Miracle-dz/UniFAR-FTUs huggingface dataset:
A low-power analog logarithmic map circuit with offset and temperature compensation for use in bionic ears

Logarithmic map circuits are useful in many applications that require non-linear signal compression, such as in speech recognition and cochlear implants. A logarithmic current-mode A/D converter with temperature compensation and automatic offset calibration is presented in this paper. It employs a dual-slope, auto-zeroing topology with a 60 dB dynamic range and 300 Hz sampling rate, for capturing the envelope of speech signals in a bionic ear. Fabricated in a 1.5 μm process, the circuit consumes only 1 μW of analog power and another 1 μW of digital power, and can therefore run for over 50 years on just a couple of AA batteries. At the current level of power consumption, we have proven that this design is thermal-noise limited to a 6-bit precision, and higher precision is possible only if we expend more power. As such, it is already useful for cochlear implants, as deaf patients can only discriminate 1 dB out of a 30 dB dynamic range in the auditory nerve bundles. For the purpose of using this circuit in other applications, we conclude with several strategies that can increase the precision without hurting the power consumption. Thesis supervisor: Rahul Sarpeshkar Title: Assistant Professor of Electrical Engineering
Rapid speaker adaptation with speaker adaptive training and non-negative matrix factorization

In this paper, we describe a novel speaker adaptation algorithm based on Gaussian mixture weight adaptation. A small number of latent speaker vectors are estimated with non-negative matrix factorization (NMF). These base vectors encode the correlations between Gaussian activations as learned from the train data. Expressing the speaker dependent Gaussian mixture weights as a linear combination of a small number of base vectors, reduces the number of parameters that must be estimated from the enrollment data. In order to learn meaningful correlations between Gaussian activations from the train data, the NMF-based weight adaptation was combined with vocal tract length normalization (VTLN) and feature-space maximum likelihood linear regression (fMLLR) based speaker adaptive training based. Evaluation on the 5k closed and 20k open vocabulary Wall Street Journal tasks shows a 4% relative word error rate reduction over the speaker independent recognition system which already incorporates VTLN. The proposed fast adaptation algorithm, using a single enrollment sentence only, results in similar performance as fMLLR adapting on 40 enrollment sentences.
Automated Segmentation for the Brain Connectome using a Multi-Scale Parallel Computing Architecture

The Brain Connectome project is a multi-institution project aimed at creating a graph of all connections between brain cells to better understand the brain circuitry and to explore the causes of neurodegenerative diseases [1]–[3]. Today’s challenge for neurobiologists is to segment the volumetric datasets of the brain imaged using electron microscopy [15]– [21]. Although an expert-supervised dense segmentation of these multi-terabyte datasets is desirable, a sparse and automated segmentation representing a tractable number of anatomical shapes would provide a huge leap in terms of speed of scientific discovery. Observing the multi-scale nature of anatomical shapes, such as large nuclei and elongated dendrites [22], [23], we designed a multi-scale segmentation architecture that offers both the scalability to analyze massive datasets and the usability required in an interdisciplinary research environment. We detail the methodology that has led to our computational architecture and report our first results on our 19-Terabyte 3D dataset of the visual cortex.
Improving the DoD's Tooth-to-Tail Ratio. Revision

Abstract : It is projected that the Department of Defense (DoD) will see a funding reduction of $487 billion over the next 10 years (Office of Management and Budget [OMB], 2013). In order to stay within budget, the DoD plans to implement targeted reductions in force structure, reprioritize key missions and the requirements that support them, promote efficiency improvements in acquisition, and continue to reform other business practices. However, these efforts, at least in their current form, will prove insufficient. The Congressional Budget Office (CBO) asserts that the DoD s costs will soon outstrip its budget as expenditures for manpower, maintenance, and health care continue to increase, thereby eliminating the funds necessary for the planned recapitalization, modernization, and transformation of the military (CBO, 2013). The DoD must make hard decisions in order to prevent such an outlook from becoming a reality. In the past, the DoD has reduced the number of military personnel (and to a lesser extent, equipment orders and program funding) in order to constrain costs. At present, however, the active military force structure is already near an all-time low, and existing equipment inventories are becoming older, smaller, and less effective against emerging technologies. It is within this challenging environment that the DoD must strive to improve its tooth-to-tail ratio. This term, familiar to defense analysts, refers to the relative level of support personnel (military, civilian, and contractor) required to maintain combat forces. The tooth refers to the personnel that train for and perform operational missions, whereas the tail refers to the personnel that support the combat forces. As of 2011, the active-duty military end-strength was 1,459,409 (BLS, 2012). Of these personnel, only 17% are identified as performing combat specialties.
Grasping the object with collision avoidance of wheeled mobile manipulator in dynamic environments

