Miracle-dz/UniFAR-FTUs huggingface dataset:
QBIC project: querying images by content, using color, texture, and shape

In the query by image content (QBIC) project we are studying methods to query large on-line image databases using the images' content as the basis of the queries. Examples of the content we use include color, texture, and shape of image objects and regions. Potential applications include medical (`Give me other images that contain a tumor with a texture like this one'), photo-journalism (`Give me images that have blue at the top and red at the bottom'), and many others in art, fashion, cataloging, retailing, and industry. Key issues include derivation and computation of attributes of images and objects that provide useful query functionality, retrieval methods based on similarity as opposed to exact match, query by image example or user drawn image, the user interfaces, query refinement and navigation, high dimensional database indexing, and automatic and semi-automatic database population. We currently have a prototype system written in X/Motif and C running on an RS/6000 that allows a variety of queries, and a test database of over 1000 images and 1000 objects populated from commercially available photo clip art images. In this paper we present the main algorithms for color texture, shape and sketch query that we use, show example query results, and discuss future directions.
Evaluation of the Baroreceptor‐Heart Rate Reflex by 24‐Hour Intra‐arterial Blood Pressure Monitoring in Humans

The baroreceptor control of the sinus node was evaluated in 10 normotensive and 10 age-matched essential hypertensive subjects in whom ambulatory blood pressure was recorded intraarterially for 24 hours and scanned by a computer to identify the sequences of three or more consecutive beats hi which systolic blood pressure (SBP) and pulse interval (PI) progressively rose (+ PI/ + SBP) or fell (− PI/ −SBP) in a linear fashion, according to a method validated in cats. In normotensive subjects, several hundred +PI/+SBP and −PI/−SBP sequences of 3 beats were found whereas the number of sequences of 4,5, and more than 5 beats showed a progressive drastic reduction. The mean slopes of plus; PI/ + SBP (7.6 ± 2.0 msec/mm Hg) and − PI/− SBP (6.4 ± 1.5 msec/mm Hg) sequences were similar, but in both instances there was a large scattering of the values around the mean (variation coefficients: 64.2 ± 4.7 and 62.6 ± 2.4%). The slopes decreased as a function of the sequence length and baseline heart rate and increased to a marked extent during the night as compared with daytime values. All sequences were more rare (−33.2% for +PI/ + SBP and −31.7% for −PI/−SBP) and less steep in hypertensive subjects (−40.3 and −36.2%, respectively), who failed to show the marked nighttime increase in slope observed in normotensive subjects. To our knowledge, these observations provide the first description in humans of the baroreceptor-heart rate reflex in daily life. This reflex is characterized by marked within-subject variations hi sensitivity due in part to hemodynamic, temporal, and behavioral factors. All features of the baroreceptor-heart rate reflex are unpaired hi essential hypertension.
Effect of Self-Occlusion on Shape Perception

The present study aims to investigate how self-occlusion and color influence the object shape perception. The Baylis' paradigm, in which subjects had to judge which of the two vertices of an object was higher, was applied to this study. The results shows that: a) If the vertices to be selected are in occluding-part of the object, responses are facilitated; while for the vertices in occluded-part, responses are inhibited. It indicates that the processing of shape perception is affected by self-occlusion; and b) Color has no effects on the vertices position judgment task.
Conversational-Side-Specific Inter-Session Variability Compensation

General techniques for inter-session variability compensation may not capture session and channel information speciﬁc to a given conversational side. This paper investigates three methods for estimating a conversational-side-speciﬁc projection or afﬁne transform to compensate for session and channel effects. In the ﬁrst, we estimate the projection based on an estimate of the within-class covariance matrix using a conversational-side-speciﬁc subset of the development data. In the second, we use a discriminative objective function to estimate the projection parameters. We present an iterative algorithm similar to the expectation maximization (EM) algorithm to estimate the projection parameters which maximize this objective function. An afﬁne transform of the observation vectors of each conversational side is estimated using maximum likelihood estimation in the third method. The maximum likelihood objective function is estimated on a selected subset of the development data. We present several experiments that show how these three techniques perform compared to our baseline system on the interview tasks of the NIST 2008 and the NIST 2010 speaker recognition evaluations. The best method of these techniques gives a performance improvement of up to 20% relative compared to the baseline system.
Sentence Generation as Planning with Probabilistic LTAG

