Miracle-dz/UniFAR-FTUs huggingface dataset:
Reducing boundary artifacts in image deconvolution

In image deconvolution, the boundary value problem, if not appropriately handled, often causes serious ringing artifacts in the restored results. This paper proposes a simple method to tackle this problem without any assumption on the noise level and the symmetry of the Point Spread Function (PSF). We establish new boundary conditions by smoothly expanding the input image to a large tile. It helps reducing the boundary discontinuities and accordingly makes all restoration filters based on Fast Fourier Transform (FFT) not produce obvious image border artifacts.
Speech and Sound Analysis : an Application of Probabilistic Models

Sound signal carry rich information which can be extracted and used by analysis systems in different modes. The medical remote monitoring systems may help elderly people to live home in security. We have already proposed an environmental sound analysis algorithm to detect distress sound or sentences. The sound and speech recognition modules based on Gaussian Mixture Models and Hidden Markov Models are detailed. A real time implementation on an embedded PC is proposed and evaluated. This implementation is flexible either for the hardware target (desktop, laptop or embedded PC) or on the alarm sending (E-Mail, SMS or remote monitoring center).
Scarcity and growth considering oil and energy : an alternative neo-classical view

The mineral economy - how prices and costs can falsely signal decreasing scarecity determining the power of prices to change oil discovery and production using a non-time dependant Hubbert model oil exploration game with incomplete information - an experimental study modelling OPEC behaviour - theories of risk aversion for oil producer decisions world oil supply forcest and the reserve-production ratio energy grades and economic growth entropy subsides the energy utilization chain - determining viable oil alternative technology the economics of alternative energey resources entropy and diminshing elasticity of substitution Soviet economic decline - did an oil crisis cause the transition in the Soviet Union?
Capitalist Welfare Systems: A Comparison of Japan, Britain, and Sweden

Introduction. Part 1: Japan: Economic, political and social context. Health, social security and social services. Education and employment. Perspectives and evaluations. Part 2: Britain: Economic, political and social context. Health, Social security and social services. Education and employment. Perspectives and evaluations. Part 3: Sweden: Economic, political and social context. Health, social security and social services. Education and employment. Perspectives and evaluations. Notes. Bibliography.
VIRON: an annotation-based video information retrieval system

To provide efficient search and retrieval of video data from large archives, we need to model video data appropriately. We propose a video data model and describe the design and implementation of the annotation-based video retrieval system VIRON (Video Information Retrieval On Notation) based on the proposed model. This model provides the mechanism of sharing and reusing annotations among users by introducing descriptor schema. In order to process a query efficiently, an annotated video unit is mapped into a unified video annotation stream. VIRON is composed of three tools: CVU manager, which is used to manage and visualize conceptual video units; annotator to annotate video data by offering an interactive video player; and a video query tool to pose and process video queries.
Crowd saliency prediction with optimal feature combinations

Crowd saliency prediction refers to predicting where people look at in crowd scene. Humans have remarkable ability to rapidly direct their gaze to select visual information of interest when looking at a visual scene. Until now, research efforts are still focused on that which type of feature is representative for crowd saliency, and which type of learning model is the robust one for crowd saliency prediction. In this paper, we propose a Random Forest (RF) based crowd saliency prediction approach with optimal feature combination, i.e., the Feature Combination Selection for Crowd Saliency (FCSCS) framework. More specifically, we first define two representative crowd saliency features: FaceSizeDiff and FacePoseDiff. Next, we adopt the Random Forest (RF) algorithm to construct our saliency learning model. Then, we evaluate the performance of crowd saliency prediction classifiers with different feature combinations (fifteen combinations in our experiments). Those selected features include low-level features (i.e., color, intensity, orientation), four existing crowd features (i.e., face size, face density, frontal face, profile face) and two new defined features (i.e., FaceSizeDiff and FacePoseDiff). Finally, we obtain the optimal feature combination that is most suitable for crowd saliency prediction. We conduct extensive experiments and empirical evaluation to demonstrate the satisfactory performance of our approach.
A Pseudo-Bayesian Algorithm for Robust PCA

Commonly used in many applications, robust PCA represents an algorithmic attempt to reduce the sensitivity of classical PCA to outliers. The basic idea is to learn a decomposition of some data matrix of interest into low rank and sparse components, the latter representing unwanted outliers. Although the resulting problem is typically NP-hard, convex relaxations provide a computationally-expedient alternative with theoretical support. However, in practical regimes performance guarantees break down and a variety of non-convex alternatives, including Bayesian-inspired models, have been proposed to boost estimation quality. Unfortunately though, without additional a priori knowledge none of these methods can significantly expand the critical operational range such that exact principal subspace recovery is possible. Into this mix we propose a novel pseudo-Bayesian algorithm that explicitly compensates for design weaknesses in many existing non-convex approaches leading to state-of-the-art performance with a sound analytical foundation.
In situ and real time determination of metallic and semiconducting single-walled carbon nanotubes in suspension via dielectrophoresis

