ppxscal/embedding_network huggingface dataset:
An Intelligent Assistant for Training of Power Plant Operators
Authors: Francisco Elizalde, Enrique Sucar, Pablo deBuen
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

During the operation of complex dynamic systems, the operator is exposed to unusual and abnormal situations, and has to be able to discriminate erroneous inputs, and promptly identify the source of the problem in order to define the corrective actions to be taken. In this work, the development and evaluation of an Intelligent Assistant for Operator's Training (IAOT) is presented. It uses, as input, a recommended plan generated by a decision-theoretic planner, which establishes the sequence of actions that will allow a steam generator to reach its optimum operation. The system monitors the operator's actions and detects his/her discrepancies, compared to those recommended by the planner. On the basis of the above, follow-up advice is given on-line, and an evaluation of performance is given later. Results obtained from an experimental evaluation of IAOT show that the usage of the intelligent assistant can be helpful to increase operator performance.
An adaptive machine learning approach to knowledge discovery in large datasets
Authors: James Cannady
Venue:  (2006)

Large text databases, such as medical records, on-line journals, or the Internet, potentially contain a great wealth of data and knowledge. However, text representation of factual information and knowledge is difficult to process. Analyzing these large text databases often rely upon time consuming human resources for data mining. Since a textual format is a very flexible way to describe and store various types of information, large amounts of information are often retained and distributed as text. "The amount of accessible textual data has been increasing rapidly. Such data may potentially contain a great wealth of knowledge. However, analyzing huge amounts of textual data requires a tremendous amount of work in reading all of the text and organizing the content. Thus, the increase in accessible textual data has caused an information flood in spite of hope of becoming knowledgeable about various topics" (Nasukawa and Nagano, 2001). Preliminary research focused on key concepts and techniques derived from clustering methodology, machine learning, and other communities within the arena of data mining. The research was based on a two-stage machine-intelligence system that clustered and filtered large datasets. The overall objective was to optimize response time through parallel processing while attempting to reduce potential errors due to knowledge manipulation. The results generated by the two-stage system were reviewed by domain experts and tested using traditional methods that included multivariable regression analysis and logic testing for accuracy. The two-stage prototype developed a model that was 85 to 90% accurate in determining childhood asthma and disproved existing stereotypes related to sleep breathing disorders. Detail results will be discussed in the proposed dissertation. While the initial research demonstrated positive results in processing large text datasets limitations were identified. These limitations included processing delays resulting from equal distribution of processing in a heterogeneous client environment and utilizing the results derived from the second-stage as inputs for the first-stage. To address these limitations the proposed doctoral research will investigate the dynamic distribution of processing in heterogeneous environment and cyclical learning involving the second-stage neural network clients modifying the first-stage expert systems.
Effects of Different Order PDEs on Blending Surfaces
Authors: Lihua You, Jian J. Zhang
Venue: Proceedings of the International Conference on Computer Graphics, Imaging and Visualisation (2006)

In this paper, we introduce second order and mixed order partial differential equations (PDEs) for surface blending and present an approximate algorithm for the resolution of the PDEs. We investigate how different orders of partial differential equations influence the continuities of blending surfaces.
Adaptive simulation
Authors: Mark K. Singley, Tracee Vetting Wolf, Peter Fairweather, Richard B. Lam
Venue: Proceedings of the 7th international conference on Learning sciences (2006)

We propose a new kind of learning environment called an adaptive simulation that more deeply explores and exploits the potential synergy between simulations and intelligent tutoring systems. In an adaptive simulation, the simulation environment is not fixed but rather can be modified by a tutoring agent for optimal pedagogical effect. Types of adaptations include manipulations of simulation time and state, changes in representation to facilitate explanations and/or task performance, and adjustments in simulation complexity by the addition and/or removal of components. Open research issues include how to perform these adaptations and when to employ them for optimal effect.
Analyzing Change Impact in Object-Oriented Systems
Authors: M. K. Abdi, H. Lounis, H. Sahraoui
Venue: Proceedings of the 32nd EUROMICRO Conference on Software Engineering and Advanced Applications (2006)

The development of software products consumes a lot of time and resources. On the other hand, these development costs are lower than maintenance costs, which represent a major concern, specially, for systems designed with recent technologies. Systems modification should be taken rigorously, and change effects must be considered. In this paper, we propose an approach, both analytical and experimental; its objective is to analyze and predict changes impacts in Object-Oriented (OO) systems. The method we follow consists first, to choose an existing impact model, and adapt it afterward. An impact calculation technique based on a meta-model is developed. To evaluate our approach, an empirical study was led on a real system in which a correlation hypothesis between coupling and change impact was advanced. A concrete change was done in the target system and coupling metrics were extracted from it. The hypothesis was verified with machine-learning (ML) techniques. Obtained results are interesting; they are presented and commented.
Compressed-Domain Encryption of Adapted H.264 Video
Authors: Razib Iqbal, Shervin Shirmohammadi, Abdulmotaleb El Saddik
Venue: Proceedings of the Eighth IEEE International Symposium on Multimedia (2006)

