ppxscal/embedding_network huggingface dataset:
Multiple snapshot direct data domain approach and ESPRIT method for direction of arrival estimation
Authors: Nuri Yilmazer, Seckin Ari, Tapan K. Sarkar
Venue: Digital Signal Processing (2008)

In this study, the performance of the matrix pencil (MP) method and the estimation of signal parameters using rotational in-variance technique (ESPRIT) method have been compared under varying number of snapshots taken. The matrix pencil method applies the technique directly to the data to estimate the poles, and works well under the correlated signal case, as opposed to ESPRIT, a statistical subspace based estimation technique, which will work after applying some additional spatial smoothing techniques to tackle the ill conditioning problem of the covariance matrix. Simulation results are provided to show the performance of these two methods.
Perfectly matched layers in 1-d : energy decay for continuous and semi-discrete waves
Authors: S. Ervedoza, E. Zuazua
Venue: Numerische Mathematik (2008)

In this paper we investigate the efficiency of the method of perfectly matched layers (PML) for the 1-d wave equation. The PML method furnishes a way to compute solutions of the wave equation for exterior problems in a finite computational domain by adding a damping term on the matched layer. In view of the properties of solutions in the whole free space, one expects the energy of solutions obtained by the PML method to tend to zero as t &#x2192; &#x221e;, and the rate of decay can be understood as a measure of the efficiency of the method. We prove, indeed, that the exponential decay holds and characterize the exponential decay rate in terms of the parameters and damping potentials entering in the implementation of the PML method. We also consider a space semi-discrete numerical approximation scheme and we prove that, due to the high frequency spurious numerical solutions, the decay rate fails to be uniform as the mesh size parameter h tends to zero. We show however that adding a numerical viscosity term allows us to recover the property of exponential decay of the energy uniformly on h. Although our analysis is restricted to finite differences in 1-d, most of the methods and results apply to finite elements on regular meshes and to multi-dimensional problems.
Distributed privacy preserving k-means clustering with additive secret sharing
Authors: Mahir Can Doganay, Thomas B. Pedersen, Yücel Saygin, Erkay Savaş, Albert Levi
Venue: Proceedings of the 2008 international workshop on Privacy and anonymity in information society (2008)

Recent concerns about privacy issues motivated data mining researchers to develop methods for performing data mining while preserving the privacy of individuals. However, the current techniques for privacy preserving data mining suffer from high communication and computation overheads which are prohibitive considering even a modest database size. Furthermore, the proposed techniques have strict assumptions on the involved parties which need to be relaxed in order to reflect the real-world requirements. In this paper we concentrate on a distributed scenario where the data is partitioned vertically over multiple sites and the involved sites would like to perform clustering without revealing their local databases. For this setting, we propose a new protocol for privacy preserving k-means clustering based on additive secret sharing. We show that the new protocol is more secure than the state of the art. Experiments conducted on real and synthetic data sets show that, in realistic scenarios, the communication and computation cost of our protocol is considerably less than the state of the art which is crucial for data mining applications.
Automated Process Classi?cation Framework using SELinux Security Context
Authors: Pravin Shinde, Priyanka Sharma, Srinivas Guntupalli
Venue: Proceedings of the 2008 Third International Conference on Availability, Reliability and Security (2008)

Stringent Quality of Service requirements from operating systems led to several extensions to the existing systems. These extensions aim at classifying the processes in a system at runtime to provide differentiated Quality of Service. Also there are many other applications which do need classification of processes for their working. The methods used for identifying the processes and grouping them, by different extensions have been ad-hoc. Enabling several of such extensions adds to the complexity of administering a system. We propose an automated mechanism to classify processes using some persistent characteristics of a process. We use persistent tokens security contexts added to all kernel objects by Security Enhanced Linux. We present the overall problem as three sub-problems viz., Notification, Classification and Enforcement. The proposed solution solves Notification and Classification problems. Enforcement is left to the specific application that uses the framework.
Capacity constrained assignment in spatial databases
Authors: Leong Hou U, Man Lung Yiu, Kyriakos Mouratidis, Nikos Mamoulis
Venue: Proceedings of the 2008 ACM SIGMOD international conference on Management of data (2008)

