Miracle-dz/UniFAR-FTUs huggingface dataset:
Convergent Learning Algorithms for Unknown Reward Games

In this paper, we address the problem of convergence to Nash equilibria in games with rewards that are initially unknown and must be estimated over time from noisy observations. These games arise in many real-world applications, whenever rewards for actions cannot be prespecified and must be learned online, but standard results in game theory do not consider such settings. For this problem, we derive a multiagent version of $\mathcal{Q}$-learning to estimate the reward functions using novel forms of the $\epsilon$-greedy learning policy. Using these $\mathcal{Q}$-learning schemes to estimate reward functions, we then provide conditions guaranteeing the convergence of adaptive play and the better-reply processes to Nash equilibria in potential games and games with more general forms of acyclicity, and of regret matching to the set of correlated equilibria in generic games. A secondary result is that we prove the strong ergoditicity of stochastic adaptive play and stochastic better-reply processes in the ca.
A Realization Algorithm for Discrete-Time Linear Systems with a non-zero initial state

s Almost-linear systems being introduced, the facts about the systems were cleared, and it was shown that the almost-linear systems contain linear systems with a non-zero initial state as a sub-class [1]. In this paper, based on the these results of almostlinear systems[1], we will discuss the real-time realization problem of linear systems with a non-zero initial state, namely, we will treat the problem to obtain the systems by single-experiment. The algorithm for the problem is presented. It is well known that a usual method to obtain linear systems with a non-zero initial state is solved through two problems. One is the problem to obtain linear systems with a zero initial state and the other is the state estimation problem for the systems with a non-zero initial state[2], that is usually called the observer problem. And the situation of these two problems is very rare in practice. This paper presents a new method to obtain them directly on real-time (equivalently, by a singleexperiment). Therefore, this new method is more useful and practical than usual.
Neuronal Mechanisms of Cortical Alpha Oscillations in Awake-Behaving Macaques

Field potential oscillations at ∼10 Hz (alpha rhythm) are widely noted in the visual cortices, but their physiological mechanisms and significance are poorly understood. In vitro studies have implicated pyramidal neurons in both infragranular and supragranular layers as pacemakers. The generality of these observations for the intact brain in the behaving subject is unknown. We analyzed laminar profiles of spontaneous local field potentials and multiunit activity (MUA) recorded with linear array multielectrodes from visual areas V2, V4, and inferotemporal (IT) cortex of two macaque monkeys during performance of a sensory discrimination task. Current source density (CSD) analysis was combined with CSD–MUA coherence to identify intracortical alpha current generators and their potential for alpha pacemaking. The role of each alpha current generator was further delineated by Granger causality analyses. In V2 and V4, alpha current generators were found in all layers, with the infragranular generator acting as primary local pacemaking generator. In contrast, in IT, alpha current generators were found only in supragranular and infragranular layers, with the supragranular generator acting as primary local pacemaking generator. The amplitude of alpha activity in V2 and V4 was negatively correlated with behavioral performance, whereas the opposite was true in IT. The alpha rhythm in IT thus appears to differ from that in the lower-order cortices, both in terms of its underlying physiological mechanism and its behavioral correlates. This work may help to reconcile some of the diverse findings and conclusions on the functional significance of alpha band oscillations in the visual system.
Classification from generation: Recognizing deep grammatical information during reading from rapid event-related fMRI

A novel fMRI classification method designed for rapid event related fMRI experiments is described and applied to the classification of loud reading of isolated words in Hebrew. Three comparisons of different grammatical complexity were performed: (i) words versus asterisks (ii) “with diacritics versus without diacritics” and (iii) “with root versus no root”. We discuss the most difficult task and, for comparison, the easiest one. Earlier work using more standard classification techniques (machine learning and statistical) succeeded fully only in the simplest of these tasks (i), but produced only partial results on (ii) and failed completely, even on the training set on the deepest task (iii). The method performs a “best match” between pre-processed data and computing a full library of artificially generated examples. The method involves a deconvolution of the rapid events on the data and performing a convolution on the generated data. The best-match is performed over all “words” constructed by convolving the response functions of each value of each event performed in a “windowed” sequence. This is accomplished separately for all voxels and then a voting procedure defines the outcome. Using the same feature selection (ANOVA) as in the earlier methods, (i) there is a dramatic increase in the accuracy rate for the third (most difficult task) on the intra-run level (88%) as well as the first task (ii) Unlike the earlier methods training and testing over all runs (within subject) achieves a significant level of classification (64% accuracy) for the training set. This shows the information for this “deeper” cognitive task can in fact be extracted from the fMRI information.
Illumination compensation for high-resolution multispectral image mosaicing of heritage paintings

