Miracle-dz/UniFAR-FTUs huggingface dataset:
Part-based set matching for face recognition in surveillance

Face recognition in surveillance is a hot topic in computer vision due to the strong demand for public security and remains a challenging task owing to large variations in viewpoint and illumination of cameras. In surveillance, image sets are the most natural form of input by incorporating tracking. Recent advances in set-based matching also show its great potential for exploring the feature space for face recognition by making use of multiple samples of subjects. In this paper, we propose a novel method that exploits the salient features (such as eyes, noses, mouth) in set-based matching. To represent image sets, we adopt the affine hull model, which can general unseen appearances in the form of affine combinations of sample images. In our proposal, a robust part detector is first used to find four salient parts for each face image: two eyes, nose, and mouth. For each part, we construct an affine hull model by using the local binary pattern histograms of multiple samples of the part. We also construct an affine model for the whole face region. Then, we find the closest distance between the corresponding affine hull models to measure the similarity between parts/face regions, and a weighting scheme is introduced to combine the five distances (four parts and the whole face region) to obtain the final distance between two subjects. In the recognition phase, a nearest neighbor classifier is used. Experiments on the public ChokePoint dataset and our dataset demonstrate the superior performance of our method.
Target detection with local discriminant bases and wavelets

A local discrimination basis is selected among the possible wavelet packet bases in order to create a two-class classifier for high dimensional signals. We use the classifier for target detection in images and signals. The position of the target is also determined. A method invariant to the localization of the target in the analyzed image is developed in order to reduce the time complexity of the algorithm. We apply the method on mine detection in sonar images.
Single-Molecule Spectroscopy of Conjugated Polymers

The molecular structure, photochemistry, and device physics of conjugated polymers have been investigated by single-molecule spectroscopy (SMS), using the unique ability of this technique to unravel complex spectra and dynamics. Surprisingly efficient and directional electronic energy funneling was observed for conjugated polymer molecules due to highly ordered conformations. Furthermore, recent studies on the SMS of conjugated polymers embedded in electronic devices demonstrate that SMS is a powerful tool for studying the photophysics and charge-transfer processes of conjugated polymers, giving new insights into the complex interactions among excited and charged species that exist in a device environment.
Training speakers of indigenous languages of Latin America at a US university

This article is published under a Creative Commons License CC-BY-NC (Attribution-NonCommercial). The licence permits users to use, reproduce, disseminate or display the article provided that the author is attributed as the original creator and that the reuse is restricted to non-commercial purposes i.e. research or educational use. See http://creativecommons.org/licenses/by-nc/4.0/ ______________________________________________________
Listening to geophysics: Audio processing tools for geophysical data analysis and interpretation

Sensitivity for music is a diffuse property of the human brain. When we listen to music, the entire brain is active. In particular, the auditory cortex has connections to the frontal lobe of the brain where many of our capabilities for abstraction and inference are located. A widely accepted idea (although it is unproven) is that humans have an inborn capacity to process music. David Huron highlighted the adaptive advantage of having a mind able to recognize sound patterns and to extract complex significances from a heterogeneous flux of sounds arriving from the environment (Huron, 1991). Probably our ability to recognize complex sound patterns is one of the results of natural evolution of humans9 cognitive capabilities (Ball, 2010). These concepts suggest the following idea: we could use complex sounds (and music in particular), and not only images, for geophysical data analysis, interpretation, and integration. An advantage to this could derive from the fact that sounds have many physical, perceptive, psychological, and cultural “dimensions”: this implies an expanded range of possibilities for analyzing and interpreting geophysical signals transformed into sounds. […] Human sensitivity for music (and for sounds in general) is nowadays supported by advanced technology and by many formats and informatics9 protocols used in digital music (such as wav, mp3, MIDI). These allow easy sound manipulation, analysis, and integration. In particular, the MIDI protocol links heterogeneous information through multiple types of media. There is an additional reason why geophysical data analysis/interpretation could be performed in the domain of sounds and music: the nature of several types of geophysical signals, like seismic data, is closer to the physics of sounds than to the physics of images. These ideas have been investigated (partially) by other authors (Benioff, 1953; Speeth, 1961; Hayward, 1994; Kilb et al., 2012; Peng et al., 2012). In this article, I expand them by proposing a new approach based on exploring new interesting connections between geosciences and the most recent technological innovations in the domain of digital music.
Rejoinder: A Model for Studying Display Methods of Statistical Graphics

The comments of the discussants reflect a thorough knowledge of visual perception and add substance to the issues raised in the article. This speaks well of the ability of a new journal to attract researchers in vision, bringing greater depth to the important area of graphical perception. Because the journal sits at the interface between computing and statistics, I will use the e-mail style of comment and response, but showing the comments in italics rather than the usual ">" at the beginning of each line.
Word Sense Disambiguation and Text Segmentation Based on Lexical Cohesion

