Miracle-dz/UniFAR-FTUs huggingface dataset:
Moving Target Detection via Efficient ATI-GoDec Approach for Multichannel SAR System

Clutter suppression and ground moving target indication (GMTI) are challenging tasks for multichannel synthetic aperture radar (MC-SAR) systems. In recent years, robust principal component analysis (RPCA), such as the augmented Lagrange multiplier method (ALM) and go decomposition (GoDec) algorithm, has drawn considerable attention for its excellent performance in distinguishing the different parts from a set of correlative database. In this letter, an efficient along-track interferometry GoDec (ATI-GoDec) approach is proposed for GMTI in MC-SAR systems under a strong clutter background. The proposed method can be separated into two sections: the predetection and the postdetection. The predetection by an efficient ATI RPCA method can decrease missing targets, and postdetection with a novel magnitude and phase (M&P) detection has the ability to reduce the false targets. As a result, the proposed method can provide a more robust performance by a comparison to the traditional ATI detection. It can also widen the tolerant values of the preset cardinality and decrease the probability of false alarm compared with the conventional GoDec algorithm. Moreover, the proposed method only takes several iterations to reach the convergence by solving the optimization problem of the RPCA model, which makes it more efficient than the previous RPCA methods. The results by applying the proposed method into a set of real SAR data are consistent with the analysis presented in this letter.
Making a fast curry: push/enter vs. eval/apply for higher-order languages

Higher-order languages that encourage currying are implemented using one of two basic evaluation models: push/enter or eval/apply. Implementors use their intuition and qualitative judgements to choose one model or the other.Our goal in this paper is to provide, for the first time, a more substantial basis for this choice, based on our qualitative and quantitative experience of implementing both models in a state-of-the-art compiler for Haskell.Our conclusion is simple, and contradicts our initial intuition: compiled implementations should use eval/apply.
Distribution of subgraphs of random regular graphs

We obtain the asymptotic distribution of the number of copies of a fixed subgraph H in a random d-regular graph, provided H is strictly balanced and d = d(n) is chosen so that the expected number of copies of H tends to infinity (but not too quickly), and the expected number of copies sharing edges with two other copies is bounded. The proof of asymptotic normality of the distribution uses a method of factorial moments for variables with unbounded means that was recently derived by the authors. © 2007 Wiley Periodicals, Inc. Random Struct. Alg. , 2008
Identifying false friends between closely related languages

In this paper we present a corpus-based approach to automatic identification of false friends for Slovene and Croatian, a pair of closely related languages. By taking advantage of the lexical overlap between the two languages, we focus on measuring the difference in meaning between identically spelled words by using frequency and distributional information. We analyze the impact of corpora of different origin and size together with different association and similarity measures and compare them to a simple frequency-based baseline. With the best performing setting we obtain very good average precision of 0.973 and 0.883 on different gold standards. The presented approach works on non-parallel datasets, is knowledge-lean and language-independent, which makes it attractive for natural language processing tasks that often lack the lexical resources and cannot afford to build them by hand.
Smart, useful, scary, creepy: perceptions of online behavioral advertising

We report results of 48 semi-structured interviews about online behavioral advertising (OBA). We investigated non-technical users' attitudes about and understanding of OBA, using participants' expectations and beliefs to explain their attitudes. Participants found OBA to be simultaneously useful and privacy invasive. They were surprised to learn that browsing history is currently used to tailor advertisements, yet they were aware of contextual targeting. Our results identify mismatches between participants' mental models and current approaches for providing users with notice and choice about OBA. Participants misinterpreted icons intended to notify them about behavioral targeting and expected that they could turn to their browser or antivirus software to control OBA. Participants had strong concerns about data collection, and the majority of participants believed that advertisers collect personally identifiable information. They also misunderstood the role of advertising networks, basing their opinions of an advertising network on that company's non-advertising activities. Participants' attitudes towards OBA were complex and context-dependent. While many participants felt tailored advertising could benefit them, existing notice and choice mechanisms are not effectively reaching users.
Ataxia-Telangiectasia, Mutated (ATM)/Nuclear Factor κ Light Chain Enhancer of Activated B Cells (NFκB) Signaling Controls Basal and DNA Damage-induced Transglutaminase 2 Expression*

