ppxscal/embedding_network huggingface dataset:
Input Feedback Networks: Classification and Inference Based on Network Structure
Authors: Tsvi Achler, Eyal Amir
Venue: Proceeding of the 2008 conference on Artificial General Intelligence 2008: Proceedings of the First AGI Conference (2008)

We present a mathematical model of interacting neuron-like units that we call Input Feedback Networks (IFN). Our model is motivated by a new approach to biological neural networks, which contrasts with current approaches (e.g. Layered Neural Networks, Perceptron etc.). Classification reasoning in IFN are accomplished by an iterative algorithm, and learning changes only structure. Feature relevance is determined during classification. Thus it emphasizes network structure over edge weights. IFNs are more flexible than previous approaches. In particular, integration of a new node can affect the outcome of existing nodes without modifying their prior structure. IFN can produce informative responses to partial inputs or when the networks are extended to other tasks. It also enables recognition of complex entities (e.g. images) from parts. This new model is promising for future contributions to integrated human-level intelligent applications due to its flexibility, dynamics and structural similarity to natural neuronal networks.
On approximating the ideal random access machine by physical machines
Authors: Gianfranco Bilardi, Kattamuri Ekanadham, Pratap Pattnaik
Venue: Journal of the ACM (JACM) (2009)

The capability of the Random Access Machine (RAM) to execute any instruction in constant time is not realizable, due to fundamental physical constraints on the minimum size of devices and on the maximum speed of signals. This work explores how well the ideal RAM performance can be approximated, for significant classes of computations, by machines whose building blocks have constant size and are connected at a constant distance. A novel memory structure is proposed, which is pipelined (can accept a new request at each cycle) and hierarchical, exhibiting optimal latency a(x) &equals; O(x1/d) to address x, in d-dimensional realizations. In spite of block-transfer or other memory-pipeline capabilities, a number of previous machine models do not achieve a full overlap of memory accesses. These are examples of machines with explicit data movement. It is shown that there are direct-flow computations (without branches and indirect accesses) that require time superlinear in the number of instructions, on all such machines. To circumvent the explicit-data-movement constraints, the Speculative Prefetcher (SP) and the Speculative Prefetcher and Evaluator (SPE) processors are developed. Both processors can execute any direct-flow program in linear time. The SPE also executes in linear time a class of loop programs that includes many significant algorithms. Even quicksort, a somewhat irregular, recursive algorithm admits a linear-time SPE implementation. A relation between instructions called address dependence is introduced, which limits memory-access overlap and can lead to superlinear time, as illustrated with the classical merging algorithm.
The Power of Optical/IR Interferometry: Recent Scientific Results and 2nd Generation Instrumentation Proceedings of the ESO Workshop held in Garching, ... 4-8 April 2005, 1st edition
Authors: A. Richichi, F. Delplancke, F. Paresce, A. Chelli
Venue: Eso Astrophysics Symposia (2007)

New interferometers as the VLTI, the Keck-I and CHARA along with their sophisticated instrumentation have provided new levels of accuracy, spectral resolution and access to various spectral bands from the optical to the thermal infrared. Investigations are now enabled on a wealth of astrophysical sources with unprecedented levels of angular resolution and sensitivity, producing a considerable body of new, exciting scientific results. Celebrating the completion of the first phase of the VLTI development, the organisors of the ESO workshop "The Power of Optical/IR Interferometry", held in April 2005, saw an opportunity to invite the community to come together to review and discuss not just interferometers, but science with interferometers and its impact on astronomy as a whole. The workshop was also intended to showcase ideas and concepts for the future of interferometry, and in particular for the second generation of VLTI instrumentation. This volume contains the proceedings of this workshop and serves as reference for astronomers working with optical and infrared interferometry.
Techniques for improved diagnosis
Authors: Spyros Tragoudas
Venue:  (2008)

Fault diagnosis is an essential part in the test cycle of an integrated circuit design. Efficient diagnosis improves the reliability of the chip, increases the production yield, and reduces the time to market. This dissertation presents three different solutions to improve fault diagnosis. The proposed techniques reduce the effort in diagnosing the source of failure by reducing the number faults considered during diagnosis, by generating additional tests which are capable of pruning faults that cannot correlate the failure in design and by prioritizing faults for diagnosis. Experimental results demonstrate the effectiveness of the proposed techniques.
Use of semantic web technology for adding 3D detail to GIS landscape data
Authors: Pedro Maroun Eid, Sudhir Mudur
Venue: Proceedings of the 2nd Canadian Conference on Computer Science and Software Engineering (2009)

