Miracle-dz/UniFAR-FTUs huggingface dataset:
Designing Interaction for Computer Musicians

In the world of computer music, interactivity is becoming an increasingly active area of interest. In their roadmap for future computer music research, Serra et. al. [5] emphasise interactivity and controllability as an area that the next generation of research needs to focus on, and there has arguably been a shift within the computer music community from the search for new sound synthesis techniques towards a search for new ways of controlling sound synthesis. Well designed interactivity is an important component of a computer music system; interaction problems can inhibit a musician’s creative process and interrupt flow [1] in performance. My area of research is to examine interaction between musicians and computer systems, and to look at ways in which interactivity can be designed to enable a better musical experience for the user. Although my research to date has not covered shared interaction, it’s extremely likely that it will in the future; playing music is at the core a social activity and collaborative control of digital music opens up new possibilities which need to be considered under my research theme. In this paper I’ll outline my research so far, and look at how collaborative control could be an important part of the next steps.
INTERFACE IN A ONE-DIMENSIONAL ISING MODEL WITH RANDOM INTERACTIONS

The purpose of this paper is to localize an interface in a one-dimensional Ising model with random Kac potentials. To study this system we de ne a Gibbs measure which depends on a quenched variable y which models the random part of interactions and on a scaling parameter which rules the range of interactions. In the Kac asymptotic, as goes to 0, we prove a large deviation principle with rate function depending on y. By using Freidlin and Wentzell methods, we show that the rst interface occurs for almost all y at a distance of the order of exp( ), where is a constant given by a variational formula.
A Model of Operant Conditioning for Adaptive Obstacle Avoidance

We have recently introduced a self-organizing adaptive neural controller that learns to control movements of a wheeled mobile robot toward stationary or moving targets, even when the robot's kinematics arc unknown, or when they change unexpectedly during operation. The model has been shown to outperform other traditional controllers, especially in noisy environments. This article describes a neural network module for obstacle avoidance that complements our previous work. The obstacle avoidance module is based on a model of classical and operant conditioning first proposed by Grossberg ( 1971 ). This module learns the patterns of ultrasonic sensor activation that predict collisions as the robot navigates in an unknown cluttered environment. Along with our original low-level controller, this work illustrates the potential of applying biologically inspired neural networks to the areas of adaptive robotics and control
Network and profile based measures for user similarities on social networks

An interesting problem in online social networks is the identification of user characteristics and the analysis of how these are reflected in the graph structure evolution. The basis of these studies are user similarity measures. In this paper, we approach user similarity from two angles. First, we propose a network similarity measure that considers only the graph structure and that, differently from existing techniques, takes into consideration also how two users are indirectly connected. Secondly, we propose a similarity measure based on user profile information, such to find semantic similarities between users. Moreover, since user profile data could be missing, we present a technique to infer them from profile items of the user contacts. We evaluate our similarity measures on Facebook and DBLP data.
An enhanced developmental staging table for the painted turtle, Chrysemys picta (Testudines: Emydidae)

Normal developmental staging tables often undergo expansion and enhancement in response to advancing research paradigms and technologies. The Painted Turtle, Chrysemys picta, has long been a preferred reference taxon for comparative embryology and recently became the first turtle species to feature a sequenced genome. However, modern descriptive studies on embryogenesis are lacking and an earlier developmental staging table has been ignored. To address these problems, we re‐evaluated descriptions of developmental stages by studying embryos under standardized laboratory conditions. We created an enhanced normal developmental staging table that clarifies and validates previous descriptions of developmental processes in this species. Moreover, we emphasized description of turtle‐specific developmental characters such as the carapacial ridge. We demonstrated that embryo growth rate, length of incubation period, and timing to developmental stages are predictable under controlled environmental conditions. The appearance of characters associated with eye, limb, and shell anatomy was congruent with observations made in other turtle species. To reduce experimental bias, we recommend the use of our enhanced staging table when describing embryogenesis in the Painted Turtle. J. Morphol. 275:442–455, 2014. © 2013 Wiley Periodicals, Inc.
Reducing the measurement footprint in the characterization of low-loss materials using the flanged-waveguide measurement geometry

The purpose of this paper is to demonstrate how the flanged-waveguide material-characterization technique, originally designed to characterize lossy materials only, can be extended to accurately extract permittivity and permeability of low-loss materials. Provided in this paper is a summary of the flanged-waveguide technique. This is followed by a discussion of how time-domain gating can be utilized to mitigate the error introduced by waves reflected from the edges of the flanges. Furthermore, it is demonstrated that by utilizing timedomain gating, the cross-sectional dimensions of the flanges can be significantly reduced. Lastly, material measurement results of plexiglass are provided to validate the time-domain gating technique.
Concept Mapping: Connecting Educators Proc. of the Third Int. Conference on Concept Mapping a Concept Sense Disambiguation Algorithm for Concept Maps

