ppxscal/embedding_network huggingface dataset:
Whose call is it? Targeting universal service programs to low-income households' telecommunications preferences
Authors: Janice A. Hauge, Eric P. Chiang, Mark A. Jamison
Venue: Telecommunications Policy (2009)

Do universal service programs give customers what they want? This paper uses new survey data to study low-income households' telecommunications choices in the United States and to consider the degree to which such households' preferences are addressed by existing universal service programs. The research shows that households that choose only one form of telecommunications increasingly are choosing a mobile phone, while those that choose to have both modes of communications are shifting their usage towards their mobile phones. These trends are less pronounced among higher-income households. One implication for universal service policy is that traditional subsidies for landline phones are increasingly ineffective in reaching low-income households such subsidies are designed to help; subsidies for acquiring and using mobile phone services might be more beneficial to low-income households than traditional subsidies for landline phones.
Multiscale cell-based coarsening for discontinuous problems
Authors: Alfonso Limon, Hedley Morris
Venue: Mathematics and Computers in Simulation (2009)

Whether tracking the eye of a storm, the leading edge of a wildfire, or the front of a chemical reaction, one finds that significant change occurs at the thin edge of an advancing line. The tracking of such change-fronts comes in myriad forms with a wide variety of applications expressible as PDEs. Expanding on Ami Harten's ideas, we construct an alternative to wavelet-based grid refinement, a multiresolution coarsening method that is capable of capturing sharp gradients across different scales, thus improving PDE-based simulations by concentrating computational resources where the solution varies sharply. We present this alternative grid coarsening method and compare its performance to other multiresolution methods by means of several examples.
Design Validation by Symbolic Simulation and Equivalence Checking: A Case Study in Memory Optimization for Image Manipulation
Authors: Kong Woei Susanto, Tim Todman, Jose Gabriel Coutinho, Wayne Luk
Venue: Proceedings of the 35th Conference on Current Trends in Theory and Practice of Computer Science (2009)

Design optimization exploration is a key element in finding an optimal resource utilization. The exploration process applies optimizations iteratively; after applying each optimization, the result has to be validated. The research challenge for formal verification is to develop an efficient design validation flow and increase the quality of the validation. In this paper, we propose an automated validation flow to check the functional equivalence of the source design and its optimized version. This approach is based on a symbolic simulation technique to obtain the design properties and automatically check them using an equivalence checker. The novelty of this approach includes the use of model simplification techniques, such as if-conversion and loop-conversion, and state encoding to ease validation analysis.
Simultaneous Hardcore Bits and Cryptography against Memory Attacks
Authors: Adi Akavia, Shafi Goldwasser, Vinod Vaikuntanathan
Venue: Proceedings of the 6th Theory of Cryptography Conference on Theory of Cryptography (2009)

This paper considers two questions in cryptography.Cryptography Secure Against Memory Attacks. A particularly devastating side-channel attack against cryptosystems, termed the "memory attack", was proposed recently. In this attack, a significant fraction of the bits of a secret key of a cryptographic algorithm can be measured by an adversary if the secret key is ever stored in a part of memory which can be accessed even after power has been turned off for a short amount of time. Such an attack has been shown to completely compromise the security of various cryptosystems in use, including the RSA cryptosystem and AES.We show that the public-key encryption scheme of Regev (STOC 2005), and the identity-based encryption scheme of Gentry, Peikert and Vaikuntanathan (STOC 2008) are remarkably robust against memory attacks where the adversary can measure a large fraction of the bits of the secret-key, or more generally, can compute an arbitrary function of the secret-key of bounded output length. This is done without increasing the size of the secret-key, and without introducing any complication of the natural encryption and decryption routines.Simultaneous Hardcore Bits. We say that a block of bits of x are simultaneously hard-core for a one-way function f(x), if given f(x) they cannot be distinguished from a random string of the same length. Although any candidate one-way function can be shown to hide one hardcore bit and even a logarithmic number of simultaneously hardcore bits, there are few examples of one-way or trapdoor functions for which a linear number of the input bits have been proved simultaneously hardcore; the ones that are known relate the simultaneous security to the difficulty of factoring integers.We show that for a lattice-based (injective) trapdoor function which is a variant of function proposed earlier by Gentry, Peikert and Vaikuntanathan, an N ¿ o(N) number of input bits are simultaneously hardcore, where N is the total length of the input.These two results rely on similar proof techniques.
Institutions, property-aware programming and testing
Authors: Magne Haveraaen
Venue: Proceedings of the 2007 Symposium on Library-Centric Software Design (2007)

