Miracle-dz/UniFAR-FTUs huggingface dataset:
Are Face and Object Recognition Independent? A Neurocomputational Modeling Exploration

Are face and object recognition abilities independent? Although it is commonly believed that they are, Gauthier et al. [Gauthier, I. , McGugin, R. W. , Richler, J. J., Herzmann, G. , Speegle, M. , & VanGulick, A. E. Experience moderates overlap between object and face recognition, suggesting a common ability. Journal of Vision, 14, 7, 2014] recently showed that these abilities become more correlated as experience with nonface categories increases. They argued that there is a single underlying visual ability, v, that is expressed in performance with both face and nonface categories as experience grows. Using the Cambridge Face Memory Test and the Vanderbilt Expertise Test, they showed that the shared variance between Cambridge Face Memory Test and Vanderbilt Expertise Test performance increases monotonically as experience increases. Here, we address why a shared resource across different visual domains does not lead to competition and to an inverse correlation in abilities? We explain this conundrum using our neurocomputational model of face and object processing [“The Model”, TM, Cottrell, G. W. , & Hsiao, J. H. Neurocomputational models of face processing. In A. J. Calder, G. Rhodes, M. Johnson, & J. Haxby (Eds.), The Oxford handbook of face perception. Oxford, UK: Oxford University Press, 2011]. We model the domain general ability v as the available computational resources (number of hidden units) in the mapping from input to label and experience as the frequency of individual exemplars in an object category appearing during network training. Our results show that, as in the behavioral data, the correlation between subordinate level face and object recognition accuracy increases as experience grows. We suggest that different domains do not compete for resources because the relevant features are shared between faces and objects. The essential power of experience is to generate a “spreading transform” for faces (separating them in representational space) that generalizes to objects that must be individuated. Interestingly, when the task of the network is basic level categorization, no increase in the correlation between domains is observed. Hence, our model predicts that it is the type of experience that matters and that the source of the correlation is in the fusiform face area, rather than in cortical areas that subserve basic level categorization. This result is consistent with our previous modeling elucidating why the FFA is recruited for novel domains of expertise [Tong, M. H. , Joyce, C. A. , & Cottrell, G. W. Why is the fusiform face area recruited for novel categories of expertise? A neurocomputational investigation. Brain Research, 1202, 14–24, 2008].
Cyclic pattern kernels for predictive graph mining

With applications in biology, the world-wide web, and several other areas, mining of graph-structured objects has received significant interest recently. One of the major research directions in this field is concerned with predictive data mining in graph databases where each instance is represented by a graph. Some of the proposed approaches for this task rely on the excellent classification performance of support vector machines. To control the computational cost of these approaches, the underlying kernel functions are based on frequent patterns. In contrast to these approaches, we propose a kernel function based on a natural set of cyclic and tree patterns independent of their frequency, and discuss its computational aspects. To practically demonstrate the effectiveness of our approach, we use the popular NCI-HIV molecule dataset. Our experimental results show that cyclic pattern kernels can be computed quickly and offer predictive performance superior to recent graph kernels based on frequent patterns.
Transparent dynamic binding with fault-tolerant cache coherence protocol for chip multiprocessors

Aggressive technology scaling causes chip multiprocessors increasingly error-prone. Core-level fault-tolerant approaches bind two cores to implement redundant execution and error detection. However, along with more cores integrated into one chip, existing static and dynamic binding schemes suffer from the scalability problem when considering the violation effects caused by external write operations. In this paper, we present a transparent dynamic binding (TDB) mechanism to address the issue. Learning from static binding schemes, we involve the private caches to hold identical data blocks, thus we reduce the global masters-lave consistency maintenance to the scale of the private caches. With our fault-tolerant cache coherence protocol, TDB satisfies the objective of private cache consistency, therefore provides excellent scalability and flexibility. Experimental results show that, for a set of parallel workloads, the overall performance of our TDB scheme is very close to that of baseline fault-tolerant systems, outperforming dynamic core coupling by 9.2%, 10.4%, 18% and 37.1% when considering 4, 8, 16 and 32 cores respectively.
A VLSI DBSCAN processor composed as an array of micro agents having self-growing interconnects