Commercial service providers and secret services yearn to employ the available environment for conveyance of their data in a secured way. In order to encrypt or to ensure personalized security of the video contents in an intermediary node, it is necessary to have the content structure conforming to an international standard. Moreover, pressure to satisfy user preferences and device requirements seamlessly are raising the need for content to be customized providing the best possible experience. In this paper, we present perceptual encryption scheme for video encryption that is incorporated with a dynamic temporal adaptation technique of the H.264 video conforming ISO/IEC MPEG-21 Digital Item Adaptation. Encryption is performed on demand directly from the adapted bitstream and its generic Bitstream Syntax Description (gBSD).
The Equivalence between Ordinal Optimization in Deterministic Complex Problems and in Stochastic Simulation Problems
Authors: Yu-Chi Ho, Qing-Shan Jia, Qian-Chuan Zhao
Venue: Discrete Event Dynamic Systems (2006)

In the last decade ordinal optimization (OO) has been successfully applied in many stochastic simulation-based optimization problems (SP) and deterministic complex problems (DCP). Although the application of OO in the SP has been justified theoretically, the application in the DCP lacks similar analysis. In this paper, we show the equivalence between OO in the DCP and in the SP, which justifies the application of OO in the DCP.
AMPol: Adaptive Messaging Policy
Authors: Raja Afandi, Jianqing Zhang, Munawar Hafiz, Carl A. Gunter
Venue: Proceedings of the European Conference on Web Services (2006)

Interoperability in a large-scale distributed system is challenged by by the diversity of node policies. We introduce AMPol (Adaptive Messaging Policy), a serviceoriented architecture that facilitates policy-aware, end-toend adaptive messaging between multiple parties. AMPol provides services for expressing non-functional QoS policies, finding them, and carrying out system extensions to adapt to them. We implement this approach with a web service middleware that allows parties to use policies for features like attachments, payment, encryption, and signatures. Our implementation demonstrates how AMPol can enhance the function of email messaging by enabling automatic deployment and use of features like cycle exhaustion puzzles, reverse Turing tests and identity based encryption without the need for global deployment or changes to the baseline messaging system.
LOCI: Load Shedding through Class-Preserving Data Acquisition
Authors: Peng Wang, Haixun Wang, Wei Wang, Baile Shi, Philip S. Yu
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

An avalanche of data available in the stream form is overstretching our data analyzing ability. In this paper, we propose a novel load shedding method that enables fast and accurate stream data classification. We transform input data so that its class information concentrates on a few features, and we introduce a progressive classifier that makes prediction with partial input. We take advantage of stream data's temporal locality . for example, readings from a temperature sensor usually do not change dramatically over a short period of time . for load shedding. We first show that temporal locality of the original data is preserved by our transform, then we utilize positive and negative knowledge about the data (which is of much smaller size than the data itself) for classification. We employ both analytical and empirical analysis to demonstrate the advantage of our approach.
A Quantum Key Distribution Network through Single Mode Optical Fiber
Authors: Muhammad Mubashir Khan, Salahuddin Hyder, Mahmood K. Pathan, Kashif H. Sheikh
Venue: Proceedings of the International Symposium on Collaborative Technologies and Systems (2006)

Quantum key distribution (QKD) has been developed within the last decade that is provably secure against arbitrary computing power, and even against quantum computer attacks. Now there is a strong need of research to exploit this technology in the existing communication networks. In this paper we have presented various experimental results pertaining to QKD like Raw key rate and Quantum bit error rate (QBER). We found these results over 25 km single mode optical fiber. The experimental setup implemented the enhanced version of BB84 QKD protocol. Based upon the results obtained, we have presented a network design which can be implemented for the realization of large scale QKD networks. Furthermore, several new ideas are presented and discussed to integrate the QKD technique in the classical communication networks.
Stochastic planning for weakly-coupled distributed agents
Authors: AnYuan Guo, Victor Lesser
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

Partially observable stochastic games (POSGs) provide a powerful framework for modeling multi-agent interactions. While elegant and expressive, this framework has been shown to be computationally intractable [1]. An exact dynamic programming algorithm for POSGs has been developed recently, but due to high computational demands, it has only been demonstrated to work on extremely small problems. Several approximate approaches have been developed [3, 5], but they lack strong theoretical guarantees. In light of these theoretical and practical limitations, there is a need to identify special classes of POSGs that can be solved tractably.
Revealing and mediating young children's memory and social cognition through digital photo journals
Authors: Cynthia Carter Ching, X. Christine Wang
Venue: Proceedings of the 7th international conference on Learning sciences (2006)

