Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of two feedforward design methods aiming at accurate trajectory tracking of the end point of a flexible robot arm

This paper discusses the design and properties of two trajectory tracking controllers for linear time-invariant systems, and compares their implementation and experimental results on a flexible one-link robot equipped with a velocity-controlled actuator. High positioning accuracy and low tracking errors within a specified bandwidth are their performance specifications. Both controllers use the same state feedback controller, but have a different feedforward design approach. Both feedforward methods design stable prefilters which approximate the unstable inverse system model. The first method designs a stable prefilter using the extended bandwidth zero phase error tracking control (EBZPETC) method. The second feedforward method adds delay to the inverse model and then uses common filter design techniques to approximate this delayed frequency response.
Autoconstructive Evolution: Push, PushGP, and Pushpop

This paper is a preliminary report on autoconstructive evolution, a framework for evolutionary computation in which the machinery of reproduction and diversification (and thereby the machinery of evolution) evolves within the individuals of an evolving population of problem solvers. Autoconstructive evolution is illustrated with Pushpop, an evolving population of programs expressed in the Push programming language. The Push programming language can also be used in a more traditional genetic programming framework and may have unique benefits when so employed; the PushGP system, which uses traditional genetic programming techniques to evolve Push programs, is also described.
Cepstrum liftering based voice conversion using RBF and GMM

Voice Conversion is a technique which morphs the speaker dependent acoustical cues of the source speaker to those of the target speaker. Speaker dependent acoustical cues are characterized at different levels such as shape of vocal tract, glottal excitation and long term prosodic parameters. In this paper, low time and high time liftering is applied to the cepstrum to separate the vocal tract and glottal excitation of the speech signal. The Radial Basis Function and Gaussian Mixture Model are developed to capture the mapping functions for modifying the cepstrum based vocal tract and glottal excitation of the source speaker according to a target speaker. The subjective and Objective measures are used to evaluate the comparative performance of RBF and GMM based voice conversion system. Results indicate that the RBF based transformation can be used as an alternative to GMM based model. Subjective evaluation illustrate that the proposed algorithm maintains target voice individuality, quality of the speech signal.
Learning Large Scale Class Specific Hyper Graphs for Object Recognition

This paper describes how to construct a hyper-graph model from a large corpus of multi-view images using local invariant features. We commence by representing each image with a graph, which is constructed from a group of selected SIFT features. We then propose a new pairwise clustering method based on a graph matching similarity measure. The positive example graphs of a specific class accompanied with a set of negative example graphs are clustered into one or more clusters, which minimize an entropy function with a restriction defined on the F-measure. Each cluster is simplified into a tree structure composed of a series of irreducible graphs, and for each of which a node cooccurrence probability matrix is obtained. Finally, a recognition oriented class specific hyper-graph (CSHG) is generated from the given graph set. Experiments are performed on over 50K training images spanning 500 objects and over 20K test images of 68 objects. This demonstrates the scalability and recognition performance of our model.
How Behavioral Economics Can Shape Firm Strategy and Public Policy: Lessons from the Field and Laboratory

Incentives are not always economic or monetary in nature. Individuals are often influenced by socially-based incentives centered on how he or she wants to be perceived in a social setting, such as the desire to publicly adhere to a norm of fairness. Likewise, individuals can also be influenced by cognitively-based incentives centered on self-perception and self-attribution, such as the desire to convince oneself that he or she is altruistic. Behavioral economists have incorporated some of these concepts into standard economic models of decision-making, but there is much we still do not understand about the role of these psychology-based incentives in organizational strategy and public policy contexts. This thesis examines the effects of several social and cognitive incentives across different settings. In Chapter I, I use a laboratory experiment to examine why individuals feel the need to reciprocate to gifts and favors, even when those gifts are from businesses looking to take advantage of our tendency to reciprocate. Specifically, I demonstrate that individuals reciprocate simply to the intent to give a gift or favor, regardless of the ulterior motives or actual utility resulting from the favor. In Chapter II, I use observational data to investigate how pharmaceutical firms exploit social incentives that invoke reciprocity in order to influence how physicians prescribe. I concurrently examine how regulators also use social incentives, but as a way to protect consumers from these manipulative marketing strategies. In Chapter III, I collaborate with a non-profit public radio station to test the interaction between psychological and economic incentives in a fundraising context. In particular, Chapter III uses a field experiment to show that economic incentives in a fundraising campaign can reduce donation rates by detracting attention from the psychological reasons for donating, and thereby inducing a different mindset in donors. This thesis builds upon the field of behavioral economics in two ways. First, it uses experimental methods to extend our theoretical understanding of non-monetary, psychological incentives, including some of the mechanisms that drive reciprocity, social image, and motivation crowding out. Second, the thesis applies this knowledge toward understanding the effects of several commonly used marketing campaigns and regulatory policies.
Digital Library Evaluation: Toward Evolution of Concepts