We present PCRISP, a sentence generation system for probabilistic TAG grammars which performs sentence planning and surface realization in an integrated fashion, in the style of the SPUD system. PCRISP operates by converting the generation problem into a metric planning problem and solving it using an offthe-shelf planner. We evaluate PCRISP on the WSJ corpus and identify trade-offs between coverage, efficiency, and accuracy.
Workflow Engine Integration in JSLEE AS

This letter proposes a new architectural solution for service creation in JSLEE-compliant platforms, where service business logic can be separated by implementation issues and designed by non JSLEE experts. The novelty consists of integrating a workflow engine inside the development environment of the JSLEE platform, thus allowing simplified management in the development of advanced services and reduction of the time to market of new services.
SELF-CONFIRMING EQUILIBRIUM IN-KOO CHO AND THOMAS J. SARGENT

A self-con rming equilibrium is the answer to the following question: what are the possible limiting outcomes of purposeful interactions among a collection of adaptive agents, each of whom averages past data to approximate moments of the conditional probability distributions of interest? If outcomes converge, a Law of Large Numbers implies that agents' beliefs about conditional moments become correct on events that are observed su ciently often. Beliefs are not necessarily correct about events that are infrequently observed. Where beliefs are correct, a self-con rming equilibrium is like a rational expectations equilibrium. But there can be interesting gaps between self-con rming and rational expectations equilibria where beliefs of some important decision makers are incorrect. Self-con rming equilibria interest macroeconomists because they connect to an in uential 1970s argument made by Christopher Sims that advocated rational expectations as a sensible equilibrium concept. This argument defended rational expectations equilibria against the criticism that they require that agents `know too much' by showing that we do not have to assume that agents start out `knowing the model'. If agents simply average past data, perhaps conditioning by grouping observations, their forecasts will eventually become unimprovable. Research on adaptive learning has shown that that the glass is `half-full' and `half-empty' for this clever 1970s argument. On the one hand, the argument is correct when applied to competitive or in nitesimal agents: by using naive adaptive learning schemes (various versions of recursive least squares), agents can learn every conditional distribution that they require to play best responses within an equilibrium. On the other hand, large agents (e.g., governments in macro models) who can in uence the market outcome cannot expect to learn everything that they need to know to make good decisions: in a self-con rming equilibrium, large agents may base their decisions on conjectures about o -equilibriumpath behaviors which turn out to be incorrect. Thus, a rational expectations equilibrium is a self-con rming equilibrium, but not vice versa. While agents' beliefs can be incorrect o the equilibrium path, the self-con rming equilibrium path still restricts them in interesting ways. For macroeconomic applications, the government's model must be such that its o -equilibrium path beliefs rationalize the decisions (its Ramsey policy or Phelps policy, in the language of [16]) that are revealed
An investigation of the applicability of fuzzy logic techniques to real-time temporal classification for threat warning systems

