Miracle-dz/UniFAR-FTUs huggingface dataset:
Robust visual tracking based on Gabor feature and sparse representation

This paper proposes a novel approach to deal with the problem of visual tracking in some challenging situations. In our approach, Gabor features of image are used for expressing the templates and candidate targets in order to enhance the robustness of the variations due to illumination and appearance changes. Then we cast tracking as a sparse approximation problem in a particle filter framework. Gabor features derived from the Gabor wavelets representation of image are robust to changes in illumination and expression of the target object. At the same time, the sparse representation is able to deal with the problem of noise, varying viewpoints, background clutter, and illumination changes. The sparse representation is achieved by solving the ℓ1-regularized least square problem. The candidate target with the smallest residual error is considered as the target we want. Most of existing algorithms are unable to track objects for a long time because of the even-changing target and background. In order to overcome the drawback, the template set is renewed by using the incremental learning algorithm which is based on principal components analysis(PCA). We use our approach and other popular methods to track 4 challenging video sequences in which the target objects and the backgrounds change intensively and the targets are partially occluded sometimes. The results show that our method has more excellent performances compared with other methods.
The Role of the Medial Prefrontal Cortex in Innate Fear Regulation in Infants, Juveniles, and Adolescents

In adult animals, the medial prefrontal cortex (mPFC) plays a significant role in regulating emotions and projects to the amygdala and periaqueductal gray (PAG) to modulate emotional responses. However, little is known about the development of this neural circuit and its relevance to unlearned fear in pre-adulthood. To address these issues, we examined the mPFC of 14-d-old (infants), 26-d-old (juveniles), and 38- to 42-d-old (adolescents) rats to represent different developmental and social milestones. The expression patterns of the neuronal marker FOS were used to assess neurological activity. Muscimol, a GABA agonist, was used to inactivate the prelimbic and infralimbic mPFC subdivisions (400 ng in 200 nl). Animals were exposed to either a threatening or nonthreatening stimulus that was ecologically relevant and age specific. Freezing was measured as an indicator of innate fear behavior. The data indicated that the mPFC is neither active nor responsive to innate fear in infant rats. In juveniles, the prelimbic mPFC became responsive in processing aversive sensory stimulation but did not regulate freezing behavior. Finally, during adolescence, inactivation of the prelimbic mPFC significantly attenuated freezing and decreased FOS expression in the ventral PAG. Surprisingly, across all ages, there were no significant differences in FOS levels in the medial and basolateral/lateral amygdala when either mPFC subdivision was inactivated. Together, unlearned fear has a unique developmental course with different brain areas involved in unlearned fear in the immature animal than the adult. In particular, the mPFC neural circuitry is different in young animals and progressively develops more capacities as the animal matures.
A Novel Mobile Wallet Based on Android OS and Quick Response Code Technology

The emergence of Android mobile operating system has brought about a huge change in the smart phone industry. It has contributed to the increase in the range of services a smart phone can provide which includes the ability to be used in the exchange of financial value. Quick Response (QR) code technology can be regarded as a key technology in the future of mobile payments. The goal of this paper is to develop a model of mobile payment solution using QR code as a communication link between the two parties engaging in a transaction and also for encryption of transaction details. The study resulted in a new android mobile wallet application which was developed using the object oriented analysis and design methodology. Our experimental results show that the new system has better security using dual authentication employed by different entities, does not require sharing of personal details, eliminates the need for agents in the payment ecosystem and satisfies the universal pr operty
Head Related Transfer Function Personalization Based on Multiple Regression Analysis

The synthesis of personalization virtual auditory space (VAS) is an important and challenging task in virtual reality. One of the key factors for personalization VAS is to obtain a set of proper head related transfer functions (HRTFs). In this paper, a customization method is presented by applying multiple linear regression analysis to HRTFs and some anthropometric parameters chosen by correlation analysis. Experiments show that the estimated HRTF has small mean square error, and has similar perception effect as the measured HRTF. Furthermore, the localization accuracy of personalized HRTF is increased compared to the non-individual HRTF
The relationship between self-efficacy and teachers' ability to integrate technology