While there were many efforts in the research and practices of digital libraries, evaluation was not a conspicuous activity. It is well recognized that digital library evaluation is a complex and difficult undertaking. Challenges facing digital library evaluation are enumerated. A conceptual framework for evaluation is suggested. A review of evaluation efforts in research and practice concentrates on derivation of criteria used in evaluation. Essential requirements for evaluation are stated. Discussed are constructs, context, and criteria of digital libraries: What should we evaluate? For what purpose do we evaluate? Who should evaluate? At what level do we evaluate? Upon what criteria do we evaluate? In addition, included are suggestions for adaptation of criteria from related activities. The article is considered as a part of the evolution of concepts for digital library evaluation.
Partial Evaluation in Prolog: Some Improvements about Cut

Two main aspects of Partial Evaluation for Prolog programs are considered: treatment of cuts and control of recursion. The analysis about cut is exhaustive: we consider occurrences of cut within both conjunctions and disjunctions. We show which restrictions are necessary to safely deal with cut in Partial Evaluation and which transformations are allowed. We define a set of conditions for compile-time execution and remotion of cuts. The safety of these conditions is formally proved. Some interesting results about the impact of mode inference techniques within this framework are finally drawn. As for control issues, we address a new approach to the problem of detecting infinite derivation paths. It is based on a theoretical characterization of non-termination and provides a general technique whose effectiveness does not depend on the structure of program domains.
Feature construction for memory-based semantic role labeling of Catalan and Spanish

In this paper we present a memory-based semantic role labeling (SRL) system for Catalan and Spanish. We approach the SRL task as two distinct classification problems: the assignment of semantic roles to arguments of verbs, and the assignment of a semantic class to verbs. We hypothesize that the two tasks can be solved in a uniform way, for both languages. Building on the same pool of features reported useful in earlier work, we train two classifiers for the two subtasks, selecting features systematically in a hillclimbing search. We use the IB1 classifier, a supervised memory-based learning algorithm based on the k-nn algorithm. The system achieves an overall score of 85.69 F-score on Catalan, and 84.12 on Spanish.
Agent-based scalable design of a cross-layer security framework for Wireless Sensor Networks Monitoring Applications

Secure monitoring services supported by flexible, manageable, and cheap systems in areas where ordinary networks are unsuitable: this is one of to-day challenges in health monitoring engineering. Wireless Sensor Networks represent a promising technological solution but resource constraints and exposure to external attacks could limit their employment. The design and the implementation of an effective security to provide the monitoring service with the reasonable level of reliability is the scope of this paper. Following the platform-based design methodology, we have designed and implemented a “Secure Platform” to support Monitoring Applications which is compliant to requirements such as modularity, optimized usage of resource, solution scalability. To this aim, the Secure Platform exploits mobile agents and we have enhanced middleware solutions already available in literature. Security functions implemented in the Secure Platform have been a distributed intrusion detection system, based on a simplified approach to Hidden Markov Models, supported by an hybrid cryptographic scheme, based on network topology authentication. These security functions have been proposed by the same authors in [12] and [13]. Detailed design and the description of the software enhancements to the middleware platform are presented in this paper.
Polymorphisms and Circuit Complexity

We present a framework for studying circuit complexity that is inspired by techniques that are used for analyzing the complexity of CSPs. We prove that the circuit complexity of a Boolean function $f$ is characterized by the partial polymorphisms of $f$'s truth table. Moreover, the non-deterministic circuit complexity of $f$ is characterized by the polymorphisms of $f$'s truth table.
A Simple Approach to Control the Time-constant of Microwave Integrators

In this paper, firstly the time-constant of an integrator is described in continuous as well as in the discrete-time domains. Further, a simple relation is expressed to find the time-constant of an integrator from continuous-time domain to discrete-time domain or vice-versa. Thereafter, the microwave integrators of different time-constants are obtained by optimizing the characteristic impedance of an open-circuited shunt stub using linear programming approach in z-domain. It is clear that all the microwave integrators of different time-constants are realized only by using a single open-circuited shunt stub.
Prevalence of and Risk Factors for Gastrointestinal Diseases in Korean Americans and Native Koreans Undergoing Screening Endoscopy

