Miracle-dz/UniFAR-FTUs huggingface dataset:
Developmental Trends in Object Recognition From Preschool to Adolescence: A Preliminary Investigation

This experiment attempts to determine developmental trends in object recognition. Two object identification questionnaires were administered to 26 children between the ages of 4 and 10. One questionnaire included pictures fragmented arbitrarily, whereas the other included pictures fragmented according to recognition-bycomponents (RBC) theory (Biederman, 1987). Factors related to performance on the questionnaires were measured using the Test of Nonverbal Intelligence (Brown, Sherbenou, & Johnson, 1990) and the Figure-Ground, Form Constancy, Closure, and Spatial Relations subtests of the Developmental Test of Visual Perception (DTVP; Hammill, Pearson, & Voress, 1993). There was a significant increase in the number of correctly identified objects with age for the arbitrarily fragmented objects, but not for the RBC objects. This findings suggests that the RBC objects contained sufficient information for identification across ages. In addition, different factors appear to influence recognition between the two types of objects. Arbitrarily fragmented objects are related to visual closure ability whereas RBC objects are related to the total of the four DTVP-2 subtests. These findings suggest that recognizing arbitrarily fragmented objects may be influenced by a specific perceptual ability but the RBC objects may be influenced by a number of related abilities.
Procedural generation of complex stable structures for angry birds levels

This paper presents a procedural content generation algorithm for the physics-based puzzle game Angry Birds. The proposed algorithm creates complex stable structures using a variety of 2D objects. These are generated without the aid of pre-defined substructures or composite elements. The structures created are evaluated based on a fitness function which considers several important structural aspects. The results of this analysis in turn affects the likelihood of particular objects being chosen in future generations. Experiments were conducted on the generated structures in order to evaluate the algorithm's expressivity. The results show that the proposed method can generate a wide variety of 2D structures with different attributes and sizes.
CloseMiner: discovering frequent closed itemsets using frequent closed tidsets

Complete set of itemsets can be grouped into non-overlapping clusters identified by closed tidsets. Each cluster has only one closed itemset and is the superset of all itemsets with the same support. Number of closed itemsets is identical to the number of clusters. Therefore, the problem of discovering closed itemsets can be considered as the problem of clustering the complete set of itemsets by closed tidsets. In this paper, we present CloseMiner, a new algorithm for discovering all frequent closed itemsets by grouping the complete set of itemsets into non-overlapping clusters identified by closed tidsets. An extensive experimental evaluation on a number of real and synthetic databases shows that CloseMiner outperforms Apriori and CHARM.
NLP based Object Oriented Analysis and Design from Requirement Specification

This paper describes a natural language-based tool which aims at supporting the Analysis stage of software development in an Object-Oriented framework. This Natural Language Processing technique is to analyze software requirement texts written in English and build an integrated discourse model of the processed text, represented in a Semantic Network. This Semantic Network is then used to automatically construct an UML diagrams such as Class Model representing the object classes mentioned in the text and the relationships anions them & sequence diagram of the dynamic model. Requirement analysis determines the user expectation for the application. We propose a method to extract the diagrams from requirement analysis with strong semantic support. The tool can also convert the user modelling information into the blocks of programming source code; Code generation is made available in Java. The aim is to demonstrate the use of NLP (Natural Language Processing) techniques for the extraction of UML diagrams with code template generation in JAVA by implementing a prototype tool that uses the NLP techniques.
An Analytic Extension of the MS Renormalization Scheme

The conventional definition of the running coupling αMS(μ) in quantum chromodynamics is based on a solution to the renormalization group equations which treats quarks as either completely massless at a renormalization scale μ above their thresholds or infinitely massive at a scale below them. The coupling is thus nonanalytic at these thresholds. In this paper we present an analytic extension of αMS(μ) which incorporates the finite-mass quark threshold effects into the running of the coupling. This is achieved by using a commensurate scale relation to connect αMS(μ) to the physical αV scheme at specific scales, thus naturally including finite quark masses. The analyticextension inherits the exact analyticity of the αV scheme and matches the conventional MS scheme far above and below mass thresholds. Furthermore just as in αV scheme, there is no renormalization scale ambiguity, since the position of the physical mass thresholds is unambiguous. 11.15. -q, 11.15. Bt, 12.38. -t, 12.38. Bx Typeset using REVTEX ∗Work supported in part by the Department of Energy, contract DE–AC03–76SF00515, Deutsche Forschungsgemeinschaft, Reference # Me 1543/1-1, and the Swedish Natural Science Research Council, contract F–PD 11264–301. †Present address: Department of Physics, University of Durham, Durham, United Kingdom ‡Present address: Department of Rad. Sciences, Uppsala University, Uppsala, Sweden
Learning the velocity kinematics of ICUB for model-based control: XCSF versus LWPR

