Miracle-dz/UniFAR-FTUs huggingface dataset:
Reconocimiento de palabras aisladas utilizando Modelos Ocultos de Markov

espanolActualmente son necesarias interfaces en las cuales la comunicacion entre el ser humano y las computadores sea eficiente, natural y que no requiera un gran esfuerzo de aprendizaje. En ello trabaja la linea de investigacion "Reconocimiento Automatico del Habla". En este trabajo se describe un sistema para el Reconocimiento de Palabras Aisladas (RPA) para vocabularios reducidos, independiente del locutor y se muestran los resultados de su implementacion en una estacion de trabajo HP-9000, sobre la que el sistema funciona en tiempo real. A partir de la senal vocal (en nuestro caso una palabra aislada del vocabulario), se obtiene una representacion parametrica de dicha senal en la etapa denominada preproceso, en el cual se realiza un tratamiento mediante Banco de Filtros, un calculo del cepstrum y un etiquetado, que reducira la cantidad de informacion con la que tratar y enfatizara las caracteristicas mas relevantes de la senal. Senales asi parametrizadas seran utilizadas para el aprendiaje de un Modelo de Markov Oculto (MMO) para cada palabra del vocabulario. Para el reconocimiento se tomaran muestras igualmente parametrizadas y se calculara la probabilidad de generar dicha muestra por cada uno de los modelos, eligiendose como palabra aquella cuyo modelo de la probalibidad mas alta. El sistema permite, ademas, la posibilidad de generacion de nuevas tareas, aprendiendo los modelos de cualquier vocabulario EnglishNowardays it is needed interfaces in which human-computer comunication is efficient, natural and that don't require a large effort of training. The line of investigation "Speech Automatic Recognition" is working in this subjet. In this work we show a Speaker-Independent, Isolated Word Recognizer for small vocabularies, and we show the implementation results on a workstation HP-9000, in real time. We obtain a parametric representation from a speech signal (in our case an isolated word of the vocabulary) in a preprocessing stage in which a filter-bank treatment, a cepstrum calculation and a labelling are made. This wil reduce the amount of information to be treated and wil emphasize the most outstanding signal features. This parametric signal will be used for training a distinct Hidden Markov Model (HMM) for each word of the vocabulary. Recognition consists of computing the probability of generating the test word with each model and choosing the word whose model gives the highest probility. This system alows us to generate new tasks to train models of other vocabulary.
A Brief Survey on Meta-Heuristic Approaches for Web Document Clustering

Internet is a gigantic information resource, which is growing rapidly as more and more data are being added to the World Wide Web. It is now becoming ever harder to search useful information from the web. It has been also been found that HTML tags which have particular meanings could be used to enhance the performance of IR system. Still, the bulk of data on the web is speedily growing. Clustering can be used to play a key role in organizing such a bulky amount of documents into groups. However, due to restrictions in prevailing clustering techniques, scientists started to use meta-heuristic algorithms for the document clustering problem. This paper provides a brief survey of the available literature on a web search in which HTML tags have been used in information retrieval and Meta-heuristics approaches used in web document clustering.
Identifying genetic markers associated with susceptibility to cardiovascular diseases

The development of cardiovascular diseases (CVDs) is due to a complex interaction between the genome and the environment. Understanding how genetic differences in individuals contribute to their susceptibility to CVDs can help guide practitioners to give the best advice to achieve a favorable outcome for the patient. As genome technologies evolve, genotyping of individuals could be available to all patients using a simple saliva test. Large-scale genome-wide association studies and meta analyses have provided powerful insights into polymorphisms that may be predictive of disease and an individual's response to certain nutrients, but moving forward it is imperative that these insights can be applied in the medical setting to reduce the incidence and mortality of CVDs.
Study of MPPT algorithms for a Boost Interleaved three-level converter

In this work the study of different algorithms of maximum power point tracking for a Boost Interleaved topology for photovoltaic applications is presented. The nature of this converter offers the possibility of using algorithms in such a way that they work independently in each module and therefore optimize the solar energy obtained from their panels. A brief description of the converter is presented, highlighting its advantages for this type of application. The algorithms Perturb and Observe, Incremental Conductance and Multiple Photovoltaic Arrangements are described which were used for the proposed converter. Several simulation tests were carried out to obtain a well-founded answer on which was the most convenient algorithm for the proposed converter.
Triple-Band Loop Antenna for 5G/WLAN Unbroken-Metal-Rimmed Smartwatch

