Miracle-dz/UniFAR-FTUs huggingface dataset:
Remembering complex objects in visual working memory

Visual working memory stores stimuli from our environment as representations that can be accessed by high-level control processes. This study addresses a longstanding debate in the literature about whether storage limits in visual working memory include a limit to the complexity of discrete items. We examined the issue with a number of change-detection experiments that used complex stimuli which possessed multiple features per stimulus item. We manipulated the number of relevant features of the stimulus objects in order to vary feature load. In all of our experiments, we found that increased feature load led to a reduction in change-detection accuracy. However, we found that feature load alone could not account for the results, but that a consideration of the number of relevant objects was also required. This study supports capacity limits for both feature and object storage in visual working memory. Working memory (WM) is a capacity-limited store for information that is actively in use or which must be maintained over a short interval (Baddeley, 2003; Cowan, 2001). One concern of WM researchers has been to specify how the constituent features of objects are integrated in visual WM into coherent internal representations of the external objects (Fougnie, Asplund, & Marois, 2010; Luck & Vogel, 1997; Treisman, 1988; Wheeler & Treisman, 2002). This study is primarily focused on the issue of whether there is a cost to processing (encoding, storing, and/or retrieving) stimuli for which there is a high feature load. In an influential study, Luck and Vogel manipulated feature load by varying the number of task-relevant features of the stimulus objects. Their finding was that no loss in accuracy resulted from an increase in feature load. We are following up on this result due to a number of results in the literature that find an effect of feature load on accuracy (Alvarez & Cavanagh, 2004; Cowan, Blume, & Saults, 2013; Delvenne & Bruyer, 2004; Fougnie et al., 2010; Oberauer & Eichenberger, 2013; Wheeler & Treisman, 2002). In this study, we will use the change-detection paradigm to measure our participants’ memory abilities (Luck & Vogel, 1997; Wheeler & Treisman, 2002). In the changedetection paradigm, participants are presented with a sample array of visual objects which must be retained in memory for a brief interval before a test array (or sometimes a single test object) is presented. The participant is required to respond to the test array by indicating whether or not anything has changed between the sample array and the test array. We are Address correspondence to: Kyle O. Hardman, Department of Psychological Sciences, University of Missouri, Columbia, MO 65211. kh832@mail.missouri. edu. Phone: 541-646-6857. HHS Public Access Author manuscript J Exp Psychol Learn Mem Cogn. Author manuscript; available in PMC 2015 April 01. Published in final edited form as: J Exp Psychol Learn Mem Cogn. 2015 March ; 41(2): 325–347. doi:10.1037/xlm0000031. A uhor M anscript
3D Reconstruction from Multiple Videos in Real Environments

Summary. We propose an advanced visual hull technique to compensate for outliers using the reliabilities of the silhouettes. The proposed method consists of a background subtraction technique using multiple thresholds and a reliability-based shape-from-silhouette algorithm. They are connected by the intra-/inter-silhouette reliabilities to compensate for carving errors from defective segmentation or partial occlusion which may occur in real environments. In final view rendering, we use a cinematographic camera control system and an ARToolkit to control virtual cameras.
A New Automated Design Method Based on Machine Learning for CMOS Analog Circuits

ABSTRACT A new simulation based automated CMOS analog circuit design method which applies a multi-objective non-Darwinian-type evolutionary algorithm based on Learnable Evolution Model (LEM) is proposed in this article. The multi-objective property of this automated design of CMOS analog circuits is governed by a modified Strength Pareto Evolutionary Algorithm (SPEA) incorporated in the LEM algorithm presented here. LEM includes a machine learning method such as the decision trees that makes a distinction between high- and low-fitness areas in the design space. The learning process can detect the right directions of the evolution and lead to high steps in the evolution of the individuals. The learning phase shortens the evolution process and makes remarkable reduction in the number of individual evaluations. The expert designer’s knowledge on circuit is applied in the design process in order to reduce the design space as well as the design time. The circuit evaluation is made by HSPICE simulator. In order to improve the design accuracy, bsim3v3 CMOS transistor model is adopted in this proposed design method. This proposed design method is tested on three different operational amplifier circuits. The performance of this proposed design method is verified by comparing it with the evolutionary strategy algorithm and other similar methods.
Micro-focused MHz pink beam for time-resolved X-ray emission spectroscopy.

The full radiation from the first harmonic of a synchrotron undulator (between 5 and 12 keV) at the Advanced Photon Source is microfocused using a stack of beryllium compound refractive lenses onto a fast-moving liquid jet and overlapped with a high-repetition-rate optical laser. This micro-focused geometry is used to perform efficient nonresonant X-ray emission spectroscopy on transient species using a dispersive spectrometer geometry. The overall usable flux achieved on target is above 1015 photons s-1 at 8 keV, enabling photoexcited systems in the liquid phase to be tracked with time resolutions from tens of picoseconds to microseconds, and using the full emission spectrum, including the weak valence-to-core signal that is sensitive to chemically relevant electronic properties.
Analytic Study Of Load Balancing Techniques Using Tool Cloud Analyst.

