Miracle-dz/UniFAR-FTUs huggingface dataset:
An Interactive Personal Audio Database for Musicians

As the high-capacity data storage devices (e.g. portable hard drives, and USB flash drives) become available to everyone, musicians are able to record all of their rehearsals and save them digitally. Given large amount of unlabeled and unorganized rehearsal recordings, manually organizing them can be a huge task. Therefore, managing music audio databases for practicing musicians automatically is a new and interesting challenge. This thesis describes a systematic investigation to provide useful capabilities to musicians both in rehearsal and when practicing alone. The goal is to allow musicians to automatically record, organize, and retrieve rehearsal (and other) audio to facilitate review and practice (for example, playing along with difficult passages). In order to accomplish this task, three separate problems should be solved: • Given the original recordings, extract the music segments and get rid of the nonmusic parts. A novel music classification system based on Eigenmusic and AdaBoost classifier to separate rehearsal recordings into segments is proposed. • Given the music segments from the previous step, the system should be able to group the segments which belong to the same composition together. An unsupervised clustering and alignment process to organize segments is introduced. • Finally, an interactive user interface is required for musicians to easily access and compare the previous rehearsals. The thesis provides a digital music display interface that provides both graphical input and output in terms of conventional music notation. The thesis will address each of these 3 problems and provide an implementation that works in practice. Some future work is also described.
Vibrating Target Micro-Doppler Signature in Bistatic SAR With a Fixed Receiver

Bistatic synthetic aperture radar (BSAR) provides strategical, technical and economical advantages in radar imaging. Motions and micro-motions of objects in an illuminated scene introduces Doppler and micro-Doppler effects in the received radar echoes. Combining the advantages introduced by the bistatic configuration and the usefulness of the micro-Doppler signature characterization will provide a powerful tool for military and civil remote sensing applications such as target recognition and classification. In this paper, a vibrating micro-Doppler signature for a BSAR system with fixed receiver is analyzed and compared to the signature obtained in a monostatic SAR system. The micro-Doppler effect is derived for a vibrating target in the bistatic SAR. The corresponding bistatic factor is shown to be a function of the bistatic acquisition geometry. Also, the effect of the target vibration on the focused image is shown to be influenced by the acquisition geometry. The derived model is useful for micro-Doppler classification. Simulations for 94 GHz and 10 GHz are given and the results confirm the derived model.
A fault-tolerant architecture for decentralized compositions of services in the wild

In this Student Research Abstract, we propose an architecture to allow the composition of web services in-the-wild in a fault-tolerant and decentralized way. This advances the state-of-the-art in service-oriented systems because it detaches and distributes the composition's logic and deal with fault-tolerance issues inherent to services in-the-wild.
Information Diffusion Mechanisms in Online Social Networks

A great deal of research interest has arisen in the area of information diffusion since the emergence of online social networks (OSN). Many models for describing how information diffuses in OSN have been proposed. But so far, the mechanisms of information diffusion remain largely unexplored. We try to find the mechanisms from the perspective of both network structure (micro-scale level) and popularity of information (macro-scale level). We focus on how these two levels interact with each other impacting information diffusion. Based on a Twitter data set which contains 196 million tweets, 10 million users, and 3 million hashtags, we perform a temporal analysis by calculating the time-evolving properties of network structure, including node degree, global clustering coefficient, the number of the nodes in the largest cluster. We then investigate how popularity evolves over time as the network structural properties change. We finally find that the moment when hashtag enter into bursting period is relevant to the largest cluster of users discussing the hashtag. When largest cluster changes from a closely connected small cluster to an emanative large cluster, hashtag enters into bursting period. We find this moment by calculating global clustering coefficient and the number of the nodes in the largest cluster. Our study on the interactive mechanisms between micro-and macro-scale levels reveals the essence of information diffusion and provides a necessary theoretical basis for predicting popularity or public sentiment warning.
How to Tell If a Particular Memory Is True or False

How can you tell if a particular memory belonging to you or someone else is true or false? Cognitive scientists use a variety of techniques to measure groups of memories, whereas police, lawyers, and other researchers use procedures to determine whether an individual can be believed or not. We discuss evidence from behavioral and neuroimaging studies and research on lying that have attempted to distinguish true from false memories.
Physical Activity, Body Composition and Metabolic Syndrome in Young Adults