Given a point set P of customers (e.g., WiFi receivers) and a point set Q of service providers (e.g., wireless access points), where each q ∈ Q has a capacity q.k, the capacity constrained assignment (CCA) is a matching M ⊆ Q × P such that (i) each point q ∈ Q (p ∈ P) appears at most k times (at most once) in M, (ii) the size of M is maximized (i.e., it comprises min{|P|, ∑q∈Qq.k} pairs), and (iii) the total assignment cost (i.e., the sum of Euclidean distances within all pairs) is minimized. Thus, the CCA problem is to identify the assignment with the optimal overall quality; intuitively, the quality of q's service to p in a given (q, p) pair is anti-proportional to their distance. Although max-flow algorithms are applicable to this problem, they require the complete distance-based bipartite graph between Q and P. For large spatial datasets, this graph is expensive to compute and it may be too large to fit in main memory. Motivated by this fact, we propose efficient algorithms for optimal assignment that employ novel edge-pruning strategies, based on the spatial properties of the problem. Additionally, we develop approximate (i.e., suboptimal) CCA solutions that provide a trade-off between result accuracy and computation cost, abiding by theoretical quality guarantees. A thorough experimental evaluation demonstrates the efficiency and practicality of the proposed techniques.
An optical interface for inter-robot communication in a swarm of microrobots
Authors: O. Alonso, A. Diéguez, R. Casanova, A. Sanuy, O. Scholz, P. Corradi, J. Samitier
Venue: Proceedings of the 1st international conference on Robot communication and coordination (2007)

It is described the optical communication interface for short-range communications of robots in a microrobotic swarm between thousands of units. The robots, of 27 mm3-size, will be deployed in an arena of A4 sheet size with controlled illumination conditions. The communication between robots is done via IR light. The interface can handle variations of IR background light from point to point in the arena, deals with robot different orientation and distance, i.e., the amplitude of the signal to be detected, and with interferences of other robots. The interface has been designed to manage the low energy available in the robot.
An Orthogonal Projection Approach for Blind Beamforming in Multipath CDMA Channels
Authors: Jianshu Chen, Jian Wang, Pengyu Zhang, Jian Yuan, Xiuming Shan
Venue: Proceedings of the Communication Networks and Services Research Conference (2008)

In this paper, we propose a blind beamforming technique for multipath CDMA channels, which requires prior knowledge of only the spreading code and the timing of the desired user. An orthogonal projection approach is used to isolate the interference and estimate its spatial covariance matrix to update the beamformer for each path. Data bits are recovered by combining the despreaded output ofall beamformers. This scheme fully exploits interference information to achieve a less perturbed noise subspace, leading to improved system performance. Theoretical analysis and simulation results show the proposed approach's superior BER performance and interferencesuppression capability over the EDIC and Maximin beamformers, especially in low SNR, angular spread and dynamic access situations.
Identification of Protein Coding Regions Using the Modified Gabor-Wavelet Transform
Authors: Jesus Mena-Chalco, Helaine Carrer, Yossi Zana, Roberto M. Cesar Jr.
Venue: IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) (2008)

An important topic in genomic sequence analysis is the identification of protein coding regions. In this context, several coding DNA model-independent methods, based on the occurrence of specific patterns of nucleotides at coding regions, have been proposed. Nonetheless, these methods have not been completely suitable due to their dependence on an empirically pre-defined window length required for a local analysis of a DNA region. We introduce a method, based on a modified Gabor-wavelet transform (MGWT), for the identification of protein coding regions. This novel transform is tuned to analyze periodic signal components and presents the advantage of being independent of the window length. We compared the performance of the MGWT with other methods using eukaryote datasets. The results show that the MGWT outperforms all assessed model-independent methods with respect to identification accuracy. These results indicate that the source of at least part of the identification errors produced by the previous methods is the fixed working scale. The new method not only avoids this source of errors, but also makes available a tool for detailed exploration of the nucleotide occurrence.
Efficiently scheduling runtime reconfigurations
Authors: Javier Resano, Juan Antonio Clemente, Carlos Gonzalez, Daniel Mozos, Francky Catthoor
Venue: ACM Transactions on Design Automation of Electronic Systems (TODAES) (2008)