Background/Aims In South Korea, health check-ups are readily accessible to the public. We aimed to compare the prevalence of upper gastrointestinal (GI) and lower GI diseases in Korean Americans and native Koreans to determine differences and risk factors. Methods In total, 1,942 subjects who visited Gangnam Severance Hospital from July 2008 to November 2010 for a health check-up were enrolled. Basic characteristics and laboratory data for the subjects were collected. Esophagogastroduodenoscopy and colonoscopy were performed. In total, 940 Korean Americans (group 1) and 1,002 native Koreans (group 2) were enrolled. Results The overall prevalence of GI diseases for each group (group 1 vs group 2) were as follows: reflux esophagitis (RE) (9.65% vs 7.9%), gastric ulcer (2.8% vs 3.4%), duodenal ulcer (2.3% vs 3.6%), gastric cancer (0.4% vs 0.3%), colorectal polyp (35.9% vs 35.6%), colorectal cancer (0.5% vs 0.5%), and hemorrhoids (29.4% vs 21.3%). The prevalence of hemorrhoids was significantly higher in group 1 than in group 2 (p=0.001). In the multivariable analysis of group 1, male sex, age over 50 years, hypercholesterolemia and hypertriglyceridemia predicted colorectal polyps. Male sex and high fasting glucose levels were associated with RE. Conclusions Our study showed that the prevalence of GI diseases (except hemorrhoids) in Korean Americans was similar to that observed in native Koreans. Therefore, the Korean guidelines for upper and lower screening endoscopy may be applicable to Korean Americans.
A Sun Spot Center Orientation Method Based on Ellipse Fitting in the Application of CPV Solar Tracker

As one of the most important part of the Concentrated Photovoltaic (CPV) system, the tracking accuracy and sensitivity of the solar tracker has a significant influence on the lighting rate and power generation rate of CPV system. The CPV solar tracker based on ARM tracks the sun mainly by using the CMOS sensor. In order to improve the tracking sensitivity, a method of sun spot center orientation based on canny edge operator and ellipse fitting is presented in this paper. The new method is not demanding for integrity and definition of the sun spot. After being used in the CPV solar tracker, the superiority of accuracy and applicability of the new method is proved by comparing with the traditional methods.
Towards acceleration of Rump's fast and parallel circular interval arithmetic for enclosing solution of non linear system of equations

It is often the practice to express measurements of experimental problems in terms of uncertainties either due to contamination of measuring instruments or inaccurate measurements in the experimental models. In this note as an attempt at solving a system of nonlinear equation by accelerating the convergence of Rump's fast and parallel interval arithmetic incorporating where in, the Carstensen and Petkovic circular arithmetic for enlarging a disk to be inverted in the complex plane. The problem of excess widths in the midpoint-radius matrix and midpoint ‐radius vector multiplication is taken into account by using the procedure of Ceberio and Kreinovich for fast multiplication of two interval matrices (or interval matrix and interval vector) whose entries are expressed in terms of midpointradius matrix. We used Interval Gaussian Elimination algorithm and Interval Gauss-Siedel iterative method as our basic tools with Newtonian steps, some significant gains over that of Rump’s method were achieved. A stopping criterion for a Newton's step is given in terms of defect measurement instead of the error. AMS SUBJECT CLASSIFICATION (2000): 65 G20, 65G30, 65G40.
Goertzel Algorithm Based Shunt Active Power Filter Using Sliding Mode Controller

In this paper control of Goertzel Algorithm based shunt active power filter with sliding mode controller is considered. Shunt active power filter involves harmonics mitigation due to three phase non linear loads under balanced and unbalanced load conditions. The sliding mode controller is used to regulate voltage of the capacitor used in inverter. The sliding mode controller improves the dynamic response of the system and provides faster convergence. The performance of the sliding mode controller is compared with the conventional PI controller. The above system is investigated for balanced and unbalanced load conditions using MATLAB/Simulink. From the analysis it can be observed that the Goertzel algorithm based shunt active power filter with sliding mode controller gives a better response than the conventional PI controller. The simulation results prove the effectiveness of the proposed system. Keywords—Shunt active power filter, total harmonic distortion,Goertzel Algorithm, sliding mode controller.
Computer-aided summarisation : How much does it really help ?

Computer-aided summarisation is a technology developed as a complement to automatic summarisation, which produces high quality summaries with less effort. To achieve this, a user-friendly environment which incorporates several well-known summarisation methods has been developed. This paper presents the main features of the computer-aided summarisation environment and evaluates the usefulness of the developed tool. Experiments showed that it is possible to reduce the time necessary to produce the summary by about 20% without any degradation in the summary’s quality.
Nomination and identification of traditionally underrepresented students for gifted programs

A dataset containing demographic, gifted nomination status, and gifted identification status for all elementary school students in the state of Georgia (N = 705,074) was examined. The results indicated that automatic and teacher referrals were much more valuable than other referral sources. Asian and White students were much more likely to be nominated than Black or Hispanic students. Students receiving free or reduced-price lunches were much less likely to be nominated than students paying for their own lunches. The results suggest that inequalities in nomination, rather than assessment, may be the primary source of the underrepresentation of minority and low-SES students in gifted programs.
Convergence in law of the minimum of a branching random walk