A design concept of integrating the loop antenna into the inner metal frame of a smartwatch for 5G/WLAN application is introduced. The antenna is constructed from a rectangular metal frame which encircled the system circuit board of the watch. A separation distance between the loop and the system ground plane is set to alleviate the strong coupling between the antenna and the ground. The antenna can easily cover the 2.4-GHz band (2400–2485 MHz) for WLAN operation, 3.4-GHz band (3300–3600 MHz) and 4.9-GHz band (4800–5000 MHz) for 5G application in China. Simulated results show that the antenna has an efficiency of 67%-91 % in these operation bands.
A Heart-Like Unidirectional Millimeter-Wave Antenna

A heart-like unidirectional millimeter-wave antenna is devised to obtain wide bandwidth and unidirectional radiation patterns. The designed heart-like antenna is composed of a heart-like radiating patch with a C-like parasitic strip, CPW ground plane, a copper cavity-backed designed on the back of the substrate. The copper cavity-backed structure is to reduce the back radiation and can get a better directional characteristic. The proposed antenna has a bandwidth ranges from 30.4GHz to 43.85GHz, indicating a relative bandwidth of 36.2%. Also, the proposed antenna has a great unidirectional radiation characteristic. The results show that the proposed heart-like millimeter-wave antenna possesses a huge bandwidth and amazing unidirectional radiation patterns.
Galactose-modified selenium nanoparticles for targeted delivery of doxorubicin to hepatocellular carcinoma

Abstract Galactose-modified selenium nanoparticles (GA-SeNPs) loading with doxorubicin (DOX) for hepatocellular carcinoma (HCC) therapy was investigated in this paper. Selenium nanoparticles (SeNPs) were modified with galactose as tumor targeting moiety to fabricate tumor-targeted delivery carrier GA-SeNPs, then doxorubicin was loaded onto the surface of GA-SeNPs for improving antitumor efficacy of DOX in HCC therapy. Chemical structure characterization of GA-Se@DOX showed that DOX was successfully loaded to the surface of GA-SeNPs to prepare functionalized antitumor drug delivery system GA-Se@DOX. GA-Se@DOX exhibited effective cellular uptake in HepG2 cells and entered HepG2 cells mainly by clathrin-mediated endocytosis pathway. GA-Se@DOX showed significant activity to induce the apoptosis of HepG2 cells in vitro. The western blotting result indicated that GA-Se@DOX induced HepG2 cells apoptosis via activating caspase signaling and Bcl-2 family proteins. Moreover, active targeting delivery system GA-Se@DOX exhibited excellent antitumor efficacy in vivo in comparison with passive targeting delivery system Se@DOX. Histology analysis showed that GA-Se@DOX exhibited no obvious damage to major organs including heart, liver, spleen, lung, and kidney under the experimental condition. Taken together, GA-Se@DOX may be one novel promising nanoscale drug candidate for HCC therapy.
High Gain Disc Resonator Antenna Array with CPW Coupled for THz Applications

This paper introduces a disc resonator antenna array with compact size and wide band for THz applications. The disc antenna is designed based on modified SOG technology platform from high resistivity Si. A Dielectric Waveguide (DWG) is matched with the disc dielectric antenna using CPW feed. The CPW feed is designed on the Pyrex side of the Si wafer bonded to the Pyrex. The proposed antenna is designed to operate from 325 GHz to 500 GHz with good return loss. The endfire and broadside antennas are introduced with high gain about 17 dB. The antenna has high efficiency and low cost.
Oscillometry and pulmonary magnetic resonance imaging in asthma and COPD