This study sought to evaluate the self-efficacy of teachers with regard to the integration of technology within the curriculum. The purpose of this study was to determine if there is a relationship between teachers’ self-efficacy within the classroom and their ability to integrate the technology available in the classroom. A quantitative, correlational study was performed. The sample was a convenience sample of 64 instructors at the middle grade level of a South Georgia school district. Middle school teachers were surveyed at one point in time, using Media and Technology Usage Attitude Scale (MTUAS) and the Teachers’ Sense of SelfEfficacy Scale. Once the data was attained, the data was analyzed using Pearson’s Product Moment Correlation Coefficient. The study determined that there is not a statistically significant relationship between teacher self-efficacy and the ability to integrate technology within the classroom. There was also no significant relationship between teacher self-efficacy and smartphone usage, internet usage, social media usage, text messaging, and email. It was suggested that a study be conducted with a larger sample.
Genome Wide Analysis of Narcolepsy in China Implicates Novel Immune Loci and Reveals Changes in Association Prior to Versus After the 2009 H1N1 Influenza Pandemic

Previous studies in narcolepsy, an autoimmune disorder affecting hypocretin (orexin) neurons and recently associated with H1N1 influenza, have demonstrated significant associations with five loci. Using a well-characterized Chinese cohort, we refined known associations in TRA@ and P2RY11-DNMT1 and identified new associations in the TCR beta (TRB@; rs9648789 max P = 3.7×10−9 OR 0.77), ZNF365 (rs10995245 max P = 1.2×10−11 OR 1.23), and IL10RB-IFNAR1 loci (rs2252931 max P = 2.2×10−9 OR 0.75). Variants in the Human Leukocyte Antigen (HLA)- DQ region were associated with age of onset (rs7744020 P = 7.9×10−9 beta −1.9 years) and varied significantly among cases with onset after the 2009 H1N1 influenza pandemic compared to previous years (rs9271117 P = 7.8×10−10 OR 0.57). These reflected an association of DQB1*03:01 with earlier onset and decreased DQB1*06:02 homozygosity following 2009. Our results illustrate how genetic association can change in the presence of new environmental challenges and suggest that the monitoring of genetic architecture over time may help reveal the appearance of novel triggers for autoimmune diseases.
On the Detection of Melody Notes in Polyphonic Audio

ABSTRACT This paper describes a method for melody detection in polyphonic musical signals. Our approach starts by ob-taining a set of pitch candidates for each time frame, with recourse to an auditory model. Trajectories of the most salient pitches are then constructed. Next, note candi-dates are obtained by trajectory segmentation (in terms of frequency and pitch salience variations). Too short, low-salience and harmonically related notes are then elimi-nated. Finally, the notes comprising the melody are ex-tracted. This is the main topic of this paper. We select the melody notes by making use of note sa-liences and melodic smoothness. First, we select the notes with highest pitch salience at each moment. Then, by the melodic smoothness principle, we exploit the fact that tonal melodies are usually smooth. Thus, long music intervals indicate the presence of possibly erroneous notes, which are substituted by notes that smooth out the melodic contour. Finally, false positives in the extracted melody should be eliminated. To this end, we remove spurious notes that correspond to abrupt drops in note saliences or du-rations. Additionally, note clustering is conducted to further discriminate between true melody notes and false positives. Keywords: Melody detection, melodic smoothness, fea-ture extraction, note clustering
Failure Prediction for Cloud Datacenter by Hybrid Message Pattern Learning

In operations and management of large-scale cloud data enters, it is essential for administrators to handle failures occurring in their infrastructure before causing service-level violations. Some techniques for failure prediction have been studied because they can be used to start the troubleshooting process at the early stage of troubles and to prevent service-level violations from occurring. By its nature, however, failure prediction involves a certain amount of incorrect detection (false-positive). When applying failure prediction to the operation and management of cloud data centers, incorrect detection can result in the execution of unnecessary workaround tasks and additional costs. Existing methods for failure prediction using Bayesian inference to identify message patterns related to a certain failure are difficult to apply to relatively stable systems, because the accuracy of their predictions deteriorates in environments where failure rarely occurs. In order to solve this problem, we propose a novel method to improve the accuracy of failure prediction by suppressing incorrect detections using a hybrid score that integrates the probability of simultaneous occurrence between a message pattern and a failure and frequency of the message patterns for the failure. We implemented this method and evaluated the accuracy in a real commercial cloud data enter. The evaluation results revealed that it improved the accuracy of failure prediction by 31.9% compared with the existing method in terms of precision in the best case.
The pause duration prediction for Mandarin text-to-speech system