GIS content is currently widely available and standardized. However, a great challenge remains in the definition of 3D GIS content. Presently, most 3D content is manually defined and refined by experts in order to result in the fidelity needed by a simulation application such as a virtual training system. In this paper, we present a new approach using semantic web technology that allows experts to formalize their knowledge in the form of an ontology which is then used to provide automated support in the definition of high fidelity 3D GIS content. This approach would allow a low-turn around between acquiring initial data from a certain area and having high fidelity 3D visualization of real world landscapes from GIS data.
Learning biological interactions from multiple data sources
Authors: Xin Zhang
Venue:  (2008)

Inferring gene and protein interactions allow us to understand the mechanism of biological processes and the events that lead to diseases. This research focuses on designing joint learning algorithms and frameworks for studying biological interactions, including gene regulatory networks, protein-protein interactions, gene-protein interactions, and gene-drug interactions for hit selection. In the gene regulatory network study, a modified Inductive Causation (mIC) algorithm is presented. It combines steady state data with partial prior knowledge of topological ordering for joint learning the causal relationship among genes. In real data analysis, the mIC algorithm identified the important causal relations associated with WNT5A, a gene playing an important role in melanoma. In the protein-protein interaction study, a Bayesian modeling framework is applied for learning high order logic relationships among proteins from multiple data sources. The method is able to identify several known disease-related interactions such as Mad Cow Disease-related prions interactions. In the protein-DNA interaction study, a kernel-based learning method is presented for predicting DNA-binding proteins. The method applies a kernel function on each type of data source and combines the kernels for classification using Support Vector Machines (SVMs). The results demonstrate that the kernel method in combination with multiple data sources has great potential in accurately predicting DNA-binding proteins. Large-scale RNAi screening is a powerful tool for discovering functional genomics and identifying drug targets. In the gene-drug interaction study, a computational analysis is presented for identifying key factors in assay optimization. A new method to account for the systemic effects from the siRNA transfection step is developed. Furthermore, hit selection processes for studying gene-drug interactions are performed for identifying drug targets. The above four topics are centered around the key issue of revealing biological interactions. The work discusses the problems from different levels of interaction networks and performs disease-related analysis of gene, protein and drug interactions. The contributions are mainly the designing and improving of the computational algorithms and methods for joint learning interactions from various kinds of biological data. These methods can be used as efficient tools for understanding gene and protein interaction relationships and identifying potential drug targets. 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
On Using Learning Curves to Evaluate ITS
Authors: Brent Martin, Kenneth R. Koedinger, Antonija Mitrovic, Santosh Mathan
Venue: Proceeding of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology (2005)

Measuring the efficacy of ITS can be hard because there are many confounding factors: short, well-isolated studies suffer from insufficient interaction with the system, while longer studies may be affected by the students' other learning activities. Coarse measurements such as pre-and post-testing are often inconclusive. Learning curves are an alternative tool: slope and fit of learning curves show the rate at which the student learns, and reveal how well the system model fits what the student is learning. The downside is that they are extremely sensitive to changes in the system's setup, which arguably makes them useless for comparing different tutors. We describe these problems in detail and our experiences with them. We also suggest some other ways of using learning curves that may be more useful for making such comparisons.
Generating Diagnoses from Conflict Sets with Continuous Attributes
Authors: Emmanuel Benazera, Louise Travé-Massuyés
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

Many techniques in model-based diagnosis and other research fields find the hitting sets of a group of sets. Existing techniques apply to sets of finite elements only. This paper addresses the computation of the hitting sets of a group of sets whose elements are convex or non-convex, bounded or unbounded continuous regions. We assume the conflict sets are known and we present a novel procedure, the Continuous Hitting Set algorithm (CHS) for transforming conflict sets of continuous elements into minimal hitting sets.
Design and fabrication of novel micro electromagnetic actuator
Authors: Chia-Yen Lee, Zgen-Hui Chen, Hsien-Tseng Chang, Chih-Yung Wen, Chiang-Ho Cheng
Venue: Microsystem Technologies (2009)

This study designs, fabricates, and characterizes a novel micro electromagnetic actuator comprising a PDMS diaphragm, a polyimide-coated copper micro coil, and a permanent magnet. When an electrical current is passed through the micro coil, a magnetic force is induced between the coil and the magnet which causes the diaphragm to deflect, thereby creating an actuation effect. The experimental results demonstrate that the diaphragm deflection can be accurately controlled by regulating the current passed through the micro coil. It is shown that the maximum diaphragm deflection within elastic limits is 150&#x00a0;&#x03bc;m; obtained by passing a current of 0.6&#x00a0;A through a micro coil with a line width of 100&#x00a0;&#x03bc;m. The micro actuator proposed in this study is easily fabricated and is readily integrated with existing bio-medical chips due to its planar structure.
Overcoming Geoinformatic Knowledge Fence: An Exploratory of Intelligent Geospatial Data Preparation within Spatial Analysis
Authors: Jian Wang, Chun-Jiang Zhao, Fang-Qu Niu, Zhi-Qiang Wang
Venue: Proceedings of the 9th International Conference on Computational Science (2009)