Developed over six decades ago, pulmonary oscillometry has re‐emerged as a noninvasive and effort‐independent method for evaluating respiratory‐system impedance in patients with obstructive lung disease. Here, we evaluated the relationships between hyperpolarized 3He ventilation‐defect‐percent (VDP) and respiratory‐system resistance, reactance and reactance area (AX) measurements in 175 participants including 42 never‐smokers without respiratory disease, 56 ex‐smokers with chronic‐obstructive‐pulmonary‐disease (COPD), 28 ex‐smokers without COPD and 49 asthmatic never‐smokers. COPD participants were dichotomized based on x‐ray computed‐tomography (CT) evidence of emphysema (relative‐area CT‐density‐histogram ≤ 950HU (RA950) ≥ 6.8%). In asthma and COPD subgroups, MRI VDP was significantly related to the frequency‐dependence of resistance (R5‐19; asthma: ρ = 0.48, P = 0.0005; COPD: ρ = 0.45, P = 0.0004), reactance at 5 Hz (X5: asthma, ρ = −0.41, P = 0.004; COPD: ρ = −0.38, P = 0.004) and AX (asthma: ρ = 0.47, P = 0.0007; COPD: ρ = 0.43, P = 0.0009). MRI VDP was also significantly related to R5‐19 in COPD participants without emphysema (ρ = 0.54, P = 0.008), and to X5 in COPD participants with emphysema (ρ = −0.36, P = 0.04). AX was weakly related to VDP in asthma (ρ = 0.47, P = 0.0007) and COPD participants with (ρ = 0.39, P = 0.02) and without (ρ = 0.43, P = 0.04) emphysema. AX is sensitive to obstruction but not specific to the type of obstruction, whereas the different relationships for MRI VDP with R5‐19 and X5 may reflect the different airway and parenchymal disease‐specific biomechanical abnormalities that lead to ventilation defects.
An Electrically Small On-Chip Antenna Scaled down to One-Twentyfifth by One-Fiftieth of Wavelength

An electrically small on-chip antenna for RFID tags operating at 5.8 GHz is presented. The proposed antenna has dimensions of 2.1 mm (λ/25) by 1.2 mm (λ/50), implemented in a 0.18 µm pure CMOS technology. The antenna consists of two loops. By changing the size of the inner loop, we can manage the antenna impedance while maintaining its gain. The antenna has a gain and a bandwidth of −22.21 dBi and 4.9 GHz, respectively.
New approach for the evaluation of magnetic fields in dynamic wireless charging for electric vehicles

This paper showcases a new approach for the evaluation of magnetic field radiation of a dynamic wireless power transfer system (DWPT) for electric vehicles (EVs), by using the co-simulation capabilities between finite element analysis (FEA) software and electric simulation in order to consider simultaneously the electric behaviour and the magnetic response of such system. In this study, electric simulation is used to control the motion of the receiving coil and to drive the emitting coil, and FEA software is used to illustrate the system reaction, regarding the induced field.
K-Nearest Neighbor (KNN) Analysis on Genes Expression Datasets of Maize Nested Association Mapping (NAM) Showed Confident Classification on Organ-specific Expression

Genes expression data in large data matrix provide challenges in applying analytical methods, interpreting, and drawing conclusions. This study aims to evaluate genes expression classification on different maize lines and different organs (Apex, Root, Shoot, Ear, and Tassel) based on Maize Nested Association Mapping (NAM) datasets using K-Nearest Neighbor (KNN) approach. As a result, we obtained the accuracy value and AUC value of 0. 926 and 0.992 respectively from KNN analysis with k = 5. Besides, we showed the classification of genes expression datasets to distinguish organ-specific expression.
Impact of thermal overload on the insulation aging in short duty cycle motors for aerospace

Electric motors for aerospace applications are often characterised by short-time duty rather than continuous-duty operations. Some of the main requirements for these machines are high torque density and reliability. Considerable torque density improvement can be achieved by supplying the windings with current greater than the rated value and thus thermally overloading the machine for short periods of time. However, if the insulation is overheated, the machine lifetime is shortened, and reliability issues can arise. This paper experimentally investigates the influence of short-time thermal overload on the insulation lifetime of low voltage, random wound electrical machines. The analysis is performed on round enamelled magnet wires coils aged by accelerated thermal cycles, and the results are statistically processed by the two-parameter Weibull distribution. The experimental data is also used for building a lifetime estimation model, which is employed for predicting the lifetime of a motor embedded into an electromechanical actuator for landing gear extension/retraction.
A scoping review of mentor training programs in medicine between 1990 and 2017

