ppxscal/embedding_network huggingface dataset:
Oblivious and Adaptive Strategies for the Majority and Plurality Problems
Authors: Fan Chung, Ron Graham, Jia Mao, Andrew Yao
Venue: Algorithmica (2007)

In the well-studied Majority problem, we are given a set of n balls colored with two or more colors, and the goal is to use the minimum number of color comparisons to find a ball of the majority color (i.e., a color that occurs for more than n/2 times). The Plurality problem has exactly the same setting while the goal is to find a ball of the dominant color (i.e., a color that occurs most often). Previous literature regarding this topic dealt mainly with adaptive strategies, whereas in this paper we focus more on the oblivious (i.e., non-adaptive) strategies. Given that our strategies are oblivious, we establish a linear upper bound for the Majority problem with arbitrarily many different colors assuming a majority label exists. We then show that the Plurality problem is significantly more difficult by establishing quadratic lower and upper bounds. In the end we also discuss some generalized upper bounds for adaptive strategies in the k-color Plurality problem.
Towards a platform for intelligent activity at the edge
Authors: Hilarie Orman
Venue: Proceedings of the Workshop on Intelligence at the Network Edge (2000)

Proxy caches for content on the Internet are high-performance platforms with complex software services. Because they understand application semantics, and because they have a great deal of memory, they are the natural place for new services that are tailored closely to site or user preferences and requirements. The engineering aspects of caches and how they contribute to a new network infrastructure for highly capable or intelligent services are examined in this paper.
Robust matched-field beamforming with benchmark shallow-water acoustic array data
Authors: J. L. Krolik
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 02 (1996)

In this paper, four robust matched-field beamforming methods are evaluated using benchmark shallow-water Mediterranean data. While the Bartlett beamformer, reduced minimum variance beamformer (RMV), and minimum variance beamformer with neighborhood location constraints (MV-NLC) assume a known ocean, the minimum variance beamformer with environmental perturbation constraints (MV-EPC) exploits a model for uncertainties in the ocean parameters. For modest environmental uncertainty, the MV-EPC beamformer is shown to achieve higher probability of correct localization with simulated data and better tracking and sidelobe performance with experimental data than the Bartlett, RMV, and MV-NLC methods.
A Unified Approach to Construct Search Trees in Parallel
Authors: Sajal K. Das, Kwang Bae Min
Venue: Proceedings of the 1994 International Conference on Parallel Processing - Volume 03 (1994)

We present a unified parallel algorithm for constructing various search trees. The tree construction is based on a unified scheme, called bottom-level balancing, which constructs a height balanced search tree having a uniform distribution of keys. The algorithm takes O(loglogN) time using N/loglogN processors on the EREW PRAM model, and 0(1) time with N processors on the CREW PRAM model, where N is the number of keys in the tree.
Exterminator: automatically correcting memory errors with high probability
Authors: Gene Novark, Emery D. Berger, Benjamin G. Zorn
Venue: Proceedings of the 2007 ACM SIGPLAN conference on Programming language design and implementation (2007)

Programs written in C and C++ are susceptible to memory errors, including buffer overflows and dangling pointers. These errors, whichcan lead to crashes, erroneous execution, and security vulnerabilities, are notoriously costly to repair. Tracking down their location in the source code is difficult, even when the full memory state of the program is available. Once the errors are finally found, fixing them remains challenging: even for critical security-sensitive bugs, the average time between initial reports and the issuance of a patch is nearly one month. We present Exterminator, a system that automatically correct sheap-based memory errors without programmer intervention. Exterminator exploits randomization to pinpoint errors with high precision. From this information, Exterminator derives runtime patches that fix these errors both in current and subsequent executions. In addition, Exterminator enables collaborative bug correction by merging patches generated by multiple users. We present analytical and empirical results that demonstrate Exterminator's effectiveness at detecting and correcting both injected and real faults.
Random dynamics and finance: constructing implied binomial trees from a predetermined stationary density: Research Articles
Authors: Wael Bahsoun, Paweł Góra, Silvia Mayoral, Manuel Morales
Venue: Applied Stochastic Models in Business and Industry (2007)

We introduce a general binomial model for asset prices based on the concept of random maps. The asymptotic stationary distribution for such model is studied using techniques from dynamical systems. In particular, we present a technique to construct a general binomial model with a predetermined stationary distribution. This technique is independent of the chosen distribution making our model potentially useful in financial applications. We briefly explore the suitability of our construction as an implied binomial tree. Copyright &copy; 2006 John Wiley & Sons, Ltd.
A criterion for atomicity revisited
Authors: Wim H. Hesselink
Venue: Acta Informatica (2007)