In this paper, we enter into detailed analysis on how the pause duration under different prosodic boundaries are affected by various contextual factors in natural speech. To get the correlation between them, the paper calculates the mean pause duration under different prosodic boundaries. The contextual factors investigated in this paper contains both linguistic features, such as boundary types, syllable tones of boundary sides, initial and final types etc, and acoustic features, such as pitch gap across the boundary. The paper makes experiments and discussion which reveals the influence of these factors on pause duration. Based on that, the paper creates a pause duration prediction model for Mandarin speech synthesis system. The model was proved to be able to generate high quality prosody output with the listening test.
A Real-time Music Scene Description System: Detecting Melody and Bass Lines in Audio Signals

This paper describes a predominant-pitch estimation method that enables us to build a realtime system detecting melody and bass lines as a subsystem of our music scene description system. The purpose of this study is to build such a real-time system that is practical from the engineering viewpoint, that gives suggestions to the modeling of music understanding, and that is useful in various applications. Most previous pitch-estimation methods premised either a single-pitch sound with aperiodic noises or a few musical instruments and had great difficulty dealing with complex audio signals sampled from compact discs, especially discs recording jazz or popular music with drum-sounds. Our method can estimate the most predominant fundamental frequency (F0) in such signals containing sounds of various instruments because it does not rely on the F0’s frequency component, which is often overlapped by other sounds’ components, and instead estimates the F0 by using the Expectation-Maximization algorithm on the basis of harmonics’ frequency components within an intentionally limited frequency range. It also uses a multiple-agent architecture to stably track the temporal trajectory of the F0. Experimental results show that the system is robust enough to estimate the predominant F0s of the melody and bass lines in real-world audio signals.
Fuzzy Scheduling For Ensuring Qos in VMAC for VANETs Shruthi R ( M . Tech )

The need of a medium access control (MAC) protocol for an efficient broadcast service is of great importance to support the high priority safety applications in vehicular ad hoc networks (VANETs). Hassan omar proposed VeMAC, a novel multichannel TDMA MAC protocol proposed specifically for a VANET scenario. The VeMAC supports efficient one-hop and multi-hop broadcast services on the control channel by using implicit acknowledgments and eliminating the hidden terminal problem. The protocol reduces transmission collisions due to node mobility on the control channel by assigning disjoint sets of time slots to vehicles moving in opposite directions and to road side units. But the protocol has high packet loss & does not support different class of broadcast services. Taking this as motivation we propose a fuzzy scheduler based mechanism to ensure QOS for different class of broadcast messages along with VeMAC. Through simulation we measure the packet delivery ratio & prove that our mechanism is able to increment the delivery ratio by 20% over VeMAC. Keywords-fuzzy scheduler, medium access control, reliable broadcast, TDMA, vehicular ad hoc networks.
White matter maturation of normal human fetal brain. An in vivo diffusion tensor tractography study

We demonstrate for the first time the ability to determine in vivo and in utero the transitions between the main stages of white matter (WM) maturation in normal human fetuses using magnetic resonance diffusion tensor imaging (DTI) tractography. Biophysical characteristics of water motion are used as an indirect probe to evaluate progression of the tissue matrix organization in cortico‐spinal tracts (CSTs), optic radiations (OR), and corpus callosum (CC) in 17 normal human fetuses explored between 23 and 38 weeks of gestation (GW) and selected strictly on minimal motion artifacts. Nonlinear polynomial (third order) curve fittings of normalized longitudinal and radial water diffusivities (Z‐scores) as a function of age identify three different phases of maturation with specific dynamics for each WM bundle type. These phases may correspond to distinct cellular events such as axonal organization, myelination gliosis, and myelination, previously reported by other groups on post‐mortem fetuses using immunostaining methods. According to the DTI parameter dynamics, we suggest that myelination (phase 3) appears early in the CSTs, followed by the OR and by the CC, respectively. DTI tractography provides access to a better understanding of fetal WM maturation.
Institutionalistische Konzepte finanzwirtschaftlicher Wandlungsprozesse: Theorie, Methodologie, Operationalisierung

