ppxscal/embedding_network huggingface dataset:
The Future of AI in Space
Authors: Steve Chien, Richard Doyle, Ashley Gerard Davies, Ari Jonsson, Ralph Lorenz
Venue: IEEE Intelligent Systems (2006)

Two key flight technology experiments--the Remote Agent Experiment (RAX) and the AutonomousSciencecraft Experiment (ASE)--validated appropriate uses of AI-based capabilities in future robotic andhuman exploration of the Moon, Mars, and beyond. A survey of future missions describes some of them.
How Portugal Celebrated AI's 50th Anniversary
Authors: Carlos Ramos
Venue: IEEE Intelligent Systems (2006)

On 31 May 2006, the Institute of Engineering at Polytechnic of Porto (ISEP/IPP) in Portugal celebrated the 50th anniversary of AI. At that event, the ISEP/IPP museum unveiled its "Artificial Intelligence: 50 Years" exhibition.
Visualizing Clone Cohesion and Coupling
Authors: Zhen Ming Jiang, Ahmed E. Hassan, Richard C. Holt
Venue: Proceedings of the XIII Asia Pacific Software Engineering Conference (2006)

Coupling and cohesion between subsystems are commonly studied metrics when analyzing the architecture of software systems. It is usually desirable for subsystems to have high cohesion within the subsystem and to have low coupling to other subsystems. High cohesion implies cohesive concerns and low coupling implies localized changes. We extend the ideas of coupling and cohesion to code cloning. A code clone is a segment of code that has been created through duplication of another piece of code. Previous research has shown that in some instances code cloning is desirable, whereas in other cases it is not. We believe that it is justifiable to have code cloning within subsystems (high cohesion), whereas it is not justifiable and likely not desirable to have it across subsystems (high coupling). We present an approach, which consists of a framework that generates and filters cloning data and a visualization technique which graphically highlights clone cohesion and coupling between architectural subsystems. Our approach can be used by developers to locate undesirable cloning in their software system. We demonstrate our approach through a case study on the SCSI drivers in the Linux kernel.
Mining Complex Time-Series Data by Learning Markovian Models
Authors: Yi Wang, Lizhu Zhou, Jianhua Feng, Jianyong Wang, Zhi-Qiang Liu
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

In this paper, we propose a novel and general approach for time-series data mining. As an alternative to traditional ways of designing specific algorithm to mine certain kind of pattern directly from the data, our approach extracts the temporal structure of the time-series data by learning Markovian models, and then uses well established methods to efficiently mine a wide variety of patterns from the topology graph of the learned models. We consolidate the approach by explaining the use of some well-known Markovian models on mining several kinds of patterns. We then present a novel high-order hidden Markov model, the variable-length hidden Markov model (VLHMM), which combines the advantages of well-known Markovian models and has the superiority in both efficiency and accuracy. Therefore, it can mine a much wider variety of patterns than each of prior Markovian models. We demonstrate the power of VLHMM by mining four kinds of interesting patterns from 3D motion capture data, which is typical for the high-dimensionality and complex dynamics.
The effect of internet technology in the exporter-distributor relationship
Authors: Gary A. Knight
Venue:  (2005)

The effect of Internet technology use on the relationship between U.S. exporters and their overseas distributors is investigated. This study examines the effects Internet technology may have on the quality of communication, the quality of relationship, the level of distributor motivation, and distributor performance. Results of a study of 261 exporting manufacturers from across the United States suggests that Internet technology has a positive effect on the quality of communication between exporters and distributors. However, for that increase in communication quality to affect distributor performance, it must be mediated by either (a) distributor motivation through cooperation in the relationship, or (b) commitment in the relationship. Results also suggest that the role of trust in the exporter-distributor relationship may not be as vital as previously thought. These results are discussed with regard to their theoretical and practical implications.
The 2-dipath chromatic number of Halin graphs
Authors: Chen Min, Wang Weifan
Venue: Information Processing Letters (2006)

A 2-dipath k-coloring f of an oriented graph G→ is a mapping from V(G→) to the color set {1, 2 ....k} such that f(x) ≠ f(y) whenever two vertices x and y are linked by a directed path of length 1 or 2. The 2-dipath chromatic number χ→2(G→) of G→ is the smallest k such that G→ has a 2-dipath k-coloring. In this paper we prove that if G→ is an oriented Halin graph, then χ→2(G→) ≤ 7. There exist infinitely many oriented Halin graphs G→ such that χ→2(G→) = 7.
Supernova Recognition Using Support Vector Machines
Authors: Raquel A. Romano, Cecilia R. Aragon, Chris Ding
Venue: Proceedings of the 5th International Conference on Machine Learning and Applications (2006)