In this paper, we describe how word sense ambiguity can be resolved with the aid of lexical cohesion. By checking lexical cohesion between the current word and lexical chains in the order of the salience, in tandem with generation of lexical chains, we realize incremental word sense disambiguation based on contextual information that lexical chains, reveal. Next, we describe how segment boundaries of a text can be determined with the aid of lexical cohesion. We can measure the plausibility of each point in the text as a segment boundary by computing a degree of agreement of the start and end points of lexical chains.
of Vitualization Domain in User Level Virtualization

In this paper, we proposed new virtualization technology that is more convenient and stable in local computing environment, then found technique elements need to desktop virtualization which is based on clients in various virtualization technologies. After running excution of process explorer utility in user level virtualization and VMWare, we found memory capacity that is used 30.1MB in VMWare and 16.6MB in user level virtualization respectively to compare private bytes each of process. We found no significant difference of CPU utilization which is executed application program in local computing environment and user domain with user level virtualization. In this result, proposed vitualization technology is able to minimize performance degradation of local computing envrionment
Keyword-spotting in noisy continuous speech using word pattern vector subabstraction and noise immunity learning

Noise immunity learning, previously proposed by the authors (1991) for isolated word recognition in noisy environments, is extended to keyword spotting in noisy continuous speech. The powerful features of the noise immunity keyword-spotting method are keyword spotting based on the multiple similarity (MS) method for reliable keyword detection, noise immunity learning for greater robustness in recognition of spontaneous or noisy speech, and word pattern vector subabstraction to represent noisy keyword patterns from different viewpoints. Integrating the spotting results obtained by different kinds of subabstracted word pattern vectors significantly improved the performance of the keyword spotting. A system to spot 30 keywords currently runs in real-time on a workstation with two accelerators. The spotted keywords are fed into a keyword sequence LR parser for spontaneous speech understanding. <<ETX>>
Effect of different sampling rates and feature vector sizes on speech recognition performance

We conduct a systematic study to evaluate the effect of the sampling rate and feature vector size on the performance of a hidden Markov model (HMM) based speech recognizer. We investigate the use of the following two types of features: linear prediction (LP) derived cepstral coefficients (LPCC) and Mel frequency cepstral coefficients (MFCC). We demonstrate that for the LPCC front-end, the optimum sampling rate and feature vector size are 12 kHz and 14, respectively. We also show that for different sampling rates, the accuracy peaks at different sizes of the feature vector. For the MFCC front-end, the optimum feature vector size and sampling rate are 14 and 14 kHz, respectively.
Automatic blemish detection in liquid crystal flat panel displays

Visual defects sometimes occur during the manufacturing of flat panel liquid crystal displays (LCDs). One class of defects includes a variety of blemishes variously called stain (English), mura (Japanese) or alluk (Korean). These blemishes appear as low contrast, non-uniform brightness regions, typically larger than single pixels. They are caused by a variety of factors such as non-uniformity distributed liquid crystal material and foreign particles within the panel. Such blemishes cannot be repaired. Automatic inspection systems, designed for pixel and line defect detection, have had difficulty accurately detecting and quantifying LCD blemishes. At present, most blemish detection is performed by human inspectors. This paper describes a recently developed automatic inspection system, which reliably detects, quantifies and classifies LCD blemishes in the presence of single pixel and line pixel defects that tend to obscure the subtle blemishes. The algorithm underlying this system, called MuraLookTM, uses conventional image processing operators such as convolutional filtering, morphological filtering and blob shape analysis under region-of-interest control in a novel combination to systematically separate each of over twenty different blemish patterns. Strength measures for each class of blemish are used under human operator control to grade each blemish as pass or fail. The paper discusses various types of defects in LCD panels and relates them to the MuraLook system defect class patterns. The architecture of the MuraLook defect detection system is described.
A study of test oracle for application interface testing of distributed system

The application interface testing is an important part of automated software testing of distributed system. It is based on network data which is produced when the distributed system is running. It is used to verify whether the network data is correctly exchanged. In this paper firstly we design test oracle for application interface testing of distributed system. Test oracle includes two parts: oracle information and oracle procedure. Oracle information represents expected output while oracle procedure compares the expected output with the actual output. Test cases need to be decided whether their operating results are correct by test oracle. And then, four types of test oracle are designed and divided according to the range of oracle information and the strategy of oracle procedure. Through the experiment, we can see that the choice of test oracle will seriously affect the efficiency and cost of software testing. At last, some suggestion is given about how to design test oracle in the software test.
Prosody, phonology and parsing in closure ambiguities