In this paper, the authors proposed a local motion planner with robot controller of the mobile manipulator to grasp the object in dynamic environments without any prior knowledge of environments. Our local motion planner is based on the concept of potential field and composed of the attractive and repulsive vectors. Then, the local motion planner decides the potential vector according to the attractive and repulsive vectors in various situations. Also, an approach to deal with the drawback of local minima is contained. The attractive and repulsive vectors are generated by the distances between the target, obstacles and the manipulator. For robot control, we take the end-effector as the control point and apply the potential vector with joint-level control, and moreover evaluate the mobility and the kinematic constraints of the robot to modify the joint velocities. The experiment platform is a wheeled mobile robot with a 5-DOF manipulator using Softkinetic DS325 which is a close range RGB-D camera as our sensor. Through several experiments, the results show that our framework is fast enough and valid to grasp the object in dynamic environments.
Design by physical composition for complex tangible user interfaces

In this paper, we present a novel approach to create devices with tangible user interfaces by physical com-position. While the separation of the user interface from the application logic has a long tradition in software engineering, for products with tangible user interfaces there is no equivalent approach that realizes a true separation and flexible combination of interface components, underlying technology, and software parts. We propose a novel concept that is based on an inner Core for the basic technical and software platform of a product and an outer Shell that builds a flexible and ex-changeable tangible user interface from passive components. Using vision-based tracking, we can realize a clear separation between the components. No wiring is necessary. This paper introduces our novel approach and presents a first working prototype as well as initial results from its application in a design workshop.
Rich Linguistic Knowledge for Empirical Machine Translation

In this work, a new architecture for Empirical Machine Translation is suggested. We build a state-of-the art Phrase-based Statistical Machine Translation system and study different alternatives so as to provide it with rich linguistic knowledge. Natural Language Processing technology and external knowledge sources are suavely integrated into the system. We utilize existing resources and develop new ones. We have tested our approach in two tasks: the Spanish-to-English translation of parliament proceedings and the English-to-Spanish translation of dictionary definitions. Initial results, based on the utilization of shallow syntactic analysis techniques and lexical databases, suggest that significant improvements may be attained by working with rich linguistic knowledge. Further steps are devised in a detailed work plan. We intend to move from syntax onto semantics by incorporating information about word senses and semantic roles. Additionally, we consider also the possibility of working on a hybrid system combining the best properties of empirical-based and rule-based approaches. We also plan to work on new language pairs, particulary Catalan-English and Catalan-Spanish.
The improved Turbo-decoding Message-passing algorithm and corresponding decoder for LDPC based on LTE

The Turbo-decoding Message-passing (TDMP) algorithm of Low-Density Parity-Check (LDPC) codes has a faster convergence speed, lower hardware implementation complexity, and less storage units than the Belief-Passing (BP) algorithms. However, because of the integer quantization operations for initial information, restriction of storage units will cause the problem of decoding information overflowing. This paper gives the reason of overflow errors, proposes the improved decoding algorithm which can partially eliminate overflow errors, and designs the corresponding decoder which only requires some extra subtractors and shift operations. We analyze the computation complexity and compute decoder throughput. Finally, we simulate the error performances of the LDPC codes over the LTE channel, and simulation results show that the proposed algorithm effectively suppresses the overflow errors with a low decoder complexity and a high throughput.
Acquiring Selectional Preferences in a Thai Lexical Database

In this paper, we consider the problem of enriching a Thai lexical database by extending the semantic information with selectional preferences. We propose a novel approach for acquiring selectional preferences of verbs, which is motivated by the tree cut model. We apply a model selection technique called the Bayesian Information Criterion (BIC). Given a semantic hierarchy, our goal is to generalize initial noun classes to the most plausible levels on that hierarchy. We present an iterative algorithm for generalization. The algorithm performs agglomerative merging on the semantic hierarchy in a bottomup manner. The BIC is used to measure the improvement of the model both locally and globally. In our experiments, we consider the Web as large corpora. We also propose approaches for extracting examples from the Web. Preliminarily experimental results are given to show the feasibility and effectiveness of our approach.
A Caudal Proliferating Growth Center Contributes to Both Poles of the Forming Heart Tube

