ppxscal/embedding_network huggingface dataset:
Extracting Symbolic Rules from Clustering of Gene Expression Data
Authors: Welbson S. Costa, Mateus S. de Assis, Marcilio C. P. de Souto
Venue: Proceedings of the Sixth International Conference on Hybrid Intelligent Systems (2006)

In the last few years, the increasing automation applied to Biology processes has led to a fast accumulation of im- portant biological data. The wide biological implications present in these data makes its analysis unsuitable via con- ventional computing. In this context, Machine Learning (ML) techniques have been showing very promising. One of the ML techniques for analyzing these data is cluster- ing methods. Experimental studies have shown that, often, clusters generated via such methods are biologically mean- ingful. However, in general, the interpretation of the bio- logical meaning of the clusters formed is a very complex task. Thus, this paper invests its efforts in the study of tech- niques that makes the interpretation of clusters formed by clustering techniques more straightforward. In order to do so, unsupervisedML techniques (clustering techniques) will be associated with supervised ML techniques (rule genera- tion). The goal is to generate symbolic structures, such as IF-THEN rules, which are more comprehensible for humans
Transitioning students from simulation mechanics to simulation as a process improvement tool: a multimedia case study approach
Authors: Scott R. Schultz, Christopher D. Geiger
Venue: Proceedings of the 37th conference on Winter simulation (2005)

Many undergraduate Industrial Engineering programs offer a course in discrete event simulation. While students often grasp the theory behind simulation and can perform the mechanics of model building and analysis, they often have difficulty formulating creative, viable process improvement ideas, which is a need of today's industrial employers. In this paper, a novel multimedia case-based teaching approach is presented that addresses this need. These multimedia cases are presented as course learning modules to the students. The components of the case-based learning modules include not only the requisite problem background, summary and relevant data, but they also include additional streaming video of the real-world process being studied, actual engineering drawings and still photos of the product and process, and a base simulation model. It is these additional components of the proposed multimedia teaching approach that help "bring the factory to the student" and better prepare graduates for the national workforce.
Comparison of three automated stacking alternatives by means of simulation
Authors: Yvo A. Saanen, Margaret V. Valkengoed
Venue: Proceedings of the 37th conference on Winter simulation (2005)

Container terminals are struggling with ever-increasing volumes, and are therefore searching for solutions to increase throughput capacity without expanding their physical footprint. They are also looking for cost-efficient solutions, leading to the application of semi-automated high density stacking systems for container storage. However, when selecting such a system, it needs to be determined what is the best configuration for that particular terminal, and secondly: how to make such a system productive? So far, we have seen various applications in practice that are quite different. How come? In this paper, we will compare three different automated container storage concepts on their efficiency in terms of productivity, flexibility, area utilization, and cost to come to a verdict: what is the best automated high-density concept yet existing? Furthermore, we will define the conditions under which a certain concept has to be preferred over another one.
Increasing Human-Organ Transplant Availability: Argumentation-Based Agent Deliberation
Authors: Pancho Tolchinsky, Ulises Cortes, Sanjay Modgil, Francisco Caballero, Antonio Lopez-Navidad
Venue: IEEE Intelligent Systems (2006)

This article is part of a special issue on Intelligent Agents in Healthcare. The shortage of human organs for transplantation is a serious problem, yet the current organ selection and assignment processes discard many organs deemed nonviable for transplantation. However, these processes ignore that medical specialists might disagree as to whether an organ is viable. A novel organ selection process lets transplant physicians, who might be geographically dispersed, deliberate over an organ's viability. This argument-based deliberation is formalized in a multiagent system called Carrel+, which requires the deliberation to adhere to formal rigorous standards acknowledging the domain's safety-critical nature.
Adaptive reorder buffers for SMT processors
Authors: Joseph Sharkey, Deniz Balkan, Dmitry Ponomarev
Venue: Proceedings of the 15th international conference on Parallel architectures and compilation techniques (2006)

In SMT processors, the complex interplay between private and shared datapath resources needs to be considered in order to realize the full performance potential. In this paper, we show that blindly increasing the size of the per-thread reorder buffers to provide a larger number of in-flight instructions does not result in the expected performance gains but, quite in contrast, degrades the instruction throughput for virtually all multithreaded workloads. The reason for this performance loss is the excessive pressure on the shared datapath resources, especially the instruction scheduling logic. We propose intelligent mechanisms for dynamically adapting the number of reorder buffer entries allocated to each thread in an effort to avoid such allocations if they detrimentally impact the scheduler. We achieve this goal through categorizing the program execution into issue-bound and commit-bound phases and only performing the buffer allocations to the threads operating in commit-bound phases. Our adaptive technique achieves improvements of 21% in instruction throughput and 10% in the fairness metric compared to the best performing baseline configuration with static ROBs.
Taking Newspapers from Hot Lead into the Electronic Age
Authors: Mike Marcus
Venue: IEEE Annals of the History of Computing (2006)