Abstract Any coherent theory of speech comprehension must account for the ways in which different information sources are combined in the analysis and interpretation of the spoken language input. In this paper, we investigate the relationship primarily of syntactic structure with prosodic and phonological information. In particular, we consider distinctions between early and late closure sentences, in terms both of intonational phrasing and of stress placement on so-called “stress shift” items such as Hong Kong. In previous work, we have found a high incidence of early stress in the late closure context, as in “… Hong Kong problems…”, and of late stress in the early closure context, as in “… Hong Kong, problems…” In the experimental work reported here, we find that stress placement in stress-shift items can be utilised by listenen in on-line comprehension, as reflected in patterns of latencies in a cross-modal naming task. However, shifted stress is not used as a structural cue in cases where it can be mo.
Étude des mécanismes de perturbation membranaire de peptides amphiphiles par spectroscopies de RMN à l'état solide et infrarouge

This thesis is related to the détermination of the membrane perturbation mechanisms of 14 and 21 amino acid amphipathic synthetic peptides by solid-state NMR and infrared spectroscopies. Previous studies hâve shown that the 14and 21-mer peptides exhibit membrane activities similar to those observed for natural antimicrobial peptides and their related analogues. To better understand the type of interactions that are involved in the modes of membrane perturbation of the 14and 21 -mer peptides, and then to plan the design and synthesis of synthetic peptides with sélective antimicrobial activity, we hâve studied the interaction between the peptides and a variety of model membranes. The types of model membranes used in thèse studies are zwitterionic and anionic multilamellar vesicles, oriented bilayers stacked between glass plates and bicelles. We first investigated the effects of the 14and 21-mer peptides on the conformation of polar headgroups and orientational order of lipid acyl chains by phosphorus-31 and deuterium NMR spectroscopy. The results reveal that the 14and 21-mer model peptides perturb to a greater extent the polar région of phospholipid bilayers, and to a lesser extent the lipid hydrophobic acyl chains. Nitrogen-15 NMR results indicate that the 14and 21-mer peptides réside at the surface of bilayers stacked between glass plates. Also, intermolecular heteronuclear distance measurements confirm the proximity of the 14-mer peptide to DMPC lipid polar headgroups. We hâve also studied the membrane interaction and rotational diffusion of the 21mer peptide in interaction with bicelles by P, H and N NMR. The results reveal that the 21-mer peptide stabilizes the bicelle structure and do not show a circular orientational distribution in the bicelle planar région. Finally, the 21-mer peptide dynamics has been studied by C NMR experiments via the analysis of the number and intensity of spinning sidebands, and the results suggest that the 21-mer peptide is immobilized upon binding.
Assigning meaning to programs

Floyd 3 On page 25, the author states “this fact offers the possibility of automatic verification of programs, the programmer merely tagging entrances and one edge in each innermost loop; the verifying program would extend the interpretation and verify it, if possible, by mechanical theorem-proving techniques. ” Give a brief overview of the state of formal verification (yes, you can just Google this). You may also find it interesting to look at this Digital Library article.
Fine-Grained Controllable Delegation Authorization Model Based on Trustworthiness

A fine-grained controllable delegation authorization model (FCDAM) suitable for open environments is presented. It integrates the merits of both RBAC (role based access control) and role-based trust management and can effectively control the propagation of permissions of different sensitivity levels in roles. An approach for assigning trustworthiness thresholds to permissions in local access control policy is discussed. The RT0 framework is extended to support trustworthiness and the algorithm of calculating the values of trustworthiness of entities in the extended framework is proposed. The usage of the FCDAM model is illustrated through a typical example.
Synthesis and Structure of the One-Dimensional Telluride Cs4Zr3Te16

The compound Cs 4 Zr 3 Te 16 has been synthesized at 900 o C through the reaction of Zr with a Cs 2 Te 3 /Te melt as a reactive flux. The compound crystallizes in the space group C 5 2h -P2 1 /n of the monoclinic system with four formula units in a cell of dimensions a=12.012(3) A, b=18.999(7) A, c=15.264(5) A, β=101.71(2) o , and V=3411(2) A 3 (T=113 K). The structure of Cs 4 Zr 3 Te 16 has been determined from single-crystal X-ray data
Discrete cosine transform JPEG compression vs. 2D JPEG2000 compression: JNDmetrix visual discrimination model image quality analysis