When investigating artworks, having the ability to examine the reflectance spectra at every image pixel can us give insight into the materials and pigments used in its creation. Multispectral imaging is a great tool to perform this task, however, when acquiring images with a multispectral camera, in addition to the reflectance spectra, the surface interaction with the illumination is also captured. This hampers quantitative measurements of the surface. We introduce a novel multispectral imaging system and illumination compensation approach, that mitigates the influence of illumination on image formation. We showcase the performance of our system by producing high-resolution multispectral mosaic images (low or high dynamic range) of artworks dated from the beginning of the XIX-th century, to the present day.
Analysis of the stochastic FitzHugh-Nagumo system

In this paper we study a system of stochastic differential equations with dissipative nonlinearity which arise in certain neurobiology models. Besides proving existence, uniqueness and continuous dependence on the initial datum, we shall be mainly concerned with the asymptotic behaviour of the solution. We prove the existence of an invariant ergodic measure $\nu$ associated with the transition semigroup $P_t$; further, we identify its infinitesimal generator in the space $L^2(H;\nu)$.
Analysis of electromigration void nucleation failure time in open copper TSVs

Through silicon vias (TSVs) are innovative interconnects which provide wider functionality and higher performance per unit area in three-dimensional (3D) integrated circuits. The reliability of TSVs in integrated circuits constitutes an important issue in microelectronics. One of the most relevant degradation mechanisms in interconnects is electromigration (EM). Therefore, the prediction of the EM failure behavior is a crucial necessity. Traditionally, Black's equation has been used from the early times of EM investigations for the estimation of the time to failure (TTF) for a wide spectrum of different interconnects. In this work we investigate the applicability of Black's equation for the estimation of the EM failure time in open copper TSV technologies. The EM void nucleation model has been solved by numerical calculations. Simulations have been carried out for different current densities. The results are in good agreement with Black's equation.
A novel three-dimensional localization algorithm based on DV-HOP

The traditional DV-HOP algorithm for three-dimensional localization precision is not good enough to use. Its positioning deviation is too large to find out the unknown nodes, and the scope of coverage is too small to find out all the nodes. Because of these shortcomings, a novel three-dimensional localization DV-Hop algorithm (NTLDV-HOP) is proposed. The proposed algorithm revises per jump distance to enhance the accuracy of distance calculation between unknown nodes and anchor nodes, and uses the Total Least Squares (TLS) method to modify the positioning deviation of the anchor node itself. Simulation shows that the NTLDV-HOP improves the location accuracy.
Introduction to Ox

Preface This is a hands-on introduction to the Ox programming language. It may be used for self study, or in a classroom setting with an instructor. Exercises are spread throughout the text, both to check and extend the understanding of the language. Some more extensive exercises are given, which may be set as take home tests for students (for example, the questions at the end of Chapter 11). Not all details of the language are discussed here; for more information we refer to Doornik (2001), which contains a full reference of the Ox language. We hope that a working knowledge of the material in this booklet will allow you to use Ox more productively, whether in your studies or research. Please let us know if you have any comments on this introduction. It is assumed that you have a copy of Ox installed on your machine and working. If not, you can download a copy from Some conventions are used in this book. Source code, variables in source code and file names are written in typewriter font. Exercises are indicated with a in the margin, and referred to as [3.1] (for example), where 3 is the chapter number, and 1 the exercise number in that chapter. Sections are referred to as e.g. §3.1. Source code is listed in a grey box. For many of these the code is provided to save typing. In that case, the upper-right corner of the box the filename in italics. All the files will have the . ox extension, although some of those will not be valid Ox code as such (the file is always an exact copy of the code in the text, and occasionally this is only part of a program). We wish to thank Francisco Cribari-Neto for helpful comments. We assume that you have access to a properly installed version of Ox. If you do not have Ox yet, you can download a copy from You can follow these tutorials using Ox version 3 or newer, on any available computer platform. Parts of Chapter 11 require Ox Professional under Windows. The reference book for the Ox language is Doornik (2001). Much of that is also available in the online help. This help system is in the form of HTML documents, which can be read with an internet browser such as Netscape or the Internet Explorer. The help files can be found in the …
Temporal Projection and Explanation

We propose a solution to problems involving temporal projection and explanation (e.g., the Yale shooting problem) based on the idea that whether a situation is abnormal should not depend upon historical information about how the situation arose. We apply these ideas both to the Yale shooting scenario and to a blocks world domain that needs to address the qualification problem.
Clinical applications of diffusion tensor imaging