Concurrent and reactive programs are specified by their behaviours in the presence of a nondeterministic environment. In a natural way, this gives a specification (ARW) of an atomic variable in the style of Abadi and Lamport. Several implementations of atomic variables by lower level primitives are known. A few years ago, we formulated a criterion to prove the correctness of such implementations. The proof of correctness of the criterion itself was based on Lynch&#x2019;s definition of atomicity by serialization points. Here, this criterion is reformulated as a specification HRW in the formal sense. Simulations from HRW to ARW and vice versa are constructed. These now serve as a constructive proof of correctness of the criterion. Eternity variables are used in the simulation from HRW to ARW. We propose so-called gliding simulations to deal with the problems that appear when occasionally the concrete implementation needs fewer steps than the abstract specification.
User Behavior Identification for Trust Management in Pervasive Computing Systems
Authors: Zhaoyu Liu, Dichao Peng
Venue: Proceedings of the 11th IEEE International Workshop on Future Trends of Distributed Computing Systems (2007)

Pervasive computing systems is becoming widespread as the next generation of computing systems. In pervasive computing systems, the users are frequently hopping from one computing space to another, which makes user profile management an essential component of the system. Because such a dynamic-populated computing system has to be newcomer-friendly, malicious users with bad reputation to a system may take advantage of the system by claiming themselves as new users. In addition, user identity can also be compromised by controlling the victim node via normal invasions or even by inside identity thefts. A valid user identity is the foundation and prerequisite of trust. Failures to correctly identify a user is catastrophic to trust management system. Traditional intrusion detection systems can only detect an attack when it already happens. But before the intrusion the attackers may have some specific behavioral signatures indicating of their suspicious identities. We need a more powerful and practical system to identify these suspicious behaviors and signal an early warning to stop them. In this paper we assume that user identity is compromised either by attacking and controlling a node or by malicious users' claiming themselves as new users. We will introduce a novel user behavior identification and profile management system to detect the suspicious behaviors, and a dynamically triggered reaction module to monitor the suspicious node and collect the necessary evidences.
Group Work About Geometrical Concepts Among Blind and Sighted Pupils Using Haptic Interfaces
Authors: Eva-Lotta Sallnas, Jonas Moll, Kerstin Severinson-Eklundh
Venue: Proceedings of the Second Joint EuroHaptics Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (2007)

In the study presented in this paper two haptic and visual prototypes for learning about geometrical concepts in group work in primary school have been designed and evaluated. The aim was for the prototypes to support collaborative learning between sighted and visually impaired pupils. The first prototype was a 3D environment, that supported learning of spatial geometry. The second prototype was a flattened 3D environment that supported learning to distinguish between angles. The two prototypes were evaluated in four schools with small groups of pupils - two sighted and one visually impaired. The results showed that the support for the visually impaired user was good and that co-operation and learning are satisfactorily supported. However, a number of interesting problems were also discovered that need to be investigated further. A promising result was that the power of the touch-based haptic interface for supporting visually impaired people was made clear.
Reliability Engineering & Data Collection
Authors: Michel Houtermans, Tino Vande Capelle
Venue: Proceedings of the Second International Conference on Systems (2007)

International Petrochemical, Chemical, Refining and Petroleum Industries are trying to implement reliability programs to improve plant safety while trying to maintain plant availability. These programs can vary significantly in size and complexity. Any kind of reliability program, like a preventive maintenance (PM) program, consists always of one or more reliability models and reliability data to execute these models. It is needless to say that the actual successful implementation and utilization of these reliability programs heavily depends on the accuracy of the reliability models and the availability of realistic data, or at least as close as possible data. The objective of this paper is to give the reader a better understanding of the importance of reliability engineering focusing on the collection of reliability data for the purpose of process availability, safety and preventive maintenance programs. The paper will first explain what reliability engineering is and why it is important for processing plants to have a reliability program. Second the paper will give an overview of different programs in use today by companies (Preventive maintenance, risk based inspections, etc). Next the paper will focus on the role of reliability modeling and data. The paper will explain the kind of reliability data needed and the current available sources for this data. The focus will be on the actual data available within the plant that can among others be collected through the information derived from the archived data in the DCS systems. An excellent time to collect data is during scheduled plant turnarounds. Based on the example of a control valve the paper will explain the role that humans can play to improve the administration of reliability data during plant turnaround. Also the importance of failure analysis will be addressed. Finally the paper will conclude with an example of a decision support model which heavily depends on accurate reliability data. This example demonstrates how a plant owner can benefit from a practical application of reliability engineering.
IdeaMurals: supporting ideation in public policy knowledge work
Authors: Jennifer Stoll
Venue: Proceedings of the 6th ACM SIGCHI conference on Creativity cognition (2007)