The institution notion is a general model theoretic framework, explaining how specifications (algebraic axioms) relate to models (mathematical models or even software constructions) in a formalism-independent manner. There is a large set of institution-independent structuring mechanisms for specifications. Property aware programming, as e.g. supported by concepts in C++0X, provides algebraic axioms as part of the code to ensure correctness of generic software composition. Testing is very important for the validation of software, but tests are all too often developed on an ad hoc basis. Here we present a library testing framework, with a basis in structured specifications. The approach will be demonstrated on Sophus, a medium-sized software library for coordinate-free numerics. Sophus was developed using (informal) algebraic specifications in order to improve reusability and reduce development costs.
A new look at existence dependency in databases
Authors: T. C. Chiang
Venue: Proceedings of the May 16-19, 1983, national computer conference (1983)

To ensure data consistency, existence dependencies between records must be preserved when the records are updated. It is necessary to identify such dependencies when the system is designed, so that update operations can be performed correctly. This paper presents a new look at existence dependencies in databases. It identifies a set of basic update rules that can be incorporated into a database management system (DBMS) to preserve existence dependencies between records. The paper shows that the existence dependencies supported by other existing commercially available DBMSs can be defined precisely in terms of the basic rules. Furthermore, a combination of these basic rules captures new existence dependency semantics that are not handled by the commercially available systems. This paper also discusses solutions to the "interference" problems associated with closely related records. These interference problems have never been discussed in the literature before, but are important to system operations.
Predicting Future Decision Trees from Evolving Data
Authors: Mirko Böttcher, Martin Spott, Rudolf Kruse
Venue: Proceedings of the 2008 Eighth IEEE International Conference on Data Mining (2008)

Recognizing and analyzing change is an important human virtue because it enables us to anticipate future scenarios and thus allows us to act pro-actively. One approach to understand change within a domain is to analyze how modelsand patterns evolve. Knowing how a model changes over time is suggesting to ask: Can we use this knowledge to learn a model in anticipation, such that it better reflects the near-future characteristics of an evolving domain? In this paper we provide an answer to this question by presenting an algorithm which predicts future decision trees based ona model of change. In particular, this algorithm encompasses a novel approach to change mining which is based on analyzing the changes of the decisions made during model learning. The proposed approach can also be applied to other types of classifiers and thus provides a basis for future research. We present our first experimental results which show that anticipated decision trees have the potential to outperform trees learned on the most recent data.
An exponential-linear backoff algorithm for contention-based wireless networks
Authors: Cheng-Han Lin, Ce-Kuen Shieh, Wen-Shyang Hwang, Chih-Heng Ke
Venue: Proceedings of the International Conference on Mobile Technology, Applications, and Systems (2008)

In this paper, a backoff mechanism, Exponential Linear Backoff Algorithm (ELBA), is proposed to improve system performance over contention-based wireless networks. In the ELBA, the variation of contention window size is combined both exponentially and linearly, dependent on the network load, as indicated by the number of consecutive collisions. In the ELBA scheme, a threshold is set to determine the network load. If the contention window size is smaller than the threshold, a light network load, the contention window is tuned exponentially. Conversely, if the contention window size is larger than the threshold, a heavy network load, the contention window size is tuned linearly. The numerical results show that the ELBA provides a better system throughput and collision rate in both light and heavy network loads than the related backoff schemes, including binary exponential backoff (BEB), exponential increase exponential decrease (EIED) and linear increase linear decrease (LILD).
Approximation of Curvature and Velocity for Gesture Segmentation and Synthesis
Authors: Sylvie Gibet, Pierre-François Marteau
Venue: Gesture-Based Human-Computer Interaction and Simulation: 7th International Gesture Workshop, GW 2007, Lisbon, Portugal, May 23-25, 2007, Revised Selected Papers (2009)

This paper describes a new approach to analyze hand gestures, based on an experimental approximation of the shape and kinematics of compressed arm trajectories. The motivation of such a model is on the one hand the reduction of the gesture data, and on the other hand the possibility to segment gestures into meaningful units, yielding to an analysis tool for gesture coding and synthesis. We show that the measures of the inverse of the distance between adaptive samples and velocity estimated at these points are respectively correlated to the instantaneous curvature and tangential velocity directly computed on motion capture data. Based on these correlation results, we propose a newway to automatically segment hand gestures. We show also that this approach can be applied to a global analysis / synthesis framework, useful for automatic animation of virtual characters performing sign langue gestures.
Preventing knowledge transfer errors: Probabilistic decision support systems through the users' eyes
Authors: Hermi J. M. Tabachneck-Schijf, Petra L. Geenen
Venue: International Journal of Approximate Reasoning (2009)