Directionally‐ordered cellular structures that impede water motion, such as cell membranes and myelin, result in water mobility that is also directionally‐dependent. Diffusion tensor imaging characterizes this directional nature of water motion and thereby provides structural information that cannot be obtained by standard anatomic imaging. Quantitative apparent diffusion coefficients and fractional anisotropy have emerged from being primarily research tools to methods enabling valuable clinical applications. This review describes the clinical utility of diffusion tensor imaging, including the basic principles of the technique, acquisition, data analysis, and the major clinical applications. J. Magn. Reson. Imaging 2004;19:6–18. © 2003 Wiley‐Liss, Inc.
Guiding visually impaired people in the exhibition

We have implemented a location-aware tour-guide based on RFID localization. The guide is specifically aimed at supporting blind users. We tested it in the context of EuroFlora 2006, one of the most important exhibitions of Europe. In this paper we briefly describe the development process and discuss some preliminary results from usability tests. The experimentation involved over 100 blind people, who have been observed and interviewed by experts of disabilities and HCI designers.
Race Identification for Face Images

Humans are able to process a face in a variety of ways to categorize it by its identity, along with a number of other demographic characteristics, including race, gender , and age. Experimental results are based on a face database containing subjects. Race and gender also play an important role in face-related applications. Experimental results are indicated that participants categorized the race of the face and this categorization drives the perceptual process. A face image data set is collected from Internet, and divided into a training dataset and a test dataset. Experimental results based on a face database containing 250 subjects. The proposed system can also be applied to other image-based classification tasks.
An Efficient Method for Architecture-Based Reliability Evaluation for Evolving Systems with Changing Parameters

Probabilistic models are widely used in Architecture-based reliability prediction in software intensive systems. However, for most of the cases, it is computationally expensive to compute the reliability metrics and re-compute them once the system has evolved or is used in a different environment. In this paper, we introduce an efficient computation method for Discrete Time Markov Chain based abstractions, which computes reliability metrics once, and we provide an incremental technique to recompute these metrics in case of a single change in the reliability evaluation model. As a result, fast an efficient reliability computation can be provided for scenarios like design-time architecture optimization and run time adaptation. An experimental validation of the new method shows a significant improvement in terms of computation time required to re-evaluate an evolved architecture.
Boundary Tracing of Fish Image

There are several techniques to obtain boundary of an object in a digital image. Some of the well known techniques are contour tracing and edge detection technique. The result of this boundary tracing is used for analyzing an object in the image. This result is critical for some certain image analysis. In this study, the techniques will be used for obtaining the fish boundary from a digital image. The study will evaluate the suitable approach to get the fish boundary. This study is important for the next study on analyzing the physical characteristic of the fish.
Tetris Write: Exploring More Write Parallelism Considering PCM Asymmetries

The noises at the power lines limit the charge pump to provide large instantaneous current to PCM cells, which results in the number of bits can be written concurrently, i.e. the size of write unit, is restricted in PCM. When implementing PCM as the main memory, the inequality of cache line's size and write unit's size may result in many consecutive executed write units, which greatly decreases the system performance. Existing PCM write schemes, however, consider the worst power and time cases of written data, and ignore the actual current consumption. It is assumed that all data bits are changed and the electric current of each data unit is under fully utilized. The write performance is blocked due to pessimistic estimates, i.e. the current is often excessively supplied but is not used effectively, which leads to huge energy consumption. As a result, the write parallelism is limited and therefore restricts the overall system performance. To address this problem, this paper proposes a novel PCM write scheme named Tetris Write to explore more write parallelism and reduce the critical number of write units in PCM chip. The key idea behind Tetris Write is to monitor the number of '1' and '0' changed in each data unit, and schedule the order of data units' write-1 and write-0 execution considering not only the time and power asymmetries, but also the number asymmetry between RET and SET operations, to allow a larger number of concurrent bit-writes and make the best use of power supply. Tetris Write tries to schedule the dominating long term write-1s first and attempts to steal interspaces remained by write-1s to put the extraessential short write-0s. 4-core PARSEC benchmarks' results show that Tetris Write can get 65% read latency reduction, 40% write latency reduction, 46% running time reduction and 2X IPC improvement compared with the baseline on average. In addition, Tetris Write earns 26%, 15% and 10% more read latency reduction, 15%, 7% and 5% more write latency reduction, and outperforms 22%, 12% and 7% more running time reduction, compared with the state-of-the-art Flip-N-Write, 2-Stage-Write and Three-Stage-Write schemes, whose IPC improvements are 1.4X, 1.6X and 1.8X, respectively.
LibDSL: a library for developing embedded domain specific languages in d via template metaprogramming

