Miracle-dz/UniFAR-FTUs huggingface dataset:
Privacy Protection in Biometric-Based Recognition Systems: A marriage between cryptography and signal processing

Systems employing biometric traits for people authentication and identification are witnessing growing popularity due to the unique and indissoluble link between any individual and his/her biometric characters. For this reason, biometric templates are increasingly used for border monitoring, access control, membership verification, and so on. When employed to replace passwords, biometrics have the added advantage that they do not need to be memorized and are relatively hard to steal. Nonetheless, unlike conventional security mechanisms such as passwords, biometric data are inherent parts of a person? s body and cannot be replaced if they are compromised. Even worse, compromised biometric data can be used to have access to sensitive information and to impersonate the victim for malicious purposes. For the same reason, biometric leakage in a given system can seriously jeopardize the security of other systems based on the same biometrics. A further problem associated with the use of biometric traits is that, due to their uniqueness, the privacy of their owner is put at risk. Geographical position, movements, habits, and even personal beliefs can be tracked by observing when and where the biometric traits of an individual are used to identify him/her.
A ug 2 00 1 Open Strings in Simple Current Orbifolds

We study branes and open strings in a large class of orbifold backgrounds using microscopic techniques of boundary conformal field theory. In particular, we obtain factorizing operator product expansions of open string vertex operators for such branes. Applications include branes in Z2 orbifolds of the SU(2) WZW model and in the D-series of unitary minimal models considered previously by Runkel. e-mail: keizo.matsubara@teorfys.uu. se, vschomer@aei.mpg. de, mikael.smedback@teorfys.uu. se
Regulation of the mTOR signaling network in hibernating thirteen-lined ground squirrels

SUMMARY For many small mammals, survival over the winter months is a serious challenge because of low environmental temperatures and limited food availability. The solution for many species, such as thirteen-lined ground squirrels (Ictidomys tridecemlineatus), is hibernation, an altered physiological state characterized by seasonal heterothermy and entry into long periods of torpor that are interspersed with short arousals back to euthermia. During torpor, metabolic rate is strongly reduced to achieve major energy savings, and a coordinated depression of non-essential ATP-expensive functions such as protein synthesis takes place. This study examines the mammalian target of rapamycin (mTOR) signaling pathway, a crucial component of the insulin receptor network, over six stages of the torpor–arousal cycle of hibernation. Immunoblots showed that the phosphorylation state of mTORSer2448 was strongly reduced in skeletal muscle (by 55%) during late torpor but increased by 200% during early arousal compared with euthermia. However, the phosphorylation state of this residue remained relatively constant in cardiac muscle during torpor but was enhanced during entrance into torpor and early arousal from torpor stages (by 2.9- and 3.2-fold, respectively). Phosphorylation states of upstream regulators of mTOR, p-AktThr473 and p-TSC2Thr1462, were also suppressed in skeletal muscle by 55 and 51%, respectively, during late torpor, as were selected downstream substrates – p-4E-BP1Thr46 and p-S6Ser235 contents dropped by 74 and 41%, respectively. Overall, the results indicate suppressed mTOR signaling in skeletal muscle, but not cardiac muscle, during torpor. By contrast, activation of mTOR and other components of the mTORC1 complex (p-PRAS40Thr246 and GβL) occurred during early arousal in both skeletal and cardiac muscle.
Corpus-based discovery of semantic intensity scales

Gradable terms such as brief, lengthy and extended illustrate varying degrees of a scale and can therefore participate in comparative constructs. Knowing the set of words that can be compared on the same scale and the associated ordering between them (brief < lengthy < extended) is very useful for a variety of lexical semantic tasks. Current techniques to derive such an ordering rely on WordNet to determine which words belong on the same scale and are limited to adjectives. Here we describe an extension to recent work: we investigate a fully automated pipeline to extract gradable terms from a corpus, group them into clusters reflecting the same scale and establish an ordering among them. This methodology reduces the amount of required handcrafted knowledge, and can infer gradability of words independent of their part of speech. Our approach infers an ordering for adjectives with comparable performance to previous work, but also for adverbs with an accuracy of 71%. We find that the technique is useful for inferring such rankings among words across different domains, and present an example using biomedical text.
An Integrated Nine-Switch Power Conditioner for Power Quality Enhancement and Voltage Sag Mitigation