The authors discuss how they helped the Merganthaler Linotype Company adopt a computerized typesetting system.
An analysis of high-frequency noise in RF active CMOS mixers
Authors: Payam Heydari
Venue: Analog Integrated Circuits and Signal Processing (2006)

An analysis of high-frequency noise in RF active CMOS mixers including single-balanced and double-balanced architectures is presented. The analysis investigates the contribution of non-white gate-induced noise to the output noise power as well as the spot noise figure (NF) of the RF CMOS mixer. It accounts for the non-zero correlation between the gate-induced noise and the channel's thermal noise. The noise contribution of the RF transconductor and the switching pair to the output noise power is studied. Experimental results verify the accuracy of the analytical model.
The Research of Competitive Intelligence Organization of Dynamic Alliance (CIODA) in E-Commerce
Authors: Xiaowei Wu, Xiaobei Liang, Wenguan Song
Venue: Proceedings of the 2006 IEEE Asia-Pacific Conference on Services Computing (2006)

This paper points out the research of Competitive Intelligence Organization of dynamic alliance (CIODA) in E-commerce and analyzes the frame and the operation flow of CIODA with the modeling tools such as IDEF0 and IDEF3. Then it studies the complexity as well as the solution mentality of CIODA.
Enhancing Web Supported Learning by Adding a Management Layer to SCORM Compliant LMSs
Authors: Carlos Sousa Pinto, Fernando M. S. Ramos
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

Many Web based learning experiences fail due to bad or absent support. LMSs (Learning Management Systems) must incorporate mechanisms for real time monitorization of the involvement of each participant in a course, allowing the detection of deviations to the scheduled activities, enabling the correction of these deviations [1]. The principal standardization projects in the area do not cover this type of aspects. Those projects are mainly focused on contents and its delivery to the learners participating in the courses [2], [3], [4]. This article describes a proposal of a reference model and functionalities towards a specification of a layer for real-time management of user interactions with SCORM (Sharable Content Object Reference Model) compliant LMSs.
Automating Change Detection and Notification of Web Pages (Invited Paper)
Authors: Sharma Chakravarthy, Subramanian C. Hari Hara
Venue: Proceedings of the 17th International Conference on Database and Expert Systems Applications (2006)

Search engines provide an invaluable capability to search the web which is growing at a fast pace. In addition to growth, the content of the pages on the web is also changing continuously. Periodical retrieval of pages for understanding changes is both inefficient and time consuming. Search engines do not help in this aspect of information retrieval at all. In this paper, we present an overview of WebVigiL, a system that automates the change detection and timely notification of HTML/XML pages based on userspecified changes of interest. User interest, specified as a sentinel/profile, is automatically monitored by the system using a combination of learning-based and event-driven techniques. The system is currently available for use.
Data embedding techniques and applications
Authors: Li Yang
Venue: Proceedings of the 2nd international workshop on Computer vision meets databases (2005)

As an effective way for dimensionality reduction, data embedding has direct applications in data mining, data indexing and searching, information retrieval, and multimedia data processing. As two representative techniques for data embedding, both Isomap and LLE require the construction of neighborhood graphs on which every point is connected to its neighbors. This paper reviews several techniques that have been developed to construct connected neighborhood graphs. These methods have made Isomap and LLE applicable to a wide range of data including under-sampled data and non-uniformly distributed data. Application-related issues of data embedding techniques are also discussed.
ML grid programming with ConCert
Authors: Tom Murphy,  VII
Venue: Proceedings of the 2006 workshop on ML (2006)

Grid computing has become increasingly popular with the growth of the Internet, especially in large-scale scientific computation. Computational Grids are characterized by their scale, their heterogeneity, and their unreliability, making the creation of Grid software quite a challenge. Security concerns make the deployment of Grid infrastructure similarly daunting.We argue that functional programming techniques, both well-known and new, make an excellent practical foundation for Grid computing. We present a prototype Grid framework called ConCert built entirely in Standard ML which allows for the trustless dissemination of Grid programs through the use of certified code. The framework is fault-tolerant and relatively easy to implement, owing to a simplified network abstraction. This network abstraction is tedious to program for directly, so we present a high level ML-like language Grid/ML and a compiler Hemlock for the language.
Privacy mechanisms supporting the building of trust in e-commerce
Authors: Ildemaro Araujo
Venue: Proceedings of the 21st International Conference on Data Engineering Workshops (2005)