A DBSCAN (Density Based Spatial Clustering of Applications with Noise) processor has been developed. The original DBSCAN algorithm has been divided into two parts: the self-growing process and the labeling process for efficient VLSI hardware implementation. An array of micro agents having self-growing interconnects has been developed to achieve full pixel-parallel processing for self-growing as well as for labeling by single clock-cycle connection. A proof-of-concept chip was designed in a 0.18-μm CMOS technology. From the simulation results, a frame rate of 12K fps is demonstrated even for the worst case processing of an image of 80 × 80 pixels at an operating frequency of 100 MHz.
Detection of Alicyclobacillus spp. in Fruit Juice by Combination of Immunomagnetic Separation and a SYBR Green I Real-Time PCR Assay

An approach based on immunomagnetic separation (IMS) and SYBR Green I real-time PCR (real-time PCR) with species-specific primers and melting curve analysis was proposed as a rapid and effective method for detecting Alicyclobacillus spp. in fruit juices. Specific primers targeting the 16S rDNA sequences of Alicyclobacillus spp. were designed and then confirmed by the amplification of DNA extracted from standard strains and isolates. Spiked samples containing known amounts of target bacteria were used to obtain standard curves; the correlation coefficient was greater than 0.986 and the real-time PCR amplification efficiencies were 98.9%- 101.8%. The detection limit of the testing system was 2.8×101 CFU/mL. The coefficient of variation for intra-assay and inter-assay variability were all within the acceptable limit of 5%. Besides, the performance of the IMS-real-time PCR assay was further investigated by detecting naturally contaminated kiwi fruit juice; the sensitivity, specificity and accuracy were 91.7%, 95.9% and 95.3%, respectively. The established IMS-real-time PCR procedure provides a new method for identification and quantitative detection of Alicyclobacillus spp. in fruit juice.
Autoencoding Blade Runner: Reconstructing Films with Artificial Neural Networks

In this paper, the authors explain how they created Blade Runner—Autoencoded, a film made by training an autoencoder—a type of generative neural network—to recreate frames from the film Blade Runner. The autoencoder is made to reinterpret every individual frame, reconstructing it based on its memory of the film. The result is a hazy, dreamlike version of the original film. The authors discuss how the project explores the aesthetic qualities of the disembodied gaze of the neural network and describe how the autoencoder is also capable of reinterpreting films it has not been trained on, transferring the visual style it has learned from watching Blade Runner (1982).
Optimizing stable mode-locked operation of Yb-doped fiber laser

We report on a novel simple configuration of an Yb-doped fiber laser cavity comprising only Yb-doped fiber and a saturable absorber element. Numerical results show that stable mode-locked operation does exist in such a laser cavity in limited range of parameters. The conditions to obtain stable pulses are investigated as a function of the Yb-fiber bandwidth, length, and gain coefficient. The temporal and spectral behavior of the femtosecond pulses are also studied for different input parameters. The instability dynamics of the mode-locked pulse is also elucidated.
HMM-based speech synthesis adaptation using noisy data: Analysis and evaluation methods

This paper investigates the role of noise in speaker-adaptation of HMM-based text-to-speech (TTS) synthesis and presents a new evaluation procedure. Both a new listening test based on ITU-T recommendation 835 and a perceptually motivated objective measure, frequency-weighted segmental SNR, improve the evaluation of synthetic speech when noise is present. The evaluation of voices adapted with noisy data show that the noise plays a relatively small but noticeable role in the quality of synthetic speech: Naturalness and speaker similarity are not affected in a significant way by the noise, but listeners prefer the voices trained from cleaner data. Noise removal, even when it degrades natural speech quality, improves the synthetic voice.
Crack growth and development of fracture zones in plain concrete and similar materials