ABSTRACT Effective mentoring enhances the personal and professional development of mentees and mentors, boosts the reputation of host organizations and improves patient outcomes. Much of this success hinges upon the mentor’s ability to nurture personalized mentoring relationships and mentoring environments, provide effective feedback and render timely, responsive, appropriate, and personalized support. However, mentors are often untrained raising concerns about the quality and oversight of mentoring support. To promote effective and consistent use of mentor training in medical education, this scoping review asks what mentor training programs are available in undergraduate and postgraduate medicine and how they may inform the creation of an evidenced-based framework for mentor training. Six reviewers adopted Arksey and O’Malley’s approach to scoping reviews to study prevailing mentor-training programs and guidelines in postgraduate education programs and in medical schools. The focus was on novice mentoring approaches. Six reviewers carried out independent searches with similar inclusion/exclusion criteria using PubMed, ERIC, EMBASE, SCOPUS, Google Scholar, and grey literature databases. Included were theses and book chapters published in English or had English translations published between 1 January 1990 and 31 December 2017. Braun and Clarke’s approach to thematic analysis was adopted to circumnavigate mentoring’s and mentor training’s evolving, context-specific, goal-sensitive, learner-, tutor- and relationally dependent nature that prevents simple comparisons of mentor training across different settings and mentee and mentor populations. In total, 3585 abstracts were retrieved, 232 full-text articles were reviewed, 68 articles were included and four themes were identified including the structure, content, outcomes and evaluation of mentor training program. The themes identified provide the basis for an evidence-based, practice-guided framework for a longitudinal mentor training program in medicine and identifies the essential topics to be covered in mentor training programs.
The Preventive Effects of Standardized Extract of Zataria multiflora and Carvacrol on Acetaminophen-Induced Hepatotoxicity in Rat

Objectives The hepatotoxicity induced by Acetaminophen (AAP) mostly mediated by effect on oxidative stress parameters. The Zataria multiflora (Z.M) is an herbal medicine with well-known antioxidant effect. The aim of this study is investigation of preventive effects of Z.M and Carvacrol (CAR) on AAP-induced hepatotoxicity in rats. Methods Rats were randomly divided into four groups including: 1) Control, 2) Acetaminophen (AAP), 3) and 4) CAR. The saline, Z.M (200 mg/kg) and CAR (20 mg/kg) were administrated orally for 6 days, after that AAP (600 mg/kg) was administrated in the 7th day. Blood sampling was performed on the first and last days. Also, the liver tissue was removed for evaluation of Malondyaldehide (MDA), Thiol content, Superoxide dismutase (SOD) and Catalase (CAT). Total Protein (tPro), Glutamic Oxaloacetic Transaminase (GOT), Glutamic Pyruvic Transaminase (GPT) and Alkaline Phosphatase (ALP) in liver tissue were evaluated. The changes (Δ) of enzymes activities were presented. Results The Δ GOT, Δ GPT and Δ ALP in CAR group significantly decreased compared to AAP group (P < 0.01 to P < 0.001) and Δ GPT in Z.M group was significantly reduced in comparison with AAP group (P < 0.05). Also, MDA, Thiol, SOD and CAT levels in treated groups were attenuated compared to AAP group (P < 0.05 to P < 0.001). Conclusion Z.M and CAR have a powerful hepatoprotective effect. CAR is more effective than Z.M. Based on the results. Z.M and CAR could be potent supplementary agents against hepatotoxicity of AAP in patients.
A Compact Single Layer Orthogonal Polarized Yagi-Like Directional Antenna

A compact Vagi-like directional antenna is presented based on a slot loop excitation. Two orthogonally polarized beams are generated by orthogonally feeding the slot using two microstrip lines. Both the horizontally polarized (HP) and the vertically polarized (VP) beams constitute an omnidirectional radiation patterns that are made directional by using two complementary slot reflector elements. The proposed antenna has a measured bandwidth of 330 MHz (3.56−3.89) targeting the WiMAX band. The antenna is compact with a total board size of 35 × 40 mm2 Both end-fire directional beams have a minimum gain of 3.8 dBi and front-to-back ratio (FBR) of 6 dB. The efficiency of the antenna is 94% for both ports.
RF-based Breast Surface Estimation - Registration with Reference Imaging Modality