The nine-switch converter has already been proven to have certain advantages, in addition to it s component saving topological feature A nine-switch power converter having two sets of output terminals was recently proposed in place of the traditional back-to-back power converter that uses 12 switches in total . Instead of accepting these tradeoffs as limitations, a nine-switch power conditioner is proposed here that virtually "converts" most of these topological short comings into interesting performance advantages. Despite these advantages, the nine-switch converter has so far found limited applications due to its many perceived performance tradeoffs like requiring an oversized dc-link capacitor, limited amplitude sharing and constrained phase shift between its two sets of output terminals. With an appropriately designed control scheme then incorporated, the nine-switch converter is shown to favorably raise the overall power quality in experiment, hence justifying its role as a power conditioner at a reduced semiconductor cost. Aiming further to reduce its switching losses, an appropriate discontinuous modulation scheme is proposed and studied here in detail to doubly ensure that maximal reduction of commutations is achieved.
A comprehensive aesthetic quality assessment method for natural images using basic rules of photography

In this paper we propose a comprehensive photo aesthetic assessment method that represents each photo according to a set of photographic rules. Specifically, our method exploits the information derived from both low- and high-level analysis of photo layout, not only for the photo as a whole, but also for specific spatial regions of it. Five feature vectors are introduced for describing the photo's simplicity, colorfulness, sharpness, pattern and composition. Subsequently, they are concatenated in a final feature vector where a Support Vector Machine (SVM) classifier is applied in order to perform the aesthetic quality evaluation. The experimental results and comparisons show that our approach achieves consistently more accurate quality assessment than the relevant literature methods and also that the proposed features can be combined with other generic image features so as to enhance the performance of previous methods.
Humotion: A Human Inspired Gaze Control Framework for Anthropomorphic Robot Heads

In recent years, an attempt is being made to control robots more intuitive and intelligible by exploiting and integrating anthropomorphic features to boost social human-robot interaction. The design and construction of anthropomorphic robots for this kind of interaction is not the only challenging issue -- smooth and expectation-matching motion control is still an unsolved topic. In this work we present a highly configurable, portable, and open control framework that facilitates anthropomorphic motion generation for humanoid robot heads by enhancing state-of-the-art neck-eye coordination with human-like eyelid saccades and animation. On top of that, the presented framework supports dynamic neck offset angles that allow animation overlays and changes in alignment to the robots communication partner whileretaining visual focus on a given target. In order to demonstrate the universal applicability of the proposed ideas we used this framework to control the Flobi and the iCub robot head, both in simulation and on the physical robot. In order to foster further comparative studies of different robot heads, we will release all software, based on this contribution, under an open-source license.
Segmentation of lines and words in handwritten Gurmukhi script documents

Optical Character Recognition (OCR) is an essential part of Document Analysis System. Among few phases of an OCR system, segmentation is an important phase. After preprocessing phase, it is necessary to segment the text into lines, words and characters before the recognition of text. Segmentation is one of the most important and challenging tasks in a handwritten recognition system. Gurmukhi script can be segmented into paragraphs, lines, words and characters. This paper describes a technique for segmentation of handwritten Gurmukhi script documents into lines with the use of strip based projection profile technique, and to segment lines into words using white space and pitch method.
Multi-resolution super-pixels and their applications on fluorescent mesenchymal stem cells images using 1-D SIFT merging

A new multi-resolution super-pixel based algorithm is proposed to track cell size, count and motion in Mesenchymal Stem Cells (MSCs) images. Multi-resolution super-pixels are obtained by placing varying density seeds on the image. The density of the seeds are determined according to the local high frequency components of the MSCs image. In this way a multi-resolution super-pixels decomposition of the image is obtained. A second contribution of the paper is novel decision rule for merging similar neighboring super-pixels. One-dimensional version of the well known scale invariant feature transform (SIFT) is developed and applied to the histograms of the neighboring super-pixels to determine similar regions. The proposed algorithm is experimentally shown to be successful in segmenting and tracking cells in MSCs images.
A study of precise road feature localization using mobile mapping system

In the near future, precise digital map data is said to be applied to the next generation car navigation system as well as ITS to increase the driving safety. It is important to maintain digital map data's freshness and accuracy. A MMS (Mobile Mapping System) can acquire this highway database, while offering unbeatable productivity with the combination of navigation and videogrammetry tools. The proposed MMS, featuring a GPS/DR combined navigation system, a GPS-Gyro/IMU, nearly horizontal cameras, laser scanners, high sampling rate road data measurement logger, and the network-based RTK-GPS PAStrade can acquire road feature location like snow-poles, guard-rails, road signs and road line precisely at normal cruising speed considering 3D road surface model. The carrier phased D-GPS/DR combined navigation system and GPS-Gyro/IMU performs highly accurate positioning performance at a few centimeter and posture estimation at 0.073 [deg rms] for heading and 0.064 [deg rms] for pitching, and 0.116 [deg rms] for rolling. Furthermore, the proposed road feature digitizing method, featuring 2D camera image projection to the 3D road surface model, allows users to understand complicated 3D point-cloud data intuitively and to designate desired road feature with few mistakes. The accuracy comparison between the static RTK-GPS/Total-Station measurement with the dynamic MMS mobile measurement reveal that the system allows 0.3 [m] road feature measurement accuracy with unbeatable productivity when sufficient GPS visibility is obtained.
A Framework for enabling Service migration in Ubiquitous Computing