Concept maps are a graphically rich tool for representing knowledge in natural language. An important aspect for their automatic or semi-automatic processing, including concept mapping, formalization and evaluation, is the identification of the most rational sense of the concepts. In this paper, we present an algorithm for concept sense disambiguation based on contextual analysis, domain information and gloss. The algorithm takes advantage of the whole map's topology and use WordNet as sense repository. Results of preliminary experimental evaluations of the concept disambiguation algorithm applied to several concept maps in the Spanish language are presented and compared with the state of the art.
The Suffix of a square matrix, with applications

We describe a new data structure, the Lst@ix tree, which is a generalization to a souare matrix of McCreieht’s suffix tree ‘ior a string ordered alohabet . All-matrices have entries ii a totally . Based on the Lsuffix tree. we eive efficient algorithms for the static and dynamic ver&ns of the following problems that arise in many important applications in low-level image processing [19] and in visual databases [1S]: Two-Dimensional Pattern Retrieval: We have a library of texts S = {TEXT’, . ,TEXT’}, where TEXT’ is an ni x ni matrix, 1 < i < r. In the static version, we may preprocess the.libr&y. -Given an m x m pattern matrix PAT, we want to find all occurrences of PAT in TEXT (query), for all TEXT E S. In th e d ynamic version, we can update the librarv S bv insertine in it or deletine from it some TEXT. The query is as i; the static versi& but is intermixed with update operations. Two-Dimensional Dictionary Matching: We have a dictionary of patterns DC = {PAZ, . , PAT,}, where PAZ is of dimension mi x mi, 1 < i < s. In the static case, we may preprocess the dictionary. liven an n x n text matrix TEXT, we want to search for all occurrences of patterns in the dictionary in the text (search step). In the dynamic version, we can update DC by inserting or deleting some matrix (pattern) from it.
Disrupted resting-state functional architecture of the brain after 45-day simulated microgravity

Long-term spaceflight induces both physiological and psychological changes in astronauts. To understand the neural mechanisms underlying these physiological and psychological changes, it is critical to investigate the effects of microgravity on the functional architecture of the brain. In this study, we used resting-state functional MRI (rs-fMRI) to study whether the functional architecture of the brain is altered after 45 days of −6° head-down tilt (HDT) bed rest, which is a reliable model for the simulation of microgravity. Sixteen healthy male volunteers underwent rs-fMRI scans before and after 45 days of −6° HDT bed rest. Specifically, we used a commonly employed graph-based measure of network organization, i.e., degree centrality (DC), to perform a full-brain exploration of the regions that were influenced by simulated microgravity. We subsequently examined the functional connectivities of these regions using a seed-based resting-state functional connectivity (RSFC) analysis. We found decreased DC in two regions, the left anterior insula (aINS) and the anterior part of the middle cingulate cortex (MCC; also called the dorsal anterior cingulate cortex in many studies), in the male volunteers after 45 days of −6° HDT bed rest. Furthermore, seed-based RSFC analyses revealed that a functional network anchored in the aINS and MCC was particularly influenced by simulated microgravity. These results provide evidence that simulated microgravity alters the resting-state functional architecture of the brains of males and suggest that the processing of salience information, which is primarily subserved by the aINS–MCC functional network, is particularly influenced by spaceflight. The current findings provide a new perspective for understanding the relationships between microgravity, cognitive function, autonomic neural function, and central neural activity.
How Well Do Patients Understand Written Instructions?