Consumer trust is crucial for the survival of Webbased businesses, since the lack of faith on Web merchants or stores can prevent the accomplishment of transactions. Techniques guaranteeing privacy in the management of customers' data in Web stores can help building trust by giving users a feeling of control on the vendor's handling of their personal information. This article analyzes the privacy concerns of Internet users and evaluates and proposes methods to handle privacy issues in Web stores that can help the development of trust in e-commerce.
Language Experience and the Organization of Brain Activity to Phonetically Similar Words: ERP Evidence from 14- and 20-Month-Olds
Authors: Debra L. Mills, Chantel Prat, Renate Zangl, Christine L. Stager, Helen J. Neville, Janet F. Werker
Venue: Journal of Cognitive Neuroscience (2004)

The ability to discriminate phonetically similar speech sounds is evident quite early in development. However, inexperienced word learners do not always use this information in processing word meanings [Stager & Werker (1997). Nature, 388, 381&ndash;382]. The present study used event-related potentials (ERPs) to examine developmental changes from 14 to 20 months in brain activity important in processing phonetic detail in the context of meaningful words. ERPs were compared to three types of words: words whose meanings were known by the child (e.g., ''bear''), nonsense words that differed by an initial phoneme (e.g., ''gare''), and nonsense words that differed from the known words by more than one phoneme (e.g., ''kobe''). These results supported the behavioral findings suggesting that inexperienced word learners do not use information about phonetic detail when processing word meanings. For the 14-month-olds, ERPs to known words (e.g., ''bear'') differed from ERPs to phonetically dissimilar nonsense words (e.g., ''kobe''), but did not differ from ERPs to phonetically similar nonsense words (e.g., ''gare''), suggesting that known words and similar mispronunciations were processed as the same word. In contrast, for experienced word learners (i. e., 20-month-olds), ERPs to known words (e.g., ''bear'') differed from those to both types of nonsense words (''gare'' and ''kobe''). Changes in the lateral distribution of ERP differences to known and unknown (nonce) words between 14 and 20 months replicated previous findings. The findings suggested that vocabulary development is an important factor in the organization of neural systems linked to processing phonetic detail within the context of word comprehension.
Query-Sensitive Similarity Measure for Content-Based Image Retrieval
Authors: Zhi-Hua Zhou, Hong-Bin Dai
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

Similarity measure is one of the keys of a high-performance content-based image retrieval (CBIR) system. Given a pair of images, existing similarity measures usually produce a static and constant similarity score. However, an image can usually be perceived with different meanings and therefore, the similarity between the same pair of images may change when the concept being queried changes. This paper proposes a query-sensitive similarity measure, Qsim, which takes the concept being queried into account in measuring image similarities, by exploiting the query image as well as the images labeled by user in the relevance feedback process. Experimental comparisons to state-of-the-art techniques show that Qsim has superior performance.
Robotics and Intelligent Systems in Support of Society
Authors: Raj Reddy
Venue: IEEE Intelligent Systems (2006)

Over the past 50 years, there has been extensive research into robotics and intelligent systems. While much of the research has targeted specific technical problems, advances in these areas have led to systems and solutions that will have a profound impact on society. This article provides several examples of the use of such ecotechnologies in the service of humanity, in the areas of robotics, speech, vision, human computer interaction, natural language processing, and artificial intelligence. This article is part of a special issue on the Future of AI.
Mapped WENO and weighted power ENO reconstructions in semi-discrete central schemes for Hamilton-Jacobi equations
Authors: Steve Bryson, Doron Levy
Venue: Applied Numerical Mathematics (2006)

We incorporate new high-order WENO-type reconstructions into Godunov-type central schemes for Hamilton-Jacobi equations. We study schemes that are obtained by combining the Kurganov-Noelle-Petrova flux with the weighted power ENO and the mapped WENO reconstructions. We also derive new variants of these reconstructions by composing the weighted power ENO and the mapped WENO reconstructions with each other. While all schemes are, formally, fifth-order accurate, we show that the quality of the approximation does depend on the particular reconstruction that is being used. In certain cases, it is shown that the approximate solution may not converge to the viscosity solution at all.
Tracing Problem Solving in Real Time: fMRI Analysis of the Subject-paced Tower of Hanoi
Authors: John R. Anderson, Mark V. Albert, Jon M. Fincham
Venue: Journal of Cognitive Neuroscience (2005)