Objective Low physical activity (PA) is a major risk factor for cardiovascular and metabolic disorders in all age groups. We measured intensity and volume of PA and examined the associations between PA and the metabolic syndrome (MS), its components and body composition among young Finnish adults. Research Design and Methods The study comprises 991 men and women born 1985-86, who participated in a clinical study during the years 2009-11 which included assessments of metabolism, body composition and PA. Objectively measured (SenseWear Armband) five-day PA data was available from 737 participants and was expressed in metabolic equivalents of task (MET). Results The prevalence of MS ranged between 8-10%. Higher total mean volume (MET-hours) or intensity (MET) were negatively associated with the risk of MS and separate components of MS, while the time spent at sedentary level of PA was positively associated with MS. Conclusions MS was prevalent in approximately every tenth of the young adults at the age of 24 years. Higher total mean intensity and volume rates as well as longer duration spent at moderate and vigorous PA level had a beneficial impact on the risk of MS. Longer time spent at the sedentary level of PA increased the risk of MS.
Detection of zero-day malware based on the analysis of opcode sequences

Today, rapid growth in the amount of malicious software is causing a serious global security threat. Unfortunately, widespread signature-based malware detection mechanisms are not able to deal with constantly appearing new types of malware and variants of existing ones, until an instance of this malware has damaged several computers or networks. In this research, we apply an anomaly detection approach which can cope with the problem of new malware detection. First, executable files are analyzed in order to extract operation code sequences and then n-gram models are employed to discover essential features from these sequences. A clustering algorithm based on the iterative usage of support vector machines and support vector data descriptions is applied to analyze feature vectors obtained and to build a benign software behavior model. Finally, this model is used to detect malicious executables within new files. The scheme proposed allows one to detect malware unseen previously. The simulation results presented show that the method results in a higher accuracy rate than that of the existing analogues.
Runtime compilation techniques for data partitioning and communication schedule reuse

The authors describe ways in which an HPF compiler can deal with irregular computations effectively. The first mechanism invokes a user specified mapping procedure via a set of compiler directives. The directives allow the user to use program arrays to describe graph connectivity, spatial location of array elements and computational load. The second is a simple conservative method that in many cases enables a compiler to recognize that it is possible to reuse previously computed results from inspectors (e.g. communication schedules, loop iteration partitions, information that associates off-processor data copies with on-processor buffer locations). The authors present performance results for these mechanisms from a Fortran 90D compiler implementation.
The dual-gain mode: a way to enhance the dynamic range of X-ray detectors

Varian Medical Systems has manufactured and recently put into operation a clinically-applicable solution for image-guided radiation therapy. Cone-beam CT imaging, one of the operation modes of the imaging unit of this device, aims at high-quality volumetric reconstruction. To boost the image quality, the dual-gain mode, a successful means for enhancing the dynamic range of the flat-panel detectors and obtaining better results in the contrast of the reconstructed image, was developed and successfully tested during the last few years. The important steps in the calibration of this mode involve a correction to the pulse widths associated with the X-ray production, the assessment of the detector signal above which nonlinear effects become significant and the determination of some properties of the detector pixels, namely, of dark fields, flatness corrections, etc. Finally, the defect-pixel map is obtained, containing dead and flickering pixels, as well as pixels with properties which are sufficiently `out of range'. An effect observed in the offset correction of raw images seems to originate in the mismatch between the measured and extrapolated values of the dark field; a correction scheme is proposed to take account of this effect. In the data processing, which is achieved on the basis of the files produced in the calibration of the mode, the high-gain signal is used whenever meaningful; otherwise, it is substituted by the low-gain signal, properly scaled. Defect pixels are interpolated from their good neighbours; a procedure achieving a correction in case of small defect-pixel clusters is outlined.
BINDING KINETICS INVESTIGATION OF A PEPTIDE FRAGMENT OF THE PSYCHIATRIC RISK PROTEIN, DISC1, TO THE KINASE GSK3β

ii Acknowledgements . iii Dedication . iv List of Tables . ix List of Figures . x List of Abbreviations . xiii 1.0 Introduction . 1 1.1 General Topic & Significance . 1 1.2 GSK3b Structure and Function. 2 1.3 The WNT/b-Catenin Pathway . 5 1.4 FRAT Function and Role in WNT Signalling . 8 1.5 DISC1 Function and Role in GSK3b/WNT Signalling . 11 1.6 Project Outline and Research Objectives . 15 1.6. 1 Hypothesis . 15 1.6. 2 Objective 1: Optimization of Heterologous Overexpression of Human GSK3b in Bacteria. 15
Adaptive Gain and Order Scheduling of Optimal Fractional Order PIlamdaDµ Controllers with Radial Basis Function Neural-Network

Gain and order scheduling of fractional order (FO) PIeDi controllers are studied in this paper considering four different classes of higher order processes. The mapping between the optimum PID/FOPID controller parameters and the reduced order process models are done using Radial Basis Function (RBF) type Artificial Neural Network (ANN). Simulation studies have been done to show the effectiveness of the RBFNN for online scheduling of such controllers with random change in set-point and process parameters.
A simple framework to simulate the mobility and activity of theme park visitors