Recent studies have shown that the primary heart tube continues to grow by addition of cells from the coelomic wall. This growth occurs concomitantly with embryonic folding and formation of the coelomic cavity, making early heart formation morphologically complex. A scarcity of data on localized growth parameters further hampers the understanding of cardiac growth. Therefore, we investigated local proliferation during early heart formation. Firstly, we determined the cell cycle length of primary myocardium of the early heart tube to be 5.5 days, showing that this myocardium is nonproliferating and implying that initial heart formation occurs solely by addition of cells. In line with this, we show that the heart tube rapidly lengthens at its inflow by differentiation of recently divided precursor cells. To track the origin of these cells, we made quantitative 3D reconstructions of proliferation in the forming heart tube and the mesoderm of its flanking coelomic walls. These reconstructions show a single, albeit bilateral, center of rapid proliferation in the caudomedial pericardial back wall. This center expresses Islet1. Cell tracing showed that cells from this caudal growth center, besides feeding into the venous pole of the heart, also move cranially via the dorsal pericardial mesoderm and differentiate into myocardium at the arterial pole. Inhibition of caudal proliferation impairs the formation of both the atria and the right ventricle. These data show how a proliferating growth center in the caudal coelomic wall elongates the heart tube at both its venous and arterial pole, providing a morphological mechanism for early heart formation.
Magnetorotational instability in stratified, weakly ionized accretion discs

We present a linear analysis of the vertical structure and growth of the magnetorotational instability in stratified, weakly ionized accretion discs, such as protostellar and quiescent dwarf novae systems. The method includes the effects of the magnetic coupling, the conductivity regime of the fluid and the strength of the magnetic field, which is initially vertical. The conductivity is treated as a tensor and is assumed to be constant with height. We obtained solutions for the structure and growth rate of global unstable modes for different conductivity regimes, strengths of the initial magnetic field and coupling between ionized and neutral components of the fluid. The envelopes of short-wavelength perturbations are determined by the action of competing local growth rates at different heights, driven by the vertical stratification of the disc. Ambipolar diffusion perturbations peak consistently higher above the midplane than modes including Hall conductivity. For weak coupling, perturbations including the Hall effect grow faster and act over a more extended cross-section of the disc than those obtained using the ambipolar diffusion approximation. Finally, we derived an approximate criterion for when Hall diffusion determines the growth of the magnetorotational instability. This is satisfied over a wide range of radii in protostellar discs, reducing the extent of the magnetic ‘dead zone’. Even if the magnetic coupling is weak, significant accretion may occur close to the midplane, rather than in the surface regions of weakly ionized discs.
Refactoring and its Relationship with Fan-in and Fan-out: An Empirical Study

Many of the seventy-two refactorings originally proposed by Fowler have the aim of reducing coupling in classes and thereby aiding programmer maintainability. While we might assume that classes with high levels of coupling would be the targets for refactoring more often than any other type of class, no empirical evidence exists to support this assumption. In this paper, we explore that open question through the extraction of fifty-two of Fowler's catalog of refactorings drawn from versions of four open-source systems. We compare the coupling characteristics of each set of refactored classes with the corresponding set of non-refactored classes (those for which no refactorings were applied across versions), we seek to inform one overriding research question: is there a significant difference between these two sets of classes in terms of their level of coupling? Results showed that highly-coupled classes were more prone to refactoring, particularly through a set of 'core' refactorings. However, wide variations were found across systems for our measures of coupling namely, fan-in and fan-out. Specific individual refactorings were also explored to gain an understanding of why these differences may have occurred.
Study on the grain size, valence state and electrical properties of bismuth ferrite nanofibers

We report the effect of diameter on the composition, optical, and electronic properties of the BiFeO3 (BFO) nanofibers. Bismuth ferrite nanofibers with different diameter (20 to 150nm) have been fabricated by a sol gel based electrospinning route. The effect of quantum confinement has been found to influence the photoconductivity, grain size and optical properties of the nanofibers. A shift in the band gap to 2.1 eV was observed as a result of the variation on the nanofiber diameter. The position and intensity of the Raman peaks in the low wavenumber are found to shift depending on the diameter due to local stress in the nanofiber. Transmission electron microscopy revealed the nanocrystalline morphology. The composition analysis through energy dispersive detector and electron energy loss spectroscopy revealed the heterogeneous nature of the composition with Bi-rich and Fe-rich regions. X-ray photoelectron spectroscopy results confirmed the combination of Fe3+ and Fe2+ valence state in the nanofibers with a major contribution from Fe3+ which varies with the nanofiber diameter. Photoconductivity measurements show a considerable increase in the current flowing through the nanofibers when measured under illumination. The photoresponse of the nanofibers is increased considerably with decreasing the diameter. This effect is described by a size dependent surface recombination mechanism.
Iterative Learning of Specified Motions in Task-Space for Redundant Multi-Joint Hand-Arm Robots