Due to the emergence of portable devices that must run complex dynamic applications there is a need for flexible platforms for embedded systems. Runtime reconfigurable hardware can provide this flexibility but the reconfiguration latency can significantly decrease the performance. When dealing with task graphs, runtime support that schedules the reconfigurations in advance can drastically reduce this overhead. However, executing complex scheduling heuristics at runtime may generate an excessive penalty. Hence, we have developed a hybrid design-time/runtime reconfiguration scheduling heuristic that generates its final schedule at runtime but carries out most computations at design-time. We have tested our approach in a PowerPC 405 processor embedded on a FPGA demonstrating that it generates a very small runtime penalty while providing almost as good schedules as a full runtime approach.
Security and Performance of Mobile XML Web Services
Authors: Thao Thanh Nguyen, Ivar Jørstad, Do van Thanh
Venue: Proceedings of the Fourth International Conference on Networking and Services (2008)

The development of new mobile services can benefit from adopting XML Web Services technologies, because this can dramatically reduce the time to market for many types of mobile services. However, it is often believed that XML Web Services will become too large a bottleneck in service performance, rendering the service unusable, as well as it can compromise service usage due to lack of security features. This paper provides a thorough study of these topics, i.e., a study of the typical performance of mobile services built on top of XML Web Services, how security features can be introduced for these services and how these security features influence on the performance of services. The results of this paper should apply to any mobile services implementation based on XML Web Services technologies.
Utilizing Natural Language for One-Shot Task Learning
Authors: Hyuckchul Jung, James Allen, Lucian Galescu, Nathanael Chambers, Mary Swift, William Taysom
Venue: Journal of Logic and Computation (2008)

Learning tasks from a single demonstration presents a significant challenge because the observed sequence is specific to the current situation and is inherently an incomplete representation of the procedure. Observation-based machine-learning techniques are not effective without multiple examples. However, when a demonstration is accompanied by natural language explanation, the language provides a rich source of information about the relationships between the steps in the procedure and the decision-making processes that led to them. In this article, we present a one-shot task learning system built on TRIPS, a dialogue-based collaborative problem solving system, and show how natural language understanding can be used for effective one-shot task learning.
Graphical Models of Residue Coupling in Protein Families
Authors: John Thomas, Naren Ramakrishnan, Chris Bailey-Kellogg
Venue: IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) (2008)

Many statistical measures and algorithmic techniqueshave been proposed for studying residue coupling inprotein families. Generally speaking, two residue positions areconsidered coupled if, in the sequence record, some of theiramino acid type combinations are significantly more commonthan others. While the proposed approaches have proven useful infinding and describing coupling, a significant missing componentis a formal probabilistic model that explicates and compactlyrepresents the coupling, integrates information about sequence,structure, and function, and supports inferential procedures foranalysis, diagnosis, and prediction.We present an approach to learning and using probabilisticgraphical models of residue coupling. These models capturesignificant conservation and coupling constraints observable ina multiply-aligned set of sequences. Our approach can place astructural prior on considered couplings, so that all identifiedrelationships have direct mechanistic explanations. It can alsoincorporate information about functional classes, and therebylearn a differential graphical model that distinguishes constraintscommon to all classes from those unique to individual classes.Such differential models separately account for class-specificconservation and family-wide coupling, two different sourcesof sequence covariation. They are then able to perform interpretablefunctional classification of new sequences, explainingclassification decisions in terms of the underlying conservationand coupling constraints. We apply our approach in studies ofboth G protein-coupled receptors and PDZ domains, identifyingand analyzing family-wide and class-specific constraints, andperforming functional classification. The results demonstrate thatgraphical models of residue coupling provide a powerful toolfor uncovering, representing, and utilizing significant sequencestructure-function relationships in protein families.
Validation for data classification
Authors: Hilario López, Iván Machón, Eva Fernández
Venue: Proceedings of the 9th WSEAS International Conference on Systems (2005)