Background: Transglutaminase-2 (TG2) is up-regulated in response to stress through an unknown mechanism. Results: Disruption of NFκB subunit p65 or its activator ATM abrogates genotoxin-induced and basal TG2 expression. Conclusion: NFκB/ATM signaling drives TG2 expression, and both molecules are components in TG2-linked drug resistance. Significance: DNA damage response is crucial to understanding cancer development and treatment. Transglutaminase 2 (TG2) is a ubiquitously expressed enzyme that cross-links proteins and its overexpression, linked to a drug resistant phenotype, is commonly observed in cancer cells. Further, up-regulation of TG2 expression occurs during response to various forms of cell stress; however, the molecular mechanisms that drive inducible expression of the TG2 gene (TGM2) require elucidation. Here we show that genotoxic stress induces TG2 expression through the Ataxia-Telangiectasia, Mutated (ATM)/Nuclear Factor κ light chain enhancer of activated B cells (NFκB) signaling pathway. We further document that NFκB is both necessary and sufficient to drive constitutive TG2 expression in cultured cell lines. Additionally, shRNA-mediated knockdown or pharmacological inhibition of the ATM kinase results in reduced constitutive TG2 expression and NFκB transcriptional activity. We document that the NFκB subunit p65 (RelA) interacts with two independent consensus NFκB binding sites within the TGM2 promoter, that mutation of either site or pharmacological inhibition of NFκB reduces TGM2 promoter activity, and genotoxic stress drives heightened association of p65 with the TGM2 promoter. Finally, we observed that knockdown of either p65 or ATM in MDA-MB-468 breast cancer cells expressing recombinant TG2 partially reduces resistance to doxorubicin, indicating that the drug resistance linked to overexpression of TG2 functions, in part, through p65 and ATM. This work establishes a novel ATM-dependent signaling loop where TG2 and NFκB activate each other resulting in sustained activation of NFκB and acquisition of a drug-resistant phenotype.
Embedded 8-bit AES in wireless Bluetooth application

This paper presents an 8-bit AES direct FPGA hardware implementation of CFB/OFB operations without using the Block RAM (BRAM). The 8-bit AES core is then embedded through a microcontroller to interface with Bluetooth wireless for performing encryption or decryption. Two sets of the embedded systems are configured together to experiment the AES operation of the image encryption and decryption through wireless communication achieved the baud rate of 0.23 Megabits per second (Mbps). CFB/OFB operations have two advantages over ECB operation; one is the low area circuit design, and the other is the complete hiding of input patterns in plain image with identical colors. Though CFB/OFB implementation without BRAM has a little larger slice area then the implementation with RAM, yet the non-BRAM in ASIC implementation achieved only 2.2K gates, synthesized using 0. 18μm technology, which is the smallest gate count for the 8-bit ASIC implementation ever proposed.
A comparison of lexical-gustatory and grapheme-colour synaesthesia

This study compares two different profiles of synaesthesia. One group (N = 7) experiences synaesthetic colour and the other (N = 7) experiences taste. Both groups are significantly more consistent over time than control subjects asked to generate analogous associations. For the colour synaesthetes, almost every word elicits a colour photism and there are systematic relationships between the colours generated by words and those generated by graphemes within the word (hence “grapheme-colour” synaesthesia). For the taste synaesthetes, by contrast, some words elicit no synaesthesia at all, and in those words that do, there is no relationship between the taste attributed to the word and the taste attributed to component graphemes. Word frequency and lexicality (word vs. nonword) appear to be critical in determining the presence of synaesthesia in this group (hence “lexical-gustatory” synaesthesia). Moreover, there are strong phonological links (e.g., cinema tastes of “cinnamon rolls”) suggesting that the synaesthetic associations have been influenced by vocabulary knowledge from the semantic category of food. It is argued that different cognitive mechanisms are responsible for the synaesthesia in each group, which may reflect, at least in part, the different geographical locations of the affected perceptual centres in the brain.
1993 International Conference on Parallel Processing Allocation of Parallel Progralns With Time Variant Resource Requirements *

This paper presents an innovcrtiue allocation strategy for parallel programs composed oJ communicating processes whose resource requirements v a q daring program execution. The primary di$erence between this and previous work is ihe incorporation into the ollocotion process of the esfimalion of variation in resource requirenaen! ~ over time. Experimental results are presented $hat complare this model with previous work and indicate ihat this melhod achieves superior aIlocaiion results without any increase in compvtaiional complexity. Results ijtdicate a high correlation between the improvemenl achieved and the degree of process clustering in Ihe parallel pro-
Morphology of the Jaw-Closing Musculature in the Common Wombat (Vombatus ursinus) Using Digital Dissection and Magnetic Resonance Imaging

