ppxscal/embedding_network huggingface dataset:
Ontology-Based Context Information Modelling for Managing Pervasive Applications
Authors: J. Martin. Serrano, Joan Serrat, Alex Galis
Venue: Proceedings of the International Conference on Autonomic and Autonomous Systems (2006)

This paper introduces a case study on an innovative based-ontology information model approach and the architecture for supporting customization, definition, deployment and management of context-aware service applications; for this purpose this paper describes some fundamental concepts that introduce the base of knowledge such as context-aware services, context information models and ontologies, paying special attention to ontology-oriented philosophy. We contribute to the research challenges in pervasive services setting the bases for a solid context information model through the study of formal ontologies and proposing the functional validation in a context-aware system that highlights the importance of formal information models.
Considering Learning Styles in Learning Management Systems: Investigating the Behavior of Students in an Online Course
Authors: Sabine Graf, Kinshuk Kinshuk
Venue: Proceedings of the First International Workshop on Semantic Media Adaptation and Personalization (2006)

Many researchers agree that considering learning styles increases the learning progress and makes learning easier for students. Learning management systems (LMS) are very successful in e-education but do not incorporate learning styles. As a requirement for taking learning styles into consideration in LMS, the behavior of students in online courses needs to be investigated. In this paper, we analyze the behavior of 43 students based on their learning styles and predefined patterns of behavior. Firstly, we concentrated on whether students with different learning style preferences act differently in the course. This information can be used to create courses that include features for each learning style. Secondly, we investigated correlations between the learning style preferences and the behavior of students during the course. These correlations can be use to develop an approach for identifying learning styles in LMS based on students' behavior.
Two priority buffered multistage interconnection networks
Authors: Galia Shabtai, Israel Cidon, Moshe Sidi
Venue: Journal of High Speed Networks (2006)

This paper presents a novel architecture of internally two priority buffered Multistage Interconnection Network (MIN). First, we compare by simulation the new architecture against a single priority MIN and demonstrate up to N times higher throughput for the high priority traffic in a hot spot situation, when N is the number of inputs. In addition, under uniform traffic assumption we show an increase in the low priority throughput, without any change in the high priority throughput. Moreover, while in the single priority system the high priority delay and its standard deviation are increased when low priority traffic is present, it is kept constant in the dual priority system. Finally, we introduce a new approach of long Markovian memory performance model to better capture the packets dependency in a single priority MIN under uniform traffic and extend this model for a dual priority MIN. Model results are shown to be very accurate.
Converting Semi-structured Clinical Medical Records into Information and Knowledge
Authors: Xiaohua Zhou, Hyoil Han, Isaac Chankai, Ann A. Prestrud, Ari D. Brooks
Venue: Proceedings of the 21st International Conference on Data Engineering Workshops (2005)

Clinical medical records contain a wealth of information, largely in free-textual form. Thus, means to extract structured information from free-text records becomes an important research endeavor. In this paper, we propose and implement an information extraction system that extracts three types of information - numeric values, medical terms and categorical value - from semi-structured patient records. Three approaches are proposed to solve the problems posed by each of the three types of values, respectively, and very good performance (precision and recall) is achieved. A novel link-grammar based approach was invented to associate feature and number in a sentence, and extremely high accuracy was achieved. A simple but efficient approach, using POS-based pattern and domain ontology, was adopted to extract medical terms of interest. Finally, an NLPbased feature extraction method coupled with an ID3 baseddecision tree is used to classify and extract categorical cases. This preliminary approach to categorical fields has, so far, proven to be quite effective.
Towards Pedagogically Neutral EML Making Use of De-Contextualized Learning Objects: Myth or Reality?
Authors: Thierry Nodenot
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

The first aim of this work is to assess the IMS-LD specification against a case-study relying on constructivist educational principles. From the analysis of the pros and cons of IMS-LD, we outline modelling principles and a language to specify diverse views of in context concepts (roles, activities, learning events, etc). Some capabilities of this language are then exemplified on the same case-study.
A Joint Illumination and Shape Model for Visual Tracking
Authors: Amit Kale, Christopher Jaynes
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (2006)

Visual tracking involves generating an inference about the motion of an object from measured image locations in a video sequence. In this paper we present a unified framework that incorporates shape and illumination in the context of visual tracking. The contribution of the work is twofold. First, we introduce a a multiplicative, low dimensional model of illumination that is defined by a linear combination of a set of smoothly changing basis functions. Secondly, we show that a small number of centroids in this new space can be used to represent the illumination conditions existing in the scene. These centroids can be learned from ground truth and are shown to generalize well to other objects of the same class for the scene. Finally we show how this illumination model can be combined with shape in a probabilistic sampling framework. Results of the joint shape-illumination model are demonstrated in the context of vehicle and face tracking in challenging conditions.
The cost of social agents
Authors: Guido Governatori, Antonino Rotolo, Vineet Padmanabhan
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