This study examines children's construction of digital photo journals and how this activity both mediates and reveals basic characteristics of their memory and social cognitive development. Twenty-one k/1st students created photo journals using a digital camera and iPhoto software. When children talked about their pictures and created captions for their journals, they demonstrated different kinds of autobiographical memory, as well as revealing gender-specific social views. First-graders showed greater awareness of their own memory capability (metamemory) in talking about their pictures than kindergarteners. Digital images seemed to present a relatively immediate yet imperfect or incomplete reminder that encouraged children's elaboration. Besides the process of journal construction, the contents of children's journals also reveal aspects of memory and social cognition that expand our existing knowledge in these areas.
Cryptographically private support vector machines
Authors: Sven Laur, Helger Lipmaa, Taneli Mielikäinen
Venue: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining (2006)

We propose private protocols implementing the Kernel Adatron and Kernel Perceptron learning algorithms, give private classification protocols and private polynomial kernel computation protocols. The new protocols return their outputs - either the kernel value, the classifier or the classifications - in encrypted form so that they can be decrypted only by a common agreement by the protocol participants. We show how to use the encrypted classifications to privately estimate many properties of the data and the classifier. The new SVM classifiers are the first to be proven private according to the standard cryptographic definitions.
On the simultaneous realization problem: Markov-parameter and covariance interpolation
Authors: P. Enqvist
Venue: Signal Processing (2006)

An efficient algorithm for determining the unique minimal and stable realization of a window ot Markov parameters and covariances is derived. The main difference compared to the Q-Markov COVER theory is that here we let the variance of the input noise be a variable, thus avoiding a certain data consistency criterion. First, it is shown that maximizing the input variance of the realization over all interpolants yields a minimal degree solution--a result closely related to maximum entropy. Secondly, the state space approach of the Q-Markov COVER theory is used for analyzing the stability and structure of the realization by straightforward application of familiar realization theory concepts, in particular the occurrence of singular spectral measures is characterized.
Group-awareness for Mobile Cooperative Learning
Authors: Roc Messeguer, Leandro Navarro, Angelica Reyes
Venue: Proceedings of the Fourth IEEE International Workshop on Wireless, Mobile and Ubiquitous Technology in Education (2006)

Collaborative learning traditionally relies on the arrangement of space and physical artifacts to mediate group activities. Our claim is that CSCL environments should enhance collaborative learning in a complementary way without introducing additional burden to human participants. This paper present research results on how tracking the location of people could be used to incorporate automatic group awareness in existing and new CSCL applications that support mobile cooperative learning. After presenting the requirements and structure of a middleware to handle automatic group awareness based on location information, two applications are presented. Experiments in a real setting on a jigsaw activity, with students using laptops with WiFi on a university course, confirm the validity of using location technology to automatically derive group structure and the positive effect on the learning results.
Modeling one human decision maker with a multi-agent system: the CODAGE approach
Authors: Jean-Daniel Kant, Samuel Thiriot
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

In this paper, we propose an agent-based model of human decision making: CODAGE (Cognitive Decision AGEnt). Classical Decision Theories have been widely used in multi-agent systems, but imply a too rational behavior when faced with real-world human data. Moreover, classical model usually exceeds human capabilities. Therefore, we derived our decision model from several cognitive psychological theories (e.g. Simon's decision theory, Montgomery's search of dominance structure, etc.) to take human bounded rationality into account. While most of existing cognitive agents use the BDI framework, we propose a new kind of architecture. In the CODAGE model, the decision maker is modeled by an entire multi-agent system, where each agent is in charge a particular sub-process of the whole decision. The architecture is intended to be as generic as possible. It could be viewed as an agent-based decision framework, in which different decision heuristics and biases could be implemented. We illustrate this approach with a simulation of a small experimental financial market, for which our model was able to replicate some human decision behaviors.
Interconnected Large-Scale Systems for Three Fundamental Cognitive Tasks Revealed by Functional MRI
Authors: Joy Hirsch, Diana Rodriguez Moreno, Karl H.S. Kim
Venue: Journal of Cognitive Neuroscience (2001)