Wombats are unique among marsupials in having one pair of upper incisors, and hypsodont molars for processing tough, abrasive vegetation. Of the three extant species, the most abundant, the common wombat (Vombatus ursinus), has had the least attention in terms of masticatory muscle morphology, and has never been thoroughly described. Using MRI and digital dissection to compliment traditional gross dissections, the major jaw adductor muscles, the masseter, temporalis and pterygoids, were described. The masseter and medial pterygoid muscles are greatly enlarged compared to other marsupials. This, in combination with the distinctive form and function of the dentition, most likely facilitates processing a tough, abrasive diet. The broad, flat skull and large masticatory muscles are well suited to generate a very high bite force. MRI scans allow more detail of the muscle morphology to be observed and the technique of digital dissections greatly enhances the knowledge obtained from gross dissections.
Design and evaluation of multimodal biometric system with fingerprint and face recognition

Biometric systems are getting popularity since last decade. As per the demand of IT industry, this technology is satisfying authentication and authorization needs. But Unimodal Biometric systems have their own limitations. To overcome the limitations of Unimodal Biometric Systems, we can choose the approach of Multimodal Biometric Systems. In this paper, researchers have given details about Multimodal Biometric system designed and developed to improve success ratio of authentication. They have adapted fingerprint and face recognition methods with match score level fusion. We have tried to identify success ration under various combinations of weights assigned to fingerprint and face match scores.
Linear magnetoresistance in metals: Guiding center diffusion in a smooth random potential

We predict that guiding center (GC) diffusion yields a linear and nonsaturating (transverse) magnetoresistance in 3D metals. Our theory is semiclassical and applies in the regime where the transport time is much greater than the cyclotron period and for weak disorder potentials which are slowly varying on a length scale much greater than the cyclotron radius. Under these conditions, orbits with small momenta along magnetic field B are squeezed and dominate the transverse conductivity. When disorder potentials are stronger than the Debye frequency, linear magnetoresistance is predicted to survive up to room temperature and beyond. We argue that magnetoresistance from GC diffusion explains the recently observed giant linear magnetoresistance in 3D Dirac materials.
The sk-strings method for inferring PFSA

We describe a simple, fast and easy to implement recursive algorithm with four alternate intuitive heuristics for inferring Probabilistic Finite State Automata. The algorithm is an extension for stochastic machines of the k-tails method introduced in 1972 by Biermann and Feldman for non-stochastic machines. Experiments comparing the two are done and benchmark results are also presented. It is also shown that sk-strings performs better than k-tails at least in inferring small automata.
Trade, Patents, and International Technology Diffusion

This paper investigates international technology diffusion through trade and patenting in a sample of 48 countries for the period 1980 - 2000. We divide the sample in three income groups to detect different patterns of technology absorption. Our results show that rich countries benefit from domestic technology and foreign technology embodied in imported capital goods, middle-income countries enjoy technology spillovers from foreign patents and imported capital goods, and poor countries benefit mainly from foreign patents. We find that government policies on intellectual property rights protection and trade openness have large effects on foreign technology spillovers in middle- and low-income countries.
A Modified EPA Method 1623 that Uses Tangential Flow Hollow-fiber Ultrafiltration and Heat Dissociation Steps to Detect Waterborne Cryptosporidium and Giardia spp.

Cryptosporidium and Giardia species are two of the most prevalent protozoa that cause waterborne diarrheal disease outbreaks worldwide. To better characterize the prevalence of these pathogens, EPA Method 1623 was developed and used to monitor levels of these organisms in US drinking water supplies 12. The method has three main parts; the first is the sample concentration in which at least 10 L of raw surface water is filtered. The organisms and trapped debris are then eluted from the filter and centrifuged to further concentrate the sample. The second part of the method uses an immunomagnetic separation procedure where the concentrated water sample is applied to immunomagnetic beads that specifically bind to the Cryptosporidium oocysts and Giardia cysts allowing for specific removal of the parasites from the concentrated debris. These (oo)cysts are then detached from the magnetic beads by an acid dissociation procedure. The final part of the method is the immunofluorescence staining and enumeration where (oo)cysts are applied to a slide, stained, and enumerated by microscopy. Method 1623 has four listed sample concentration systems to capture Cryptosporidium oocysts and Giardia cysts in water: Envirochek filters (Pall Corporation, Ann Arbor, MI), Envirochek HV filters (Pall Corporation), Filta-Max filters (IDEXX, Westbrook, MA), or Continuous Flow Centrifugation (Haemonetics, Braintree, MA). However, Cryptosporidium and Giardia (oo)cyst recoveries have varied greatly depending on the source water matrix and filters used1,14. A new tangential flow hollow-fiber ultrafiltration (HFUF) system has recently been shown to be more efficient and more robust at recovering Cryptosporidium oocystsand Giardia cysts from various water matrices; moreover, it is less expensive than other capsule filter options and can concentrate multiple pathogens simultaneously1-3,5-8,10,11. In addition, previous studies by Hill and colleagues demonstrated that the HFUF significantly improved Cryptosporidium oocysts recoveries when directly compared with the Envirochek HV filters4. Additional modifications to the current methods have also been reported to improve method performance. Replacing the acid dissociation procedure with heat dissociation was shown to be more effective at separating Cryptosporidium from the magnetic beads in some matrices9,13 . This protocol describes a modified Method 1623 that uses the new HFUF filtration system with the heat dissociation step. The use of HFUF with this modified Method is a less expensive alternative to current EPA Method 1623 filtration options and provides more flexibility by allowing the concentration of multiple organisms.
Formant Estimation and Tracking Using Deep Learning