Abstract The aim of this study was to assess health literacy (word recognition and comprehension) in patients at a rural rheumatology practice and to compare this to health literacy levels in patients from an urban rheumatology practice. Inclusion criteria for this cross-sectional study were as follows: ≥18-year-old patients at a rural rheumatology practice (Mid-North Coast Arthritis Clinic, Coffs Harbour, Australia) and an urban Sydney rheumatology practice (Combined Rheumatology Practice, Kogarah, Australia). Exclusion criteria were as follows: ill-health precluding participation; poor vision/hearing, non-English primary language. Word recognition was assessed using the Rapid Estimate of Adult Literacy in Medicine (REALM). Comprehension was assessed using the Test of Functional Health Literacy in Adults (TOFHLA). Practical comprehension and numeracy were assessed by asking patients to follow prescribing instructions for 5 common rheumatology medications. At the rural practice (Mid-North Coast Arthritis Clinic), 124/160 patients agreed to participate (F:M 83:41, mean age 60.3 ± 12.2) whereas the corresponding number at the urban practice (Combined Rheumatology Practice) was 99/119 (F:M 69:30, mean age 60.7 ± 17.5). Urban patients were more likely to be born overseas, speak another language at home, and be employed. There was no difference in REALM or TOFHLA scores between the 2 sites, and so data were pooled. REALM scores indicated 15% (33/223) of patients had a reading level ⩽Grade 8 whereas 8% (18/223) had marginal or inadequate functional health literacy as assessed by the TOFHLA. Dosing instructions for ibuprofen and methotrexate were incorrectly understood by 32% (72/223) and 21% (46/223) of patients, respectively. Up to 15% of rural and urban patients had low health literacy and <1/3 of patients incorrectly followed dosing instructions for common rheumatology drugs. There was no significant difference in word recognition, functional health literacy, and numeracy between rural and urban rheumatology patients.
Statistical Dependency Parsing in Korean: From Corpus Generation To Automatic Parsing

This paper gives two contributions to dependency parsing in Korean. First, we build a Korean dependency Treebank from an existing constituent Treebank. For a morphologically rich language like Korean, dependency parsing shows some advantages over constituent parsing. Since there is not much training data available, we automatically generate dependency trees by applying head-percolation rules and heuristics to the constituent trees. Second, we show how to extract useful features for dependency parsing from rich morphology in Korean. Once we build the dependency Treebank, any statistical parsing approach can be applied. The challenging part is how to extract features from tokens consisting of multiple morphemes. We suggest a way of selecting important morphemes and use only these as features to avoid sparsity. Our parsing approach is evaluated on three different genres using both gold-standard and automatic morphological analysis. We also test the impact of fine vs. coarse-grained morphologies on dependency parsing. With automatic morphological analysis, we achieve labeled attachment scores of 80%+. To the best of our knowledge, this is the first time that Korean dependency parsing has been evaluated on labeled edges with such a large variety of data.
A new algorithm for signal emitter recognition

This paper proposes a new algorithm for signal emitter recognition. It can recognize different emitters using the results of the TDOA/AOA joint location algorithm. Simulation results show that the accurate recognition rate of TDOA/AOA joint location algorithm is higher than that of either the TDOA or AOA location algorithm. If the distance between different signal emitters is more than 800 meters, the accurate recognition rate will be higher than 90%. Additionally, the recognition rate is almost not affected by the arrangement of the location equipments.
Active Calibration of Space Variant Sensors

This paper presents new active calibration techniques capable of handling the strong distortions of lenses that exhibit critical features of human-like vision: a wide eld of view for global detection and high resolution at the fovea for precise observation. Those techniques can be achieved online and are based on the combination of controlled camera motion and tracking of environmental features. A self-alignement process of a stereo platform using a similar procedure is also presented.
A novel efficient kernelized fuzzy C-means with additive bias field for brain image segmentation

In this paper, a suitable novel algorithm has been proposed for segmenting the brain magnetic resonance imaging (MRI) data using an efficient kernelized fuzzy c-means (EKFCM) with spatial constraints. In this proposed algorithm, the Euclidean distance in the standard fuzzy c-means (FCM) is replaced by a Gaussian radial basis function with additive bias. The proposed method will segment the given MRI data automatically, by considering the effects of intensity inhomogeneity, partial volume and noise. The neighbourhood effect acts as a regularizer, and the regularization term is useful in segmenting the MR Imaging corrupted by noise and intensity inhomogeneity. Experimental results on both real and simulated images, prove that the proposed algorithm has higher segmenting accuracy than other segmenting techniques.
VolunteerLive: Introducing Volunteer Nodes into P2P Live Streaming

In P2P live streaming system, service will be degraded when thousands of semi-riders, peers with very limited outbound bandwidth, concurrently join. Due to the limited outbound bandwidth, a semi-rider peer always gets more data than its contributions. In this paper, we propose VolunteerLive, an incentive-based P2P live streaming model, to address this issue. In VolunteerLive, these asymmetrical users are encouraged to "deposit" their bandwidth resources to relay data using their network bandwidth resources. They can enjoy the services as semi-riders in the future. We also propose ContriMax, a heuristics data scheduling algorithm designed for volunteers to collect and maximize the contributions of them. Simulations have been conducted to evaluate the performance of the proposed VolunteerLive and ContriMax. The results show that VolunteerLive model is feasible to support more semi-riders and greatly decrease the stress on the media server.
New observations on the influence of dance on body image and development of eating disorders

