Miracle-dz/UniFAR-FTUs huggingface dataset:
Master Degree Project in Speech Technology Robust Speech Recognition with an Auditory Model

This report describes a phoneme recognition system based on properties of the human auditory system. The first part of the paper summarizes knowledge about the physiology of the auditory system, which is the origin of the computational model used in the study and implemented with Matlab. The model, which extracts the critical information of the speech signal, works as an input for a neural network that is trained on the TIMIT speech database to classify English phonemes. The model is shown to be more robust to telephone disturbances of the speech signal than a system based on conventional acoustic processing techniques (MFCC) used in speech recognition. Speech Music and Hearing KTH Miguel Tena Aniés 1 Table of contents Table of contents . 1
Semantic manifold learning for image retrieval

Learning the user's semantics for CBIR involves two different sources of information: the similarity relations entailed by the content-based features, and the relevance relations specified in the feedback. Given that, we propose an augmented relation embedding (ARE) to map the image space into a semantic manifold that faithfully grasps the user's preferences. Besides ARE, we also look into the issues of selecting a good feature set for improving the retrieval performance. With these two aspects of efforts we have established a system that yields far better results than those previously reported. Overall, our approach can be characterized by three key properties: 1) The framework uses one relational graph to describe the similarity relations, and the other two to encode the relevant/irrelevant relations indicated in the feedback. 2) With the relational graphs so defined, learning a semantic manifold can be transformed into solving a constrained optimization problem, and is reduced to the ARE algorithm accounting for both the representation and the classification points of views. 3) An image representation based on augmented features is introduced to couple with the ARE learning. The use of these features is significant in capturing the semantics concerning different scales of image regions. We conclude with experimental results and comparisons to demonstrate the effectiveness of our method.
The Unified Propagation and Scaling Algorithm

In this paper we will show that a restricted class of constrained minimum divergence problems, named generalized inference problems, can be solved by approximating the KL divergence with a Bethe free energy. The algorithm we derive is closely related to both loopy belief propagation and iterative scaling. This unified propagation and scaling algorithm reduces to a convergent alternative to loopy belief propagation when no constraints are present. Experiments show the viability of our algorithm.
A Method of Pedestrian Detection for Image Analysis Bot System

In this paper, to build an efficient intelligent surveillance system, the CNN algorithm, one of the deep learning algorithms, was used for an image analysis bot (bot, the abbreviation of robot, is a software tool for processing data) system to detect and classify pedestrians in a video sequence. To optimize the system, we made some improvements to the CNN algorithm. Additionally, we implement the image analysis bot system based on the above proposed algorithm.
Cortical Areas Involved in Object, Background, and Object-Background Processing Revealed with Functional Magnetic Resonance Adaptation

Previous work has suggested that object and place processing are neuroanatomically dissociated in ventral visual areas under conditions of passive viewing. It has also been shown that the hippocampus and parahippocampal gyrus mediate the integration of objects with background scenes in functional imaging studies, but only when encoding or retrieval processes have been directed toward the relevant stimuli. Using functional magnetic resonance adaptation, we demonstrated that object, background scene, and contextual integration of selectively repeated objects and background scenes could be dissociated during the passive viewing of naturalistic pictures involving object-scene pairings. Specifically, bilateral fusiform areas showed adaptation to object repetition, regardless of whether the associated scene was novel or repeated, suggesting sensitivity to object processing. Bilateral parahippocampal regions showed adaptation to background scene repetition, regardless of whether the focal object was novel or repeated, suggesting selectivity for background scene processing. Finally, bilateral parahippocampal regions distinct from those involved in scene processing and the right hippocampus showed adaptation only when the unique pairing of object with background scene was repeated, suggesting that these regions perform binding operations.
Culture in great apes: using intricate complexity in feeding skills to trace the evolutionary origin of human technical prowess