The creativity and innovation found in knowledge work such as public policy is often hidden. This "hidden-ness" is likely due to the predominantly textual representation of the work done in this domain. Unlike other areas that are more design-oriented, public policy knowledge work generally does not rely on, or produce, graphical artifacts which can showcase the innovation. In contrast, for domains such as engineering-design or the fine arts, the generation of such artifacts is inherently a part of the work itself. IdeaMurals attempts to explore how creativity and innovation can be supported for a domain that is largely ignored. It also seeks to explore how visual elements can be leveraged to support the ideating process of policy work. The organizing principle of IdeaMurals is to support ideation based on how ideas are constructed; and the construction of these ideas is framed as being analogous to the construction of art compositions.
Class-dependence feature analysis for large population face recognition
Authors: Vijayakumar Bhagavatula
Venue:  (2006)

Reliable person recognition is important for secure access and commercial applications requiring identification. Face recognition (FR) is an important technology being developed for human identification. However, most current FR studies are based on databases with relatively small number of subjects. Developing algorithms/systems for large population face recognition (LPFR) is of significant interest in many applications such as watch lists and video surveillance. In this thesis, we propose a new method to effectively exploit the generic training data to represent a large number of subjects and thus improve the performance of correlation filters for LPFR. We propose a new general framework---class-dependence feature analysis (CFA), which can embed many common classification methods (e.g., correlation filters, support vector machines, principal component analysis etc.) to provide a discriminant feature representation for LPFR. In the CFA approach, a face discrimination model is obtained based on the subjects in the generic training set, but is applied to a larger set of subjects. In our experiments, the correlation filter based CFA approach greatly improves the face recognition rate and reduces the computational load over conventional correlation filters. Because nonlinear classifiers usually outperform their linear counterparts for classification accuracy, under the CFA framework we developed the kernel correlation filters that generate nonlinear decision boundaries. The kernel CFA (KCFA) approach significantly improves the recognition performance in our experiments, without greatly increasing the computational load. In order to further reduce the computational complexity, we extend the CFA approach to reduce the number of classifiers by using binary coding and applying error control coding (ECC) to preserve the recognition performance. This approach offers a systematic tradeoff between the computational complexity and the recognition accuracy. We test our proposed algorithms on the face recognition grand challenge (FRGC) database and show significant improvements on both verification performance and computational speed.
An Emotion Affected Action Selection Mechanism for Multiple Virtual Agents
Authors: Carlos Delgado-Mata, Jesus Ibanez-Martinez
Venue: Proceedings of the 16th International Conference on Artificial Reality and Telexistence--Workshops (2006)

This paper presents an Action Selection Mechanism, for virtual flocking animals, inspired by ethology and theories of emotion. We investigate how emotions, in this case fear, affect behaviour, considering deer and sheep as exemplary flocking mammals. The paper also describes and applies a mechanism to measure different types of flocking, using singular values and entropy to compute complexity. Results show that emotion can be used to regulate two competing and vital behaviours like those seen in herding animals: the group behaviour (herding) and the individual behaviour (grazing), thus demonstrating that emotion is a functional organiser of group behaviour.
RAPORT - a knowledge support system for administrative workflow processes
Authors: I. Budinska, V. Oravec, E. Gatial, M. Laclavik, M. Seleng, Z. Balogh, B. Frankovic, R. Forgac, I. Mokris, L. Hluchy
Venue: Proceedings of the Seventh International Conference on Application of Concurrency to System Design (2007)

The paper describes a knowledge support system for administrative workflow processes. The RAPORT system is based on ontology and e-mail communication. The description of architecture and basic functionalities and components of the RAPORT system are provided in this paper.
Technologies of parallel database systems for hierarchical multiprocessor environments
Authors: P. S. Kostenetskii, A. V. Lepikhov, L. V. Sokolinskii
Venue: Automation and Remote Control (2007)

For the multiprocessor systems of the hierarchical-architecture relational databases, a new approach to data layout and load balancing was proposed. Described was a database multiprocessor model enabling simulation and examination of arbitrary multiprocessor hierarchical configurations in the context of the on-line transaction processing applications. An important subclass of the symmetrical multiprocessor hierarchies was considered, and a new data layout strategy based on the method of partial mirroring was proposed for them. The disk space used to replicate the data was evaluated analytically. For the symmetrical hierarchies having certain regularity, theorems estimating the laboriousness of replica formation were proved. An efficient method of load balancing on the basis of the partial mirroring technique was proposed. The methods described are oriented to the clusters and Grid-systems.
Addressing Communication Issues in Software Development: A Case Study Approach
Authors: Ann Brady, Marika Seigel, Thomas Vosecky, Charles Wallace
Venue: Proceedings of the 20th Conference on Software Engineering Education & Training (2007)