We report an alternative method combining dielectrophoresis and impedance spectroscopy to provide rapid, accurate measurement of dielectrophoretic collection of single-walled carbon nanotubes (SWNTs) in real time. We analyzed a Triton X-100 suspension of mixed SWNTs to measure their precise dielectrophoretic collection behavior. Results indicate that our sample contains 21.5% of metallic and 78.5% of semiconducting carbon nanotubes before separation, and that the range of 1–15MHz is ideal to collect only the metallic ones. Optical absorption was used to confirm these proportions. We discuss the possible errors associated with using purely a Raman technique to validate the type of SWNTs collected in suspension.
An efficient parallel FP-Growth algorithm

FP-Growth algorithm recursively generates huge amounts of conditional pattern bases and conditional FP-trees when the dataset is huge. In such a case, both the memory usage and computational cost are expensive, such that, the FP-tree can not meet the memory requirement. In this work, we propose a novel parallel FP-Growth algorithm, which is designed to run on the computer cluster. To avoid memory overflow, this algorithm finds all the conditional pattern bases of frequent items by the projection method without constructing an FP-tree. Hereafter, it splits the mining task into number of independent sub-tasks, executes these sub-tasks in parallel on nodes and then aggregates the results back for the final result. Our algorithm works independently at each node. As a result, it can efficiently reduce the inter-node communication cost. Experiments show that this parallel algorithm not only avoids the memory overflow but accelerate the computational speed. In addition, it achieves much better scalability than that of the FP-Growth algorithm.
Adjacency Analysis for Unit Selection Speech Model Using MOMEL / INTSINT

— One of the speech synthesizer problems is the unnaturalness and unintelligible production of speech. It is believed that wave modification could also contribute to the distortion of synthesized speech. The objective of a unit selection speech corpus is to provide a few possible instance of unit in order to produce synthesized speech as close to human speech production without the need (or slight need) to perform wave modification. Different from a standard pre-recorded speech database, unit selection allow multiple instances for same unit to be presented in a corpus. These instances are differentiated by a unique combination of prosodic and phonemic context. These prosodic and phonemic contexts form a set of speech corpus parameter. To minimize distortion in concatenative speech synthesizer, parameters of selected segments need to reflect the quality of natural speech. The selection process depends on the priority level of each parameter in the corpus. These parameters design unit selection model. One of the proposed parameter is adjacent phoneme of the target unit. This paper will describe the analysis on pitch behaviour using MOMEL/INTSINT, an algorithm used to model speech prosody.
LESSonS FoR MonEtARy PoLICy FRoM ASSEt PRICE FLuCtuAtIonS

T he current crisis gives occasion to revisit an old question: should monetary policy be used to prevent asset price busts? The question has at least three aspects, each of which is addressed in this chapter. First, we examine the historical evidence in search of consistent macroeconomic patterns that could be used as reliable leading indicators of asset price busts. Second, we examine the role of monetary policy in the buildup to the current crisis. In particular, we assess the validity of accusations that policymakers created the current crisis by reacting insufficiently to growing inflation pressure or that they raised the likelihood of an asset price bust by placing insufficient weight on credit and asset prices when setting interest rates. Third, we consider whether the goal of monetary policy should be expanded beyond just the stability of goods price inflation, how this could be done, and the potential trade-offs involved. The chapter presents the following findings. Inflation and output do not typically display unusual behavior ahead of asset price busts. By contrast, credit, the share of investment in GDP, current account deficits, and asset prices typically rise, providing useful leading indicators of asset price busts. These patterns can also be observed in the buildup to the current crisis. Also, in the period since 1985, the stance of monetary policy has not generally been a good leading indicator of future house price busts, consistent with the evidence that inflation and output are poor leading indicators. There is some association between loose monetary policy and house price rises in the years leading up to the current crisis in some countries, but loose monetary policy was not the main, systematic cause of the boom and consequent bust. If monetary policymakers are to blame, it is mainly for acting too narrowly and not reacting strongly enough to indications of growing financial vulnerability. This chapter makes the case that putting more emphasis on macrofinancial risk could bring stabilization benefits. Simulations suggest that using a macroprudential instrument designed specifically to dampen credit market cycles would help counter accelerator mechanisms that inflate credit growth and asset prices. In addition, a stronger monetary reaction to signs of overheating or of a credit or asset price bubble could also be useful. Such a broader approach to monetary policy might require that concern for macrofinancial stability be explicitly included in central banks' mandates. However, expectations should be realistic. It is …
Learning opening books in partially observable games: Using random seeds in Phantom Go