Development and use of probabilistic decision support systems benefit by good communication between the developer on the one hand, and the user and the domain expert on the other hand. Communication is difficult because large differences in training and experience, and thus also expectations, exist between the two. This causes knowledge transfer errors. Preventing these necessitates user-centered design of the representations used in this communication, and attention to the translation of user terms to model terms and vice versa. A systematic approach to developing user-centered representations and preventing knowledge transfer errors is outlined in this paper. We demonstrate how five heuristic guidelines can be fruitfully applied in different developer-user interaction situations in different phases of decision-support system construction, and briefly outline an evaluation of a data-entry system developed using these guidelines.
A new evolutionary reinforcement scheme for stochastic learning automata
Authors: Florin Stoica, Emil M. Popa
Venue: Proceedings of the 12th WSEAS international conference on Computers (2008)

A stochastic automaton can perform a finite number of actions in a random environment. When a specific action is performed, the environment responds by producing an environment output that is stochastically related to the action. The aim is to design an automaton, using an evolutionary reinforcement scheme (the basis of the learning process), that can determine the best action guided by past actions and responses. Using Stochastic Learning Automata techniques, we introduce a decision/control method for intelligent vehicles receiving data from on-board sensors or from the localization system of highway infrastructure.
A multi-resolution statistical deformable model (MISTO) for soft-tissue organ reconstruction
Authors: Jun Feng, Horace H. S. Ip
Venue: Pattern Recognition (2009)

While active shape model (ASM) has been increasingly adopted in the medical domain, there are issues that need to be addressed for it to be applicable in practice. Among them, the small sample size problem and how to represent the variation of the clutter of surroundings are two of the challenges. In this paper, to overcome these problems, we propose a novel multi-resolution statistical deformable model and the associated techniques for the reconstruction of soft-tissue organs such as livers. To address the small sample size problem, we define a multi-resolution integrated model for soft-tissue organs called MISTO that is able to capture the most significant deformations from a small training set as well as to generate representative variation modes of the organ shapes. To deal with the complex surroundings of the model surface or landmark points in the underlying medical images during model deformation, we propose to apply multi-resolution appearance models which allows the surrounding visual context of the model surface points to be learnt and characterized automatically from the training samples. By combining the powerful shape models and the resulting context constraints, the object segmentation and reconstruction process can be carried out very robustly. Furthermore, to avoid the local minima during model optimization, we develop an adaptive deformation strategy such that the more stable parts of the surface are moved prior to the rest of the model surface. The experimental and validation results verify that our proposed approaches can be successfully and robustly applied to the reconstruction of the soft-tissue organs such as the human liver. The major contributions of our approaches are that we extend the traditional ASM to address open problems associated with reconstructing significantly deformable three-dimensional anatomies in cluttered surrounding, and we propose effective ways to formulate the perceptual knowledge of the anatomies and make use of it in the process of model construction and deformation for medical reconstruction.
Buffer Management in Multimedia Database Systems
Venue: Proceedings of the 1996 International Conference on Multimedia Computing and Systems (1996)

In this paper, we investigate the principles of buffer management for multimedia data presentations in object-oriented database environments. The primary goal is to minimize the response time of multimedia presentations while ensuring that all continuity and synchronization requirements are satisfied. Minimum buffering requirements to guarantee the continuity and synchrony of the presentation of multimedia data are proposed. These principles provide users with the full range of information required to develop a database environment for multimedia presentations. 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
Worst-case and statistical tolerance analysis based on quantified constraint satisfaction problems and Monte Carlo simulation
Authors: Jean-Yves Dantan, Ahmed-Jawad Qureshi
Venue: Computer-Aided Design (2009)