Human mobility often needs to be simulated in order to evaluate various designs in transportation and urban planning. Our target application is the design and evaluation of wireless networks and services for new theme park experiences. The performance of some wireless networks, such as mobile ad hoc networks, strongly depends on human mobility. Therefore, we developed a tool named ParkSim that allows us to simulate the mobility of theme park visitors. The tool implements an activity-based mobility model, where the mobility of park visitors is driven by the activities they wish to perform in the park. The tool is calibrated based on GPS tracks collected in an entertainment theme park and validated on a number of metrics that are relevant for the performance of wireless ad hoc networks. ParkSim will be extended to enable the evaluation of new strategies to balance the number of people in different park areas.
Electrophysiological correlates of categorical perception of lexical tones by English learners of Mandarin Chinese: an ERP study

This study examines brain responses to boundary effects with respect to Mandarin lexical tone continua for three groups of adult listeners: (1) native English speakers who took advanced Mandarin courses; (2) naïve English speakers; and (3) native Mandarin speakers. A cross-boundary tone pair and a within-category tone pair derived from tonal contrasts (Mandarin Tone 1/Tone 4; Tone 2/Tone 3) with equal physical/acoustical distance were used in an auditory oddball paradigm. For native Mandarin speakers, the cross-category deviant elicited a larger MMN over left hemisphere sensors and larger P300 responses over both hemispheres relative to within-category deviants, suggesting categorical perception of tones at both pre-attentive and attentional stages of processing. In contrast, native English speakers and Mandarin learners did not demonstrate categorical effects. However, learners of Mandarin showed larger P300 responses than the other two groups, suggesting heightened sensitivity to tones and possibly greater attentional resource allocation to tone identification.
The Effects of Communities of Practice on the Success of an Expert Recommending Service

This article presents an explorative study of the impact of Communities of Practice (CoPs) on the success of a certain category of Knowledge Management Systems, hereafter called Expert Recommender Information Systems. They regroup Information Systems that identify and display individuals who have been qualified by the system as experts, and who are in a position to help users solve problems involving a business process breakdown. Rather than focusing on the Expert Recommending Information System itself, the author concentrates on the service it delivers, the Expert Recommending Service (ERS). Using multiple case study research, five different organizations were investigated, essentially in order to identify how CoPs influence the success of their ERS.
Stability Based Routing Scheme for Vehicular Networks

The vehicles are significant entities inside a vehicular network, capable of exchanging safety and non-safety messages with the neighbouring vehicles and RSU (road-side unit). The rapidly changing connectivity, error prone wireless channels, and low vehicle density in vehicular networks can make the routing schemes perform less efficiently. It leads to two main issues: to find the best routing strategy, to adapt the routing scheme in challenging settings of vehicular networks. In this paper, we propose a scheme to construct a stable path between source and destination node by using route request and route reply packets to ensure better packet delivery ratio, lower end-to-end delays and reduced message overheads. On the basis of simulation results, we conclude that the distance parameter or the traffic model alone may not be sufficient to derive the stability factor of any link and should be incorporated with the stability factor derived from the propagation model.
XMM-Newton Observations of the M31 Northern Disk: Properties of Selected X-Ray Sources and Unresolved Emission

We present the results of an XMM-Newton survey of the northern part of M31 disk. The X-ray properties of the 37 brightest sources are studied in detail. Combining the results of X-ray analysis with available data at other wavelengths, we were able to identify 19 out of 37 sources. Two sources in our sample were previously unknown: the hard X-ray source XMMU J004415.8+413057 and a transient supersoft source XMMU J004414.1+412206. We report on the discovery of X-ray pulsations from the source XMMU J004415.8+413057 with a period of 197 s. Three X-ray sources were identified with optical and radio SNR candidates. Five bright X-ray sources coincide with Galactic foreground stars. The properties of the remaining 18 bright X-ray sources detected in the survey are consistent with an AGN in the background of M31 and X-ray binaries belonging to M31. We report on the first unambiguous detection of the soft unresolved X-ray emission from the disk of M31. It follows the pattern of the spiral arms and can be traced up to the distance of ~10 kpc from the center of the galaxy. The spectrum of the unresolved emission shows dominant soft thermal component, which can be fit with a ~0.37 keV optically thin thermal plasma emission model or a combination of two thermal plasma models with temperatures of ~0.1 and ~0.7 keV. We suggest that significant part of the unresolved X-ray emission may represent hot diffuse gas and late-type stars in the disk of M31.
A short survey on modern virtual environments that utilize AI and synthetic data