Geographical cataloguing of traits, as used in human ethnography, has led to the description of ‘culture’ in some non-human great apes. Culture, in these terms, is detected as a pattern of local ignorance resulting from environmental constraints on knowledge transmission. However, in many cases, the geographical variations may alternatively be explained by ecology. Social transmission of information can reliably be identified in many other animal species, by experiment or distinctive patterns in distribution; but the excitement of detecting culture in great apes derives from the possibility of understanding the evolution of cumulative technological culture in humans. Given this interest, I argue that great ape research should concentrate on technically complex behaviour patterns that are ubiquitous within a local population; in these cases, a wholly non-social ontogeny is highly unlikely. From this perspective, cultural transmission has an important role in the elaborate feeding skills of all species of great ape, in conveying the ‘gist’ or organization of skills. In contrast, social learning is unlikely to be responsible for local stylistic differences, which are apt to reflect sensitive adaptations to ecology.
Development of the World Health Organization WHOQOL-BREF Quality of Life Assessment

Background. The paper reports on the development of the WHOQOL-BREF, an abbreviated version of the WHOQOL-100 quality of life assessment. Method. The WHOQOL-BREF was derived from data collected using the WHOQOL-100. It produces scores for four domains related to quality of life: physical health, psychological, social relationships and environment. It also includes one facet on overall quality of life and general health. Results. Domain scores produced by the WHOQOL-BREF correlate highly (0·89 or above) with WHOQOL-100 domain scores (calculated on a four domain structure). WHOQOL-BREF domain scores demonstrated good discriminant validity, content validity, internal consistency and test–retest reliability. Conclusion. These data suggest that the WHOQOL-BREF provides a valid and reliable alternative to the assessment of domain profiles using the WHOQOL-100. It is envisaged that the WHOQOL-BREF will be most useful in studies that require a brief assessment of quality of life, for example, in large epidemiological studies and clinical trials where quality of life is of interest. In addition, the WHOQOL-BREF may be of use to health professionals in the assessment and evaluation of treatment efficacy.
Performance Prediction of Client-Server Systems by high-level Abstraction Models

Performance modeling and simulation offer powerful approaches to predict performance characteristics of software applications and in particular web applications. At the same time the usage of modeling techniques in real projects is still limited due to comprehensive structure of applications and impossibility to know internal structure of application’s components needed to create a precise model. In our work we build and evaluate the high level abstraction models of Content Management System “Joomla” to estimate their ability to provide reliable predictions for different performance characteristics. To build the models we consider three formalisms: Layered Queuing Networks, Performance Evaluation Process Algebra and Queuing Petri Nets. Predictions obtained from models simulation have been compared with measurements of the real system by HP Load Runner toolkit. Results show that overall throughput of the system can be predicted with high level of accuracy while prediction of response time by the same models is less reliable.
Pretreatment Intra-Voxel Incoherent Motion Diffusion-Weighted Imaging (IVIM-DWI) in Predicting Induction Chemotherapy Response in Locally Advanced Hypopharyngeal Carcinoma