Neural network models must be validated to be used as estimators. In this paper a detailed description for Self-Organizing Map (SOM) validation is proposed to determine the map size and the optimum training data set. This idea was applied in a wastewater biological treatment.
Composite Subscription and Matching Algorithm for RFID Applications
Authors: Xinchao Zhao, Beihong Jin, Shuang Yu, Zhenyue Long
Venue: Proceedings of the 22nd International Conference on Advanced Information Networking and Applications (2008)

RFID technology facilitates monitoring and managing products. In most RFID applications, users pay much attention to temporal and logical event patterns, which is further strengthened by highly temporal RFID data. If RFID events or other kinds of events are disseminated to users through Pub/Sub service, visibility of product states will be greatly increased and fast processing these events will become possible. However, the traditional Pub/Sub systems cannot support composite events involving abundant temporal constraints. Therefore, they cannot fully meet the needs of RFID applications. Aiming at RFID-related application scenarios, this paper designs a composite subscription language embedded with diversified temporal operators and proposes a matching algorithm for detecting composite events which has been implemented in our Pub/Sub system OncePubSub. Performance evaluation results indicate our algorithm is more efficient than the two systems based on Siena and JESS respectively.
Fast incremental proximity search in large graphs
Authors: Purnamrita Sarkar, Andrew W. Moore, Amit Prakash
Venue: Proceedings of the 25th international conference on Machine learning (2008)

In this paper we investigate two aspects of ranking problems on large graphs. First, we augment the deterministic pruning algorithm in Sarkar and Moore (2007) with sampling techniques to compute approximately correct rankings with high probability under random walk based proximity measures at query time. Second, we prove some surprising locality properties of these proximity measures by examining the short term behavior of random walks. The proposed algorithm can answer queries on the fly without caching any information about the entire graph. We present empirical results on a 600, 000 node author-word-citation graph from the Citeseer domain on a single CPU machine where the average query processing time is around 4 seconds. We present quantifiable link prediction tasks. On most of them our techniques outperform Personalized Pagerank, a well-known diffusion based proximity measure.
Constructing a Global Ontology by Concept Mapping Using Wikipedia Thesaurus
Authors: Minghua Pei, Kotaro Nakayama, Takahiro Hara, Shojiro Nishio
Venue: Proceedings of the 22nd International Conference on Advanced Information Networking and Applications - Workshops (2008)

Recently, the importance of semantics on the WWW is widely recognized and a lot of semantic information (RDF, OWL etc.) is being built/published on the WWW. However, the lack of ontology mappings becomes a serious problem for the Semantic Web since it needs well defined relations to retrieve information correctly by inferring the meaning of information. One to one mapping is not an efficient method due to the nature of distributed environment. Therefore, it would be a considerable method to map the concepts by using a large-scale intermediate ontology. On the other hand, Wikipedia is a large-scale of concept network covering almost all concepts in the real world. In this paper, we propose an intermediate ontology construction method using Wikipedia Thesaurus, an association thesaurus extracted from Wikipedia. Since Wikipedia Thesaurus provides associated concepts without explicit relation type, we propose an approach of concept mapping using two sub methods; “name mapping” and “logic-based mapping”.
Solving the Beck and Wieland model with optimal experimentation in DualPC
Authors: Hans M. Amman, David A. Kendrick, Marco P. Tucci
Venue: Automatica (Journal of IFAC) (2008)