The specific brain areas required to execute each of three fundamental cognitive tasks - object naming, same-different discrimination, and integer computation - are determined by whole-brain functional magnetic resonance imaging (fMRI) using a novel technique optimized for the isolation of neurocognitive systems. This technique (1) conjoins the activity associated with identical or nearly identical tasks performed in multiple sensory modalities (conjunction) and (2) isolates the activity conserved across multiple subjects (conservation). Cortical regions isolated by this technique are, thus, presumed associated with cognitive functions that are both distinguished from primary sensory processes and from individual differences. The object-naming system consisted of four brain areas: left inferior frontal gyrus, Brodmann's areas (BAs) 45 and 44; left superior temporal gyrus, BA 22; and left medial frontal gyrus, BA 6. The same-different discrimination system consisted of three brain areas: right inferior parietal lobule, BA 40; right precentral gyrus, BA 6; and left medial frontal gyrus, BA 6. The integer computation system consisted of five brain areas: right middle frontal gyrus, BA 6; right precentral gyrus, BA 6; left inferior parietal lobule, BA 40; left inferior frontal gyrus, BA 44; and left medial frontal gyrus, BA 6. All three neurocognitive systems shared one common cortical region, the left medial frontal gyrus, the object-naming and integer computation systems shared the left inferior frontal gyrus, and the integer computation and same-different discrimination systems shared the right precentral gyrus. These results are consistent with connectionist models of cognitive processes where specific sets of remote brain areas are assumed to be transiently bound together as functional units to enable these functions, and further suggest a superorganization of neurocognitive systems where single brain areas serve as elements of multiple functional systems.
Formal compiler construction in a logical framework
Authors: Jason Hickey, Aleksey Nogin
Venue: Higher-Order and Symbolic Computation (2006)

The task of designing and implementing a compiler can be a difficult and error-prone process. In this paper, we present a new approach based on the use of higher-order abstract syntax and term rewriting in a logical framework. All program transformations, from parsing to code generation, are cleanly isolated and specified as term rewrites. This has several advantages. The correctness of the compiler depends solely on a small set of rewrite rules that are written in the language of formal mathematics. In addition, the logical framework guarantees the preservation of scoping, and it automates many frequently-occurring tasks including substitution and rewriting strategies. As we show, compiler development in a logical framework can be easier than in a general-purpose language like ML, in part because of automation, and also because the framework provides extensive support for examination, validation, and debugging of the compiler transformations. The paper is organized around a case study, using the MetaPRL logical framework to compile an ML-like language to Intel x86 assembly. We also present a scoped formalization of x86 assembly in which all registers are immutable.
RM L-Filters for Real-Time Imaging
Authors: Jose Luis Varela-Benitez, Francisco Javier Gallegos-Funes, Volodymyr Ponomaryov
Venue: Proceedings of the 15th International Conference on Computing (2006)

In this paper we present the capability and real-time processing features of the RM L-filter for the removal of impulsive and multiplicative noise in real-time image processing applications. The proposed filter uses the robust RM-estimator in the filtering scheme of L-filter. The real-time implementation of proposed algorithm was realized on the DSP TMS320C6701. Extensive simulation results have demonstrated that the proposed filter consistently outperforms other filters by balancing the tradeoff between noise suppression and detail preservation.
Leveraging Wire Properties at the Microarchitecture Level
Authors: Rajeev Balasubramonian, Naveen Muralimanohar, Karthik Ramani, Liqun Cheng, John B. Carter
Venue: IEEE Micro (2006)

In future microprocessors, communication will emerge as the major bottleneck. The authors advocate composing future interconnects of some wires that minimize latency, some that maximize bandwidth, and some that minimize power. A microarchitecture aware of these wire characteristics can steer on-chip data transfers to the most appropriate wires, thus improving performance and saving energy.
Flash crowd in a file sharing system based on random encounters
Authors: I. Norros, B. J. Prabhu, H. Reittu
Venue: Proceedings from the 2006 workshop on Interdisciplinary systems approach in performance evaluation and design of computer & communications sytems (2006)

BitTorrent revolutionized the technique of distributing a very large file to a very large number of recipients. The file is chopped into small chunks that the recipients can immediately upload further. In the original design, a "tracker" keeps certain centralized control over the chunk transfer process. This paper studies a BitTorrent-like "information diffusion" system that has a fully distributed and symmetric architecture. The peers join a Distributed Hash Table -based overlay network and contact each other randomly. This kind of designs have been implemented and analysed recently. A trackerless BitTorrent system has been introduced which can be regarded as one based on random encounters --- the participating nodes contact each other at random and download missing chunks. On the analytical front, Massoulie and Vojnovic showed that a random encounter based system has surprisingly good performance without any chunk preference strategies, with the condition that each peer gets its first chunk from a sufficiently uniform distribution. In this paper, we focus on a scenario where this condition cannot be guaranteed, and show that a "rare chunk phenomenon" easily occurs, if both the encounters and the chunk selection are random. Classic urn models give some mathematical understanding of this phenomenon. We then discuss various techniques for alleviating the rare chunk problem and propose a simple distributed chunk selection policy that reduces the imbalance in the distribution of chunks within the network.