Failure in communication between software developers and other stakeholders is a common cause of requirements deficiencies, cost overruns, and delays. It is difficult to present in a classroom setting the complexities that can cause such failures. To address this need, we have developed instructional case study material in software communication. We demonstrate how our cases expose students to situations they will confront outside the classroom, and how they provide opportunities for critiquing and devising communication strategies. We also describe our use of the cases, in a software engineering course and a technical communication course. We give initial results of an ongoing evaluation of the material's effectiveness in the software engineering curriculum.
Continuous space language models for statistical machine translation
Authors: Holger Schwenk, Daniel Dchelotte, Jean-Luc Gauvain
Venue: Proceedings of the COLING/ACL on Main conference poster sessions (2006)

Statistical machine translation systems are based on one or more translation models and a language model of the target language. While many different translation models and phrase extraction algorithms have been proposed, a standard word n-gram back-off language model is used in most systems. In this work, we propose to use a new statistical language model that is based on a continuous representation of the words in the vocabulary. A neural network is used to perform the projection and the probability estimation. We consider the translation of European Parliament Speeches. This task is part of an international evaluation organized by the TC-STAR project in 2006. The proposed method achieves consistent improvements in the BLEU score on the development and test data. We also present algorithms to improve the estimation of the language model probabilities when splitting long sentences into shorter chunks.
Coupling Patterns in the Effective Reuse of Open Source Software
Authors: Andrea Capiluppi, Cornelia Boldyreff
Venue: Proceedings of the First International Workshop on Emerging Trends in FLOSS Research and Development (2007)

Albeit practical reuse approaches have been established in commercial environments, the Open Source Software (OSS) communities have not yet taken full advantage of the reuse mechanism. Many OSS projects, sharing the same application domain and topic, duplicate effort and code, without fully leveraging the vast amounts of available code. In order to fill these gaps, this study focuses on source code folders of OSS projects: the objective is to investigate their potential as shareable and small-grained reusable software components in other OSS projects.
POSITIF: A Policy-Based Security Management System
Authors: Cataldo Basile, Antonio Lioy, Gregorio Martinez Perez, Felix J. Garcia Clemente, Antonio F. Gomez Skarmeta
Venue: Proceedings of the Eighth IEEE International Workshop on Policies for Distributed Systems and Networks (2007)

The POSITIF project [1] -- funded by the EU in FP6 -- has developed a framework and tools to configure in a policybased way the security services of networked systems and applications. This framework has been designed with the following set of interesting features in mind.
Complementing current active queue management schemes with rechoke and receiver-window modification (rwm)
Authors: Gergely Zaruba
Venue:  (2006)

Explicit Congestion Notification (ECN) and Active Queue Management (AQM) schemes have been proposed for present-day TCP/IP networks to better manage network congestion. ECN enabled AQMs were shown to have a promising advantage over existing drop-tail queues. However, when implemented, they were susceptible to the following problems: (1) the timeout mechanism or the duration of the reception of three duplicate acknowledgements (ACKs), due to early-dropped packets by these AQMs, delays the response time of TCP (in reducing the offered rate); (2) using ECN with these AQMs has its downsides: (i) its messages may get delayed or dropped due to congestion in downstream routers; and (ii) TCP implementations at both the source and the destination have to be ECN-compliant (which presents a significant problem in today's cores and end systems); and (3) these AQM schemes, with or without ECN, fail to protect TCP-friendly flows adequately in the presence of non TCP-friendly (e.g., UDP) or malicious flows. This dissertation presents solutions to these problems by proposing two novel AQM modification schemes called Receiver-Window Modification (RWM) and RECHOKe (REpeatedly CHOose and Keep for responsive flows, REpeatedly CHOose and Kill for unresponsive flows). By combining these two schemes with RED, we produce a new AQM scheme called RCUBE (Receiver-Window Modified Random Early Detection queues with RECHOKe). By using RECHOKe as a component, RCUBE easily identifies, controls and punishes malicious flows, by requiring only a small amount of information, approximately proportional to the order of magnitude of malicious flows. By using RWM, we reduce the average TCP queue sizes in the queues and in doing so, not only make it easier to identify malicious flows but also reduce the queuing delay resulting in significant improvements in one-way end-to-end packet delays, delay jitter, throughput and number of dropped packets for TCP-friendly flows. We compare RED, CHOKe, xCHOKe, RECHOKe and RCUBE schemes and show that RCUBE outperforms these schemes in identifying, controlling and punishing malicious flows and in protecting TCP-friendly flows. We also provide a theoretical analysis for RCUBE, RECHOKe and RWM schemes to validate our claims.