Many artificial intelligences (AIs) are randomized. One can be lucky or unlucky with the random seed; we quantify this effect and show that, maybe contrarily to intuition, this is far from being negligible. Then, we apply two different existing algorithms for selecting good seeds and good probability distributions over seeds. This mainly leads to learning an opening book. We apply this to Phantom Go, which, as all phantom games, is hard for opening book learning. We improve the winning rate from 50% to 70% in 5×5 against the same AI, and from approximately 0% to 40% in 5×5, 7×7 and 9×9 against a stronger (learning) opponent.
A Web 2.0 Enabled Content Management System for Rural Youth Photographers: Social Computing Supporting Community Empowerment

Adams, F. (1975). Unearthing seeds of fire: The idea of Highlander. Winston-Salem, N.C. : John F. Blair. Bishop, A.P. & Bruce, B.C. (2005). Community informatics: Integrating action, research, and learning. Bulletin of the American Society for Information Science and Technology, 31(6), 8-10. Carroll, J.M. (2000). Making use: Scenario-based design of human-computer interactions. Cambridge, MA: MIT Press. Freire, P. (1970). Pedagogy of the oppressed. New York: Herder and Herder. Growing Tennessee: Rural Youth Cultivate Common Ground. Participatory Content Management System. Accessed July 10, 2007 at http://glaucon.sunsite. utk.edu/drupalsites/growingtn/. King, B. (2007). Self-portraits. Blast Magazine. Accessed August 14, 2007 at http://blastmagazine.com/2007/08/self-portraits/. Mehra, B. (2004). Service learning in library and information science (LIS) education: Connecting research and practice to cocmmunity. InterActions: UCLA Journal of Education and Information Studies, 1(1), n.p. Accessed October 14, 2007 at http://repositories.cdlib. org/gseis/interactions/vol1/iss1/art3/. Sandusky, R.J. & Gasser, L. (2005). Negotiation and the coordination of information and activity in distributed software problem management. GROUP ‘05: ACM 2005 International Conference on Supporting Group Work, Sanibel Island, Florida, p.Available at: http://portal.acm. org/citation.cfm? doid=1099203.1099238. Stoecker, R. (2005a). Research methods for community change: A project-based approach. Thousand Oaks, CA: Sage. Stoecker, R. (2005b). Is community informatics good for communities? Questions confronting an emerging field. Accessed May 12, 2007 at http://cijournal.net/index.php/ciej/article/view/183. System design / requirements can be expressed informally
SLOPE SCALE SPATIAL VARIABILITY ACROSS TIME AND SPACE: COMPARISON OF RESULTS FROM TWO DIFFERENT SNOW CLIMATES

U.S.D.A. Forest Service National Avalanche Center, Bozeman, Montana, USA. ABSTRACT: Understanding the spatial variability of the snowpack is a crucial step to improve accuracy in field data collection and avalanche forecasting. While there has already been a large volume of literature assessing the spatial variability of the snowpack, inconsistent sampling designs make comparing results difficult. This work uses an overlapping 10 by 10 m grid to collect Extended Column (ECT), Compression (CT) and Stuffblock (SB) test data at the slope scale across a range of environmental settings and climatic regimes in Montana and New Zealand. The overlapping grid methodology standardizes data collection between our sites, as well as allowing for repeat data collection on the same slope, thereby providing a new method for attempting to assess changes in spatial variability over time. Preliminary results suggest that the spatial variability of fracture propagation and fracture initiation may increase over time, and that the spatial variability of the fracture propagation propensity may be related to the processes causing the instability. As we collect more data, these results will provide further insight into the problem of snow pit location and representivity, both in terms of space and time. KEYWORDS: Spatial variability, Temporal variability, Fracture initiation, Fracture propagation.
Procedia Social and Behavioral Sciences Analyzing the Creative Editing Behavior of Wikipedia Editors through Dynamic Social Network Analysis

This paper analyzes editing patterns of Wikipedia contributors using dynamic social network analysis. We have developed a tool that converts the edit flow among contributors into a temporal social network. We are using this approach to identify the most creative Wikipedia editors among the few thousand contributors who make most of the edits amid the millions of active Wikipedia editors. In particular, we identify the key category of " coolfarmers " , the prolific authors starting and building new articles of high quality. Towards this goal we analyzed the 2580 featured articles of the English Wikipedia where we found two main article types: (1) articles of narrow focus created by a few subject matter experts, and (2) articles about a broad topic created by thousands of interested incidental editors. We then investigated the authoring process of articles about a current and controversial event. There we found two types of editors with different editing patterns: the mediators, trying to reconcile the different viewpoints of editors, and the zealots, who are adding fuel to heated discussions on controversial topics. As a second category of editors we look at the " egoboosters " , people who use Wikipedia mostly to showcase themselves. Understanding these different patterns of behavior gives important insights about the cultural norms of online creators. In addition, identifying and policing egoboosters has the potential to increase the quality of Wikipedia. People best suited to enforce culture-compliant behavior of egoboosters through exemplary behavior and active intervention are the highly regarded coolfarmers introduced above.
Exchange rate and equity prices relationship: an empirical evidence from Pakistani financial markets