Currently, there is a renewed interest in the use of optimal experimentation (adaptive control) in economics. Example are found in [Amman, H. M. & Kendrick, D. A. (1999). Should macroeconomic policy makers consider parameter covariances. Computational Economics 14, 263-267; Amman, H. M. & Kendrick, D. A. (2003). Mitigation of the Lucas critique with stochastic control methods. Journal of Economic Dynamics and Control 27, 2035-2057; Cosimano, T. F. Optimal experimentation and the perturbation method in the neighborhood of the augmented linear regulator problem. Journal of Economics, Dynamics and Control (in press); Cosimano, T. F., & Gapen, M. T. (2005b). Recursive methods of dynamic linear economics and optimal experimentation using the perturbation method, Working paper. Notre Dame, Indiana, USA: Department of Finance, University of Notre Dame; Cosimano, T. F., & Gapen, M. T. (2005a). Program notes for optimal experimentation and the perturbation method in the neighborhood of the augmented linear regulator problem, Working paper. Notre Dame, Indiana, USA: Department of Finance, University of Notre Dame; Cosimano, T. F., & Gapen, M. T. (2006). An algorithm for approximating optimal experimentation problems using the perturbation method, Working paper. Notre Dame, Indiana, USA: Department of Finance, University of Notre Dame; Tesfaselassie, M. F., Schaling, E., & Eijffinger, S. (2007). Learning about the term structure and optimal rules for inflation targeting, Working paper. Tilburg, The Netherlands: Tilburg University; Tucci, M. P. (1997). Adaptive control in the presence of time-varying parameters. Journal of Economic Dynamics and Control, 22, 39-47; Wieland, V. (2000a). Learning by doing and the value of optimal experimentation. Journal of Economic Dynamics and Control, 24, 501-543; Wieland, V., (2000b). Monetary policy, parameter uncertainty and optimal learning. Journal of Monetary Economics, 46, 199-228]. In this paper we present the Beck & Wieland model [Beck, G., & Wieland, V. (2002). Learning and control in a changing economic environment. Journal of Economic Dynamics and Control, 26, 1359-1378] and the methodology to solve this model with time-varying parameters using the various control methods described in [Kendrick, D. A. (1981). Stochastic control for economic models (1st ed.), New York, NY, USA: McGraw-Hill Book Company; Kendrick, D. A. (2002). Stochastic control for economic models (2nd ed.) Available at url: http://www.eco.utexas.edu/faculty/Kendrick]. Furthermore, we also provide numerical results using the DualPC software [Amman, H. M., & Kendrick, D. A. (1999). The DualI/DualPC software for optimal control models: User's guide. Working paper, Austin, TX 78712, USA: Center for Applied Research in Economics, University of Texas] and show first evidence that optimal experimentation or Dual Control may produce better results than Expected Optimal Feedback.
Secure communication for ad-hoc, federated groups
Authors: Andreas Sjöholm, Ludwig Seitz, Babak Sadighi
Venue: Proceedings of the 7th symposium on Identity and trust on the Internet (2008)

Ad-hoc federated groups are getting increasingly popular as means of addressing collaborative tasks that require information sharing. However, in some application scenarios, the security of the shared information is vital. Managing the communication security of such groups in an efficient way is a difficult task. This paper presents an architecture that enables secure communication for ad-hoc, cross-organisational groups. Our architecture covers group admission control, group key management and secure group communication. The groups in question are expected to be ad-hoc groups where the potential participants have no prior knowledge of each other and thus federation mechanisms need to be used to establish group admission rights. In order to handle group admission we use the SAML and XACML standards, for group key management we use the TGDH protocol. Our approach thus supports decentralised management of the most important tasks in secure group communication using an integrated approach based on established security standards. We have also produced a demo implementation to show the feasibility of our architecture. This research was pursued as part of the TrustDis project funded by the Swedish Governmental Agency for Innovation Systems (Vinnova).