An investigation is performed to determine the applicability of fuzzy logic techniques to temporal classification for real-time threat warning systems. Existing discrimination algorithms apply a series of classifiers designed to detect threatening targets at particular ranges in signals generated from multiple electro-optic sensors. Recent growth in the temporal complexity of this system has restricted its performance due in part to two inherent problems in the discrimination approach. Fuzzy logic is applied to a key subset of the classifiers to exploit complex temporal characteristics of signals from evolving targets at various ranges. Fuzzy logic is a discipline that utilizes approximate reasoning and multi-valued logic in dealing with complex problems that must deal with imprecise information in some tractable manner. Real-world knowledge is represented by a continuum of logical truth values ranging between false and true. These truth values simultaneously stimulate a set of fuzzy rules to varying degrees, the consequences of which are interpolated into a single crisp result. Fuzzy rules are based on both common sense laws and expert knowledge about the system being designed. The fuzzy system designed for this investigation converts a set of input signal measurements to corresponding fuzzy sets and applies a Mamdani-based fuzzy inference engine to generate output fuzzy alarm levels. The fuzzified inputs simultaneously stimulate a set of if-then fuzzy rules that are designed to capture the decision relevant expert knowledge about the discrimination process. This investigation demonstrates that by applying fuzzy logic to a key portion of the temporal discrimination problem, moderate performance improvements can be achieved. These improvements are primarily due to the ability of fuzzy logic to represent and exploit complex temporal knowledge fundamental to the threat warning process in a robust and meaningful manner. Further improvements are anticipated by converting the entire system to a fuzzy logic paradigm.
Discovering Relative Importance of Skyline Attributes

Querying databases with preferences is an important research problem. Among various approaches to querying with preferences, the skyline framework is one of the most popular. A well known deficiency of that framework is that all attributes are of the same importance in skyline preference relations. Consequently, the size of the results of skyline queries may grow exponentially with the number of skyline attributes. Here we propose the framework called p-skylines which enriches skylines with the notion of attribute importance. It turns out that incorporating relative attribute importance in skylines allows for reduction in the corresponding query result sizes. We propose an approach to discovering importance relationships of attributes, based on user-selected sets of superior and inferior examples. We show that the problem of checking the existence of and the problem of computing an optimal p-skyline preference relation covering a given set of examples are NP-complete and FNP-complete, respectively. However, we also show that a restricted version of the discovery problem -- using only superior examples to discover attribute importance -- can be solved efficiently in polynomial time. Our experiments show that the proposed importance discovery algorithm has high accuracy and good scalability.
Deep-etch visualization of 27S clathrin: a tetrahedral tetramer

It has recently been reported that 8S clathrin trimers or "triskelions" form larger 27S oligomers upon dialysis into low ionic strength buffers (Prasad, K., R. E. Lippoldt, H. Edelhoch, and M. S. Lewis, 1986, Biochemistry, 25:5214-5219). Here, deep-etch electron microscopy of the 27S species reveals that they are closed tetrahedra composed of four clathrin triskelions. This was determined by two approaches. First, standard quick-freezing and freeze-etching of unfixed 27S species suspended in 2 mM 2-(N-morpholino)ethane sulfonic acid (MES) buffer, pH 5.9, yielded unambiguous images of tetrahedra that measured 33 nm on each edge. Second, the technique of freeze-drying molecules on mica (Heuser, J. E., 1983, J. Mol. Biol., 169:155-195) was modified to overcome the low affinity of mica in 2 mM MES, by pretreating the mica with polylysine. Thereafter, 27S species adsorbed avidly to it and collapsed into characteristic configurations containing four globular domains, each linked to the others by three approximately 33-nm struts. The globular domains look like vertices of deep-etched clathrin triskelions and the links, numbering 12 in all, look like four sets of triskelion legs. New light scattering and equilibrium centrifugation data confirm that 27S polymer is four times as massive as one clathrin triskelion. We conclude that in conditions that do not favor the formation of standard clathrin cages, low affinity interactions lead to closed, symmetrical assemblies of four triskelions, each of which assumes a unique puckered, straight-legged configuration to create the edges of a tetrahedron. Tetrahedra are similar in construction to the cubic octomers of clathrin recently found in ammonium sulfate solutions (Sorger, P. K., R. A. Crowther, J. T. Finch, and B. M. F. Pearse, 1986, J. Cell Biol., 103:1213-1219) but are still smaller, involving only half as many clathrin triskelions.
Interpolatory subdivision curves via diffusion of normals

