Miracle-dz/UniFAR-FTUs huggingface dataset:
Refinement-based student modeling and automated bug library construction

A c r i t i c al c omponent of model bas ed i nt el l i gent t ut or i ng s y s t ems i s a mec hani s m f or c apt ur i ng t he c onc ept ual s t at e of t he s t udent , whi c h enabl es t he s y s t em t o t ai l or i t s f eedbac k t o s ui t i ndi v i dual s t r engt hs and weak nes s es . To be us ef ul s uc h a model i ng t ec hni que mus t be pr ac t i c al , i n t he s ens e t hat model s ar e eas y t o c ons t r uc t , and ef f ec t i v e , i n t he s ens e t hat us i ng t he model ac t ual l y i mpac t s s t udent l ear ni ng. Thi s r es ear c h pr es ent s a new s t udent model i ng t ec hni que whi c h c an aut omat i c al l y c apt ur e nov el s t udent er r or s us i ng onl y c or r ec t domai n k nowl edge, and c an aut omat i c al l y c ompi l e t r ends ac r os s mul t i pl e s t udent model s . Thi s appr oac h has been i mpl ement ed as a c omput er pr ogr am, A SSERT , us i ng a mac hi ne l ear ni ng t ec hni que c al l ed t heor y r ef i nement , whi c h i s a met hod f or aut omat i c al l y r ev i s i ng a k nowl edge bas e t o be c ons i s t ent wi t h a s et of ex ampl es . Us i ng a k nowl edge bas e t hat c or r ec t l y def i nes a domai n and ex ampl es of a s t udent ’ s behav i or i n t hat domai n, A SSERT model s s t udent er r or s by c ol l ec t i ng any r ef i nement s t o t he c or r ec t k nowl edge bas e whi c h ar e nec es s ar y t o ac c ount f or t he s t udent ’ s behav i or . The ef f i c ac y of t he appr oac h has been demons t r at ed by ev al uat i ng A SSERT us i ng 100 s t udent s t es t ed on a c l as s i f i c at i on t as k c ov er i ng c onc ept s f r om an i nt r oduc t or y c our s e on t he C ++ pr ogr ammi ng l anguage. St udent s who r ec ei v ed f eedbac k bas ed on t he model s aut omat i c al l y gener at ed by A SSERT per f or med s i gni f i c ant l y bet t er on a pos t t es t t han s t udent s who r ec ei v ed s i mpl e r et eac hi ng.
Minimising latency of pitch detection algorithms for live vocals on low-cost hardware

A pitch estimation device was proposed for live vocals to output appropriate pitch data through the musical instrument digital interface (MIDI). The intention was to ideally achieve unnoticeable latency while maintaining estimation accuracy. The projected target platform was low-cost, standalone hardware based around a microcontroller such as the Microchip PIC series. This study investigated, optimised and compared the performance of suitable algorithms for this application. Performance was determined by two key factors: accuracy and latency. Many papers have been published over the past six decades assessing and comparing the accuracy of pitch detection algorithms on various signals, including vocals. However, very little information is available concerning the latency of pitch detection algorithms and methods with which this can be minimised. Real-time audio introduces a further latency challenge that is sparsely studied, minimising the length of sampled audio required by the algorithms in order to reduce overall total latency. Thorough testing was undertaken in order to determine the best-performing algorithm and optimal parameter combination. Software modifications were implemented to facilitate accurate, repeatable, automated testing in order to build a comprehensive set of results encompassing a wide range of test conditions. The results revealed that the infinite-peak-clipping autocorrelation function (IACF) performed better than the other autocorrelation functions tested and also identified ideal parameter values or value ranges to provide the optimal latency/accuracy balance. Although the results were encouraging, testing highlighted some fundamental issues with vocal pitch detection. Potential solutions are proposed for further development.
A Design Approach for Tangible User Interfaces