This paper deals with the mathematical formulation of tolerance analysis. The mathematical formulation presented in this paper simulates the influences of geometrical deviations on the geometrical behavior of the mechanism, and integrates the quantifier notion (existential quantifier: ''there exists''; universal quantifier: ''for all''). It takes into account not only the influence of geometrical deviations but also the influence of the types of contacts on the geometrical behavior; these physical phenomena are modeled by convex hulls (compatibility hull, interface hull and functional hull) which are defined in parametric space. With this description by convex hulls, a mathematical expression of the admissible deviations of parts integrates the quantifier notion. This notion translates the concept that a functional requirement must be respected in at least one acceptable configuration of gaps (existential quantifier: ''there exists''), or that a functional requirement must be respected in all acceptable configurations of gaps (universal quantifier: ''for all''). To compute this mathematical formulation, two approaches based on Quantified Constraint Satisfaction Problem solvers and Monte Carlo simulation are proposed and tested.
AN ENHANCED DETERMINISTIC FUZZY TIME SERIES FORECASTING MODEL
Authors: Sheng-Tun Li, Yi-Chung Cheng
Venue: Cybernetics and Systems (2009)

The study of fuzzy time series has attracted great interest and is expected to expand rapidly. Various forecasting models including high-order models have been proposed to improve forecasting accuracy or reducing computational cost. However, there exist two important issues, namely, rule redundancy and high-order redundancy that have not yet been investigated. This article proposes a novel forecasting model to tackle such issues. It overcomes the major hurdle of determining the k-order in high-order models and is enhanced to allow the handling of multi-factor forecasting problems by removing the overhead of deriving all fuzzy logic relationships beforehand. Two novel performance evaluation metrics are also formally derived for comparing performances of related forecasting models. Experimental results demonstrate that the proposed forecasting model outperforms the existing models in efficiency.
Bringing Consciousness To Cognitive Neuroscience: A Computational Perspective
Authors: Alexei V. Samsonovich
Venue: Journal of Integrated Design Process Science (2007)

This paper focuses on three connected to each other fundamental beliefs that appear to be unconsciously taken for granted at the basis of modern cognitive neuroscience: (i) the attractor hypothesis, (ii) the neural code hypothesis, and (iii) the supervenience hypothesis about human subjective experience. Their precise understanding and experimental verification is an important challenge that calls for a scientific paradigm change and needs to be addressed for future progress in cognitive neuroscience. The work presents a theoretical analysis and preliminary experimental and modeling results that suggest a roadmap to solving the challenge.
Social gaming: what attracts the most attention?: an investigation using an improved diary method
Authors: Mitchell Tan, Looi Qin En, See Swee Lan
Venue: Proceedings of the 2008 International Conference on Advances in Computer Entertainment Technology (2008)

The twenty first century has seen leaps in quality of integration of computing into entertainment systems involving human-computer interaction (HCI). Various games have attracted their masses of audiences, some hitting international records of 6 million subscribers, as in World of Warcraft by Blizzard [1]. This study hopes to further develop the preferred game model by developing and testing a new methodology for HCI assessment.
Sensitivity analysis of partitioning-based face recognition algorithms on occlusions
Authors: Önsen Toygar
Venue: Proceedings of the 6th conference on Applications of electrical engineering (2007)

Holistic Principal Component Analysis (PCA) and holistic Independent Component Analysis (ICA) methods require long training times and large storage spaces for the recognition of facial images. These drawbacks can be avoided by using partitioning-based methods, namely partitioned PCA (pPCA) and partitioned ICA (pICA), which yield similar performance for pPCA and improved performance for pICA method compared to the holistic counterparts of these methods for the recognition of frontal facial images. This paper demonstrates the sensitivity analysis of pPCA and pICA methods on several types and sizes of occlusions for the recognition of facial images with similar facial expressions. The recognition rates for pPCA and pICA over occlusions are contrary to the recognition rates of these methods on occlusion-free facial images with different facial expressions.
Evolvable Systems: From Biology to Hardware 8th International Conference, ICES 2008, Prague, Czech Republic, September 21-24, 2008, Proceedings (Lecture ... Computer Science and General Issues), 1 edition
Authors: Gregory S. Hornby, Lukas Sekanina, Pauline C. Haddow
Venue:  (2008)

This book constitutes the refereed proceedings of the 8th International Conference on Evolvable Systems, ICES 2008, held in Prague, Czech Republic, in September 2008. The 28 revised full papers and 14 revised poster papers presented were carefully reviewed and selected from 52 submissions. The papers are organized in topical sections on evolution of analog circuits, evolution of digital circuits, hardware-software codesign and platforms for adaptive systems, evolutionary robotics, development, real-world applications, evolutionary networking, evolvable artificial neural networks, and transistor-level circuit evolution.