Formant frequency estimation and tracking are among the most fundamental problems in speech processing. In the former task the input is a stationary speech segment such as the middle part of a vowel and the goal is to estimate the formant frequencies, whereas in the latter task the input is a series of speech frames and the goal is to track the trajectory of the formant frequencies throughout the signal. Traditionally, formant estimation and tracking is done using ad-hoc signal processing methods. In this paper we propose using machine learning techniques trained on an annotated corpus of read speech for these tasks. Our feature set is composed of LPC-based cepstral coefficients with a range of model orders and pitch-synchronous cepstral coefficients. Two deep network architectures are used as learning algorithms: a deep feed-forward network for the estimation task and a recurrent neural network for the tracking task. The performance of our methods compares favorably with mainstream LPC-based implementations and state-of-the-art tracking algorithms.
Layout Adjustment and the Mental Map

Abstract Many models in software and information engineering use graph representations; examples are data flow diagrams, state transition diagrams, flow charts, PERT charts, organization charts, Petri nets and entity-relationship diagrams. The usefulness of these graph representations depends on the quality of the layout of the graphs. Automatic graph layout, which can release humans from graph drawing, is now available in several visualization systems. Most automatic layout facilities take a purely combinatorial description of a graph and produce a layout of the graph; these methods are called 'layout creation' methods. For interactive systems, another kind of layout is needed: a facility which can adjust a layout after a change is made by the user or by the application. Although layout adjustment is essential in interactive systems, most existing layout algorithms are designed for layout creation. The use of a layout creation method for layout adjustment may totally rearrange the layout and thus destroy the user's 'mental map' of the diagram; thus a set of layout adjustment methods, separate from layout creation methods, is needed. This paper discusses some layout adjustment methods and the preservation of the 'mental map' of the diagram. First, several models are proposed to make the concept of 'mental map' more precise. Then two kinds of layout adjustments are described. One is an algorithm for rearranging a diagram to avoid overlapping nodes, and the other is a method aimed at changing the focus of interest of the user without destroying the mental map. Next, some experience with visualization systems in which the techniques have been employed is also described.
Efficient Iris and Fingerprint Fusion for Person Identification

Security of information is one of the most important factors of information technology and communication. So systems need strong procedures to protect data and resources access from unauthorized users.Biometric-based authentication systems represent a valid alternative to conventional approaches. Multimodal biometric system is used in order to improve the accuracy. A multimodal biometric identification systems aims to fuse two or more physical or behavioral traits. Multimodal biometric identification system based on iris & fingerprint trait is proposed. Typically in a multimodal biometric system each biometric trait processes its information independently. The processed information is combined using an appropriate fusion scheme. A template level fusion algorithm results in a homogeneous biometric vector by integrating iris & fingerprint data. Successively, the comparison of data base template and the input data is done with the help of hamming-distance matching algorithm. If the templates are matched we can allow the person to access the system. The proposed multimodal biometric system will improve system accuracy & dependability.
SWAN - Scientific Writing AssistaNt. A Tool for Helping Scholars to Write Reader-Friendly Manuscripts

Difficulty of reading scholarly papers is significantly reduced by reader-friendly writing principles. Writing reader-friendly text, however, is challenging due to difficulty in recognizing problems in one's own writing. To help scholars identify and correct potential writing problems, we introduce SWAN (Scientific Writing AssistaNt) tool. SWAN is a rule-based system that gives feedback based on various quality metrics based on years of experience from scientific writing classes including 960 scientists of various backgrounds: life sciences, engineering sciences and economics. According to our first experiences, users have perceived SWAN as helpful in identifying problematic sections in text and increasing overall clarity of manuscripts.