This paper proposes a mechanism to design Tangible User Interface (TUI) based on Alexander’s (1964) design approach i.e. achieving fitness between the form and its context. Adapted to the design of TUIs, the fitness-of-use mechanism now takes into consideration the potential conflicts between the hardware of the artifact (electro-mechanical components) and the form of the user’s control (Physical-ergonomics). The design problem is a search for an effortless co-existence (fitness-of-use) between these two aspects. Tangible interface design differs from traditional graphical interface design as unsolved conflicts between hardware and ergonomics can deeply affect the desired interaction. Here we propose a mechanism (in the form of eight questions) that support the design by defining the boundaries of the task, orienting the hardware (electro-mechanics) and ergonomics of the design space for various sub-tasks and finally fitting the different components of the hardware and physical-ergonomics of the artefact to provide a component level fitness which will delineate the final tangible interfaces. We further evaluate the effectiveness and efficiency of our approach by quantitative user evaluation
Classifier Ensembles with a Random Linear Oracle

We propose a combined fusion-selection approach to classifier ensemble design. Each classifier in the ensemble is replaced by a miniensemble of a pair of subclassifiers with a random linear oracle to choose between the two. It is argued that this approach encourages extra diversity in the ensemble while allowing for high accuracy of the individual ensemble members. Experiments were carried out with 35 data sets from UCI and 11 ensemble models. Each ensemble model was examined with and without the oracle. The results showed that all ensemble methods benefited from the new approach, most markedly so random subspace and bagging. A further experiment with seven real medical data sets demonstrates the validity of these findings outside the UCI data collection
Brain Plasticity and Hand Surgery: an Overview

The hand is an extension of the brain, and the hand is projected and represented in large areas of the motor and sensory cortex. The brain is a complicated neural network which continuously remodels itself as a result of changes in sensory input. Such synaptic reorganizational changes may be activity-dependent, based on alterations in hand activity and tactile experience, or a result of deafferentiation such as nerve injury or amputation. Inferior recovery of functional sensibility following nerve repair, as well as phantom experiences in virtual, amputated limbs are phenomena reflecting profound cortical reorganizational changes. Surgical procedures on the hand are always accompanied by synaptic reorganizational changes in the brain cortex, and the outcome from many hand surgical procedures is to a large extent dependent on brain plasticity.
Bio-inspired computation: success and challenges of IJBIC

It is now five years since the launch of the International Journal of Bio-Inspired Computation IJBIC. At the same time, significant new progress has been made in the area of bio-inspired computation. This review paper summarises the success and achievements of IJBIC in the past five years, and also highlights the challenges and key issues for further research.
Dual band planar hybrid coupler with enhanced bandwidth using particle swarm optimization technique

This paper presents the design procedure, and implementation of a dual band planar quadrature hybrid with enhanced bandwidth. The topology of the circuit is a dual stage quadrature hybrid, which provides much larger flexibility to allocate the desired operating frequencies and necessary bandwidth than other previously published configurations. In this paper, small dual frequency transformers in two sections are used to modify conventional broad band hybrid coupler for having arbitrary dual band operation frequencies. This performance of the proposed coupler is verified by using commercial simulators and measurements. To this aim, by merging compilers and full-wave simulators, particle swarm optimization is used to achieve proper values to have desired goals. Finally, a dual stage quadrature hybrid for dual band (2.4 and 5.8 GHz) wireless local area network systems has been fabricated, aimed to cover the bands corresponding to the standards IEEE802.11n. The measured results validate good dual band performance at 2.4/5.8 GHz with enhanced bandwidths up to 12.5% and 25%, for the lower and upper bandwidth, respectively which satisfies the bandwidth requirement for the this standard.
A Unified Framework for Coupling Measurement in Object-Oriented Systems

