ppxscal/embedding_network huggingface dataset:
Feature extraction and matching in content-based retrieval of functional magnetic resonance images
Authors: Paul Kantor
Venue:  (2007)

Functional Magnetic Resonance Imaging (fMRI) has become a widely used technique in neuroscience research. Brain regions corresponding to certain cognitive functionalities can be located by studying the intensity change in a series of 3D brain scans. Although fMRI has been widely studied, little attention has been paid to content-based (&ldquo;content&rdquo; means the explicit or implicit cognitive process) retrieval of images despite the existence of databases equipped with textual description (fMRIDC). Content-based retrieval is potentially useful in discovering brain activation patterns, and in diagnoses by comparing observed patterns with those of known diseases, leading to clinical applications. We conducted a comprehensive investigation of feature extraction and similarity measures used in several research communities (including information retrieval (IR), signal processing, and computer vision(CV)), to set up a content-based retrieval framework for a large, heterogeneous database. We developed methods for both hypothesis-based (stimulus known) and hypothesis-free (stimulus unknown) schemes. For the former, we adapted and extended an adaptive Finite Impulse Response (FIR) Model to get a more robust estimation of the activation level of brain regions. We then relaxed the assumption that the brain responds as a linear time-invariant (LTI) system, by using a 4-parameter ordinary differential equation to model brain responses. We then evaluated a number of similarity measures used in IR and CV, such as Latent Semantic Indexing (LSI), TFIDF, and Mahalanobis distance, etc. For the latter, we used a heuristic to select independent components with low mean temporal frequency, and applied a maximum weight bipartite matching technique to integrate component-level similarity and give a more robust retrieval performance. For feature selection, we found that an FIR model with a smoothing factor can improve retrieval performance significantly. For feature matching, a method similar to &ldquo;dilation operators&rdquo; used in image processing gives better and more robust retrieval performance than other methods.
Efficient Data Clustering by Local Density Approximation
Authors: Marc-Ismaël Akodjènou, Patrick Gallinari
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

The clustering task is a key part of the data mining process. In today's context of massive data, methods with a computational complexity more than linear are unlikely to be applied practically. In this paper, we begin by a simple assumption: local projections of the data should allow to distinguish local cluster structures. From there, we describe how to obtain “pure” local sub-groupings of points, from projections on randomly chosen lines. The clustering of the data is obtained from the clustering of these sub-groupings. Our method has a linear complexity in the dataset size, and requires only one pass on the original dataset. Being local in essence, it can handle twisted geometries typical of many high-dimensional datasets. We describe the steps of our method and report encouraging results.
Technical Section: Semantics-driven best view of 3D shapes
Authors: Michela Mortara, Michela Spagnuolo
Venue: Computers and Graphics (2009)

The problem of automatically selecting the pose of a 3D object that corresponds to the most informative and intuitive view of the shape is known as the best view problem. In this paper we address the selection of the best view driven by the meaningful features of the shape, in order to maximize the visibility of salient components from the context or from the application point of view. Meaningful features can be automatically detected by means of semantic-oriented segmentations: we tested several approaches with very pleasant results in the automatic generation of thumbnails for large 3D model databases.
Microprocessors
Authors: Deepali A. Godse
Venue:  (2008)

Architecture of 8086/88 Family 8086 Hardware Design 8086 Instruction Set Assembly Language Programming Disk Operating System Mixed Language Programming Using C and Assembly 8086 Interrupt System Memory System Interfacing I/O Interfacing Programmable Peripheral Interface (8255) Serial Communication DMA Controller Design Examples 8087 Numeric Co-processor Study of I/O Processor 8089 Multiprocessor Systems 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
Windows Vista Inside Out Kit: Windows Server 2008 Inside Out and Windows Vista Inside Out
Authors: Ed Bott
Venue:  (2009)

Get two popular books for Windows administrators, now packaged in one comprehensive set at 27% savings and manage Windows Server 2008 and Windows Vista like the experts do. Containing WINDOWS SERVER 2008 INSIDE OUT by William Stanek and WINDOWS VISTA INSIDE OUT by Ed Bott, Carl Siechert, and Craig Stinson, this kit features hundreds of timesaving solutions, troubleshooting tips, and workarounds for administering your systems all in a concise, fast-answer format that makes it easy to find the exact fix you need. In WINDOWS SERVER 2008 INSIDE OUT, you ll discover the best and fastest ways to perform upgrades and migrations, automate deployments, implement security features, manage software updates, administer users and accounts, and manage Active Directory(r) directory services. In WINDOWS VISTA INSIDE OUT, you ll bypass the basics and dive right into configuring advanced setup options, managing Microsoft(r) Internet Explorer(r) settings and security zones, protecting your system against viruses and spyware, fine-tuning performance, administering accounts, and automating routine maintenance. The kit s two companion CDs come loaded with a fully searchable eBook for each title, more than 100 timesaving tools and scripts for Windows Server 2008, downloads for customizing Windows Vista, and links to the latest Windows Vista security updates and products, demos, blogs, and user communities. With INSIDE OUT, you get all muscle and no fluff.
An Open Domain-Extensible Environment for Simulation-Based Scientific Investigation (ODESSI)
Authors: Adnan M. Salman, Allen D. Malony, Matthew J. Sottile
Venue: Proceedings of the 9th International Conference on Computational Science: Part I (2009)