AbstractThe aim of this study was to predict response to induction chemotherapy in patients with locally advanced hypopharyngeal carcinoma by IVIM values.Twenty-eight patients with locally advanced hypopharyngeal carcinoma underwent IVIM studies using 12 different b values (b = 0, 10, 20, 30, 50, 70 100, 150, 200, 400, 800, and 1000 s/ mm2). All patients underwent 2 MRI studies: a baseline exam before any treatment and a mid-treatment exam 3 weeks after induction chemotherapy. In the IVIM approach, D*, f, and D were extracted from a bi-exponential fit. For comparison, the ADC map were extracted from a mono-exponential fit. At the end of induction chemotherapy, patients were classified as responders or nonresponders group according to the Response Evaluation Criteria in Solid Tumors criteria (RECIST), based on their MRI measurement. The patients were classified into high grade group (G1), moderate grade group (G2), and low grade group (G3) according to the tumor pathological grading. The predictive value of IVIM parameters were examined with Student's t test, analysis of variance (ANOVA), and receiver operating characteristic (ROC) curves.After 2 cycles of induction chemotherapy, 18 patients were categorized into the responder group whereas the other 10 patients were considered nonresponders. Compared with the pretreatment value, the post-treatment ADC value and D value was significantly higher and the posttreatment D* value was significantly lower (all P < 0.05). In contrast, post-treatment f parameter only changed slightly (P > 0.05). Compared with nonresponders, a notably lower pretreatment ADC value, D value, posttreatment D* value, and higher posttreatment ADC value, D value, &Dgr;ADC, &Dgr;D, and &Dgr;D* were observed in responders (all P < 0.05), but no significant change in &Dgr; f among the 2 group (P > 0.05). The ROC curve analysis indicated that the cutoff of pretreatment D value in best predicting tumor's chemotherapeutic response was 0.847 × 10−3 mm2/s, and the corresponding AUC, sensitivity, and specificity were 0.806, 75.0%, and 88.9%, respectively. Although pretreatment IVIM-derived parameters had no significant differences between high grade, moderate grade, and low grade group, a trend towards lower D* was observed with increasing tumor grading from G3 to G1.IVIM-DWI can potentially predict the treatment response to induction chemotherapy for hypopharyngeal carcinoma.
Mode of action of the peptide antibiotic nisin and influence on the membrane potential of whole cells and on cytoplasmic and artificial membrane vesicles

The peptide antibiotic nisin was shown to cause a rapid efflux of amino acids and Rb+ from the cytoplasm of gram-positive bacteria (Staphylococcus cohnii 22, Bacillus subtilis W 23, Micrococcus luteus ATCC 4698, and Streptococcus zymogenes 24). It strongly decreased the membrane potential of cells as judged by the distribution of the lipophilic tetraphenylphosphonium cation. Ascorbate-phenazine methosulfate-driven transport of L-proline by cytoplasmic membrane vesicles was blocked after addition of nisin, and accumulated amino acids were released from the vesicles. Soybean phospholipid (asolectin) vesicles were not affected by nisin. The data suggest that the cytoplasmic membrane is the primary target and that membrane disruption accounts for the bactericidal action of nisin.
Control and hnitation in Humanoids

Humanoid robots will increasingly become a part of human everyday lives, but require more natural and simplified methods for control and humanrobot interaction. Our approach to addressing these challenges i to use biologically inspired notions of behavior-based control, and endow robots with the ability to imitate, so that they can be programmed and interacted with through demonstration and imitation. Our approach to the problem, based on neuroscience vidence, structures the motor system into a collection of primitives, which are then used to both generate the humanoid’s movelnent repertoire and provide prediction and classification capabilities for visual perception and interpretation. Thus, what the humanoid can do helps it tmderstand what it sees, and vice versa. \’Ve describe the behavior-based background of our work and the neuroscience vidence on which our humanoid motor control and imitation model is based. Next we describe our use of human movement data as input and the huinanoid simulation test-bed for evaluation. We follow with a detailed discussion of three means of deriving primitives, the key component of our model, and describe implementations for each of them, as well as experimental results, demonstrated using human movement, captured with vision or magnetic markers, and imitated on a humanoid torso with dynamics, performing various movements from dance and athletics.
Cell-free Reconstitution of Transport from the trans-Golgi Network to the Late Endosome/Prevacuolar Compartment*

Vesicle-mediated transport between the trans-Golgi network (TGN) and the late endosome/prevacuolar compartment (PVC) is an essential step in lysosomal/vacuolar biogenesis. In addition, localization of integral membrane proteins to the TGN requires continual cycles of vesicular transport between the TGN and endosomal compartments. Genetic and biochemical analyses in yeast have identified a variety of proteins required for TGN-to-PVC transport. However, the precise mechanisms of vesicle formation, transport, and fusion have not been fully elucidated. To study the steps of TGN-to-PVC transport in mechanistic detail, we have developed a cell-free assay to monitor delivery of the processing protease Kex2p from the TGN to PVC compartments containing a Kex2p substrate. Transport is time-, temperature-, and ATP-dependent and requires the t-SNARE Pep12p. Moreover, cell-free delivery of Kex2p to the PVC results in the co-integration of Kex2p into PVC membranes containing the Kex2p substrate as determined by co-immunoisolation of Kex2p and the substrate using antibody against the Kex2p cytosolic tail. This work represents the first cell-free reconstitution and biochemical analysis of the essential vacuolar/lysosomal sorting step TGN to late endosome transport.
Planning for Machining Workpieces with a Partial-Order, Nonlinear Planner