In this paper we follow the BOID (Belief, Obligation, Intention, Desire) architecture to describe agents and agent types in Defeasible Logic. We argue that the introduction of obligations can provide a new reading of the concepts of intention and intentionality. Then we examine the notion of social agent (i.e., an agent where obligations prevail over intentions) and discuss some computational and philosophical issues related to it. We show that the notion of social agent either requires more complex computations or has some philosophical drawbacks.
Cimstore: content-aware integrity maintaining storage
Authors: Dirk Grunwald
Venue:  (2006)

CIMStore provides integrity maintenance for storage consumers in the form of "non-overwriting" block storage. To make "non-overwriting" storage feasible, content-based coalescing helps reduce space requirements an average of 95% and improves performance to close to that of a non-integrity maintaining system. CIMStore is a system where changes to all blocks that reach stable storage (whether via file system flush or direct writes to raw disk) are logged. Content-based coalescing implies only storing a single copy of any block content and is used both in memory to improve caching performance and on disk to reduce storage overheads of non-overwriting block storage. CIMStore uses hashing and other metadata for fast access. In other words, CIMStore is intended as a primary storage system, both for system partitions and home directories, not as a tape replacement or other second-line storage.
Scheduling Real-Time Components Using Jitter-Constrained Streams
Authors: Claude-Joachim Hamann, Steffen Zschaler
Venue: Proceedings of the 10th IEEE on International Enterprise Distributed Object Computing Conference Workshops (2006)

Component-based applications require good middleware support. In particular, business logic should be separated from management code for guaranteeing nonfunctional properties of a system. We present an approach called Container-Managed Quality Assurance, in which a component container uses nonfunctional specifications of components to determine how to use these components, and which system resources to allocate, to provide certain services with guaranteed nonfunctional properties. As an example, we show how this technique can be applied to automatically allocating CPU and memory resources for components with real-time constraints. To this end, we use a mathematical model based on jitterconstrained streams, a mathematical abstraction of event streams.
New refinement schemes for voice conversion
Authors: Cheng-Yuan Lin, J.-S. R. Jang
Venue: Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1 (2003)

New refinement schemes for voice conversion are proposed in this paper. We take mel-frequency cepstral coefficients (MFCC) as the basic feature and adopt cepstral mean subtraction to compensate the channel effects. We propose S/U/V (silence/unvoiced/voiced) decision rule such that two sets of codebooks are used to capture the difference between unvoiced and voiced segments of the source speaker. Moreover, we apply three schemes to refine the synthesized voice, including pitch refinement with PSOLA, energy equalization, and frame concatenation based on synchronized pitch marks. The satisfactory performance of the voice conversion system can be demonstrated through ABX listening test and MOS grade.
Characterizations of context-sensitive languages and other language classes in terms of symport/antiport P systems
Authors: Oscar H. Ibarra, Gheorghe Paun
Venue: Theoretical Computer Science (2006)

We give "syntactic" characterizations of context-sensitive languages (CSLs) in terms of some restricted models of symport/antiport P systems. These are the first such characterizations of CSLs in terms of P systems. In particular, we show the following for any language L over a binary alphabet: (1) Let m be any integer ≥ 1. Then L is a CSL if and only if it can be accepted by a restricted symport/antiport P system with m membranes and multiple number of symbols (objects). Moreover, holding the number of membranes at m, there is an infinite hierarchy in computational power (within the class of binary CSLs) with respect to the number of symbols. (2) Let s be any integer ≥ 14. Then L is a CSL if and only if it can be accepted by a restricted symport/antiport P system with s symbols and multiple number of membranes. Moreover, holding the number of symbols at s, there is an infinite hierarchy in computational power with respect to the number of membranes. (Similar results hold for languages over an alphabet of k ≥ 2 symbols.) Thus (1) and (2) say that in order for the restricted symport/antiport P systems to accept all binary CSLs, at least one parameter (either the number of symbols or the number of membranes) must grow. These are the first results of their kind in the P systems area. They contrast a known result that (unrestricted) symport/antiport P systems with s ≥ 2 symbols and m ≥ 1 membranes accept (or generate) exactly the recursively enumerable sets of numbers even for s + m = 6. We also note that previous characterizations of formal languages in the membrane computing literature are mostly for the Parikh images of languages.Variations of our model yield characterizations of regular languages, languages accepted by one-way log n space-bounded Turing machines, and recursively enumerable languages.
The Effect of Key and Tempo on Audio Onset Detection Using Machine Learning Techniques: A Sensitivity Analysis
Authors: Ching-Hua Chuan, Elaine Chew
Venue: Proceedings of the Eighth IEEE International Symposium on Multimedia (2006)