The increasing importance being placed on software measurement has led to an increased amount of research developing new software measures. Given the importance of object-oriented development techniques, one specific area where this has occurred is coupling measurement in object-oriented systems. However, despite a very interesting and rich body of work, there is little understanding of the motivation and empirical hypotheses behind many of these new measures. It is often difficult to determine how such measures relate to one another and for which application they can be used. As a consequence, it is very difficult for practitioners and researchers to obtain a clear picture of the state of the art in order to select or define measures for object-oriented systems. This situation is addressed and clarified through several different activities. First, a standardized terminology and formalism for expressing measures is provided which ensures that all measures using it are expressed in a fully consistent and operational manner. Second, to provide a structured synthesis, a review of the existing frameworks and measures for coupling measurement in object-oriented systems takes place. Third, a unified framework, based on the issues discovered in the review, is provided and all existing measures are then classified according to this framework. This paper contributes to an increased understanding of the state-of-the-art.
Emotional Communication with Virtual Humans

In this paper, we present our approach to modelling perceptive 3D virtual characters with emotion and personality. The characters are powered by a dialogue system that consists of a large set of basic interactions between the user and the computer. These interactions are encoded in finite state machines. The system is integrated with an expression recognition system, that tracks a user’s face in real-time and obtains expression data. Also, the system includes a personality and emotion simulator, so that the character responds naturally to both the speech and the facial expressions of the user. The virtual character is represented by a 3D face that performs the speech and facial animation in real-time, together with the appropriate facial expressions.
Retrieving contact points without environment knowledge

This paper paves the way for contact retrieving of human motions without environment knowledge. The goal is to find out the minimal set of contacting links of the human body, that is required to perform a recorded motion. First, we fit the captured motion to a unified representation of the human: the Master Motor Map. Looking at the Minimal Oriented Bounding Boxes of the velocity and acceleration for every link, we determine whether one part of the link is moving or not. This provides an initial guess of the contacting links. Then, based on the dynamic equations of the model, we find the minimal set of contacting links that ensure the balance. Eventually, we assess this method on several motions with actual and pretended contacts. We show that it is efficient for motions such as walking and that it deserves to be improved for more complex motions with a lot of contact points.
Genetic Algorithm for feature selection : application to prediction of mortality during hypotensive episodes in patients with sepsis and severe sepsis Louis Mayaud ,

This document describes the algorithm used to select features for prediction of mortality during the first hypotensive episode requiring medical intervention in a population of patients with sepsis and severe sepsis. Results are compared with state-of-the-art feature selection techniques and shown equivalent performance. The potential of the Genetic Algorithm as an optimization technique is briefly discussed. The code, on which this research is based, is freely available on Google Code1.
Model-Based Learning with Hierarchical Relational Skills

In this paper we describe Icarus, an architecture for physical agents that uses hierarchical skills to support reactive execution. We review an earlier version of the system, then present an extended framework that associates reward with stored concepts and utilizes a model-based approach to select among instantiated skills. Learning involves estimating expected the durations and success probabilities from execution traces. We conclude with comments on related work and plans for further extensions.
Bioinformatics Applications Note Genetics and Population Analysis Topiaryexplorer: Visualizing Large Phylogenetic Trees with Environmental Metadata

Motivation: Microbial community profiling is a highly active area of research, but tools that facilitate visualization of phylogenetic trees and associated environmental data have not kept up with the increasing quantity of data generated in these studies. Results: TopiaryExplorer supports the visualization of very large phylogenetic trees, including features such as the automated coloring of branches by environmental data, manipulation of trees and incorporation of per-tip metadata (e.g. taxonomic labels).
Dynamic Resource Management for Longevity in Web Server Systems

As the Internet became a popular source of information, more and more people are using the Internet in their everyday life. Therefore, for the servers that maintain web page sites get a lot of transactions and to maintain a stable environment, a lot of web sites have more than one server for these transaction requests. A common architecture to balance the transactional load is by using a L7 switch to distribute the requests. The current L7 switch utilizes methods that cannot sustain the web site for long if there are dynamic interactive pages. There have been researches to load balance web sites for static web pages. However, as more and more web pages become dynamic and interactive, there needed to be a method that prolongs the web site crashes without buying large number of servers. Our methods use explicit CPU utilization information to dynamically decide which transactional request is mapped where. Using our methods, the longevity (the length of the web site remains open) of a website is higher than other researched/utilized methods.
Intonational speaker verification: A study on parameters and performance under noisy conditions