Ubiquitous Computing is a computing paradigm in which applications move with the user. This requires applications to migrate automatically to the environment the user is present and adapt to different contexts and resource availabilities. An important requirement of a ubiquitous computing system is this automatic adaptation of applications to the new environment. At the time of migration, there could be incomplete services that are still in a running state. Such services may have to be suspended and transferred to destination before they are completed. In this paper, we propose a service migration framework for migrating partially executed services. When multiple destinations are available for the migration, an Ontology Server selects one after evaluating a variety of attributes such as energy level, computational ability, availability etc. Migrations are handled at thread level for accuracy. In particular, migration of response-awaiting-services is handled based on the communication behavior of the service. These services are divided into two categories viz. Continuous-Interaction-Demanding Services and Limited Interaction Services based on the nature of their interaction with the user. Two distinct protocols are then proposed for handling the migration of these services.
Ongoing Developments in Automatically Adapting Lexical Resources to the Biomedical Domain

This paper describes a range of experiments using empirical methods to adapt theWordNet noun ontology for specific use in the biomedical domain. Our basic technique is to extract relationships between terms using the Ohsumed corpus, a large collection of abstracts from PubMed, and to compare the relationships extracted with those that would be expected for medical terms, given the structure of the WordNet ontology. The linguistic methods involve the use of a variety of lexicosyntactic patterns that enable us to extract pairs of coordinate noun terms, and also related groups of adjectives and nouns, using Markov clustering. This enables us in many cases to analyse ambiguous words and select the correct meaning for the biomedical domain. While results are often encouraging, the paper also highlights evident problems and drawbacks with the method, and outlines suggestions for future work.
Protein Kinase M Maintains Long-Term Sensitization and Long-Term Facilitation in Aplysia

How the brain maintains long-term memories is one of the major outstanding questions in modern neuroscience. Evidence from mammalian studies indicates that activity of a protein kinase C (PKC) isoform, protein kinase Mζ (PKMζ), plays a critical role in the maintenance of long-term memory. But the range of memories whose persistence depends on PKMζ, and the mechanisms that underlie the effect of PKMζ on long-term memory, remain obscure. Recently, a PKM isoform, known as PKM Apl III, was cloned from the nervous system of Aplysia. Here, we tested whether PKM Apl III plays a critical role in long-term memory maintenance in Aplysia. Intrahemocoel injections of the pseudosubstrate inhibitory peptide ZIP (ζ inhibitory peptide) or the PKC inhibitor chelerythrine erased the memory for long-term sensitization (LTS) of the siphon-withdrawal reflex (SWR) as late as 7 d after training. In addition, both PKM inhibitors disrupted the maintenance of long-term (≥24 h) facilitation (LTF) of the sensorimotor synapse, a form of synaptic plasticity previously shown to mediate LTS of the SWR. Together with previous results (Bougie et al., 2009), our results support the idea that long-term memory in Aplysia is maintained via a positive-feedback loop involving PKM Apl III-dependent protein phosphorylation. The present data extend the known role of PKM in memory maintenance to a simple and well studied type of long-term learning. Furthermore, the demonstration that PKM activity underlies the persistence of LTF of the Aplysia sensorimotor synapse, a form of synaptic plasticity amenable to rigorous cellular and molecular analyses, should facilitate efforts to understand how PKM activity maintains memory.
New series representation for the trivariate non-central chi-squared distribution

This paper derives a new infinite series representation for the trivariate non-central chi-squared distribution when the underlying correlated Gaussian variables have a tridiagonal form of an inverse covariance matrix. The joint probability density function is derived using Miller's approach and Dougall's identity. Moreover, the trivariate cumulative distribution function (cdf) and characteristic function (chf) are also derived. Finally, the bivariate non-central chi-squared distribution and some known forms are shown to be special cases of the more general distribution. However, the derivation of non-central chi-squared distribution for an arbitrary covariance matrix seems intractable via Miller's approach. Two applications of the newly derived results are provided for performance analysis of multiple input multiple output (MIMO) systems with transmit antenna selection over a correlated Rician fading environment. Some numerical results are also presented to verify the accuracy of the analytical expressions.
Time-varying MPC-based energy management for HEV including engine stop & start