This paper proposes an iterative learning control (ILC) scheme for a class of redundant robot arms to acquire the desired control input signals that produce an endpoint trajectory specified in task space. The learning update law of control input signals is constructed only in task space by modifying the previous control input through adding linearly an endpoint velocity trajectory error. Although the dimension of the task space is strictly less than the DOF (degrees-of-freedom) of the robot arm, the proposed method need neither consider any inverse kinematics problem nor introduce any cost function to be optimized and to determine the inverse kinematics (or dynamics) uniquely. Convergence of trajectory trackings to the specified one is shown by numerical simulations in both cases 1) free-endpoint motion and 2) constraint-endpoint motion with specified contact force. A theoretical proof of convergences in the case of free-endpoint motion is given on the basis of an approximated dynamics linearized around a desired solution in joint state space.
Performance evaluation of a Green Scheduling Algorithm for energy savings in Cloud computing

With energy shortages and global climate change leading our concerns these days, the power consumption of datacenters has become a key issue. Obviously, a substantial reduction in energy consumption can be made by powering down servers when they are not in use. This paper aims at designing, implementing and evaluating a Green Scheduling Algorithm integrating a neural network predictor for optimizing server power consumption in Cloud computing. We employ the predictor to predict future load demand based on historical demand. According to the prediction, the algorithm turns off unused servers and restarts them to minimize the number of running servers, thus minimizing the energy use at the points of consumption to benefit all other levels. For evaluation, we perform simulations with two load traces. The results show that the PP20 mode can save up to 46.3% of power consumption with a drop rate of 0.03% on one load trace, and a drop rate of 0.12% with a power reduction rate of 46.7% on the other.
Timing and spectroscopy of accreting X-ray pulsars: the state of cyclotron line studies

A great deal of emphasis on timing in the RXTE era has been on pushing toward higher and higher frequency phenomena, particularly kHz QPOs. However, the large areas of the RXTE pointed instruments provide another capability which is key for the understanding of accreting X‐ray pulsars — the ability to accumulate high quality spectra in a limited observing time. For the accreting X‐ray pulsars, with their relatively modest spin frequencies, this translates into an ability to study broad band spectra as a function of pulse phase. This is a critical tool, as pulsar spectra are strong functions of the geometry of the “accretion mound” and the observers’ viewing angle to the ∼1012 G magnetic field. In particular, the appearance of “cyclotron lines” is sensitively dependent on the viewing geometry, which must change with the rotation of the star. These spectral features, seen in only a handful of objects, are quite important, as they give us our only direct measure of neutron star magnetic fields. Furthermore, .
Least Recently Used Page Replacement using Last Use Distance (LRUL)

Virtual memory technique is used in modern OS which permits the execution of a program while it is partially available in memory thus providing an illusion of very large memory to the user and freeing the user from the concern of large program size. This uses a page replacement technique such as first in first out (FIFO), least recently used (LRU), optimal etc. to replace a page in memory when a frame is needed and no free frame is available in memory. Here page replacement policy severely affects the performance of virtual memory. It has been observed that LRU approximates optimal so LRU and its variants are quite common in use in operating system as a reasonable choice of page replacement algorithm. But LRU performs very poor by generating continuous page faults while accessing looping pattern if all the pages does not fit in the memory simultaneously. This paper presents a simple modified LRU algorithm called LRUL overcoming this problem using the concept of last use distance (LUD). It is observed that the new algorithm gives better results than LRU. General Terms Operating system, page replacement algorithm.
EuroWordNet as a Resource for Cross-language Information Retrieval

One of the aims of EuroWordNet (EWN) was to provide a resource for Cross-Language Information Retrieval (CLIR). In this paper we present experiments to test the usefulness of EWN for this purpose via a formal evaluation using the Spanish queries from the TREC6 CLIR test set. All CLIR systems using bilingual dictionaries must find a way of dealing with multiple translations and we employ a word sense disambiguation algorithm for this purpose. Retrieval performance using when the disambiguation algorithm was used was 90% of that recorded using queries which had been disambiguated manually.
DETECTION DIRECTION AND DrSCRIMINATION OF THE OF MOTION IN CENTRAL AND PERIPHERAL VISION OF NORMAL AND AMBLYOPIC OBSERVERS

This paper describes the “motion” properties of the ambiyopic fovea and compares them to the normal periphery. Specifically, thresholds for defection of the displacement of a grating pattern, and for discrimination of displacement direction were measured. The main findings of these experiments were: (I) in the central vision of both normal and amblyopic observers, unreferenced displacements are detected with an accuracy equal to the observer’s grating acuity; (2) in the normal periphery, unreferenced motion thresholds fall off at a slower rate than does grating acuity; (3) in amblyopic eyes, displacement thresholds are most elevated centrally; (4) the addition of an abutting reference improves detection of motion for the normal fovea and in anisometropic amblyopes, but elevates motion thresholds in both the normal periphery and in the fovea of amblyopes with strabismus. The adequacy of the normal periphery as a model for the central vision of ambfyopes is discussed. Motion Acuity Amblyopia Peripheral vision Eccentricity Scaling Cortical magnification