We introduce a novel application of Support Vector Machines (SVMs) to the problem of identifying potential supernovae using photometric and geometric features computed from astronomical imagery. The challenges of this supervised learning application are significant: 1) noisy and corrupt imagery resulting in high levels of feature uncertainty, 2) features with heavy-tailed, peaked distributions, 3) extremely imbalanced and overlapping positive and negative data sets, and 4) the need to reach high positive classification rates, i.e. to find all potential supernovae, while reducing the burdensome workload of manually examining false positives. High accuracy is achieved via a sign-preserving, shifted log transform applied to features with peaked, heavy-tailed distributions. The imbalanced data problem is handled by oversampling positive examples, selectively sampling misclassified negative examples, and iteratively training multiple SVMs for improved supernova recognition on unseen test data. We present cross-validation results and demonstrate the impact on a large-scale supernova survey that currently uses the SVM decision value to rank-order 600,000 potential supernovae each night.
Semantic patches considered helpful
Authors: Gilles Muller, Yoann Padioleau, Julia L. Lawall, René Rydhof Hansen
Venue: ACM SIGOPS Operating Systems Review (2006)

Modern software development is characterized by the use of libraries and interfaces. This software architecture carries down even to the operating system level. Linux, for example, is organized as a small kernel, complemented with libraries providing generic functionalities for use in implementing network access, file management, access to physical devices, etc. Much of the Linux source code then consists of service-specific files that use these libraries. These libraries are also used by the many OS-level services that are maintained outside of the Linux source tree.
Multi-robot learning with particle swarm optimization
Authors: Jim Pugh, Alcherio Martinoli
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

We apply an adapted version of Particle Swarm Optimization to distributed unsupervised robotic learning in groups of robots with only local information. The performance of the learning technique for a simple task is compared across robot groups of various sizes, with the maximum group size allowing each robot to individually contain and manage a single PSO particle. Different PSO neighborhoods based on limitations of real robotic communication are tested in this scenario, and the effect of varying communication power is explored. The algorithms are then applied to a group learning scenario to explore their susceptibility to the credit assignment problem. Results are discussed and future work is proposed.
Sports video classification using HMMS
Authors: X. Gibert, Huiping Li, D. Doermann
Venue: Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1 (2003)

In this paper we address the problem of sports video classification using hidden Markov models (HMMs). For each sports genre, we construct two HMMs representing motion and color features respectively. The observation sequences generated from the principal motion direction and the principal color of each frame are fed to a motion and a color HMM respectively. The outputs are integrated to make a final decision. We tested our scheme on 220 minutes of sports video with four genre types: ice hockey, basketball, football, and soccer, and achieved an overall classification accuracy of 93%.
Trust Assessment Using Provenance in Service Oriented Applications
Authors: Shrija Rajbhandari, Arnaud Contes, Omer F. Rana, Vikas Deora, Ian Wootten
Venue: Proceedings of the 10th IEEE on International Enterprise Distributed Object Computing Conference Workshops (2006)

Workflow forms a key part of many existing Service Oriented applications, involving the integration of services that may be made available at distributed sites. It is possible to distinguish between an "abstract" workflow description outlining which services must be involved in a workflow execution and a "physical" workflow description outlining the particular instances of services that were used in a particular enactment. Provenance information provides a useful way to capture the physical workflow description automatically especially if this information is captured in a standard format. Subsequent analysis on this provenance information may be used to evaluate whether the abstract workflow description has been adhered to, and to enable a user executing a workflow-based application to establish "trust" in the outcome.
Natural object detection in outdoor scenes based on probabilistic spatial context models
Authors: Jiebo Luo, A. Singhal, Weiyu Zhu
Venue: Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1 (2003)

Natural object detection in outdoor scenes, i.e., identifying key object types such as sky, grass, foliage, water, and snow, can facilitate content-based applications, ranging from image enhancement to other multimedia applications. A major limitation of individual object detectors is the significant number of misclassifications that occur because of the similarities in color and texture characteristics of various object types and lack of context information. We have developed a spatial context-aware object-detection system that first combines the output of individual object detectors to produce a composite belief vector for the objects potentially present in an image. Spatial context constraints, in the form of probability density functions obtained by learning, are subsequently used to reduce misclassification by constraining the beliefs to conform to the spatial context models. Experimental results show that the spatial context models improve the accuracy of natural object detection by 13% over the individual object detectors themselves.
Design and Developmental Metrics of a `Skin-Like' Multi-Input Quasi-Compliant Robotic Gripper Sensor Using Tactile Matrix
Authors: Debanik Roy
Venue: Journal of Intelligent and Robotic Systems (2006)