The model-based control of humanoid robots requires the availability of accurate mechanical models that can be hard to obtain in practice. One approach to this problem consists in calling upon machine learning methods. In this paper, using a standard control approach based on visual servoing, we compare the accuracy of two supervised learning methods, namely LWPR and XCSF, to extract the forward velocity kinematics of the upper body of the ICUB robot. Experiments are performed in simulation, using one arm and the head for reaching tasks. We show that both methods provide accurate models of the robot, with a slight advantage to XCSF over LWPR.
Situated Observation of Human Activity

Many human activities follow a loosely defined script in which individuals assume roles. Encoding such scripts in a formal representation makes it possible to build systems that observe and understand human activity. In this paper, we first present a conceptual framework in which scripts for human activity are described as scenarios composed of actors and objects within a network of situations. We provide formal definitions for the underlying concepts for situation models, and then propose a layered, component-based, software architecture model for constructings systems to observe human activity. Both the conceptual framework and architectural model are illustrated with a system for real-time composition of a synchronized audio-video streams for recording activity within a meeting or lecture.
On the complexity of optimal priority assignment for periodic tasks upon identical processors

In this paper we study global fixed-priority scheduling of periodic task systems upon identical multiprocessor platforms. Based on existing feasibility tests for periodic task systems upon identical multiprocessor platforms, we show (using a dummy priority assignment algorithm) that optimal priority assignment for these systems exists. Then we provide an algorithm based on RMUS[m/(3m-2)] that has lower complexity. Finally, we conjuncture that, contrary to the general opinion, (pseudo-) polynomial optimal priority assignment algorithms for periodic task systems upon identical processors might exist.
Pregnancy-Associated Exosomes and Their Modulation of T Cell Signaling1

Exosome release by viable cells is a feature of activated cell types, including tumors, fetal cells, and cells of the immune system. Exosomes critically regulate immune activation, by mediating activation-induced cell death. Fetal cells may mimic these events to selectively delete reactive lymphocytes. In this study the presence and composition of placenta-derived exosomes are demonstrated in the maternal circulation along with their consequences on T cell activation markers. For all pregnant patients, exosomes were isolated from sera obtained between 28 and 30 wk gestation. For pregnant women, subsequently delivering at term, circulating levels of placental exosomes were 1.8 times greater than those delivering preterm (p < 0.0001). Exosomes isolated from pregnancies subsequently delivering at term expressed significantly higher levels of biologically active components, including Fas ligand (FasL) and HLA-DR, than those from pregnancies delivering preterm. Standardizing for protein concentrations, exosomes from term-delivering pregnancies exhibited greater suppression of CD3-ζ and JAK3 than those delivering preterm. The suppression of CD3-ζ and JAK3 correlated with exosome expression levels of FasL (r2 = 0.92 and r2 = 0.938, respectively). Fractionation of exosomes from term-delivering pregnancies by continuously eluting electrophoresis indicated that intact 42kD FasL and an unidentified 24-kDa protein were associated with CD3-ζ suppression. Our results demonstrated that exosomes from pregnancies ultimately delivering at term are present at significantly greater concentrations than those from pregnancies delivering preterm; however, exosomes from term-delivering pregnancies also exhibit significantly greater suppression of CD3-ζ and JAK3.
Thermal Aware Placement in 3D ICs

Dominance of on-chip power densities has become a critical design constraint in high-performance VLSI design. This is primarily due to increased technology scaling, number of components, frequency and bandwidth. The consumed power is usually converted into dissipated heat, affecting the performance and reliability of a chip. Moreover, recent trends in VLSI design entail the stacking of multiple active (device) layers into a monolithic chip. These 3D chips have significantly larger power densities than their 2D counterparts. In this paper, we consider the thermal placement of standard cells and gate arrays (modules) taking total wire-length as well as TSVs (through silicon via) into consideration. Our contribution includes a novel algorithm for placement of the gates or cells in the different active layers of a 3D IC such that: (i) the temperatures of the modules in each of the active layers is uniformly distributed, (ii) the maximum temperatures of the active layers are not too high, (iii) the maximum temperatures of the layers vary in a non-increasing manner from bottom layer to top layer, (iv) the estimated total interconnect lengths connecting the modules of the different layers are also improved, and (v) the total number of interlayer vias is quite reasonable. Experimental results on randomly generated and standard benchmark instances are encouraging.
RESTful Web Services for the Internet of Things

In the coming years, the size and scope of the Internet will greatly increase as physical world devices (e.g., sensors and home appliances) are becoming smart enough to communicate and share data over the Internet—a phenomenon known as the Internet of Things (IoT). The problem of realizing the IoT is, however, how to effectively penetrate the devices into the existing Web. In this paper, we present Constrained Application Protocol (CoAP) and other key enabling technologies together with an end-to-end IP and RESTful Web Services based architecture for integrating physical world devices in constrained environments with the Web. Keywords-CoAP; HTTP; Internet of Things; REST; Web Services
Neural weighted least-squares design of FIR higher-order digital differentiators