Within a rather abstract computational framework Artificial Intelligence (AI) may be defined as intelligence exhibited by machines. In computer science, though, the field of AI research defines itself as the study of “intelligent agents. ” In this context, interaction with popular virtual environments, as for instance in virtual game playing, has gained a lot of focus recently in the sense that it provides innovative aspects of AI perception that did not occur to researchers until now. Such aspects are typically formed by the computational intelligent behavior captured through interaction with the virtual environment, as well as the study of graphic models and biologically inspired learning techniques, like, for instance, evolutionary computation, neural networks, and reinforcement learning. In this short survey paper, we attempt to provide an overview of the most recent research works on such novel, yet quite interesting, research domains. We feel that this topic forms an attractive candidate for fellow researchers that came into sight over the last years. Thus, we initiate our study by presenting a brief overview of our motivation and continue with some basic information on recent virtual graphic models utilization and the state-of-the-art on virtual environments, which constitutes two clearly identifiable components of the herein attempted summarization. We then continue, by briefly reviewing the interesting video games territory, and by discerning and discriminating its useful types, thus envisioning possible further utilization scenarios for the collected information. A short discussion on the identified trends and a couple of future research directions conclude the paper.
Facilitated physical activity as a treatment for depressed adults: randomised controlled trial

Objective To investigate the effectiveness of facilitated physical activity as an adjunctive treatment for adults with depression presenting in primary care. Design Pragmatic, multicentre, two arm parallel randomised controlled trial. Setting General practices in Bristol and Exeter. Participants 361 adults aged 18-69 who had recently consulted their general practitioner with symptoms of depression. All those randomised had a diagnosis of an episode of depression as assessed by the clinical interview schedule-revised and a Beck depression inventory score of 14 or more. Interventions In addition to usual care, intervention participants were offered up to three face to face sessions and 10 telephone calls with a trained physical activity facilitator over eight months. The intervention was based on theory and aimed to provide individually tailored support and encouragement to engage in physical activity. Main outcome measures The primary outcome was self reported symptoms of depression, assessed with the Beck depression inventory at four months post-randomisation. Secondary outcomes included use of antidepressants and physical activity at the four, eight, and 12 month follow-up points, and symptoms of depression at eight and 12 month follow-up. Results There was no evidence that participants offered the physical activity intervention reported improvement in mood by the four month follow-up point compared with those in the usual care group; adjusted between group difference in mean Beck depression inventory score −0.54 (95% confidence interval −3.06 to 1.99; P=0.68). Similarly, there was no evidence that the intervention group reported a change in mood by the eight and 12 month follow-up points. Nor was there evidence that the intervention reduced antidepressant use compared with usual care (adjusted odds ratio 0.63, 95% confidence interval 0.19 to 2.06; P=0.44) over the duration of the trial. However, participants allocated to the intervention group reported more physical activity during the follow-up period than those allocated to the usual care group (adjusted odds ratio 2.27, 95% confidence interval 1.32 to 3.89; P=0.003). Conclusions The addition of a facilitated physical activity intervention to usual care did not improve depression outcome or reduce use of antidepressants compared with usual care alone. Trial registration Current Controlled Trials ISRCTN16900744.
Recovery of Bioenergetics Parameters from Information on Growth: Overview of an Approach Based on Statistical Analysis of Tagging and Size-At- Age Data

Parameters for size allometry in feeding and metabolic rates, along with Q10 parameters for responses of these rates to seasonal temperature change, can in principle be estimated from field data on growth, particularly seasonal tag- ging studies. However, it is still typically necessary to complement or constrain the field estimates with information from laboratory studies, particularly on power parameters for size allometry in metabolism, Q10 for metabolism, and responses of feeding rate at high temperatures. Ontogenetic habitat shifts can cause apparent changes in the size power parameters that are in fact due to temperature differences between the habitats. Seasonal changes in body condition (due to feeding, metabolism, and reproduction) can be represented using simple models for allocation of food intake to skeletal growth, though parameter estimation for such models is grossly unreliable when only seasonal changes in length growth rates have been measured.
Cost Effective Rumor Containment in Social Networks

The spread of rumors through social media and online social networks can not only disrupt the daily lives of citizens but also result in loss of life and property. A rumor spreads when individuals, who are unable decide the authenticity of the information, mistake the rumor as genuine information and pass it on to their acquaintances. We propose a solution where a set of individuals (based on their degree) in the social network are trained and provided resources to help them distinguish a rumor from genuine information. By formulating an optimization problem we calculate the optimum set of individuals, who must undergo training, and the quality of training that minimizes the expected training cost and ensures an upper bound on the size of the rumor outbreak. Our primary contribution is that although the optimization problem turns out to be non convex, we show that the problem is equivalent to solving a set of linear programs. This result also allows us to solve the problem of minimizing the size of rumor outbreak for a given cost budget. The optimum solution displays an interesting pattern which can be implemented as a heuristic. These results can prove to be very useful for social planners and law enforcement agencies for preventing dangerous rumors and misinformation epidemics.