In this paper, we explore the effect of musical context on audio onset detection using machine learning techniques. We extract the signal intensity and frequency energy of audio as the attributes of input instances for the machine learning techniques. The audio is synthesized from MIDI files, providing exact information of onset events. We test three state-of-the-art machine learning algorithms, Support Vector Machines (SVM), Neural Networks (NN), and Naïve Bayes (NB) with Ada boosting, for learning and classifying audio onsets. We found that SVMs perform best in general, based on the average of training and 10-fold cross validation errors as the evaluation criterion. We then test the SVM and NN, the two best performing methods, on Bach's Prelude in C major BWV 943, transposed to different keys and time-stretched to various tempi. The error rates ranged from 23.91% (when training set key and tempo equals those of the test set) to 37.22% (when the key is off by four accidentals) and 37.91% (when tempo is 20 beats per minute faster). The results show that audio onset detection performs significantly better when the key and tempo attributes of the test and training sets concur, than when they are different, thus supporting the utility of tempo and key knowledge in designing onset detection systems, or in prescribing confidence statistics to onset detection outcomes.
KLASSP: Entering Passwords on a Spyware Infected Machine Using a Shared-Secret Proxy
Authors: Dinei Florencio, Cormac Herley
Venue: Proceedings of the 22nd Annual Computer Security Applications Conference (2006)

In this paper we examine the problem of entering sensitive data, such as passwords, from an untrusted machine. By untrusted we mean that it is suspected to be infected with spyware which snoops on the user's activity. Using such a machine is obviously undesirable, and yet roaming users often have no choice. They are in no position to judge the security status of internet cafe, airport lounge or business center machines. Either malice or negligence on the part of an administrator means that any such machine can easily be running a keylogger. The roaming user has no reliable way of determining whether it is safe, and has no alternative to typing the password. We consider whether it is possible to enter data to confound spyware assumed to be running on the machine in question. The difficulty of mounting a collusion attack on a single user's password makes the problem more tractable than it might appear. We explore several approaches. In the first, we show how the user can embed a password in random keystrokes to confuse spyware, while leaving the actual login unaffected. In the second we employ a proxy server to strip random keys. In the third we again employ a proxy that inverts a key mapping performed by the user. We examine also several potential attacks.
A Single-Stream Pipelined Instruction Decompression System for Embedded Microprocessors
Authors: Yuan-Long Jeang, Tzuu-Shaang Wey, Hung-Yu Wang, Chih-Chung Tai
Venue: Proceedings of the 2006 International Conference on Intelligent Information Hiding and Multimedia (2006)

For instruction decompression, techniques such as single buffering, double buffering and pipelining have been proposed. However, due to jumping penalty, these techniques incur more delays in pipeline or system has to be stopped to refill the cache buffers. A Pipeline with Back-up for Flushing (PBF) technique has been developed that incurs no delay and without stopping due to jumping. However, the first instruction of each basic block should not be compressed and be put in another ROM, and thus the compression ratio should be sacrificed. This paper improves the PBF technique such that a single program ROM needed only. The simulation results for several benchmarks show that the average compression ratio is decreased about 11%, and the hardware cost deceased about 8%.
On the importance of having an identity or, is consensus really universal?
Authors: Harry Buhrman, Alessandro Panconesi, Riccardo Silvestri, Paul Vitanyi
Venue: Distributed Computing (2006)

We show that Naming - the existence of distinct IDs known to all - is a hidden, but necessary, assumption of Herlihy's universality result for Consensus. We then show in a very precise sense that Naming is harder than Consensus and bring to the surface some relevant differences existing between popular shared memory models.
How do small velocity-dependent forces (de)stabilize a non-conservative system?
Authors: O. N. Kirillov
Venue: Proceedings of the 2003 International Conference on Physics and Control - Volume 4 (2003)

The influence of small velocity-dependent forces on the stability of a linear autonomous non-conservative system of general type is studied. The problem is investigated by an approach based on the analysis of multiple roots of the characteristic polynomial whose coefficients are expressed through the invariants of the matrices of a non-conservative system. For systems with two degrees of freedom approximations of the domain asymptotic stability are constructed and the structure of the matrix of velocity-dependent forces stabilizing a circulatory system is found. As mechanical examples the Bolotin problem and the Herrman-Jong pendulum are considered in detail. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Analysis of the Message Waiting Time for the FioranoMQ JMS Server
Authors: Michael Menth, Robert Henjes
Venue: Proceedings of the 26th IEEE International Conference on Distributed Computing Systems (2006)