Prosody-based speaker verification using fundamental frequency (f0) is considered. Our study consists of two phases. First, we do extensive optimization of parameters to establish a baseline system before dealing with noisy conditions. This includes a study of f0 extractor parameters, choice of features (discrete cosine transform, discrete Fourier transform, Legendre polynomials, linear prediction), f0 track interpolation (none, linear, Hermite), framing parameters and windowing (none, Hamming), f0 representation domain (linear, log), number of transformation coefficients and, finally, use of higher-level delta coefficients. Using the optimized parameters, we then explore the robustness of prosody features under white noise and factory noise degradations. Using a GMM-UBM system on the NIST 2006 SRE corpus, we reach an EER of 28.4 % and 27.6 % for the intonational and MFCC features respectively at -20 dB SNR white noise contamination; fusion of the two yields an EER of 24.38 %.
Inhibitors of Leishmania mexicana CRK3 Cyclin-Dependent Kinase: Chemical Library Screen and Antileishmanial Activity

ABSTRACT The CRK3 cyclin-dependent kinase of Leishmania has been shown by genetic manipulation of the parasite to be essential for proliferation. We present data which demonstrate that chemical inhibition of CRK3 impairs the parasite's viability within macrophages, thus further validating CRK3 as a potential drug target. A microtiter plate-based histone H1 kinase assay was developed to screen CRK3 against a chemical library enriched for protein kinase inhibitors. Twenty-seven potent CRK3 inhibitors were discovered and screened against Leishmania donovani amastigotes in vitro. Sixteen of the CRK3 inhibitors displayed antileishmanial activity, with a 50% effective dose (ED50) of less than 10 μM. These compounds fell into four chemical classes: the 2,6,9-trisubstituted purines, including the C-2-alkynylated purines; the indirubins; the paullones; and derivatives of the nonspecific kinase inhibitor staurosporine. The paullones and staurosporine derivatives were toxic to macrophages. The 2,6,9-trisubstituted purines inhibited CRK3 in vitro, with 50% inhibitory concentrations ranging from high nanomolar to low micromolar concentrations. The most potent inhibitors of CRK3 (compounds 98/516 and 97/344) belonged to the indirubin class; the 50% inhibitory concentrations for these inhibitors were 16 and 47 nM, respectively, and the ED50s for these inhibitors were 5.8 and 7.6 μM, respectively. In culture, the indirubins caused growth arrest, a change in DNA content, and aberrant cell types, all consistent with the intracellular inhibition of a cyclin-dependent kinase and disruption of cell cycle control. Thus, use of chemical inhibitors supports genetic studies to confirm CRK3 as a validated drug target in Leishmania and provides pharmacophores for further drug development.
Models of Cognition: Neurological possibility does not indicate neurological plausibility

Many activities in Cognitive Science involve complex computer models and simulations of both theoretical and real entities. Artificial Intelligence and the study of artificial neural nets in particular, are seen as major contributors in the quest for understanding the human mind. Computational models serve as objects of experimentation, and results from these virtual experiments are tacitly included in the framework of empirical science. Cognitive functions, like learning to speak, or discovering syntactical structures in language, have been modeled and these models are the basis for many claims about human cognitive capacities. Artificial neural nets (ANNs) have had some successes in the field of Artificial Intelligence, but the results from experiments with simple ANNs may have little value in explaining cognitive functions. The problem seems to be in relating cognitive concepts that belong in the `top-down' approach to models grounded in the `bottom-up' connectionist methodology. Merging the two fundamentally different paradigms within a single model can obfuscate what is really modeled. When the tools (simple artificial neural networks) to solve the problems (explaining aspects of higher cognitive functions) are mismatched, models with little value in terms of explaining functions of the human mind are produced. The ability to learn functions from data-points makes ANNs very attractive analytical tools. These tools can be developed into valuable models, if the data is adequate and a meaningful interpretation of the data is possible. The problem is, that with appropriate data and labels that fit the desired level of description, almost any function can be modeled. It is my argument that small networks offer a universal framework for modeling any conceivable cognitive theory, so that neurological possibility can be demonstrated easily with relatively simple models. However, a model demonstrating the possibility of implementation of a cognitive function using a distributed methodology, does not necessarily add support to any claims or assumptions that the cognitive function in question, is neurologically plausible.
Simultaneously Learning and Optimizing Using Controlled Variance Pricing