A calculation model (the Fictitious Crack Model), based on fracture mechanics and the finite element method, 1s presented. In the model the fracture zone in front of a crack is represented by a fictitious crack that 1s able to transfer stress. The stress transferring capability of the fictitious crack normally decreases when the crack width increases. The applicability of linear elastic fracture mechanics to concrete and similar materials is analysed by use of the Fictitious Crack Model. It" Is found that linear elastic fracture mechanics 1s too dependent on, among other things, specimen dimensions to be useful as a fracture approach, unless the dimensions, for concrete structures, are in order of meters. The usefulness of the J-integral, the COD-approach and the R-curve analysis is also found to be very limited where cementitious materials are concerned. The complete tensile stress-strain curve is introduced as a fracture mechanical parameter. The curve can be approximatively determined if the tensile strength, the Young's modius and the fracture energy are known. Su1table~lest methods Tor determining" TRise~~/'Voerties are presented and test results are reported for a number of concrete qua! » a. A new tyr * very stiff tensile testing machine Is presented by which it is possible to carry r . itable tensile tests on concrete. The complete tensile stress-strain curves h •«• feen determined for a number of concrete qualities. The thesi' overs a complete system for analysing crack propagation in concrete as it Include* -ealistic material model, a functional calculation model and methods for determiv" «/ the material properties necessary for the calculations. Therefore this work oi r t to be of use as a base for further studies of the fracture process of concrete < i similar materials.
Radial truncations in stellar discs in galaxies

We discuss the possible origin of the radial truncations in stellar discs, using measurements that we presented in an earlier paper. A tentative correlation is found with the de-projected face-on central surface brightness; lower surface brightness discs tend to have a smaller truncation radius in units of scalelength. This and our earlier finding that in smaller spirals the truncation tends to occur at a larger number of scalelengths are best reproduced when the truncation is caused by a constant gas-density threshold on star formation.
Thermal Degradation Kinetics of Poly (vinyl chloride)

The thermal degradation of PVC resin was examined by the thermogravimetric analysis (TGA). The pyrolysis volatile products were analyzed by Fourier transform infrared spectrometer synchronized with TG test (TG-FTIR). Based on the TG results, the kinetics of thermal degradation was studied by Friedman method. The pyrolysis mechanism was discussed also. The results indicate that the pyrolysis process of PVC can be divided into two main stages: 220°C - 380°C and 380°C - 560°C. By the calculation of mass conservation and TG-FTIR results, it can be supposed that not only HCl, but also some unsubstituted aromatics such as benzene were released during the first stage. The comparison of activation energy shows that the second stage exhibited higher activation energy than the first stage. Two activation energy values in the first stage confirm that there arose two reactions in the first stage.
Interactive implicit modeling with hierarchical spatial caching

Complex implicit CSG models can be represented hierarchically as a tree of nodes (the BlobTree) . However, current methods cannot be used to visualize changes made to these models at interactive rates due to the large number of potential field evaluations required. A hierarchical spatial caching technique is presented which accelerates evaluations of the potential function. This method introduces the concept of a caching node inserted into the implicit model tree. Caching nodes store exact potential field values at the vertices of a voxel grid and rely on tri-linear and tri-quadratic reconstruction filters to locally approximate the potential field of a sub-tree. A lazy evaluation scheme is used to avoid expensive pre-computation. Polygonization timings with and without caching are compared for a complex model undergoing manipulation in an interactive modeling tool. An order-of-magnitude improvement in visualization time is achieved for complex implicit models containing thousands of primitives.
Videorealistic talking faces: a morphing approach

We present a method for the construction of a videorealistic text-to-audiovisual speech synthesizer. A visual corpus of a subject enunciating a set of key words is initially recorded. The key words are chosen so that they collectively contain most of the American English viseme images, which are subsequently identified and extracted from the data by hand. Next, using optical flow methods borrowed from the computer vision literature, we compute realistic transitions between every viseme to every other viseme. The images along these transition paths are generated using a morphing method. Finally, we exploit phoneme and timing information extracted from a text-tospeech synthesizer to determine which viseme transitions to use, and the rate at which the morphing process should occur. In this manner, we are able to synchronize the visual speech stream with the audio speech stream, and hence give the impression of a videorealistic talking face.
Risk analysis for intellectual property litigation