Empfohlene Zitierung / Suggested Citation: Langenohl, Andreas: Institutionalistische Konzepte finanzwirtschaftlicher Wandlungsprozesse: Theorie, Methodologie, Operationalisierung. In: Rehberg, Karl-Siegbert (Ed.) ; Deutsche Gesellschaft für Soziologie (DGS) (Ed.): Die Natur der Gesellschaft: Verhandlungen des 33. Kongresses der Deutschen Gesellschaft für Soziologie in Kassel 2006. Teilbd. 1 u. 2. Frankfurt am Main : Campus Verl. , 2008. ISBN 978-3-593-38440-5, 1427-1438. https://nbn-resolving.org/ urn:nbn:de:0168-ssoar-152682
An Accelerated SMO-Type Online Learning Algorithm

In order to accelerate the learning speed for online learning algorithm, a fast support vector machine online learning algorithm is presented in this paper. In the proposed algorithm, the learning condition is relaxed and a novel learning strategy is presented while Sequential Minimal Optimization (SMO) training method which has been improved by Keerthi, is embedded. In order to verify the performance of the proposed algorithm, it has been applied to seven UCI datasets and a benchmark problem. Experimental results show that the novel algorithm is very faster than Online Support Vector Classifier (OSVC), SimpleSVM algorithms without losing generalized performance. Keywords: Support Vector Machine, Sequential Minimal Optimization, Online Learning
Results for Whites and Blacks

We investigate the impact of various family background, socioeconomic, and life-course factors on the likelihood of white and black women returning to school after marriage. Using data from the National Longitudinal Study of the High School Class of 1972, results indicate the following: (a) many married women return to two-year schools rather than four-year schools, (b) blacks are more likely than whites to return to school after marriage, (c) fewer measured predictors are significant in models for blacks and for two-year schools, and (d) changing life-course position affects the likelihood of returning to school.
Angiogenesis in Inflammatory Bowel Disease

Angiogenesis is an important component of pathogenesis of inflammatory bowel disease (IBD). Chronic inflammation and angiogenesis are two closely related processes. Chronic intestinal inflammation is dependent on angiogenesis and this angiogenesis is modulated by immune system in IBD. Angiogenesis is a very complex process which includes multiple cell types, growth factors, cytokines, adhesion molecules, and signal transduction. Lymphangiogenesis is a new research area in the pathogenesis of IBD. While angiogenesis supports inflammation via leukocyte migration, carrying oxygen and nutrients, on the other hand, it has a major role in wound healing. Angiogenic molecules look like perfect targets for the treatment of IBD, but they have risk for serious side effects because of their nature.
22 7 v 1 2 2 N ov 2 00 6 Physical propositions and quantum languages

The word proposition is used in physics with different meanings, which must be distinguished to avoid interpretational problems. We construct two languages L∗(x) and L(x) with classical set-theoretical semantics which allow us to illustrate those meanings and to show that the nonBoolean lattice of propositions of quantum logic (QL) can be obtained by selecting a subset of p-testable propositions within the Boolean lattice of all propositions associated with sentences of L(x). Yet, the aforesaid semantics is incompatible with the standard interpretation of quantum mechanics (QM) because of known no-go theorems. But if one accepts our criticism of these theorems and the ensuing SR (semantic realism) interpretation of QM, the incompatibility disappears, and the classical and quantum notions of truth can coexist, since they refer to different metalinguistic concepts (truth and verifiability according to QM, respectively). Moreover one can construct a quantum language LTQ(x) whose Lindenbaum-Tarski algebra is isomorphic to QL, the sentences of which state (testable) properties of individual samples of physical systems, while standard QL does not bear this interpretation.
Gray Incidence Analysis of Protein 3D Structural Similarity