We describe a hybrid architecture supporting planning for machining workpieces. The archi- tecture is built around CAPlan, a partial-order nonlinear planner that represents the plan already generated and allows external control decision made by special purpose programs or by the user. To make planning more efficient, the domain is hierarchically modelled. Based on this hierarchical representation, a case-based control component has been realized that allows incremental acquisition of control knowledge by storing solved problems and reusing them in similar situations.
Analysis of Dispersion Compensation using Fiber Bragg Grating in Optical Fiber Communication System

Dispersion is the most important factor which determines the data rate and the maximum repeater distance spacing in a fiber optical link. In this paper, investigation has been done on performance of Fiber Bragg Grating as a technique to compensate chromatic dispersion in a 100 km long fiber optic link using different modulation formats such as RZ and NRZ modulation formats and different values of transmission power levels. It was observed that RZ modulation format showed a better performance with a maximum value of Qfactor of 54.5192 than NRZ modulation format which obtained maximum Q-factor value of 31.4792. General Term Performance Analysis, Dispersion compensation, Fiber Bragg Grating
Hyperbolicity of scalar-tensor theories of gravity

Two first order strongly hyperbolic formulations of scalar-tensor theories of gravity allowing non- minimal couplings (Jordan frame) are presented along the lines of the 3 � 1 decomposition of spacetime. One is based on the Bona-Massoformulation, while the other one employs a conformal decomposition similar to that of Baumgarte-Shapiro-Shibata-Nakamura. A modified Bona-Massoslicing condition adapted to the scalar-tensor theory is proposed for the analysis. This study confirms that the scalar-tensor theory has a well-posed Cauchy problem even when formulated in the Jordan frame. Scalar-tensor theories of gravity (STT) are alternative theories of gravitation where a scalar field is coupled non- minimally to the curvature associated with the physical metric (this is the so-called Jordan frame representation). The term ''physical metric'' refers to a situation where test particles follow the geodesics of that metric. The variation of the action of the STT with respect to the physical metric gives rise to field equations which contain an effective energy-momentum tensor (EMT) involving second order derivatives in time and space of the scalar field. Such EMT has the property that ''ordinary matter,'' i.e., matter asso- ciated with fields other that the scalar field, obeys the (weak) equivalence principle which mathematically trans- lates into a conserved EMT for ordinary matter alone. Since a priori, it was not clear how such second order derivatives could be eliminated (in terms of lower order derivatives), or managed so as to obtain a quasilinear system of hyperbolic equations for which the Cauchy problem was well-posed (in the Hadamard sense), many people decided to abandon this approach in favor of the so- called Einstein frame representation where the nonminimal coupling is absorbed into the curvature by means of a conformal transformation of the metric. The new confor- mal metric is unphysical in the sense that (non-null) test particles do not follow the geodesics of that metric. However, the mathematical advantage is that the field equations for the nonphysical metric resemble the standard Einstein field equations with an unphysical effective EMT which involves at most first order derivatives of a suitable transformed scalar field (this EMT is unphysical because the ''ordinary matter'' part is not separately conserved). In the Einstein frame one can show that by using standard gauges (e.g., harmonic gauge) the field equations acquire the form required in the application of theorems that establish the well-posedness of the Cauchy problem. In view of the apparent mathematical advantages and disadvantages of the Jordan and Einstein frames, several
Kinectrack: Agile 6-DoF tracking using a projected dot pattern