We consider the minimum of a super-critical branching random walk. Addario-Berry and Reed [Ann. Probab. 37 (2009) 1044–1079] proved the tightness of the minimum centered around its mean value. We show that a convergence in law holds, giving the analog of a well-known result of Bramson [Mem. Amer. Math. Soc. 44 (1983) iv+190] in the case of the branching Brownian motion.
An efficient implementation of PBKDF2 with RIPEMD-160 on multiple FPGAs

A weakness of many security systems is the strength of the chosen password or key derivation function. We show how FPGA technology can be used to effectively attack cryptographic applications with a password dictionary. We have implemented two independent PBKDF2 cores each using four HMAC cores with pipelines calculating a RIPEMD-160 hash to derive encryption keys together with one resource optimized AES-256 XTS core for direct decryption on a Xilinx Spartan6-LX150 FPGA. Our design targets TRUECRYPT containers, but may be applied to similar encryption tools with little adaption. In order to save resources and maximize speed, we have further optimized the RIPEMD-160 hash function for this purpose. Our design executed on the multi-FPGA system RIVYERA S6-LX150 containing 128 S6-LX150 FPGAs, finally reaches a peak performance of about 245,000 passwords per second.
The Image Quality Standard based on Human Visual System for the Spectral Sensitivity Crosstalk Depending on Lens F-number

The color reproduction of an image sensor is one of the important characteristics which determine the performance of the image sensor. Recently, the pixel size of image sensor has become smaller due to the demand of large pixel count. So, small F-number lens is needed to improve the sensitivity. However, the crosstalk component of spectral sensitivity characteristics increases due to using the small F-number lens, and the color reproduction of the image sensor becomes worse. Therefore, we propose a color difference standard based on human visual characteristics to solve this problem due to the lens with small F-number. If the color difference corresponds to these standards, the color reproduction will be satisfied even if the crosstalk component of spectral sensitivity characteristics ncreases. i
Deceleration of a Relativistic, Photon-rich Shell: End of Preacceleration, Damping of Magnetohydrodynamic Turbulence, and the Emission Mechanism of Gamma-Ray Bursts

We consider the interaction of a relativistically moving shell, composed of thermal photons, a reversing magnetic field, and a small admixture of charged particles, with a dense Wolf-Rayet wind. A thin layer of Wolf-Rayet material is entrained at the head of this outflow; it cools and becomes Rayleigh-Taylor unstable, thereby providing an additional source of inertia and variability. The gamma rays streaming across the forward shock load the wind material with electron-positron pairs and push it to relativistic speeds close to the engine. This defines a characteristic radiative compactness at the point where the reverse shock has completed its passage back through the shell. We argue that the prompt gamma-ray emission is triggered by this external braking, at an optical depth ~1 to electron scattering. Torsional MHD waves, excited by the forced reconnection of the reversing magnetic field, carry a fluctuating current and are Landau damped at high frequencies on the parallel motion of the light charges. We show that the heated charges cool primilarly by inverse Compton radiation, which is beamed along the magnetic field. Thermal radiation that is advected out from the base of the jet cools the particles. The observed relation between peak energy and isotropic luminosity—both its amplitude and scaling—is reproduced if the blackbody seeds are generated in a relativistic jet core that is subject to Kelvin-Helmholtz instabilities with the Wolf-Rayet envelope. This relation is predicted to soften below an isotropic luminosity Liso ~ 3 × 1050 ergs s-1. Spectrally harder bursts will arise in outflows which encounter no dense stellar envelope. The duration of spikes in the inverse-Compton emission is narrower at higher frequencies, as observed. The transition from prompt gamma-ray emission to afterglow can be explained by the termination of the thermal X-ray seed and the onset of synchrotron-self-Compton emission.
Conventional and model predictive direct torque control techniques for induction motor drive

Finite control set model predictive control (FCS-MPC) is one of the promising alternatives for classical controllers (PID, hysteresis, etc…) in electric drive applications. The inherent discrete nature of FCS-MPC is suitable for a converter fed direct torque control (DTC) of induction motor drive. This paper presents a comparative study between conventional DTC and finite control set model predictive direct torque control (FCS-MPDTC) for an induction motor drive. The conventional DTC offers fast dynamic response, however the presence of nonlinear controllers causes considerable torque and flux ripples. In this paper, a simple one step ahead FCS-MPDTC is used by considering stator flux and rotor flux as state variables. In this method, nonlinear controllers and heuristic switching table are replaced with a cost function based online optimization for the selection of suitable switching state. Further, a new cost function is introduced based on simple weighted sum method to eliminate the selection of weighting factors. The results are verified for both control techniques applied to a 6 kW squirrel-cage induction motor under different operating conditions using MATLAB/Simulink. Proposed method resulted in improved steady state and dynamic response along with reduced torque and flux ripples compared to its counterpart.