The relationship between stock prices and exchange rate in Pakistan has been examined by using monthly data from July 1981 to June 2004. The cointegration and error-correction model and Granger trivariate causality techniques are used to test the causal relationship between exchange rate and stock prices. The empirical results indicate the uni-directional causal relationship between stock prices and exchange rate. The results indicate that the stock price has negative significant short run causal effect on exchange rate in Pakistan. However, during short run the exchange rate has a bi-directional causal effect on stock prices. No significance relationship is found between stock prices and gold. It suggests that the stock market in Pakistan is inefficient with respect to gold prices. However, money supply and interest rate do affect stock prices, suggesting that monetary policy could be used more effectively to check the movement in stock prices in Pakistan.
Learning to Adapt Across Multimedia Domains

In multimedia, machine learning techniques are often applied to build models to map low-level feature vectors into semantic labels. As data such as images and videos come from a variety of domains (e.g., genres, sources) with different distributions, there is a benefit of adapting models trained from one domain to other domains in terms of improving performance and reducing computational and human cost. In this thesis, we focus on a generic adaptation setting in multimedia, where supervised classifiers trained from one or more auxiliary domains are adapted to a new classifier that works well on a target domain with limited labeled examples. Our main contribution is a discriminative framework for function-level classifier adaptation based on regularized loss minimization, which adapts classifiers of any type by modifying their decision functions in an efficient and principled way. Two adaptation algorithms derived from this general framework, adaptive support vector machines (aSVM) and adaptive kernel logistic regression (aKLR), are discussed in details. We further extend this framework by integrating domain analysis approaches that measure and weight the utility of auxiliary domains, and sample selection methods that identify informative examples to help the adaptation process. The proposed approaches are evaluated on cross-domain video concept detection using the TRECVID corpus, where preliminary experiments have shown promising results. Our general approaches can be applied to other adaptation problems including retrieval model adaptation and cross-corpus text categorization. Thesis Committee: Alexander G. Hauptmann (Chair) Christos Faloutsos Jie Yang Shih-Fu Chang (Columbia University)
Extracting Farsi text from a video in the wavelet domain

In this paper, a new method for extracting Farsi text from a video in the wavelet domain is proposed. In an image including text, due to the complexity of the background and the quick changes of contrast in the text areas, the energy intensity variation is high. Therefore, by exploiting this property a method is proposed for extracting text. Moreover, for increasing the accuracy of the proposed method, some motion characteristics of the movies have been used. The proposed method is able to localize both Farsi and Latin Text in video with a high performance. The experimental results confirms the effectiveness of the proposed method.
Globalization and public sector reform in China

1. Globalization and Public Sector Reform in China Kjeld Erik Brodsgaard 2. Looking West: The Impact of Western Ideas on Public Sector Reform Policies in China John Burns 3. Transitional Meritocracy? Institutions and Practices of Personnel Management in State-Building in Contemporary China Wang Zhengxu and Dragan Pavlicevic 4. Digital Monitoring and Public Administrative Reform in China Jesper Schlaeger 5. Public Sector Reform in China: Who is Losing Out? Kjeld Erik Brodsgaard and Chen Gang 6. Health Sector Reforms in Contemporary China: A Political Perspective Daniele Brombal 7. China's Centrally-Managed State-Owned Enterprises: Dilemma and Reform Huang Yanjie and Zheng Yongnian 8. Creating Corporate Goups to Strengthen China's State-Owned Enterprises Jean Oi and Zhang Xiaowen 9. China's Bureaucratic Capitalism: Creating the Corporate Steel Sector Andrew Walder 10. Public Sector Units in India and China: Inefficient Producers or Creators of Crucial Knowledge Assets? Jayan Jose Thomas 11. Public Sector Reforms and Political Discourse in India and China Manoranjan Mohanty
Games with Procedurally Rational Players

We study interactive situations in which players are boundedly ra- tional. Each player, rather than optimizing given a belief about the other players' behavior. as in the theory of Nash equilibrium, uses the following choice procedure. She first associates one consequence with each of her actions by sampling (literally or virtually) each of her actions once. Then she chooses the action that has the best consequence. We define a notion of equilibrium for such situations and study its properties.
Interprocedural Def-Use associations in C programs

We present the first high-precision algorithm for obtaining Def-Use Associations in C programs with single level pointers. While the precise solution of the problem is lVP-hani, our polynomial-time algorithm uses program-point-specific pointer-induced aliases to obtain good approximations to the set of definitions reaching a program point. This information is crucial to effective debugging, testing and maintenance of C software systems. Initial implementation experiences with this approach are presented.