This paper extends the neural network based algorithm for equiripple design of higher-order digital differentiators in the weighted least-squares sense. The proposed approach formulates an error representation reflecting the difference between the desired amplitude response and the designed response in a Lyapunov error function. The optimal filter coefficients are obtained when neural network achieves convergence. Furthermore, by using a weighted updating function, the proposed method can find a very good approximation of the minimax solution. Simulation results indicate that the proposed technique is able to achieve good performance in a parallelism manner.
Silicon implementation of the generalized integrate-and-fire neuron model

In this paper we present the design, implementation and preliminary results from a silicon neuron (SiN) based on the generalized integrate-and-fire neuron model. The SiN is integrated onto a chip with a number of similar SiNs. In this paper we show the results from a single neuron, however, in the future it is our aim to show that real-time, low-power and highly configurable spiking neural networks are feasible on silicon chips.
Implementation of NAS Parallel Benchmarks in Java

A number of features make Java an attractive but a debatable choice for High Performance Computing (HPC). In order to gauge the applicability of Java to the Computational Fluid Dynamics (CFD) we have implemented NAS Parallel Benchmarks in Java. The performance and scalabili_y of the benchmarks point out the areas where improvement in Java compiler technology and in Java thread implementation would move Java closer to Fortran in the competition for CFD applications.
Robust design of unconstrained predictive controllers

A systematic and complete design procedure for robust predictive controllers is proposed. The synthesis method is based on rigorous theoretical foundations, without resorting to approximations or ad hoc design guidelines, yet it remains a viable tool for practical utilization. A significant feature is that the robustified predictive controller retains the servo performance of a nominal predictive controller designed using conventional methods. In addition, the robust predictive controller can be designed to guarantee perfect steady-state rejection of asymptotically constant disturbances. The robust design method is developed for systems affected by unmodeled dynamics, and is based on solving a discrete-time model-matching problem. It is shown that the robustified controller can legitimately be classified as a predictive controller. An illustrative design example is given.
A System Architecture for Reconfigurable Trusted Platforms

For improving the security of embedded systems, trusted computing is a promising technology. For the area of microprocessors in general and personal computers in particular the Trusted Computing Group (TCG) has published detailed specifications. The resulting hardware has been available for some years. This contribution discusses the feasibility of deploying ideas from trusted computing in the domain of reconfigurable hardware, esp. FPGAs, and possible benefits and drawbacks. We give a proposal to use actually available FPGA technology to build a trusted platform on reconfigurable hardware. We also show how trusted computing can deal with partial dynamic reconfiguration while still allowing the user to fully exploit its potentials.
A nominal axiomatisation of the lambda-calculus

The lambda-calculus is a fundamental syntax in computer science. It resists an algebraic treatment because of capture- avoidance side-conditions. Nominal algebra is a logic of equality designed with formalisation of speciﬁcations involving binding in mind. In this paper we axiomatise the lambda-calculus using nominal algebra, demonstrate how proofs with these axioms reﬂect the informal arguments on syntax, and we prove the axioms sound and complete. This makes a formal connection between a ‘nominal’ approach to variables, and the more traditional view of variables as a syntactic convenience for describing functions.
A Generative Probabilistic Model for Multi-label Classification

Traditional discriminative classification method makes little attempt to reveal the probabilistic structure and the correlation within both input and output spaces. In the scenario of multi-label classification, most of the classifiers simply assume the predefined classes are independently distributed, which would definitely hinder the classification performance when there are intrinsic correlations between the classes. In this article, we propose a generative probabilistic model, the Correlated Labeling Model (CoL Model), to formulate the correlation between different classes. The CoL model is presented to capture the correlation between classes and the underlying structures via the latent random variables in a supervised manner. We develop a variational procedure to approximate the posterior distribution and employ the EM algorithm for the empirical Bayes parameter estimation. In our evaluations, the proposed model achieved promising results on various data sets.
Hemispheric Differences in Auditory Perception Are Similar to Those Found in Visual Perception

In a pitch discrimination task, subjects were faster and more accurate in judging low-frequency sounds when these stimuli were presented to the left ear, compared with the right ear. In contrast, a right-ear advantage was found with high-frequency sounds. The effect was in terms of relative frequency and not absolute frequency, suggesting that the effect arises from postsensory mechanisms. A simitar laterality effect has been reported in visual perception with stimuli varying in spatial frequency. These multimodal laterality effects may reflect a general computational difference between the two cerebral hemispheres, with the left hemisphere biased for processing high-frequency information and the right hemisphere biased for processing low-frequency information.
A classification scheme of 3D interaction techniques