In this paper, the energy management of hybrid electric vehicles is considered and two problems are addressed: torque split and engine stop-start policies. Model predictive control potential is proven especially for the decision to stop the engine at the proper moment and also to anticipate engine restart. A piecewise linear polynomial with respect to torque is used to approximate the fuel consumption and it will be shown that its partition can be exploited to implicitly consider engine stop decision. The strategy is applied to a dual-clutch transmission hybrid architecture which was simulated on a high-fidelity vehicle model.
English Language and Literature Students’ Perceptions of Critical Thinking

The fundamental purpose of the function of thinking is to attribute meaning to events in our lives, classify these events into categories and identify them subjectively. As an important dimension of education on thinking, the teaching of critical thinking since the 1950s has attained a wide conceptual framework. Accepted as a factor that facilitates the aquisition and comprehension of information, critical thinking is a desirable learning outcome of education. Some of the characteristics and properties of critical thinking are being aware, systematic, flexible and patient, encompassing open-meaning, metacognition, reconstruction, motivation and discussion. From this point, the perceptions of the students of Karabuk University, English Language and Literature Department, regarding critical thinking, were investigated in detail, in the Spring semester of the academic year 2017-2018. This study is a descriptive one and utilises the survey model to determine the levels of critical thinking in 222 teacher candidates, comprised of students ranging from freshmen to seniors and from both daytime and evening education. The findings have been evaluated and a set of conclusions have been drawn. While a statistical difference according to classes was not found when Anova results were analysed on the sub-dimensions of metacognition, flexibility, systematicity, open-mindedness, a difference was found between the sophomore and senior students on the sub-dimension of perseverance-patience.
Dust content of core-collapse supernova hosts

We study 13 core-collapse supernova (CCSN) host galaxies at z = 0.1−0.6. Continuum observations at 250 GHz were performed using MAMBO at the IRAM-30 m telescope. No source is detected and the error-weighted mean flux is 0.25 ± 0.32 mJy. Upper limits on their dust masses are derived and the corresponding sample mean corresponds to 1.4 ± 2.2 × 10 8 M� . These results are comparable to previous submillimetre observations of SN-Ia hosts completed by Farrah et al. and Clements et al. We conclude that CCSN hosts are not extreme sources at millimetre wavelengths, and as confirmed using the optical luminosities of a subset of our sample, they are typical of the local galaxy population.
Identity salience and the football self: a critical ethnographic study of women and girls in football

ABSTRACT The focus on identity has enjoyed a certain permanency within sports studies research, and the relationship between athlete identity and sport is complex and nuanced. Ordinarily literature on girls’ and women’s football (soccer) tends to focus on gender identities rather than identities per se. The purpose of the current paper is to address this issue and examine the way in which player identities are negotiated within the game. A season-long critical ethnographic exploration undertaken across three sites (football academy, school and family homes) underpins the research design for this exploration. It was found that the football self is managed and organised differently depending on the centrality of football within the lives of the women and girls who play. The development of the Football Self Continuum examines identity shifts vis-à-vis life transitions and football commitment. Identities are viewed in both hierarchical and fluid terms dependent on whether the player has a ‘salient’ or ‘contingent’ football self. This research has useful implications for coaches, family members and National Governing Bodies with regard to understanding and therefore supporting player identity changes in relation to life transitions.
Parametric average-value model of synchronous machine-rectifier systems

A new average-value model of a rectifier circuit in a synchronous-machine-fed rectifier system is set forth. In the proposed approach, a proper state model of the synchronous machine in the qd-rotor reference frame is used, whereas the rectifier/dc-link dynamics are represented using a suitable proper transfer function and a set of nonlinear algebraic functions that are obtained from the detailed model using numerical averaging. The new model is compared to a detailed simulation as well as to measured data and is shown to be very accurate in predicting the large-signal time-domain transients as well as small-signal frequency-domain characteristics.
Quantification and compensation of the impact of faults in system throughput

Performability relates the performance (throughput) and reliability of software systems whose normal behaviour may degrade owing to the existence of faults. These systems, naturally modelled as discrete event systems using shared resources, can incorporate fault-tolerant techniques to mitigate such a degradation. In this article, compositional fault-tolerant models based on Petri nets, which make its sensitive performability analysis easier, are proposed. Besides, two methods to compensate existence of faults are provided: an iterative algorithm to compute the number of extra resources needed, and an integer-linear programming problem that minimises the cost of incrementing resources and/or decrementing fault-tolerant activities. The applicability of the developed methods is shown on a Petri net that models a secure database system.