This paper presents a library called LibDSL that helps the implementer of an embedded domain specific language (EDSL) effectively develop it in D language. The LibDSL library accepts as input some kinds of ``specifications'' of the EDSL that the implementer is going to develop and a D program within which an EDSL source program written by the user is embedded. It produces the front-end code of an LALR parser for the EDSL program and back-end code of the execution engine. LibDSL is able to produce two kinds of execution engines, namely compiler-based and interpreter-based engines, either of which the user can properly choose depending on whether an EDSL program is known at compile time or not. We have implemented the LibDSL system by using template metaprogramming and other advanced facilities such as compile-time function execution of D language. EDSL programs developed by means of LibDSL have a nice integrativeness with the host language.
Identifying state space reduction techniques from behavioural design patterns

Model checking has always been associated with a scalability problem when verifying systems with large state spaces. This problem can be addressed using techniques that reduce the state space during verification. This paper proposes guidelines to identify suitable reduction techniques from design patterns. The selection of suitable state space reduction techniques is demonstrated using a complex concurrent system as case study. Using this case study, we discuss the reasons and conditions for selecting a reduction technique when a design pattern is used. The proposed guidelines are evaluated by checking if the selected reduction techniques reduces the number of states; implying that these techniques are suitable. The result of this evaluation shows that suitable reduction techniques can be identified from design patterns.
Façade Segmentation in a Multi-view Scenario

We examine a new method of façade segmentation in a multi-view scenario. A set of overlapping, thus redundant street-side images exists and each image shows multiple buildings. A semantic segmentation identifies primary areas in the image such as sky, ground, vegetation, and façade. Subsequently, repeated patterns are detected in image segments previous labeled as "façade areas" and are applied to separate specific facades from each other. Experimentation is based on an industrial street-view dataset from a moving car by well-designed, calibrated, automated cameras. High overlap images define a multi-view scenario. We achieve 97% pixel-wise segmentation effectiveness, outperforming current state-of-the-art methods.
Efficient event-driven simulations shed new light on microtubule organization in the plant cortical array

The dynamics of the plant microtubule cytoskeleton is a paradigmatic example of the complex spatiotemporal processes characterising life at the cellular scale. This system is composed of large numbers of spatially extended particles, each endowed with its own intrinsic stochastic dynamics, and is capable of non-equilibrium self-organisation through collisional interactions of these particles. To elucidate the behaviour of such a complex system requires not only conceptual advances, but also the development of appropriate computational tools to simulate it. As the number of parameters involved is large and the behaviour is stochastic, it is essential that these simulations be fast enough to allow for an exploration of the phase space and the gathering of sufficient statistics to accurately pin down the average behaviour as well as the magnitude of fluctuations around it. Here we describe a simulation approach that meets this requirement by adopting an event-driven methodology that encompasses both the spontaneous stochastic changes in microtubule state as well as the deterministic collisions. In contrast with finite time step simulations this technique is intrinsically exact, as well as several orders of magnitude faster, which enables ordinary PC hardware to simulate systems of $\sim 10^3$ microtubules on a time scale $\sim 10^{3}$ faster than real time. In addition we present new tools for the analysis of microtubule trajectories on curved surfaces. We illustrate the use of these methods by addressing a number of outstanding issues regarding the importance of various parameters on the transition from an isotropic to an aligned and oriented state.
Analyzing Formation Of K Mean Clusters Using Similarity And Dissimilarity Measures

 Abstract : Measurement of similarity and dissimilarity between two data objects is a challenging problem for data mining . Mainly the clustering algorithms use distance function between the data points to define dissimilarity measure to form clusters but normalized scaler product can also be used as similarity function to form clusters among data points. This paper presents the results of an experimental study of some common k mean clustering techniques. In particular, we compare the two main approaches to k mean clustering. ( we used Euclidean distance as dissimilarity measure and cosine similarity .)
On Charactering of Word-of-Mouth Propagation in Heterogeneous Online Social Networks

Recent years have witnessed the explosive growth of research on online social networks (OSNs), which provide a perfect platform for observing the Word-of-Mouth (WOM) propagation. However, recent research regarded OSNs as homogeneous networks, while the real-world OSNs are heterogeneous. This paper considered the heterogeneity of OSNs, proposed a WOM propagation model called HOSN to simulate WOM propagation in different types of nodes in OSNs. Numerical simulation experiments based on agents have been extensively conducted, which show the mechanism of WOM propagation in heterogeneous online social networks. It can be seen from the experimental results that along with the WOM spreading and time passing, more and more users in OSNs review and know the WOM information. Moreover, from the network structure and user behavior perspective, some interesting findings are got. First, the number of initial known nodes has a certain impact on the WOM propagation scope and speed. Then, the number of neighbors has a great impact on the WOM propagation process and results. Finally, percentage of different user type is the decisive factor for WOM propagation either in final propagated number or propagation speed. Findings in this paper attempt to complement the theoretical framework of WOM propagation and complex networks, and thus to further promote the practice of WOM control in OSNs