In this paper, two estimation problems are tackled. Firstly, the robust estimation of the external contour of the breast, using data from a Radio-Frequency (RF) Ultra-Wide Band (UWB) scan. Secondly, the registration between the RF breast scan and the breast scan using a 3D stereographic infrared camera. The bi-modality data registration is meant for controlled patient positioning and breast deformation during the RF breast examination.
Reconfigurable Multiband FarIR Notch Filter Employing Phase Change Material

We propose a reconfigurable multiband notch filter in the FarIR band of 7 to 17 μm (40–18 THz) utilizing phase change material. The use of the phase change material, VO2, allows the cross shaped FSS to effectively change its resonant frequencies. The FSS unit cell is divided into four quadrants containing two different dimensions of cross dipoles. Dividing the unit cell in this method allows for multiple notches in the transmission response.
Mouth States using LSTM Neural Network

This paper presents the application of a sequence-to-label network, in which an architecture with Long-Short Term Memory (LSTM) is implemented, in a way that verifies if a user is chewing or waiting to receive food by means of the classification of 3 different states of the mouth that are: closed, intermediate closed-open and open. To develop this task, 2 databases were built, one of training with 260 sequences of 3 seconds of the states with 15 time steps, within which there are 2 characteristics: opening and the relationship between the height and width of the mouth, and another of test, of 145 sequences with the same parameters as the previous one. For the training of the network, it was first proposed that the network identified 2 states: chewing and waiting (open mouth), however, due to the large variations that exist in the state “chewing”, because users tend to chew not only with their mouths closed, but also with their mouths open, this state was divided into two sub-states (closed and intermediate). With this, the neural network is trained, reaching an 84.8% accuracy by classifying the 3 states and 97.9% merging the two states belonging to “chewing”, which verifies the ability of this type of network to recognize the states of the mouth through sequences over time.
A Substrate-Integrated Fan-Beam Dipole Antenna with Varied Fence Shape for mm-Wave 5G Wireless

A mm-Wave 5G dipole antenna is presented featuring high gain, fan-beam with wide HPBW in the elevation plane (HPBWEI), and high front-to-back radiation ratio (F/B). The dipole is implemented using vias at the edge of Rogers RO5880 substrate. For boosting the gain and HPBW, flared parasitic vias are added in front of the dipole. To suppress the back radiation, the dipole is surrounded by a via-fence. Two fence shapes were investigated; namely, the rectangular fence and the U-fence where a single dipole, 2×1, and 4×1 arrays were fabricated for each of them. The single elements achieve a measured bandwidth of more than 6.5 GHz around 28 GHz. All fabricated prototypes have F/B greater than 36 dB, with the rectangular fence and U-fence 4×1 dipole arrays achieving HPBWE1/gain of 133.1°/12.61-dBi and 118°/13.5-dBi, respectively.
Multimodal Fuzzy Fusion for Enhancing the Motor-Imagery-Based Brain Computer Interface

Brain-computer interface technologies, such as steady-state visually evoked potential, P300, and motor imagery are methods of communication between the human brain and the external devices. Motor imagery-based brain-computer interfaces are popular because they avoid unnecessary external stimuli. Although feature extraction methods have been illustrated in several machine intelligent systems in motor imagery-based brain-computer interface studies, the performance remains unsatisfactory. There is increasing interest in the use of the fuzzy integrals, the Choquet and Sugeno integrals, that are appropriate for use in applications in which fusion of data must consider possible data interactions. To enhance the classification accuracy of brain-computer interfaces, we adopted fuzzy integrals, after employing the classification method of traditional brain-computer interfaces, to consider possible links between the data. Subsequently, we proposed a novel classification framework called the multimodal fuzzy fusion-based brain-computer interface system. Ten volunteers performed a motor imagery-based brain-computer interface experiment, and we acquired electroencephalography signals simultaneously. The multimodal fuzzy fusion-based brain-computer interface system enhanced performance compared with traditional brain-computer interface systems. Furthermore, when using the motor imagery-relevant electroencephalography frequency alpha and beta bands for the input features, the system achieved the highest accuracy, up to 78.81% and 78.45% with the Choquet and Sugeno integrals, respectively. Herein, we present a novel concept for enhancing brain-computer interface systems that adopts fuzzy integrals, especially in the fusion for classifying brain-computer interface commands.