We introduce the problem of risk analysis for Intellectual Property (IP) lawsuits. More specifically, we focus on estimating the risk for participating parties using solely prior factors, i. e. , historical and concurrent behavior of the entities involved in the case. This work represents a first step towards building a comprehensive legal risk assessment system for parties involved in litigation. This technology will allow parties to optimize their case parameters to minimize their own risk, or to settle disputes out of court and thereby ease the burden on the judicial system. In addition, it will also help U.S. courts detect and fix any inherent biases in the system. We model risk estimation as a relational classification problem using conditional random fields [6] to jointly estimate the risks of concurrent cases. We evaluate our model on data collected by the Stanford Intellectual Property Litigation Clearinghouse, which consists of over 4,200 IP lawsuits filed across 88 U.S. federal districts and ranging over 8 years, probably the largest legal data set reported in data mining research. Despite being agnostic to the merits of the case, our best model achieves a classification accuracy of 64%, 22% (relative) higher than the majority-class baseline.
Recognizing Algorithms Using Language Constructs, Software Metrics and Roles of Variables: An Experiment with Sorting Algorithms

Program comprehension (PC) is a research field that has been extensively studied from different points of view, including human program understanding and mental models, automated program understanding, etc. In this paper, we discuss algorithm recognition (AR) as a subfield of PC and explain their relationship. We present a method for automatic AR from Java source code. The method is based on static analysis of program code including various statistics of language constructs, software metrics, as well as analysis of roles of variables in the target program. In the first phase of the method, a number of different implementations of the supported algorithms are analyzed and stored in the knowledge base of the system as learning data, and in the second phase, previously unseen algorithms are recognized using this information. We have developed a prototype and successfully applied the method for recognition of sorting algorithms. This process is explained in the paper along with the experiment we have conducted to evaluate the performance of the method. Although the method, at its current state, is still sensitive to changes made to target algorithms, the encouraging results of the experiment demonstrate that it can be further developed to be used as a PC method in various applications, as an example, in automatic assessment tools to check the algorithms used by students, the functionality that is currently missing from these tools.
Algorithms for Enhanced Inter-Cell Interference Coordination (eICIC) in LTE HetNets

The success of LTE heterogeneous networks (HetNets) with macrocells and picocells critically depends on efficient spectrum sharing between high-power macros and low-power picos. Two important challenges in this context are: 1) determining the amount of radio resources that macrocells should offer to picocells, and 2) determining the association rules that decide which user equipments (UEs) should associate with picos. In this paper, we develop a novel algorithm to solve these two coupled problems in a joint manner. Our algorithm has provable guarantee, and furthermore, it accounts for network topology, traffic load, and macro-pico interference map. Our solution is standard compliant and can be implemented using the notion of Almost Blank Subframes (ABS) and Cell Selection Bias (CSB) proposed by LTE standards. We also show extensive evaluations using RF plan from a real network and discuss self-optimized networking (SON)-based enhanced inter-cell interference coordination (eICIC) implementation.
Improving route discovery in on-demand routing protocols using local topology information in MANETs