Abstract Studies indicate that female dance students are more preoccupied with weight, eating habits, and body image than girls in the general population and are in greater danger of developing eating disorders. In this study, questionnaires were distributed to 90 females aged 15–30; 47 dancers or former dancers and 43 non-dancers. Consistent with prior studies, BMI had a positive and significant contribution to predicting eating disorders. Surprisingly, no statistical difference was found between the two groups with regard to body image, opinions about eating, or eating behaviors. This finding contradicts prior research and merits further examination given the popularity and health benefits of dance training.
Browser-oriented universal cross-site recommendation and explanation based on user browsing logs

Our research aims to bridge the gap between different websites to provide cross-site recommendations based on browsers. Recent advances have made recommender systems essential to various online applications, such as e-commerce, social networks, and review service websites. However, practical systems mainly focus on recommending inner-site homogeneous items. For example, a movie review website usually recommends other movies within the site when a user has enjoyed a movie online. However, it would be exciting if the system recommends some attractive products related to this movie from some e-commerce websites like Amazon or eBay. Such an ability to provide heterogeneous cross-site recommendations may shed light on brand new and promising business models, which could benefit both the online shops in expanding the marketing efforts, and the online users in discovering items of interest from a wider scope. In this research, we propose and formalize the problem of universal recommendation, record and analyze user browsing actions in web browsers, and provide browser-oriented cross-site recommendations when the users are surfing online.
Study of a microwave ferrite resonator antenna, based on a ferrimagnetic composite (Gd3Fe5O12)GdIGX–(Y3Fe5O12)YIG1−X

The authors report a study on microwave properties of a ferrimagnetic ceramic composite (Gd 3 Fe 5 O 12 )GdIG x- (Y 3 Fe 5 O 12 )YIG 1-x . The magnetic and dielectric measurements at microwave frequency were made through the Hakki-Coleman-s procedure and through the excitation of a cylindrical ferrite resonator antenna (FRA). The hysteresis loops of the GdIG x YIG 1-x ferrimagnetic composite were obtained. The numerical simulation study was performed using Ansoft's High Frequency Structure Simulator (HFSS') software. The agreement between the experimental data and the simulated results is very good. These results demonstrated that, by varying the material composition of the resonator, ferrimagnetic composite GdIG x YIG 1-x could operate as a magneto-dielectric antenna with bandwidth in the range of 7.5-11- and in the frequency range of 4.4-5.3-GHz. Additionally, all FRAs presented a low negative value of tau f , which indicates suitability for microwave applications such as mobile communication systems or satellite broadcast systems.
Perceived Control: Scales for Privacy in Ubiquitous Computing

Ubiquitous computing (UC) environments have triggered a strong research interest in privacy. How can people remain private when the infrastructure and objects around them begin to talk? Heading for an answer to this question many studies have rushed over past years to present guidelines for privacy-friendly UC design and have tempted even to rewrite the vocabulary of this socio-psychological construct. In doing so, most authors notice though that when it comes to requirements specification for privacy in UC, user-friendly technology design is really more about perceived control than it actually is about the end state of privacy itself. The current position statement therefore attempts to pull the two constructs - privacy and control - apart by theoretically reflecting on their mutual dependencies. It then proceeds by proposing a scale for appropriate measurement of perceived control in UC environments.
Quantitative global dataflow analysis on virtual instruction set simulators for hardware/software co-design

One of the main challenges in system design whether for high performance computing or in embedded systems is to partition software for target architectures like multi-core, heterogeneous, or even hardware/software co-design systems. Several compiler techniques handle partitioning and related problems by using static analysis and therefor have no means to capture the global data flow in quantity and its dynamics which is essential for extracting tasks or exploiting coarse grained parallelism. We present a novel solution for capturing and analyzing an applicationpsilas quantitative data flow in this paper. The core part is the LLILA (Low Level Intermediate Language Analyzer) tool set, which automatically generates and augments self-profiling instruction set simulators from assembly level descriptions for a virtual machine. During run-time of the augmented program several properties (frequency, quantity and locality reflecting inter-procedural communication) of data exchange are captured at instruction level and as a consequence in the highest possible degree of accuracy.
Decomposing power measurements for mobile devices

Modern mobile phones are an appealing platform for pervasive computing applications. However, the complexity of these devices makes it difficult for developers to understand the power consumption of their applications. Our measurement framework is the first we have seen which can produce fine-grained, annotated traces of a phone's power consumption and is designed to develop an understanding of how particular aspects of an application drive energy use. We are using our framework to analyse the power consumption of Android-based G1 and Magic handsets and show that particular choices of message size and send buffer can alter the energy required to send data by an order of magnitude in certain cases.