Cloud computing, as of today has boomed the use of internet services and has enhanced the use of network services where the capability of one node can be utilized by other nodes. Central to the architecture is SoA and IS which raises a big question on performance and complexity. To properly manage the resources of the service provider we require balancing the load of the jobs that are submitted to the service provider. Load balancing is required as we don’t want one centralized server’s performance to be degraded. A lot of algorithms have been proposed to do this task. In this paper we present a comparison of various policies utilized for load balancing using a tool called cloud analyst.
Onsager vortex formation in Bose-Einstein condensates in two-dimensional power-law traps

We study computationally dynamics of quantised vortices in two-dimensional superfluid Bose-Einstein condensates confined in highly oblate power-law traps. We have found that the formation of large scale Onsager vortex clusters prevalent in steep-walled traps is suppressed in condensates confined by harmonic potentials. However, the shape of the trapping potential does not appear to adversely affect the evaporative heating efficiency of the vortex gas. Instead, the suppression of Onsager vortex formation in harmonic traps can be understood in terms of the energy of the vortex configurations. Furthermore, we find that the vortex-antivortex pair annihilation that underpins the vortex evaporative heating mechanism requires the interaction of at least three vortices. We conclude that experimental observation of Onsager vortices should be the most apparent in flat or inverted-bottom traps.
Performance analysis and optimization of parallel Best-First Search algorithms on multicore and cluster of multicore

Since the emergence of clusters, multicore processors and clusters of multicore machines, researchers and developers have faced the challenge of parallelizing different kinds of applications in order to take advantage of the computing power and/or the accumulated memory that these architectures provide. In the area of Artificial Intelligence, heuristic search algorithms are used as the basis to solve combinatorial optimization problems, such as: optimal route planning, robot navigation, optimal sequence alignments, among others (Russel & Norvig, 2003). One of the most widely used heuristic search algorithms for that purpose is A* (Hart, et al., 1968), a variant of Best-First Search, which requires high computing power and a large amount of memory. Consequently, during the last decades, the development of the parallel Best-First Search algorithms has been promoted which, in particular, may benefit from the parallel architectures mentioned formerly. The contribution of the thesis is the development of two parallel Best-First Search algorithms, one that is suitable for execution on shared-memory machines (multicore), and another one that is suitable for execution on distributed memory machines (cluster). The former is based on the adaptation of the HDA* (Hash Distributed A*) algorithm for multicore machines proposed by (Burns et al., 2010), while the latter is based on the HDA* (Hash Distributed A*) algorithm proposed by (Kishimoto, et al., 2013). The implemented algorithms incorporate parameters and/or techniques that improve their performance, with respect to the original algorithms proposed by the authors mentioned above. Additionally, a comparison of the performance achieved and the memory consumed by both algorithms, when they are run on a multicore machine, is presented. These results show that a benefit would be obtained by converting HDA* into a hybrid application, that uses programming tools for shared and distributed memory, when the underlying architecture is a cluster of multicore, and therefore the bases for this hybrid algorithm are established.
Entropy of extremal black holes: Horizon limits through charged thin shells in a unified approach

Using a unified approach, we study the entropy of extremal black holes through the entropy of an electrically charged thin shell. We encounter three cases in which a shell can be taken to its own gravitational or horizon radius and become an extremal spacetime. In case 1, we use a nonextremal shell, calculate all the thermodynamic quantities including the entropy, take it to the horizon radius, and then take the extremal limit. In case 2, we take the extremal limit and the horizon radius limit simultaneously; i.e., as the shell approaches its horizon radius, it also approaches extremality. In case 3, we take first an extremal shell, and then take its horizon radius. We find that the thermodynamic quantities, in general, have different expressions in the three different cases. The entropy is the Bekenstein-Hawking entropy S=A+/4 (where A+ is the horizon area) in cases 1 and 2, and in case 3 it can be any well-behaved function of A+. The contributions from the various thermodynamic quantities for the entropy in all three cases are distinct. Indeed, in cases 1 and 2, the limits agree in what concerns the entropy but they disagree in the behavior of all other thermodynamic quantities. Cases 2 and 3 disagree in what concerns the entropy but agree in the behavior of the local temperature and electric potential. Case 2 is, in a sense, intermediate between cases 1 and 3. Our approach sheds light on the extremal black hole entropy issue.
Adaptive logic networks for machine-printed character recognition