Price experimentation is an important tool for firms to find the optimal selling price of their products. It should be conducted properly, since experimenting with selling prices can be costly. A firm, therefore, needs to find a pricing policy that optimally balances between learning the optimal price and gaining revenue. In this paper, we propose such a pricing policy, called controlled variance pricing CVP. The key idea of the policy is to enhance the certainty equivalent pricing policy with a taboo interval around the average of previously chosen prices. The width of the taboo interval shrinks at an appropriate rate as the amount of data gathered gets large; this guarantees sufficient price dispersion. For a large class of demand models, we show that this procedure is strongly consistent, which means that eventually the value of the optimal price will be learned, and derive upper bounds on the regret, which is the expected amount of money lost due to not using the optimal price. Numerical tests indicate that CVP performs well on different demand models and time scales. This paper was accepted by Assaf Zeevi, stochastic models and simulation.
Exploitation of producer intent in relation to bandwidth and QoE for online video streaming services

This paper is the product of recent advances in research on users' intent during multimedia content retrieval. Our goal is to save bandwidth while streaming video clips from a browsable on-demand service, while maintaining or even improving the users' quality of experience (QoE). Understanding user intent allows us to predict whether streaming a particular video in a low quality constitutes a reduced QoE for a user. However, many VoD streaming services today are used by users for a wide variety of reasons, meaning that user intent cannot be inferred from their use of the service alone. However, our investigation demonstrates that user intent does in most cases coincide with producer intent. We can also demonstrate that the latter can be inferred from the content itself as well as associated metadata. By transitivity, we can choose a default video quality that satisfies the users QoE in the majority of cases.
FRL-1, a member of the EGF-CFC family, is essential for neural differentiation in Xenopus early development

Recent studies indicate an essential role for the EGF-CFC family in vertebrate development, particularly in the regulation of nodal signaling. Biochemical evidence suggests that EGF-CFC genes can also activate certain cellular responses independently of nodal signaling. Here, we show that FRL-1, a Xenopus EGF-CFC gene, suppresses BMP signaling to regulate an early step in neural induction. Overexpression of FRL-1 in animal caps induced the early neural markers zic3, soxD and Xngnr-1, but not the pan-mesodermal marker Xbra or the dorsal mesodermal marker chordin. Furthermore, overexpression of FRL-1 suppressed the expression of the BMP-responsive genes, Xvent-1 and Xmsx-1, which are expressed in animal caps and induced by overexpressed BMP-4. Conversely, loss of function analysis using morpholino-antisense oligonucleotides against FRL-1 (FRL-1MO) showed that FRL-1 is required for neural development. FRL-1MO-injected embryos lacked neural structures but contained mesodermal tissue. It was suggested previously that expression of early neural genes that mark the start of neuralization is activated in the presumptive neuroectoderm of gastrulae. FRL-1MO also inhibited the expression of these genes in dorsal ectoderm, but did not affect the expression of chordin, which acts as a neural inducer from dorsal mesoderm. FRL-1MO also inhibited the expression of neural markers that were induced by chordin in animal caps, suggesting that FRL-1 enables the response to neural inducing signals in ectoderm. Furthermore, we showed that the activation of mitogen-activated protein kinase by FRL-1 is required for neural induction and BMP inhibition. Together, these results suggest that FRL-1 is essential in the establishment of the neural induction response.