The Java messaging service (JMS) is a means to organize communication among distributed applications according to the publish/subscribe principle. If the subscribers install filter rules on the JMS server, JMS can be used as a message routing platform, but it is not clear whether its message throughput is sufficiently high to support large-scale systems. We perform measurements for the FioranoMQ JMS server and derive a simple model for its message processing time that takes message filters and the message replication grade into account. Then, we analyze the JMS server capacity and the message waiting time for various application scenarios. We show that the message waiting time is not an issue as long as the server throughput is sufficiently high. Finally, we assess the capacity of two different distributed JMS architectures whose objective is to increase the capacity of the JMS beyond the limit of a single server.
A Compensation-Based Approach for View Maintenance in Distributed Environments
Authors: Songting Chen Xin Zhang Elke A. Rundensteiner
Venue: IEEE Transactions on Knowledge and Data Engineering (2006)

Data integration over multiple heterogeneous data sources has become increasingly important for modern applications. The integrated data is usually stored as materialized views to allow better access, performance, and high availability. In loosely coupled environments, such as the Data Grid, the data sources are autonomous. Hence, the source updates can be concurrent and cause erroneous results during view maintenance. State-of-the-art maintenance strategies apply compensating queries to correct such errors, making the restricting assumption that all source schemata remain static over time. However, in such dynamic environments, the data sources may change not only their data but also their schema. Consequently, either the maintenance queries or the compensating queries may fail. In this paper, we propose a novel framework called DyDa that overcomes these limitations and handles both source data updates and schema changes. We identify three types of maintenance anomalies, caused by either source data updates, data-preserving schema changes, or non-data-preserving schema changes. We propose a compensation algorithm to solve the first two types of anomalies. We show that the third type of anomaly is caused by the violation of dependencies between maintenance processes. Then, we propose dependency detection and correction algorithms to identify and resolve the violations. Put together, DyDa extends prior maintenance solutions to solve all types of view maintenance anomalies. The experimental results show that DyDa imposes a minimal overhead on data update processing while allowing for the extended functionality to handle concurrent schema changes.
Application Development in Vision-Enabled Wireless Sensor Networks
Authors: Stephan Hengstler, Hamid Aghajan
Venue: Proceedings of the International Conference on Systems and Networks Communication (2006)

Wireless networks in combination with image sensors open up a multitude of previously unthinkable sensing applications. Capable tools and testbeds for these wireless image sensor networks can greatly accelerate development of complex, yet efficient algorithms that meet application requirements. In this paper, we introduce WiSNAP (Wireless Image Sensor Network Application Platform), a Matlab-based application development platform intended for wireless image sensor networks. It allows researchers and developers of such networks to investigate, design, and evaluate algorithms and applications using real target hardware. WiSNAP offers standardized and easy-to-use Application Program Interfaces (APIs) to control image sensors and wireless motes, which do not require detailed knowledge of the target hardware. Nonetheless, its open system architecture enables support of virtually any kind of sensor or wireless mote. Several application examples illustrate the usage of WiSNAP as a powerful development tool.
Efficient multivariate data-oriented microaggregation
Authors: Josep Domingo-Ferrer, Antoni Mart&#x00ed;nez-Ballest&#x00e9;, Josep Maria Mateo-Sanz, Francesc Seb&#x00e9;
Venue: The VLDB Journal &mdash; The International Journal on Very Large Data Bases (2006)

Microaggregation is a family of methods for statistical disclosure control (SDC) of microdata (records on individuals and/or companies), that is, for masking microdata so that they can be released while preserving the privacy of the underlying individuals. The principle of microaggregation is to aggregate original database records into small groups prior to publication. Each group should contain at least k records to prevent disclosure of individual information, where k is a constant value preset by the data protector. Recently, microaggregation has been shown to be useful to achieve k-anonymity, in addition to it being a good masking method. Optimal microaggregation (with minimum within-groups variability loss) can be computed in polynomial time for univariate data. Unfortunately, for multivariate data it is an NP-hard problem. Several heuristic approaches to microaggregation have been proposed in the literature. Heuristics yielding groups with fixed size k tends to be more efficient, whereas data-oriented heuristics yielding variable group size tends to result in lower information loss. This paper presents new data-oriented heuristics which improve on the trade-off between computational complexity and information loss and are thus usable for large datasets.