In this paper we investigate an approach to the recognition of machine-printed characters using the Adaptive Logic Network (ALNs). Traditional approaches to character recognition such as Nearest Neighbor Classifiers, Template Matching Schemes and Artificial Neural Networks are very computationally expensive. We have implemented a relatively inexpensive recognition module based on ALNs. This type of network achieves recognition results nearly comparable to those obtained using more conventional methods.
Attack prediction model based on static Bayesian game

This paper described an attack prediction model based on static Bayesian game.The model could predict the probabi-lity of attacks or defenses that reasonable attacker or defender would take,in order to maximize their payoff.Thus the result could be used to assist security administrators to configure the network system.It might improve the passive detection to the active protection for the defender.This paper also presented the process of experimental and analysis result for validity of the model.
Design of Wireless Network for Multi-parameter Patient Monitor Based on ZigBee Technology

Objective To study the technology of multi-parameter monitoring system based on ZigBee wireless network.Methods A asynchronous serial interface of IC CC2430 was used to receive the data of multi-parameter patient monitor,and then the ZigBee channels of IC CC2430 was sent to transmit the data to the central monitoring control system.Results The data of eight multi-parameter patient monitors was successfully transmitted to the central control system,and was not interfered by wireless transmission circuits.Conclusion ZigBee wireless network technology can be successfully applied to a wireless network of multi-parameter patient monitor control system.
New watershed segmentation algorithm via marker threshold

An improved marker-controlled watershed segmentation method is proposed to reduce the oversegmentation of watershed algorithm.Firstly,regional minimas in the gradient image are extracted according to the connectivity of adjacent pixels.Then,a maximum entropy threshold method is used to exclude the local minimas generated by the noise and texture.Finally,regarding the modified minimum points as markers,the watershed algorithm is applied to the modified gradients by the markers.The advantages of this method is that makers are extracted adaptively without the need for prior knowledges,which overcomes marker extraction difficulties.Experimental results show that the proposed algorithm can be effective overcomes the over-segmentation problem of watershed.
Computational and Cognitive Approaches to Narratology

Studying narratives is often the best way to gain a good understanding of how various aspects of human information are organized and integratedthe narrator employs specific informational methods to build the whole structure of a narrative through combining temporally constructed events in light of an array of relationships to the narratee and these methods reveal the interaction of the rational and the sensitive aspects of human information. Computational and Cognitive Approaches to Narratology discusses issues of narrative-related information and communication technologies, cognitive mechanism and analyses, and theoretical perspectives on narratives and the story generation process. Focusing on emerging research as well as applications in a variety of fields including marketing, philosophy, psychology, art, and literature, this timely publication is an essential reference source for researchers, professionals, and graduate students in various information technology, cognitive studies, design, and creative fields.
7. On The Notion Of Boundary Conditions In Comparison Principles For Viscosity Solutions

We collect examples of boundary-value problems of Dirichlet and Dirichlet–Neumann type which we found instructive when designing and analysing numerical methods for fully nonlinear elliptic partial differential equations. In particular, our model problem is the Monge–Ampere equation, which is treated through its equivalent reformulation as a Hamilton–Jacobi–Bellman equation. Our examples illustrate how the different notions of boundary conditions appearing in the literature may admit different sets of viscosity sub-and supersolutions. We then discuss how these examples relate to the validity of comparison principles for these different notions of boundary conditions.
Research on Dynamic Task Allocation for MAS Based on Hybrid Genetic and Ant Colony Algorithm

In multi-agent systems(MAS),because of the complexity and the difference between respective agents,the dynamic task allocation for multi-agent systems is a NP-hard combinatorial optimization problem.According to the dynamic characteristic of task allocation,first this paper established the mathematical model of task allocation and the target function.And then the hybrid genetic and ant colony algorithm which possesses the trait such as rapid iteration,positive reaction and distribution,was put forward to achieve combinatorial optimization of task allocation.Finally,the simulation experiments demonstrated that,the algorithm is accomplished in convergence efficiency and solution precision can significantly enhance the performance of MAS.
Accurate initial conditions in mixed Dark Matter--Baryon simulations

We quantify the error in the results of mixed baryon--dark-matter hydrodynamic simulations, stemming from outdated approximations for the generation of initial conditions. The error at redshift 0 in contemporary large simulations, is of the order of few to ten percent in the power spectra of baryons and dark matter, and their combined total-matter power spectrum. After describing how to properly assign initial displacements and peculiar velocities to multiple species, we review several approximations: (1) {using the total-matter power spectrum to compute displacements and peculiar velocities of both fluids}, (2) scaling the linear redshift-zero power spectrum back to the initial power spectrum using the Newtonian growth factor ignoring homogeneous radiation, (3) using longitudinal-gauge velocities with synchronous-gauge densities, and (4) ignoring the phase-difference in the Fourier modes for the offset baryon grid, relative to the dark-matter grid. Three of these approximations do not take into account that dark matter and baryons experience a scale-dependent growth after photon decoupling, which results in directions of velocity which are not the same as their direction of displacement. We compare the outcome of hydrodynamic simulations with these four approximations to our reference simulation, all setup with the same random seed and simulated using Gadget-III.
Cooperative transmitter-receiver arrayed communications