The second-order moment is applied to analyze the protein's principal component which is used to construct a three-dimensional unified coordinates under which a three dimensional protein structural spectra is obtained by means of wavelet transform. Furthermore, with a gray incidence analysis of the structural spectra, the three-dimensional structures of different proteins are compared. Experimental results demonstrate that the speed and effectiveness of the proposed method are identical to that provided by http://cl.sdsc. edu/, and can be applied in protein structure multi-scale comparison.
0 41 11 20 v 1 2 5 N ov 2 00 4 P o S ( W C 2 0 0 4 ) 0 3 4 Dilatonic , Chiral Cosmic Strings

In this work, we deal with the chiral string model for which th e world-sheet current is null in the framework of a scalar-tensor gravity. Our main goal is to ana lyse the impact of such a current on the gravitational macroscopic effects. For the purpose o f this analysis, we first study the gravitational properties of the spacetime generated by thi s string in the presence of a dilaton field. Then, we carry out an investigation of the mechanism of forma tion and evolution of wakes in this framework, showing the explicit contribution of the chiral ty to this effect.
TWO IRRECONCILABLE THEORIES OF JUSTICE : SOCIAL ENGINEERING VS . ETHICS OF PROPERTY

IF ECONOMICS IS UNDERSTOOD AS being the science of the implications of voluntary and monetary exchanges among different people (Mises, 1985), the terminology “economics of crime” is a contradiction in terms. Indeed the economic exchange consists in voluntary and peaceful cooperation, whereas crime refers to concepts of violence and coercion (Mises, 1983). The contrast is then more marked between the notion of economics that refers to a process of collaboration and cooperation, and that of criminal activity, which is associated with the invasion of property
Serial MR Analysis of Early Permanent and Transient Ischemia in Rats: Diffusion Tensor Imaging and High b Value Diffusion Weighted Imaging

Objective To evaluate the temporal evolution and diagnostic values of the diffusion tensor imaging (DTI) and the high b value diffusion weighted imaging (DWI) in the early permanent and transient cerebral ischemia. Materials and Methods For permanent or 30-minute transient-ischemia induced 30 rats, DTI and DWIs at both high b (b = 3000 s/mm2) and standard b value (b = 1000 s/mm2) were obtained at the following conditions: at 15, 30, 45, 60 minutes after the occlusion of what for hyperacute permanent ischemia; at 1, 3, 5, 7, 9 hours after the occlusion for acute permanent ischemia; and at 15 minutes before reperfusion, 0.5, 2.5, and 24 hours after reperfusion for transient ischemia. The diffusion parameters and their ratios were obtained and compared between different b values, and among different time points and groups, respectively. Results For both b values, the apparent diffusion coefficient (ADC) ratio decreased for first three hours, and then slightly increased until 9 hours after the occlusion during a gradual continuous increase of DWI signal intensity (SI) ratio, with excellent correlation between ADC ratios and DWI SI ratios. The DWI showed a higher contrast ratio, but the ADC map showed a lower contrast ratio for permanent ischemia at high b value than at standard b value. Fractional anisotropy (FA) increased for 1 hour, then gradually decreased until 9 hours after the occlusion in permanent ischemia and showed transient normalization and secondary decay along with change in ADC in transient ischemia. Conclusion This study presents characteristic initial elevation and secondary decay of FA, higher contrast ratio of DWI, and lower contrast ratio of ADC map at high b value, in addition to the time evolutions of diffusion parameters in early permanent and transient ischemia.
Detecting the direction of listening with the emg signals measured behind ears

In this paper, we describe the design of the ear tracker. The ear tracker detects the direction to which a person is listening. We propose the technique as a new form of an input device technology, which potentially allows the user to control machines with vague intention rather than explicit commands. Our ear tracker makes the detection with the electromyogram (EMG) signals probed behind ears. We have prototyped its hardware and algorithm. In our experiment, it shows 70% accuracy for detecting whether the testee is listening to the left or right.