The JPEG2000 compression standard is increasingly a preferred industry method for 2D image compression. Some vendors, however, continue to use proprietary discrete cosine transform (DCT) JPEG encoding. This study compares image quality in terms of just-noticeable differences (JNDs) and peak signal-to-noise ratios (PSNR) between DCT JPEG encoding and JPEG2000 encoding. Four computed tomography and 6 computed radiography studies were compressed using a proprietary DCT JPEG encoder and JPEG2000 standard compression. Image quality was measured in JNDs and PSNRs. The JNDmetrix computational visual discrimination model simulates known physiological mechanisms in the human visual system, including the luminance and contrast sensitivity of the eye and spatial frequency and orientation responses of the visual cortex. Higher JND values indicate that a human observer would be more likely to notice a significant difference between compared images. DCT JPEG compression showed consistently lower image distortions at lower compression ratios, whereas JPEG2000 compression showed benefit at higher compression ratios (>50:1). The crossover occurred at ratios that varied among the images. The magnitude of any advantage of DCT compression at low ratios was often small. Interestingly, this advantage of DCT JPEG compression at lower ratios was generally not observed when image quality was measured in PSNRs. These results suggest that DCT JPEG may outperform JPEG2000 for compression ratios generally used in medical imaging and that the differences between DCT and JPEG2000 could be visible to observers and thus clinically significant.
Simulating brightness temperatures at SSM/I channels in the Mediterranean area

An accurate retrieval of atmospheric and sea surface parameters from spaceborne microwave radiometers requires to validate the radiative forward model capable to simulate the brightness temperatures for known atmospheric and surface conditions. Matching the forward model and the retrieval algorithm to the climatological condition of the area of interest is also essential to obtain better retrieval accuracy. This work focuses on the Mediterranean Sea and aims to set up a consistent and accurate forward model using different sources of geophysical quantities and a large set of SSM/I data for validation purposes.
Active biosonar systems based on multiscale signal representations and hierarchical neural networks

Signal features based on multiresolution short-time Fourier transforms (STFT) and the Morlet wavelet transform (MWT) have been developed to classify echo returns from targets ensonified by simulated dolphin echolocation clicks. Spectrogram features are obtained at different scales of resolution using analysis windows of different sizes. A method of compressing the highly redundant time-scale representations provided by the MWT has been developed based on multiscale edge analysis (MSEA) of wavelet local maxima. Neural networks are used to evaluate the efficacy of the various feature sets for target recognition. Hierarchical neural networks are used to combine different feature sets for improved classification performance.
Degraded documents recognition using pseudo-2D hidden Markov models in gray-scale images

The Pseudo 2D Hidden Markov Model (PHMM), which is an extension of the 1D HMM, has been shown to be an effective approach in recognition of highly degraded and connected text. In this paper, the PHMM is extended to directly recognize poorly-printed gray-level document images. The performance of the system is further enhanced by the N-best hypotheses search, coupled with duration constraint. Experimental results show that the new system has significantly improved the performance when compared to a similar system using threshold binary images as inputs. The recognition rate improves from 97.7% in binary system to 99.9% in gray-level with modified N-best search, over a testing set with similar blur and noise condition as the training set. For a much more degraded testing set, it improves from 89.59% to 98.51%. This also demonstrates the robustness of the proposed system.
Hardware assisted high level debugging (Preliminary Draft)

Hardware assistance has long been used for logic level and functional unit level hardware debugging, as well as for machine language level software debugging. Such hardware assistance includes probes to detect signals, comparators to identify matches with expected patterns, buffers to record selected events, and independent logic and software to analyze and interpret the observed events. It can also include the ability to generate selected signals to stimulate the object being debugged and the ability to isolate it from normal changes so its state can be examined. Through knowledge of the data structures and algorithms used by the operating systems, and the runtime representation, register usage, and code bursts produced by compilers, it is possible to take advantage of such hardware assistance in high-level debugging. High level debugging here refers to debugging in terms of abstractions supported by the operating system and programming languages, as well as user defined abstractions built on top of these.
Template‐Based Reconstruction of Surface Mesh Animation from Point Cloud Animation

In this paper, we present a method for reconstructing a surface mesh animation sequence from point cloud animation data. We mainly focus on the articulated body of a subject — the motion of which can be roughly described by its internal skeletal structure. The point cloud data is assumed to be captured independently without any inter‐frame correspondence information. Using a template model that resembles the given subject, our basic idea for reconstructing the mesh animation is to deform the template model to fit to the point cloud (on a frame‐by‐frame basis) while maintaining inter‐frame coherence. We first estimate the skeletal motion from the point cloud data. After applying the skeletal motion to the template surface, we refine it to fit to the point cloud data. We demonstrate the viability of the method by applying it to reconstruct a fast dancing motion
Can a robot deceive humans

In the present study, we investigated whether a robot is able to deceive a human by producing a behavior against him/her prediction. A feeling of being deceived by a robot would be a strong indicator that the human treat the robot as an intentional entity. We conducted a psychological experiment in which a subject played Darumasan ga Koronda, a Japanese children's game, with a robot. A main strategy to deceive a subject was to make his/her mind believe that the robot is stupid so as not to be able to move quickly. The experimental result indicated that unexpected change of a robot behavior gave rise to an impression of being deceived by the robot.