In scientific domains where discovery is driven by simulation modeling there are found common methodologies and procedures applied for scientific investigation. ODESSI (Open Domain-extensible Environment for Simulation-based Scientific Investigation) is an environment to facilitate the representation and automatic conduction of scientific studies by capturing common methods for experimentation, analysis, and evaluation used in simulation science. Specific methods ODESSI will support include parameter studies, optimization, uncertainty quantification, and sensitivity analysis. By making these methods accessible in a programmable framework, ODESSI can be used to capture and run domain-specific investigations. ODESSI is demonstrated for a problem in the neuroscience domain involving computational modeling of human head electromagnetics for conductivity analysis and source localization. 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
Model Checking Communicative Agent-Based Systems
Authors: Jamal Bentahar, John-Jules Meyer
Venue: Proceeding of the 2007 conference on New Trends in Software Methodologies, Tools and Techniques: Proceedings of the sixth SoMeT_07 (2007)

Model checking is a formal technique used to verify communication protocols against given properties. In this paper, we address the problem of verifying systems designed as a set of autonomous interacting agents using such a technique. These software agents are equipped with knowledge and beliefs and interact with each other according to protocols governed by a set of logical rules. We present a tableau-based model checking algorithm for these systems and provide the termination and complexity results.
Bayesian inference of protein–protein interactions from biological literature
Authors: Rajesh Chowdhary, Jinfeng Zhang, Jun S. Liu
Venue: Bioinformatics (2009)

Motivation: Protein–protein interaction (PPI) extraction from published biological articles has attracted much attention because of the importance of protein interactions in biological processes. Despite significant progress, mining PPIs from literatures still rely heavily on time-and resource-consuming manual annotations. Results: In this study, we developed a novel methodology based on Bayesian networks (BNs) for extracting PPI triplets (a PPI triplet consists of two protein names and the corresponding interaction word) from unstructured text. The method achieved an overall accuracy of 87% on a cross-validation test using manually annotated dataset. We also showed, through extracting PPI triplets from a large number of PubMed abstracts, that our method was able to complement human annotations to extract large number of new PPIs from literature. Availability: Programs/scripts we developed/used in the study are available at http://stat.fsu.edu/~jinfeng/datasets/Bio-SI-programs-Bayesian-chowdhary-zhang-liu.zip Contact: jliu@stat.harvard.edu Supplementary information:Supplementary data are available at Bioinformatics online.
Handling prioritized goals and subgoals in a logical account of goal change
Authors: Shakil M. Khan, Yves Lespérance
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

Most existing formal models of goals [2, 3] assume that all goals are equally important and many only deal with achievement goals. Moreover, they do not guarantee that an agent's goals will properly evolve when an action/event occurs, e.g. when the agent's beliefs/knowledge changes or a goal is adopted or dropped. Also, most of these frameworks do not model the dependencies between goals and the subgoals and plans adopted to achieve these goals -- subgoals adopted to bring about a goal should be dropped when the parent goal becomes impossible, is achieved, or is dropped. Dealing with these issues is important for developing effective models of rational agency and BDI agent programming languages.
Analog Circuit Fault Fusion Diagnosis Method Based on Support Vector Machine
Authors: Zhihong Feng, Zhigui Lin, Wei Fang, Wei Wang, Zhitao Xiao
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

Lack of fault samples and statistic characteristic of artificial neural network, which restrict its more development and application in fault diagnosis. Support Vector Machine (SVM) is a machine --- learning algorithm based on structural risk minimization principle, it has the capability of solving commendably learning problem with few samples. Now, analog circuit fault diagnosis on SVM mainly by single information, the diagnosis result is uncertain. Multi-source information fusion technology is introduced to diagnose analog circuits by integrating multi-source information. An analog circuit fault fusion diagnosis method based on SVM is proposed, binary classification algorithm of SVM is introduced and multi-fault SVM classifiers are developed in the paper. An analog circuit's multi-fault are classified, the results show that the proposed method has many advantages, such as simple algorithm, quick fault class, good classification ability, approving diagnosis purpose with few samples and so on.
Transformation and Entropy for Vague Sets
Authors: Chengyi Zhang, Houyong Zhou
Venue: Proceeding of the 2006 conference on Advances in Intelligent IT: Active Media Technology 2006 (2006)