Slip-resistant robust grasping of objects during remote manipulation remains one of the major open issues in robotics. Finer measurement of tangential force and slippage need to be considered for the task planning and control of robotic gripper in operation. Design and development of such a multi-sensory tactile array is reported in this paper, which is aimed for direct use in an instrumented jaw intelligent robot gripper for potentially hazardous radioactive environments. A new design has been reported in the paper, wherein sensing members of the prototype follow a combination of beam (bending) and truss-type (axial deformation) behavior under external loadings. Various characteristics of the sensor, viz. condition number, static and dynamic stiffness, sensitivity and repeatability have been evaluated, based on the results from field trials of the prototype. Besides the comparatively larger prototype, a miniaturized version of the sensor has also been developed and tested for object grasping in real-time.
Classifier Combination Types for Biometric Applications
Authors: Sergey Tulyakov, Venu Govindaraju
Venue: Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (2006)

In this paper we present four types of classifier combinations determined by the numbers of trained combining functions and their input parameters. We discuss the usage of these combination types in biometric applications and give an example of suboptimal combination as a result of choosing non-appropriate combination type. Finally, we present results of combinations in biometric identification systems utilizing similar methods, but related to different combination types.
Electroencephalograph Signal Analysis During Bramari
Authors: S. T. Patil, D. S. Bormane
Venue: Proceedings of the 9th International Conference on Information Technology (2006)

Bramari is one part of the Pranayama, as traditionally conceived, involves much more than merely breathing for relaxation. Bramari is a term with a wide range of meanings. "The regulation of the incoming and outgoing flow of breath with retention''. Bramari also denotes cosmic power, or the power of the entire universe which manifests itself as conscious living being in us through the phenomenon of breathing. Because of this connection between breath and consciousness. Pranayama has devised Bramari to stabilize energy and consciousness. A wavelet transformation is applied to electroencephalograph (EEG) records from persons under Bramari. Correlation dimension, Largest lyapunov exponent, Approximate entropy and coherence values are analyzed. This model along with software is used to keep track on the improvement of the persons mind, aging, balance, flexibility, personnel values, mental values, social values, love, sex, knowledge, weight reduction and body fitness.
Software Demand, Hardware Supply
Authors: Jesus Alastruey, Jose Luis Briz, Pablo Ibanez, Victor Cinals
Venue: IEEE Micro (2006)

Do the demands of new software outpace developments in hardware? Experiments with the behavior of SPEC CPU on-chip caches and data collection from a wide range of processors over time address this question and illuminate trends in software and hardware evolution.
Types, bytes, and separation logic
Authors: Harvey Tuch, Gerwin Klein, Michael Norrish
Venue: Proceedings of the 34th annual ACM SIGPLAN-SIGACT symposium on Principles of programming languages (2007)

We present a formal model of memory that both captures the low-level features of C's pointers and memory, and that forms the basis for an expressive implementation of separation logic. At the low level, we do not commit common oversimplifications, but correctly deal with C's model of programming language values and the heap. At the level of separation logic, we are still able to reason abstractly and efficiently. We implement this framework in the theorem prover Isabelle/HOL and demonstrate it on two case studies. We show that the divide between detailed and abstract does not impose undue verification overhead, and that simple programs remain easy to verify. We also show that the framework is applicable to real, security- and safety-critical code by formally verifying the memory allocator of the L4 microkernel.
A Neural Key Generator for a Public Block Cipher
Authors: Ana Maria G. Guerreiro, Carlos Paz de Araujo
Venue: Proceedings of the Ninth Brazilian Symposium on Neural Networks (2006)

In this paper, the applicability of using an artificial Spiking Neural Network with a symmetric block cipher is explored. Our goal is to develop a novel neural block cipher where the keys are generated by a spiking neural network and can have any desired block length. With the new algorithm the private keys do not have to be exchanged and present a stronger process of key scheduling. The system allows a rapid change in encryption keys and a network level encryption to be done at very high speed without the problem of factorization of other systems. The block cipher will be transformed in a public cryptosystem, less vulnerable to brute force attacks, and it is hoped to be also resistant to linear attacks since the spiking neuron network architecture brings non-linearity to the encryption/decryption process.
Distances and (Indefinite) Kernels for Sets of Objects
Authors: Adam Woznica, Alexandros Kalousis, Melanie Hilario
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

The main disadvantage of most existing set kernels is that they are based on averaging, which might be inappropriate for problems where only specific elements of the two sets should determine the overall similarity. In this paper we propose a class of kernels for sets of vectors directly exploiting set distance measures and, hence, incorporating various semantics into set kernels and lending the power of regularization to learning in structural domains where natural distance functions exist. These kernels belong to two groups: (i) kernels in the proximity space induced by set distances and (ii) set distance substitution kernels (non-PSD in general). We report experimental results which show that our kernels compare favorably with kernels based on averaging and achieve results similar to other state-of-the-art methods. At the same time our kernels systematically improve over the naive way of exploiting distances.
Information technology infusion model for health sector in a developing country: Nigeria as a case
Authors: Bayo Idowu, Rotimi Adagunodo, Rufus Adedoyin
Venue: Technology and Health Care (2006)