Most existing routing protocols proposed for MANETs use flooding as a broadcast technique for the propagation of network control packets; a particular example of this is the dissemination of route requests (RREQs), which facilitate route discovery. In flooding, each mobile node rebroadcasts received packets, which, in this manner, are propagated network-wide with considerable overhead. This paper improves on the performance of existing routing protocols by reducing the communication overhead incurred during the route discovery process by implementing a new broadcast algorithm called the adjusted probabilistic flooding on the Ad-Hoc on Demand Distance Vector (AODV) protocol. AODV [3] is a well-known and widely studied algorithm which has been shown over the past few years to maintain an overall lower routing overhead compared to traditional proactive schemes, even though it uses flooding to propagate RREQs. Our results, as presented in this paper, reveal that equipping AODV with fixed and adjusted probabilistic flooding, instead, helps reduce the overhead of the route discovery process whilst maintaining comparable performance levels in terms of saved rebroadcasts and reachability as achieved by conventional AODV\@. Moreover, the results indicate that the adjusted probabilistic technique results in better performance compared to the fixed one for both of these metrics
Effect of calcium supplementation on serum cholesterol and blood pressure. A randomized, double-blind, placebo-controlled, clinical trial.

OBJECTIVE To test the effect of daily supplemental calcium on serum total and high-density lipoprotein cholesterol (HDL-C) levels and blood pressure in adults. DESIGN Randomized, double-blind, placebo-controlled clinical trial; adjunct study to a trial of calcium and colon cell proliferation in patients with sporadic adenoma. SETTING Outpatient clinic. PATIENTS A total of 193 men and women, aged 30 to 74 years. INTERVENTION Treatment with 1.0 and 2.0 g/d of elemental calcium vs placebo over a 4-month period for cholesterol determinations and 6 months for blood pressure. MAIN OUTCOME MEASURES Serum total cholesterol and HDL-C levels, systolic and diastolic blood pressure. RESULTS Because there were no apparent differences in responses between the 1.0-g and 2.0-g calcium groups, their data were combined and compared with those of the placebo group. Among all participants, the mean total cholesterol level dropped 0.07 mmol/L (2.9 mg/dL) (1.3%) (P = .43) more, and the mean HDL-C level dropped 0.01 mmol/L (0.4 mg/dL) (1.1%) (P = .71) less in the calcium group than in the placebo group. Among participants without a history of hypercholesterolemia, the mean total cholesterol level dropped 0.18 mmol/L (6.8 mg/dL) (3.3%) (P = .10) and the HDL-C level dropped 0.02 mmol/L (0.6 mg/dL) (1.5%) (P = .61) more in the calcium group than in the placebo group. Among all participants, there was no apparent change in blood pressure until 6 months, when the mean systolic blood pressure dropped 0.8 mm Hg (0.6%) (P = .85) and the mean diastolic blood pressure dropped 0.4 mm Hg (0.5%) (P = .80) more in the calcium group than in the placebo group. CONCLUSIONS There were no substantial or statistically significant effects of calcium supplementation on total cholesterol or HDL-C levels or on blood pressure. There was a suggestion (not statistically significant) of a 0.07 to 0.18 mmol/L (3-7 mg/dL) or 2% to 4% drop in the total cholesterol level, a finding similar to that reported in other studies, which indicates the need for further study.
Development of Plastic Lenses for High-Resolution Phone Camera by Injection-Compression Molding

This study aims to develop a plastic aspheric lens for a 13-megapixel mobile phone camera by injection-compression molding. A mold for injection-compression molding experiments was fabricated with a movable upper plate and four springs. During cavity filling for an aspheric lens with a thickness ratio of 2, a weldline was formed under conventional injection molding, whereas no weldline was formed under injection-compression molding with a compression stroke of 0.3 mm. The flow patterns were in good agreement with the simulation results. The birefringence decreased as the compression stroke increased, and the birefringence produced by injection-compression molding was very low and more uniform compared with that produced by injection molding. In addition, the bulk birefringence of an assembly composed of four plastic lenses was significantly affected by the orientation of the lenses to be mounted.
Paving the Way to a Large-scale Pseudosense-annotated Dataset

In this paper we propose a new approach to the generation of pseudowords, i.e., artificial words which model real polysemous words. Our approach simultaneously addresses the two important issues that hamper the generation of large pseudosense-annotated datasets: semantic awareness and coverage. We evaluate these pseudowords from three different perspectives showing that they can be used as reliable substitutes for their real counterparts.