This thesis is concerned with array processing for wireless communications. In particular, cooperation between the transmitter and receiver or between systems is exploited to further improve the system performance. Based on this idea, three technical chapters are presented in this thesis. Initially in Chapter 1, an introduction including array processing, multipleinput multiple-output (MIMO) communication systems and the background of cognitive radio is presented. In Chapter 2, a novel approach for estimating the direction-of-departure (DOD) is proposed using the cooperative beamforming. This proposed approach is featured by its simplicity (beam rotation at the transmitter) and e¤ectiveness (illustrated in terms of channel capacity). Chapter 3 is concerned with integration of spatio-temporal (ST) processing into an antenna array transmitter, given a joint transmitter-receiver system with ST processing at the receiver but spatial-only processing at the transmitter. The transmit ST processing further improves the system performance in convergence, mean-square error (MSE) and bit error rate (BER). In Chapter 4, a basic system structure for radio coexistence problem is proposed based on the concept of MIMO cognitive radio. Cooperation between the licensed radio and the cognitive radio is exploited. Optimisation of the sum channel capacity is considered as the criterion and it is solved using a multivariable water- lling algorithm. Finally, Chapter 5 concludes this thesis and gives suggestions for future work.
Process Development Fine Chemicals From Grams To Kilograms

Thank you for reading process development fine chemicals from grams to kilograms. Maybe you have knowledge that, people have look hundreds times for their chosen readings like this process development fine chemicals from grams to kilograms, but end up in malicious downloads. Rather than reading a good book with a cup of coffee in the afternoon, instead they cope with some infectious bugs inside their laptop.
Exact and Perturbed Friedmann-Lemaitre Cosmologies

In this thesis we first apply the 1+3 covariant description of general relativity to analyze n-fluid Friedmann-Lemaitre (FL) cosmologies; that is, homogeneous and isotropic cosmologies whose matter-energy content consists of n non-interacting fluids. We are motivated to study FL models of this type as observations suggest the physical universe is closely described by a FL model with a matter content consisting of radiation, dust and a cosmological constant. Secondly, we use the 1+3 covariant description to analyse scalar, vector and tensor perturbations of FL cosmologies containing a perfect fluid and a cosmological constant. In particular, we provide a thorough discussion of the behaviour of perturbations in the physically interesting cases of a dust or radiation background.
Parallel Approach for Visual Clustering of Protein Databases

Visualization of a large-scale protein databases may help biologists in discovering similarity between sequences of different organisms. In this article we present a complex approach for visually representing relations between proteins in large scale databases. Our approach includes sequence alignment, mutual distance measurement, clustering and classification of protein sequences. We propose a visual representation method for considered as well-established Pfam 4.0 proteins database. Our objective is to visually reflect the similarity of protein sequences in three dimensional space using non-standard approach.
A Study of Web Service and Agent Technology

In this paper,we discuss primary concept and characteristics of Web Service and Agent technology.Further,we study how to combine Web Service with Agent technology,we use Agent technology as a good way in information processing region and make use of Web Service as a way of communication in the distribution system so as to promote the use of web technologies in information processing region.
Derived category of projectivization and flops

In this paper, we first show a projectivization formula for the derived category $D^b_{\rm coh} (\mathbb{P}(\mathcal{E}))$, where $\mathcal{E}$ is a coherent sheaf on a regular scheme which locally admits two-step resolutions. Second, we show that "flop-flop=twist" results hold for flops obtained by two different Springer-type resolutions of a determinantal hypersurface. This also gives a sequence of higher dimensional examples of flops which present perverse schobers, and provide further evidences for the proposal of Bondal-Kapranov-Schechtman [BKS,KS]. Applications to symmetric powers of curves, Abel-Jacobi maps and $\Theta$-flops following Toda are also discussed.
Research on UML-based Modeling and Analyzing Method for Multi-agent

In the background of robotic soccer simulation ga me , the method of building mapping between agent model and architecture is discuss ed by analyzing theory and architecture model of agent in this paper. By using u nified modeling language (UML) to describe the internal structure and behavior of agent, we unify the work of agent modeling and software modeling. The course about iterative designing the agent of robotic soccer simulation team AFU2004 us ing UML is described.