To date, information technology (IT) has not been widely adopted in the health sector in the developing countries. Information Technology may bring an improvement on health care delivery systems. It is one of the prime movers of globalization. Information technology infusion is the degree to which a different information technology tools are integrated into organizational activities. This study aimed to know the degree and the extent of incorporation of Information Technology in the Nigerian health sector and derive an IT infusion models for popular IT indicators that are in use in Nigeria (Personal computers, Mobile phones, and the Internet) and subsequently investigates their impacts on the health care delivery system in Nigerian teaching hospitals. In this study, data were collected through the use of questionnaires. Also, oral interviews were conducted and subsequently, the data gathered were analyzed. The results of the analysis revealed that out of the three IT indicators considered, mobile phones are spreading fastest. It also revealed that computers and mobile phones are in use in all the teaching hospitals. Finally in this research, IT infusion models were developed for health sector in Nigeria from the data gathered through the questionnaire and oral interview.
WISENT: e-Science for Energy Meteorology
Authors: Wilhelm Hasselbring, Detlev Heinemann, Johannes Hurka, Thomas Scheidsteger, Ludger Bischofs, Christoph Mayer, Jan Ploski, Guido Scherp, Sina Lohmann, Carsten Hoyer-Klick, Thilo Erbertseder, Gerhard Gesell, Marion Schroedter-Homscheidt, Gerd Heilscher, Jochen Rehwinkel, Stefan Rensberg
Venue: Proceedings of the Second IEEE International Conference on e-Science and Grid Computing (2006)

Our energy production increasingly depends on renewable energy sources, which impose new challenges for distributed and decentralized systems. One problem is that the availability of renewable energy sources such as wind and solar is not continuous as it is affected by meteorological factors. The challenge is to develop forecast methods capable of determining the level of power generation in near real-time in order to control power plants for optimal energy production. Another scenario is the identification of optimal locations for such power plants. In our collaborative project, these tasks are investigated in the domain of energy meteorology. For that purpose large data sources from many different sensors (e.g., satellites and ground stations) are the base for complex computations. The idea is to parallelize these computations in order to obtain significant speedup. This paper reports on an ongoing project employing Grid technologies in that context. Our approach to processing large data sets from a variety of heterogeneous data sources as well as ideas for parallel and distributed computing in energy meteorology are presented. Preliminary experience with several Grid middleware systems in our application scenario is discussed.
IMPDET - an Online PhD Study Program in Educational Technology
Authors: Elina Hartikainen, Jarkko Suhonen, Erkki Sutinen
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

In the IMPDET (International Multidisciplinary PhD Studies in Educational Technology) online study program, students study towards the PhD degree in educational technology. The program brings together international experts in computer science, education, cultural studies, engineering, and other fields in order to prepare future generations of educational technologists to carry out projects that are tailored to a variety of global contexts, however, in a culturally sensitive way. The first IMPDET students started their studies in 2005, and the first courses were run between October 2005 and February 2006. The first experiences indicate the need for student mentoring and an architecture that allows building a real learner community where both supervisors and learners are actively engaged in improving the used learning environments.
DuoTracker: Tool Support for Software Defect Data Collection and Analysis
Authors: Olusegun Akinwale, Sergiu Dascalu, Marcel Karam
Venue: Proceedings of the International Conference on Software Engineering Advances (2006)

In today software industry defect tracking tools either help to improve an organization's software development process or an individual's software development process. No defect tracking tool currently exists that help both processes. In this paper we present DuoTracker, a tool that makes possible to track and analyze software defects for organizational and individual software process decision making. To accomplish this, DuoTracker has capabilities to classify defects in a manner that makes analysis at both organizational and individual software processes meaningful. The benefit of this approach is that software engineers are able to see how their personal software process improvement impacts their organization and vice versa. This paper shows why software engineers need to keep track of their program defects, how this is currently done, and how DuoTracker offers a new way of keeping track of software errors. Furthermore, DuoTracker is compared to other tracking tools that enable software developers to record program defects that occur during their individual software processes.
Hierarchical molecular modelling with ellipsoids
Authors: Nelson Max
Venue: Journal of Molecular Graphics (2004)

Protein and DNA structures are represented at varying levels of details using ellipsoidal RGBA textured splats. The splat texture at each level is generated by rendering its children in a hierarchical model, from a distribution of viewing directions, and averaging the result. For rendering, the ellipsoids to be used are chosen adaptively, depending on the distance to the viewpoint. This technique is applied to visualize DNA coiling around nucleosomes in chromosomes.