We propose a new interpolatory subdivision scheme for generating nice-looking curvature-continuous curves of round shapes. The scheme is based on a diffusion of normals. Given a subdivided polyline, the new polyline vertices inserted at the splitting step are updated in order to fit diffused (averaged with appropriate weights) normals. Although the resulting interpolatory subdivision scheme is nonstationary, nonlinear, and nonuniform from the traditional point of view, the scheme is easy to implement because the same simple geometric procedure for generating new vertices is used at each subdivision step. According to our experiments, the scheme is robust and demonstrates very good convergence properties.
Driving Factors of Carbon Dioxide Emissions and the Impact from Kyoto Protocol

In the last two decades increasing attention has been paid to the relationship between environmental degradation and economic development. According to the Environmental Kuznets Curve (EKC) hypothesis this relationship may be described by an inverted-U curve. However, recent evidence rejects the EKC hypothesis for GHG emissions in a broad sense. In this paper we aim to investigate whether the EKC behavior for CO2 emissions could be proved on the behalf of institutional regulations. We analyze the driving factors of CO2 for developed and developing countries to test the theory of the EKC in the context of environmental regulations using a static and dynamic panel data model. We consider the Kyoto Protocol and the Clean Development Mechanism (CDM). The results from this study indicate that the Kyoto obligations have a reducing effect on CO2 emissions in developed and developing countries.
FloatBoost Learning for Classification

AdaBoost [3] minimizes an upper error bound which is an exponential function of the margin on the training set [14]. However, the ultimate goal in applications of pattern classification is always minimum error rate. On the other hand, AdaBoost needs an effective procedure for learning weak classifiers, which by itself is difficult especially for high dimensional data. In this paper, we present a novel procedure, called FloatBoost, for learning a better boosted classifier. FloatBoost uses a backtrack mechanism after each iteration of AdaBoost to remove weak classifiers which cause higher error rates. The resulting float-boosted classifier consists of fewer weak classifiers yet achieves lower error rates than AdaBoost in both training and test. We also propose a statistical model for learning weak classifiers, based on a stagewise approximation of the posterior using an overcomplete set of scalar features. Experimental comparisons of FloatBoost and AdaBoost are provided through a difficult classification problem, face detection, where the goal is to learn from training examples a highly nonlinear classifier to differentiate between face and nonface patterns in a high dimensional space. The results clearly demonstrate the promises made by FloatBoost over AdaBoost.
An Objective and Automatic Cluster Finder: An Improvement of the Matched-Filter Method

We describe an objective and automated method for detecting clusters of galaxies from optical imaging data. This method is a variant of the so-called "matched-filter” technique pioneered by Postman et al. (1996). Simultaneously using positions and apparent magnitudes of galaxies, this method can, not only find cluster candidates, but also estimate their redshifts and richnesses as byproducts of detection. We examine errors in the estimation of cluster's position, redshift, and richness with a number of Monte Carlo simulations. No systematic discrepancies between the true and estimated values are seen for either redshift or richness. For clusters with and with richness similar to that of the Coma cluster, typical errors in the estimation of position, redshift, and richness are evaluated as (one third of the projected core radius), 0.02, and 12%, respectively. Spurious detection rate of the method is about less than 10% of those of conventional ones which use only surface density of galaxies. A cluster survey in the North Galactic Pole region is executed to verify the performance characteristics of the method with real data. Despite poor quality of the data, two known real clusters are successfully detected. No unknown cluster with low or medium redshift ( 0.3) is detected. We expect these methods based on "matched-filter” technique to be essential tools for compiling large and homogeneous optically-selected cluster catalogs.
Private Money and Counterfeiting

The liabilities of private financial institutions (private money) have circulated historically. Current interest in private money has been spurred by advances in information technology that permit new types of payments arrangements. The author uses a search model of money to evaluate some of the benefits and costs of monetary systems with private money. Private money promotes productive financial intermediation, but it also may encourage counterfeiting. Counterfeiting, if achievable at a sufficiently low cost, may necessitate prohibition of private money in order to support monetary exchange.
Efficient Post-Quantum Zero-Knowledge and Signatures ( Draft )