The booming of earth observation provides decision-makers with more available geospatial data as well as more puzzles about how to understand, evaluate, search, process, and utilize those overwhelming resources. The paper distinguishes a concept termed geoinformatic knowledge fence (GeoKF) to discuss the knowledge-aspect of such puzzles and the approach to overcoming them. Basing on analysis of the gap between common geography sense and geoinformatic professional knowledge, the approach composes analysis space modeling and spatial reasoning to match decision models to the online geospatial data sources they need. Such approach enables automatically and intelligently searching of suitable geospatial data resources and calculating their suitability to given spatial decision and analysis. An experiment with geo-services, geo-ontology and rule-based reasoning (Jess) is developed to illustrate the feasibility of the approach in scenario of data preparation within decisions of bird flu control.
Software composition with Linda
Authors: Ana M. Roldan, Ernesto Pimentel, Antonio Brogi
Venue: Computer Languages, Systems and Structures (2009)

Nowadays, tuple spaces have turned out to be one of the most fundamental abstractions for coordinating communicating agents. Some models, as Linda, were presented as a set of inter-agent communication primitives which can virtually be added to any programming language. These models have the advantage of capturing both communication and synchronization in a natural and simple way. In this paper, we analyze the use of Linda to specify the interactive behavior of software components. We first introduce a process algebra for Linda and we define a notion of process compatibility that ensures the safe composition of components. This definition of compatibility takes into account the state of a global store (tuple space), which gives relevant information about the current execution of the system. Indeed, a Linda-based computation is characterized by the store's evolution, so that the set of tuples included into the store governs each computation step. In particular, we prove that compatibility implies successful computation (i.e. without deadlock). We also argue that Linda features some advantages with respect to similar proposals in the context of dynamic compatibility checking. In this context, the success of the composition of a pair of agents in presence of a suitable store can be useful to condition the acceptance of a given component into an open running system. In order to extend our approach to complex systems, where constructing a system involves more than two components, we propose the use of distributed tuple spaces as the glue to join components.
Word Sense Disambiguation: Algorithms and Applications, 1st edition
Authors: Eneko Agirre, Philip Edmonds
Venue: Text, Speech And Language Technology (2007)

This is the first book to cover the entire topic of word sense disambiguation (WSD) including: all the major algorithms, techniques, performance measures, results, philosophical issues, and applications. Leading researchers in the field have contributed chapters that synthesize and provide an overview of past and state-of-the-art research across the field. The editors have carefully organized the chapters into sub-topics. Researchers and lecturers will learn about the full range of what has been done and where the field is headed. Developers will learn which technique(s) will apply to their particular application, how to build and evaluate systems, and what performance to expect. An accompanying Website provides links to resources for WSD and a searchable index of the book.
Scheduling on Unrelated Machines under Tree-Like Precedence Constraints
Authors: V. S. Anil Kumar, Madhav V. Marathe, Srinivasan Parthasarathy, Aravind Srinivasan
Venue: Algorithmica (2009)

We present polylogarithmic approximations for the R|prec|C max&#x2009; and R|prec|&#x2211;j w j C j problems, when the precedence constraints are &#x201c;treelike&#x201d;&#x2014;i.e., when the undirected graph underlying the precedences is a forest. These are the first non-trivial generalizations of the job shop scheduling problem to scheduling with precedence constraints that are not just chains. These are also the first non-trivial results for the weighted completion time objective on unrelated machines with precedence constraints of any kind. We obtain improved bounds for the weighted completion time and flow time for the case of chains with restricted assignment&#x2014;this generalizes the job shop problem to these objective functions. We use the same lower bound of &#x201c;congestion&#x2009;+&#x2009;dilation&#x201d;, as in other job shop scheduling approaches (e.g. Shmoys, Stein and Wein, SIAM J. Comput. 23, 617&#x2013;632, 1994). The first step in our algorithm for the R|prec|C max&#x2009; problem with treelike precedences involves using the algorithm of Lenstra, Shmoys and Tardos to obtain a processor assignment with the congestion&#x2009;+&#x2009;dilation value within a constant factor of the optimal. We then show how to generalize the random-delays technique of Leighton, Maggs and Rao to the case of trees. For the special case of chains, we show a dependent rounding technique which leads to a bicriteria approximation algorithm for minimizing the flow time, a&#x00a0;notoriously hard objective function.
Experimenting with a computer essay-scoring program based on esl student writing scripts
Authors: David Coniam
Venue: ReCALL (2009)