An enhanced classiication scheme is described, capable to provide accurate analysis of 3D interaction techniques. It is based on examples found in the literature and summarized here in a review. The feature space of the scheme has proven to be useful in analysing particular subjects of their behavior and in deriving new interaction techniques. Several interaction techniques for the rotation task are analyzed using Fitts' law to predict their performance. The treatment specializes on 2D input devices, but several results are easily generalizable to higher dimensional input devices.
Milk Production and Income over Feed Costs in Dairy Cows Fed Medium-roasted Soybean Meal and Corn Dried Distiller’s Grains with Solubles

The aims of this study were to determine the effects of feeding medium-roasted soybean meal (SBM) and corn dried distiller’s grains with solubles (CDDGS) in dairy cows on milk production and income over feed costs. A randomized complete block design experiment was conducted with 24 crossbred multiparous Holstein Friesian dairy cows in early- and mid-lactation. Four dietary treatments were as follows: basal diet without feed substitute (Control), 7.17% dry matter (DM) roasted SBM replaced for concentrate (R-SBM), 11.50% DM CDDGS replaced for concentrate (DDGS), and 3.58% DM roasted SBM plus 5.75% DM CDDGS replaced for concentrate (SB-DG). The roasted SBM was produced using a medium-heated treatment at 100°C for 180 min. Dry matter intake was not affected by feeding high rumen undegradable protein (RUP) sources, but the replacement of roasted SBM and CDDGS for concentrate significantly improved (p<0.001) RUP intake (0.90, 0.86, and 0.88 kg/d corresponding to R-SBM, DDGS, and SB-DG) compared to the control (0.61 kg/d). Feeding roasted SBM and CDDGS alone or in combination had no significant effect on milk composition of dairy cows (p>0.05), whereas milk yield was significantly increased by 3.08 kg/d in the SB-DG group relative to the control group (p<0.01). Net income was meaningfully increased (p<0.05) from 4th week post feeding, the SB-DG group reached the greatest net income ($3.48/head/d) while the control group had the lowest value ($2.60/head/d). In conclusion, the use of CDDGS alone or in combination with medium-roasted SBM as substitute for concentrate in lactating dairy cattle diet led to improved milk production and net income over feed costs without affecting total dry matter intake and milk composition, while feeding medium-roasted SBM seemed to show intermediate values in almost parameters.
Soft Selective Sweeps in Evolutionary Rescue

Evolutionary rescue occurs when a population that is declining in size because of an environmental change is rescued from extinction by genetic adaptation. Evolutionary rescue is an important phenomenon at the intersection of ecology and population genetics, and the study of evolutionary rescue is critical to understanding processes ranging from species conservation to the evolution of drug and pesticide resistance. While most population-genetic models of evolutionary rescue focus on estimating the probability of rescue, we focus on whether one or more adaptive lineages contribute to evolutionary rescue. We find that when evolutionary rescue is likely, it is often driven by soft selective sweeps where multiple adaptive mutations spread through the population simultaneously. We give full analytic results for the probability of evolutionary rescue and the probability that evolutionary rescue occurs via soft selective sweeps. We expect that these results will find utility in understanding the genetic signatures associated with various evolutionary rescue scenarios in large populations, such as the evolution of drug resistance in viral, bacterial, or eukaryotic pathogens.
Teaching by demonstration on dual-arm robot using variable stiffness transferring

Teaching by demonstration (TbD) techniques have been extensively investigated in the recent decades to enable transferring various task skills from human to robots. The traditional TbD techniques focus on teaching motion trajectories that may be sufficient for routine tasks with fixed objects. While for interactive tasks in contact with dynamic environment and objects, e.g., the payload of a robot manipulator may change from one to another, teaching robot only by motion demonstration may cause undesired contact force and inefficiency in the task execution. In this paper, we present a novel TbD method enhanced by transferring the stiffness profile during human robot interaction (HRI). The method is developed on a bimanual robot, whereas one slave arm plays the role of the tutee, and the other master arm coupled with human demonstrator plays the role of tutor. A rendering algorithm is employed to provide demonstrator with force feedback via a purposely built coupling device according to the motion disparity between the two arms. The muscle surface electromyography (sEMG) signals collected during HRI is processed to extract the demonstrator's variable stiffness as well as hand grasping patterns. Comparative tests have been carried out on a bimanual Baxter robot for a lifting task with three different set-ups: i) TbD with predefined fixed stiffness; ii) TbD with demonstrator transferred variable stiffness without force feedback; and iii) TbD with demonstrator transferred variable stiffness with force feedback. Results show that the proposed TbD method performs best by transferring the demonstrator's physical interactive skill to the robot in a natural and efficient manner.