We present Kinectrack, a new six degree-of-freedom (6-DoF) tracker which allows real-time and low-cost pose estimation using only commodity hardware. We decouple the dot pattern emitter and IR camera of the Kinect. Keeping the camera fixed and moving the IR emitter in the environment, we recover the 6-DoF pose of the emitter by matching the observed dot pattern in the field-of-view of the camera to a pre-captured reference image. We propose a novel matching technique to obtain dot pattern correspondences efficiently in wide- and adaptive-baseline scenarios. We also propose an auto-calibration method to obtain the camera intrinsics and dot pattern reference image. The performance of Kinectrack is evaluated and the rotational and translational accuracy of the system is measured relative to ground truth for both planar and multi-planar scene geometry. Our system can simultaneously recover the 6-DoF pose of the device and also recover piecewise planar 3D scene structure, and can be used as a low-cost method for tracking a device without any on-board computation, with small size and only simple electronics.
Alcoholism and Catatonia: An Underappreciated Relationship

Catatonia is a complex neuropsychiatric syndrome that has been described in medical literature since the 16th century. Lifethreatening complications involving every organ system can ensue, signaling high levels of associated morbidity and mortality. To this day, little is known about the etiology of catatonia. Catatonia occurs most frequently in patients with affective disorders and schizophrenia, and is more common in medical or neurologic conditions
Multivariate predictors of social skills performance in middle-aged and older out-patients with schizophrenia spectrum disorders

Background Cognitive impairment and negative symptoms are two of the primary features of schizophrenia associated with poor social functioning. We examined the relationships between clinical characteristics, specific cognitive abilities and social skills performance in middle-aged and older out-patients with schizophrenia and normal comparison subjects. Method One hundred and ninety-four middle-aged and older schizophrenia out-patients and 60 normal comparison subjects were administered a standardized, performance-based measure of social skills using role-plays of various social situations [Social Skills Performance Assessment (SSPA)] and measures of current level of social contact (the Lehman Quality of Life Interview), psychiatric symptom severity [the Positive and Negative Syndrome Scale (PANSS) and the Hamilton Depression Rating Scale (HAMD)], insight [the Birchwood Insight Scale (IS)] and cognitive functioning [the Mattis Dementia Rating Scale (DRS)]. Results Patients demonstrated worse social skills compared with normal subjects. Better performance on the SSPA was associated with having less severe positive and negative symptoms, fewer social contacts, and better attention, initiation/freedom from perseveration, visuospatial ability, abstraction ability and memory. After controlling for demographic, clinical and insight-related factors, abstraction ability was the strongest predictor of social skills performance, followed by frequency of social contact. Conclusions Social functioning (as measured through direct observation of social skills performance) was related to cognitive ability in out-patients with schizophrenia. Addressing such cognitive impairment may help to improve social functioning and result in greater overall quality of life.
Electrical properties of mammalian lens epithelial gap junction channels.

PURPOSE To establish an "electrical fingerprint" for the gap junction channels between mammalian lens epithelial cells. METHODS The double whole cell patch clamp technique was applied to isolated cell pairs obtained from mouse lens epithelium and a continuous cell line of lens epithelial cells derived from the sheep lens (SLE 2.1). RESULTS The junctional conductance in mouse lens epithelial cells and in cultured SLE 2.1 cells was found to be moderately voltage dependent. SLE 2.1 cells were analyzed in more detail. The voltage dependence could be described by a Boltzmann distribution with Vo = +/- 63.1 mV and Gmin = 0.34. In cell pairs that exhibited spontaneously low junctional conductance, single channel events could be distinguished. Single gap junction channel currents had a linear current-voltage relationship. A frequency histogram of single channel conductances from eight cell pairs had three major peaks of 35, 60 and 97 pS. CONCLUSION The electrical properties of gap junction channels between mammalian lens epithelial cells were virtually identical to those previously reported for transfected cell lines expressing connexin43. The authors' physiological data are therefore in agreement with molecular studies that have identified connexin43 as the major connexin of lens epithelial cells.