A new method translating a vague set to a fuzzy set is introduced and the fuzzy approximation of a vague set is given. The properties of the fuzzy approximation of a vague set is studied and a fuzzy entropy measure for vague sets is proposed.
Programming Entity Framework, 1st edition
Authors: Julia Lerman
Venue:  (2009)

Programming Entity Framework is a thorough introduction to Microsoft's new core framework for modeling and interacting with data in .NET applications. This book not only gives experienced developers a hands-on tour of the Entity Framework and explains its use in a variety of applications, it also provides a deep understanding of its architecture and APIs. From the Entity Data Model (EDM) and Object Services to EntityClient and the Metadata Workspace, Programming Entity Framework covers it all. Written by Julia Lerman, the leading independent authority on the framework, Programming Entity Framework, includes scores of reusable examples -- written in both Visual Basic and C# -- that you can implement right away. This book will help you: Understand the core concepts you need to make the best use of the Entity Framework (EF) in your applications Learn to query your data, using either LINQ to Entities or Entity SQL Create Windows Forms, WPF, and ASP.NET applications Build ASMX web services and WCF services Use Object Services to work directly with your entity objects Delve into model customization, relationship management, change tracking, data concurrency, and more Presented in a clear narrative style that reflects the hundreds of hours the author has spent consulting, teaching, and writing about this new data access technology and testing its myriad features, Programming Entity Framework will help you master the technology and put it to work.
A Steering Taxis Model and the Qualitative Analysis of its Trajectories
Authors: I. Rañó
Venue: Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems (2009)

Taxis is a well-known steering technique used by simple animals to approach a stimulus in the real world. However, no mathematical motion model of taxis can be found in the literature. This article derives the differential ordinary equations describing the motion of a Braitenberg vehicle, a widely used taxis model. A qualitative technique for non-linear dynamical systems analysis is applied to investigate the motion generated by the model. Validation of the analysis is performed through several simulations, and conditions for the stimulus source to be reached are obtained. This work fills the theoretical hole in formal models of Braitenberg vehicles and thereby provides theoretical support for the many previous experimental uses of those vehicles for steering tasks.
Global Exponential Stability and Global Convergence in Finite Time of Neural Networks with Discontinuous Activations
Authors: Sitian Qin, Xiaoping Xue
Venue: Neural Processing Letters (2009)

In this paper, we consider a general class of neural networks, which have arbitrary constant delays in the neuron interconnections, and neuron activations belonging to the set of discontinuous monotone increasing and (possibly) unbounded functions. Based on the topological degree theory and Lyapunov functional method, we provide some new sufficient conditions for the global exponential stability and global convergence in finite time of these delayed neural networks. Under these conditions the uniqueness of initial value problem (IVP) is proved. The exponential convergence rate can be quantitatively estimated on the basis of the parameters defining the neural network. These conditions are easily testable and independent of the delay. In the end some remarks and examples are discussed to compare the present results with the existing ones.
Consensus of multi-agent moving systems with heterogeneous communication delays
Authors: Hong-yong Yang, Si-ying Zhang
Venue: International Journal of Systems, Control and Communications (2009)

A consensus of mobile multi-agent systems is a question with practical significance in the complex dynamics system. In this paper, a multi-agent moving system with the heterogeneous communication delays is studied under the hypothesis of fixed, undirected and connected topology. Applying the generalised Nyquist criterion, the multi-agent delayed algorithm is analysed, and many sufficient conditions are obtained to ensure the consensus of the moving systems. Finally, many computer simulations are used to show the validity of the results.
Behavioral task processing for cognitive robots using artificial emotions
Authors: Evren Daglarli, Hakan Temeltas, Murat Yesiloglu
Venue: Neurocomputing (2009)