This paper describes a study of the computer essay-scoring program BETSY. While the use of computers in rating written scripts has been criticised in some quarters for lacking transparency or lack of fit with how human raters rate written scripts, a number of essay rating programs are available commercially, many of which claim to offer comparable reliability with human raters. Much of the validation of such programs has focused on native-speaking tertiary-level students writing in subject content areas. Instead of content areas with native-speakers, the data for this study is drawn from a representative sample of scripts from an English as a second language (ESL) Year 11 public examination in Hong Kong. The scripts (900 in total) are taken from a writing test consisting of three topics (300 scripts per topic), each representing a different genre. Results in the study show good correlations between human raters’ scores and the program BETSY. A rater discrepancy rate, where scripts need to be re-marked because of disagreement between two raters, emerged at levels broadly comparable with those derived from discrepancies between paired human raters. Little difference was apparent in the ratings of test takers on the three genres. The paper concludes that while computer essay-scoring programs may appear to rate inside a ‘black box’ with concomitant lack of transparency, they do have potential to act as a third rater, time-saving assessment tool. And as technology develops and rating becomes more transparent, so will their acceptability.
FastCARD: Microsoft Access 2007, 1st edition
Venue: Fastcards (2007)

Get up to speed quickly with Course Technology's new four-color, tri-fold, six-sided FastCARDs! Our easy-to-follow design makes each FastCARD the perfect self-study tool to get you started with a new application, technology, or business skill. Use FastCARDs to roll out a new application, Office suite, or business topic, get answers to frequently asked questions, or teach a 1-2 hour or half-day course. 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
On defining affinity graph for spectral clustering through ranking on manifolds
Authors: Tian Xia, Juan Cao, Yong-dong Zhang, Jin-tao Li
Venue: Neurocomputing (2009)

Spectral clustering consists of two distinct stages: (a) construct an affinity graph from the dataset and (b) cluster the data points through finding an optimal partition of the affinity graph. The focus of the paper is the first step. Existing spectral clustering algorithms adopt Gaussian function to define the affinity graph since it is easy to implement. However, Gaussian function is hard to depict the intrinsic structure of the data, and it has to specify a scaling parameter whose selection is still an open issue in spectral clustering. Therefore, we propose a new definition of affinity graph for spectral clustering from the graph partition perspective. In particular, we propose two consistencies: smooth consistency and constraint consistency, for affinity graph to hold, and then define the affinity graph respecting these consistencies in a regularization framework of ranking on manifolds. Meanwhile the proposed definition of affinity graph is applicable to both unsupervised and semi-supervised spectral clustering. Encouraging experimental results on synthetic and real world data demonstrate the effectiveness of the proposed approach.
Privacy Enhanced Information Systems
Authors: Sabah S. Al-Fedaghi, Gunar Fiedler, Bernhard Thalheim
Venue: Proceeding of the 2006 conference on Information Modelling and Knowledge Bases XVII (2006)

Privacy is becoming a major issue of social, ethical and legal concern on the Internet. The development of information technology and the Internet has major implications for the privacy of individuals. Studies of private or personal information have related it to such concepts as identifiably, secrecy, anonymity, control, etc. Few studies have examined the basic features of this type of information. Also, database models (e.g., 'Hippocratic' [AKX02] database) for this type of information have been proposed. This paper studies the nature of private information and develops a new conceptual model for databases that contain exclusively private information. The model utilizes the theory of infons to define “private infons”, and develops taxonomy of these private infons based on the notions of proprietary and possession. The proposed model also specifies different privacy rules and principles, derives their enforcement, and develops and tests architecture for this type of databases.
Functional decomposition and interactions in hybrid intrusion-tolerant systems
Authors: Hans P. Reiser, Tobias Distler, Rüdiger Kapitza
Venue: Proceedings of the 3rd International DiscCoTec Workshop on Middleware-Application Interaction (2009)

Hybrid wormhole-based architectures have recently been proposed as an approach for building intrusion-tolerant systems. The wormhole, a trusted entity in the system, can be implemented in software using virtualization technology. The architecture of such systems poses the question of distribution of functionality and interactions between three layers: the trusted wormhole, the untrusted part of the replication infrastructure, and the replicated application. For example, a total-ordering service for client requests that is needed for consistent replication can be implemented in the trusted or untrusted part of the infrastructure. In this paper, we discuss this distribution of functionality and the impact on semantics, interfaces, and functional constraints. Finally, we propose a flexible toolkit that eases the implementation and comparison of different architectures.