In this paper, we present a new post-quantum digital signature algorithm that derives its security entirely from assumptions about symmetric-key primitives, which are very well studied and believed to be quantum-secure (with increased parameter sizes). We present our new scheme with a complete post-quantum security analysis, and benchmark results from a prototype implementation. Our construction is an efficient instantiation of the following design: the public key is y = f(x) for preimage-resistant function f , and x is the private key. A signature is a non-interactive zero-knowledge proof of x, that incorporates a message to be signed. Our security analysis uses recent results of Unruh (EUROCRYPT’12,’15,’16) that show how to securely convert an interactive sigma protocol to a non-interactive one in the quantum random oracle model (QROM). The Unruh construction is generic, and does not immediately yield compact proofs. However, when we specialize the construction to our application, we can reduce the size overhead of the QROM-secure construction to 1.6x, when compared to the Fiat-Shamir transform, which does not have a rigorous post-quantum security analysis. Our implementation results compare both instantiations, with multiple choices of f for comparison. Our signature scheme proposal uses the block cipher LowMC for f , as it gives the shortest signatures. In addition to reducing the size of signatures with Unruh’s construction, we also improve the size of proofs in the underlying sigma protocol (of Giacomelli et al., USENIX’16) by a factor of two. This is of independent interest as it yields more compact proofs for arbitrary choices of f in the classical case as well. Further, this reduction in size comes at no additional computational cost.
Accurate position and velocity control for trajectories based on dynamic movement primitives

This paper presents a novel method for trajectory generation based on dynamic movement primitives (DMPs) treated from a control theoretical perspective. We extended the key ideas from the original DMP formalism by introducing a velocity convergence mechanism in the reformulated system. Theoretical proof is given to guarantee its validity. The new method can deal with complex paths as a whole. Based on this, we can generate smooth trajectories with automatically generated transition zones, satisfy position- and velocity boundary conditions at start and endpoint with high precision, and support multiple via-point applications. Theoretic proof of this method and experiments are presented.
Long term optimization of asset replacement in energy infrastructures

In the western energy distribution systems, the assets are relatively old. Distribution companies expect a large number of assets to fail because they reach their end of life in 10 to 30 years from now. Those failed assets will have to be replaced, which would potentially double the total workload in this 20 year period. Unfortunately, half of the work force is expected to retire in the next 10 years. This combination of trends presents the distribution companies with a number of questions. What is the expected number of assets to fail due to age problems? What would be the cost-optimal preventive replacement strategy for those assets? What is the feasibility of this strategy, given the constraints caused by the employee shortage? What are alternatives to overcome those limitations? We have explored those questions with a System Dynamics model, based on real data from a distribution company. We determined that an increase in the number of failures is to be expected in the coming 10-20 years, even under a cost-optimal replacement strategy. However, because of employee shortages, this cost-optimal strategy cannot be executed with the current Human Resource policies, worsening the problem. Hence, optimal strategies would not only have to define asset replacement programs but also a matching HR policy.
Modeling of the supporting legs for a water-jumping robot mimicking water striders

The performance of the robot mimicking water striders is mainly influenced by the driven mechanism, trajectory of actuating legs and hydrophobic property of the material. Clarify the forces exerted on the hydrophobic legs helps optimize the rowing trajectory and performance of the water striders. Limited by the complex fluid dynamics on air-water interface and the lack of the relevant theories, the analysis is mainly focused on the static forces, the research on hydrodynamic forces is still challengeable. In this paper, we firstly built theoretical force models of the hydrophobic supporting legs, then a force platform was designed to verify the models, a series of experiments were carried out to measure the actual forces. The experiment results can provide empirical parameters for the biomimetic surface water strider robot motion theory.