This paper presents an artificial emotional-cognitive system-based autonomous robot control architecture for a four-wheel driven and four-wheel steered mobile robot. Discrete stochastic state-space mathematical model is considered for behavioral and emotional transition processes of the autonomous mobile robot in the dynamic realistic environment. The term of cognitive mechanism system which is composed from rule base and reinforcement self-learning algorithm explain all of the deliberative events such as learning, reasoning and memory (rule spaces) of the autonomous mobile robot. The artificial cognitive model of autonomous robot control architecture has a dynamic associative memory including behavioral transition rules which are able to be learned for achieving multi-objective robot tasks. Motivation module of architecture has been considered as behavioral gain effect generator for achieving multi-objective robot tasks. According to emotional and behavioral state transition probabilities, artificial emotions determine sequences of behaviors for long-term action planning. Also reinforcement self-learning and reasoning ability of artificial cognitive model and motivational gain effects of proposed architecture can be observed on the executing behavioral sequences during simulation. The posture and speed of the robot and the configurations, speeds and torques of the wheels and all deliberative and cognitive events can be observed from the simulation plant and virtual reality viewer. This study constitutes basis for the multi-goal robot tasks and artificial emotions and cognitive mechanism-based behavior generation experiments on a real mobile robot.
Building a Common Understanding of Critical Success Factors for an ERP Project Implementation
Authors: David Sammon, Frederic Adam
Venue: Proceeding of the 2008 conference on Collaborative Decision Making: Perspectives and Challenges (2008)

This paper reports on a novel approach to Enterprise Resource Planning (ERP) project implementation and introduces the use of a sense-making workshop to facilitate an improved shared understanding of the Critical Success Factors (CSFs) for the implementation of such an IT innovation. The sense-making workshop strives to overcome hindering knowledge barriers by raising stakeholder awareness through the development of a logically minimal Boolean expression (truth function) which promotes discussion and a shared understanding as to the project preparations required for the successful implementation of an ERP package in an organisational context. The design of the sense-making workshop requires participants to use a set of CSFs for ERP project implementation and a simple scenario in order to retrospectively make sense of the actions taken during the ERP project (represented in the scenario) and therefore represent their individual understanding as a truth function. A process of Boolean minimisation is then used (facilitated through the construction of a truth table and a prime implicant chart) to achieve logically maximum parsimony in the form of a logically minimal Boolean expression (truth function) which is representative of the workshop participants' shared understanding of the CSFs at play in the scenario.
From DPS to MAS to ...: continuing the trends
Authors: Michael N. Huhns
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1 (2009)

The most important and interesting of the computing challenges we are facing are those that involve the problems and opportunities afforded by massive decentralization and disintermediation. The problems and opportunities arise in domains where controlled action is necessary, but centralized control is infeasible. These are the traditional domains of distributed problem solving and multiagent systems, and they include information systems for healthcare, commerce, energy distribution, and traffic control. However, the current incarnations of these domains are scaled well beyond anything envisioned originally. Nevertheless, traditional techniques derived from artificial intelligence are still mostly appropriate. Specifically, representation, reasoning, learning, planning, and situated semantics---when distributed computationally and extended to multiple loci of intelligence---will all be part of potential solutions. They will affect not only the ways systems will be implemented and executed in the future, but also the ways they will be designed, developed, and deployed. This paper focuses on the domains and their challenges. It describes the trends that are observable in our research technologies and shows how they can be used to confront the challenges. It is hoped that new avenues of research will be revealed from following the trends.
A digital predistorter for wireless transmitters
Authors: D. Bondar, D. Budimir
Venue: International Journal of RF and Microwave Computer-Aided Engineering (2009)

A novel digital baseband predistorter with improved reduction of spectral regrowth is proposed and investigated. The improvements are achieved by using a proposed predistortion technique and extended power amplifier (PA) fundamental-frequency modeling. The digital baseband predistortion (DPD), known for its simplicity of realization, low cost and integrability; however, it suffers from poor linearizing performances. We incorporate baseband iterative injection of in-band distortion components into the baseband DPD to enhance the nonlinearity compensation. General formulas for the fundamental-frequency output of a PA with n-order nonlinearity and recursive formulas for calculating the injected components for different number of iterations are developed. The proposed iterative digital baseband predistorter is verified experimentally with a wireless PA and measured results are presented to demonstrate feasibility of the proposed concept. The spectral regrowth suppression of 20 dB is achieved for a 3.5 MHz digitally modulated signal. &copy; 2009 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2009.
Integrating Statistics and Visualization for Exploratory Power: From Long-Term Case Studies to Design Guidelines
Authors: Adam Perer, Ben Shneiderman
Venue: IEEE Computer Graphics and Applications (2009)

Evaluating visual-analytics systems is challenging because laboratory-based controlled experiments might not effectively represent analytical tasks. One such system, SocialAction, integrates statistics and visualization in an interactive exploratory tool for social network analysis. This article describes results from long-term case studies with domain experts and extends established design goals for information visualization.