learners to implement adaptive mobile learning.
Dynamic Selection and Optimization of Design Paradigms in Mobile Services
Authors: Songqiao Han, Shensheng Zhang, Yong Zhang
Venue: Proceedings of the 2006 IEEE Asia-Pacific Conference on Services Computing (2006)

Mobile computing environments pose two challenging problems for the design and configuration of mobile services: constant changes of computation contexts and resource limitation of mobile devices. This paper presents a dynamic software configuration approach implemented by using different design paradigms during execution time. After analyzing the features of these paradigms, we propose the selection rules of design paradigms under different contexts, which are used to dynamically reconfigure mobile services to adapt to environmental changes and meet the users' requirements. The rules make the automatic or semi-automatic software configuration possible. To conserve resources, we present an optimal software partitioning algorithm based on network flow theory to optimize the design paradigms. Finally, a case study shows the flexibility and effectiveness of our approach.
What is the Dimension of Your Binary Data?
Authors: Nikolaj Tatti, Taneli Mielikainen, Aristides Gionis, Heikki Mannila
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

Many 0/1 datasets have a very large number of variables; however, they are sparse and the dependency structure of the variables is simpler than the number of variables would suggest. Defining the effective dimensionality of such a dataset is a nontrivial problem. We consider the problem of defining a robust measure of dimension for 0/1 datasets, and show that the basic idea of fractal dimension can be adapted for binary data. However, as such the fractal dimension is difficult to interpret. Hence we introduce the concept of normalized fractal dimension. For a dataset D, its normalized fractal dimension counts the number of independent columns needed to achieve the unnormalized fractal dimension of D. The normalized fractal dimension measures the degree of dependency structure of the data. We study the properties of the normalized fractal dimension and discuss its computation. We give empirical results on the normalized fractal dimension, comparing it against PCA.
Agent-based simulation of enterprise communication network
Authors: Hideyuki Mizuta, Fusashi Nakamura
Venue: Proceedings of the 37th conference on Winter simulation (2005)

In this paper, we consider an agent-based simulation of dynamic enterprise organization and communication networks. Along with recent progress and popularization of Information Technology, social sciences have been experiencing great advances in survey methodology. It has become possible for researchers to utilize huge social data with computers. However, there have been only conceptual studies in business school and few quantitative studies about enterprise organizations. In a survey of an enterprise, we evaluated strategic organization changes with graph/network analysis of the communication network constructed from email transaction data. Moreover, there is strong business needs to know how activities change according to an organization transformation. Utilizing the agent-based approach, we have constructed a dynamic model and simulation of communication over an organization structure. The result of the simulation indicates the power distribution for link degrees which is also observed in the real world as universal characteristics of the scale-free network.
Constructing codes identifying sets of vertices
Authors: Julien Moncel
Venue: Designs, Codes and Cryptography (2006)

For all t ¿ 2, we give an explicit construction of an infinite family of graphs such that G admits a code identifying sets of at most t vertices of G of cardinality O(t 2 ln |V(G)|) for all members G of the family. This beats the best previously known explicit construction by a factor of t 2.
Visual Recognition of Manual Tasks Using Object Motion Trajectories
Authors: Andrew Naftel, Fahad Bin Anwar
Venue: Proceedings of the IEEE International Conference on Video and Signal Based Surveillance (2006)

Motion trajectories are powerful cues for event detection and recognition. In this paper we present a system for manual task analysis that distinguishes between skin and object motion and learns activity patterns through analysing object trajectories. It is particularly suited to the recognition of common object handling tasks. Our vision system performs hand skin detection and object segmentation for each frame in a sequence. The object trajectories are then modelled as motion time series. We have compared the performance of several different time series indexing schemes: symbolic, polynomial and orthonormal basis functions used for trajectory similarity retrieval and classification. We then attempt to cluster objectcentred motion patterns in the coefficient feature space. The proposed technique is validated on two different datasets, Australian Sign Language and object handling data obtained in the laboratory. Applications to task recognition and motion data mining in industrial surveillance applications are envisaged.