Previous research has found three brain regions for tracking components of the ACT-R cognitive architecture: a posterior parietal region that tracks changes in problem representation, a prefrontal region that tracks retrieval of task-relevant information, and a motor region that tracks the programming of manual responses. This prior research has used relatively simple tasks to incorporate a slow event-related procedure, allowing the blood oxygen level-dependent (BOLD) response to go back to baseline after each trial. The research described here attempts to extend these methods to tracking problem solving in a complex task, the Tower of Hanoi, which involves many complex steps of cognition and motor actions in rapid succession. By tracking the activation patterns in these regions, it is possible to predict with intermediate accuracy when participants are planning a future sequence of moves. The article describes a cognitive model in the ACT-R architecture that is capable of explaining both the latency data in move generation and the BOLD responses in these three regions.
Quantifying instruction-level parallelism limits on an EPIC architecture
Authors: Hsien-Hsin Lee
Venue: Proceedings of the 2000 IEEE International Symposium on Performance Analysis of Systems and Software (2000)

EPIC architectures rely heavily on state-of-the-art compiler technology to deliver optimal performance while keeping hardware design simple. It is generally believed that an optimizing compiler has an enormous scheduling window to exploit instruction-level parallelism (ILP) since the compiler orchestrates the entire program. Many state-of-the-art compilers typically confine optimizations to loop boundaries (e.g. software pipelining, trace scheduling, and loop unrolling) and function boundaries (e.g. loop peeling, loop exchanges, invariant hoisting, and global optimizations). Although techniques such as function inlining and interprocedural optimizations can alleviate these constraints to a limited extent, loop and function boundaries are often the real scopes of the compiler scheduler. Several previous ILP studies have explored the limits of parallelism on dynamic superscalar machines; however, those results are not applicable to EPIC architectures since they rely on dynamic scheduling, not static code scheduling by the compiler, to reorder instructions. In this paper, we evaluate the limits in ILP obtained through compiler scheduling alone. We quantify these limits as more restrictive scheduling constraints are imposed-starting from inter-procedural code scheduling, to intra-procedural and finally to loop-confined code scheduling.
Combining Response Surface Methodology with Numerical Methods for Optimization of Markovian Models
Authors: Peter Kemper, Dennis Muller, Axel Thummler
Venue: IEEE Transactions on Dependable and Secure Computing (2006)

In general, decision support is one of the main purposes of model-based analysis of systems. Response surface methodology (RSM) is an optimization technique that has been applied frequently in practice, but few automated variants are currently available. In this paper, we show how to combine RSM with numerical analysis methods to optimize continuous time Markov chain models. Among the many known numerical solution methods for large Markov chains, we consider a Gauss-Seidel solver with relaxation that relies on a hierarchical Kronecker representation as implemented in the APNN Toolbox. To effectively apply RSM for optimizing numerical models, we propose three strategies which are shown to reduce the required number of iterations of the numerical solver. With a set of experiments, we evaluate the proposed strategies with a model of a production line and apply them to optimize a class-based queueing system.
The Semantic Pathfinder: Using an Authoring Metaphor for Generic Multimedia Indexing
Authors: Cees G. M. Snoek, Marcel Worring, Jan-Mark Geusebroek, Dennis C. Koelma Frank J. Seinstra, Arnold W. M. Smeulders
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2006)

This paper presents the semantic pathfinder architecture for generic indexing of multimedia archives. The semantic pathfinder extracts semantic concepts from video by exploring different paths through three consecutive analysis steps, which we derive from the observation that produced video is the result of an authoring-driven process. We exploit this authoring metaphor for machine-driven understanding. The pathfinder starts with the content analysis step. In this analysis step, we follow a data-driven approach of indexing semantics. The style analysis step is the second analysis step. Here, we tackle the indexing problem by viewing a video from the perspective of production. Finally, in the context analysis step, we view semantics in context. The virtue of the semantic pathfinder is its ability to learn the best path of analysis steps on a per-concept basis. To show the generality of this novel indexing approach, we develop detectors for a lexicon of 32 concepts and we evaluate the semantic pathfinder against the 2004 NIST TRECVID video retrieval benchmark, using a news archive of 64 hours. Top ranking performance in the semantic concept detection task indicates the merit of the semantic pathfinder for generic indexing of multimedia archives.
SDG Cut: 3D Reconstruction of Non-lambertian Objects Using Graph Cuts on Surface Distance Grid
Authors: Tianli Yu, Narendra Ahuja, Wei-Chao Chen
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (2006)

We show that the approaches to 3D reconstruction that use volumetric graph cuts to minimize a cost function over the object surface have two types of biases, the minimal surface bias and the discretization bias. These biases make it difficult to recover surface extrusions and other details, especially when a non-lambertian photo-consistency measure is used. To reduce these biases, we propose a new iterative graph cuts based algorithm that operates on the Surface Distance Grid (SDG), which is a special discretization of the 3Dspace, constructed using a signed distance transform of the current surface estimate. It can be shown that SDG significantly reduces the minimal surface bias, and transforms the discretization bias into a controllable degree of surface smoothness. Experiments on 3D reconstruction of non-lambertian objects confirm the effectiveness of our algorithm over previous methods.