Miracle-dz/UniFAR-FTUs huggingface dataset:
MESTRADO EM ODONTOLOGIA rea de Concentrao em Periodontia

Earlier studies have shown that the simultaneous sinus mucosal lining elevation and installation of dental implants without graft materials could be a predictable procedure. Nevertheless, there are no controlled studies that evaluated this technique. The aim of this prospective, controlled and randomized clinical study was to evaluate whether sinus membrane elevation and simultaneous placement of dental implants without autogenous bone graft can create sufficient bone support to allow implant success after 6 months post-surgically. Sinus membrane elevation and simultaneous placement of dental implants were performed bilaterally in 15 patients. The sinuses were assigned in 2 groups: test group, with simultaneous sinus mucosal lining elevation and installation of dental implants without graft materials, and control group, with simultaneous sinus mucosal lining elevation and installation of dental implants with intra-oral autogenous bone graft. After 6 months of healing, abutments were connected. For each implant, length of implant protruded into the sinus, resonance frequency analysis (RFA) and bone gain were recorded at baseline and at 6-month follow-up. Clinical complications were not observed, except for two postoperative fistulas/suppuration in both groups. Only one implant from the test group was lost, reaching a success rate of 96.4% and 100% for test and control groups, respectively. After healing, radiographic new peri-implant bone was observed in both groups ranging between 8.3+2.6mm and 7.9+3.6mm for control and test group, respectively (p>0.05). RFA values were lower for the control group when compared with baseline (p<0.05). A significant positive correlation was found between the protruded implant length/bone gain and implant survival/sinusitis (p<0.0001). Simultaneous sinus mucosa elevation and implant placement resulted in peri-implant bone formation over a period of 6 months. Key-words: maxillary sinus/augmentation, sinus membrane, autogenous bone graft, dental implants
Probabilistic Power Flow for Hybrid AC/DC Grids with Ninth-Order Polynomial Normal Transformation and Inherited Latin Hypercube Sampling

This paper proposes a new probabilistic power flow method for the hybrid AC/VSC-MTDC (Voltage Source Control-Multiple Terminal Direct Current) grids, which is based on the combination of ninth-order polynomial normal transformation (NPNT) and inherited Latin hypercube sampling (ILHS) techniques. NPNT is utilized to directly handle historical records of uncertain sources to build the accurate probability model of random inputs, and ILHS is adopted to propagate the randomness from inputs to target outputs. Regardless of whether the underlying probability distribution is known or unknown, the proposed method has the ability to adaptively evaluate the sample size according to a specific operational scenario of the power systems, thus achieving a good balance between computational accuracy and speed. Meanwhile, the frequency histograms, probability distributions, and some more statistics of the results can be accurately and efficiently estimated as well. The modified IEEE 118-bus system, together with the realistic data of wind speeds and diverse consumer behaviors following irregular distributions, is used to demonstrate the effectiveness and superiority of the proposed method.
An Open-Source Hardware Acquisition Platform for Physiological Measurements

In this article we present a new low-cost physiological signal acquisition platform in compliance with Open-Source Hardware philosophy. The device contains an electrocardiography circuit; two electrodermal activity channels that implement a time-multiplexing technique to remove inter-channel coupling interference; and a skin temperature module. These features make the platform suitable for experiments involving Affective Computing. We have assessed the performance of this device in terms of Signal-to-Noise Ratio (SNR) and Background Noise Level (BNL), an adapted MPEG7 feature for electrocardiography signals. This platform outperforms other commercial devices and most similar state-of-art studies on SNR. Results show values of 11.96, 30.01, 68.40 dB for ECG, EDA and ST, respectively, for SNR, and −28.31 dB for BNL in ECG. Both features were obtained by sampling physiological signals at a frequency of 256 Hz.
Efficient Uncertainty Quantification for Biotransport in Tumors With Uncertain Material Properties

We consider modeling of single phase fluid flow in heterogeneous porous media governed by elliptic partial differential equations (PDEs) with random field coefficients. Our target application is biotransport in tumors with uncertain heterogeneous material properties. We numerically explore dimension reduction of the input parameter and model output. In the present work, the permeability field is modeled as a log-Gaussian random field, and its covariance function is specified. Uncertainties in permeability are then propagated into the pressure field through the elliptic PDE governing porous media flow. The covariance matrix of pressure is constructed via Monte Carlo sampling. The truncated Karhunen–Loève (KL) expansion technique is used to decompose the log-permeability field, as well as the random pressure field resulting from random permeability. We find that although very high-dimensional representation is needed to recover the permeability field when the correlation length is small, the pressure field is not sensitive to high-oder KL terms of input parameter, and itself can be modeled using a low-dimensional model. Thus a low-rank representation of the pressure field in a low-dimensional parameter space is constructed using the truncated KL expansion technique.
A CPW FED DENIM BASED WEARABLE ANTENNA WITH DUAL BAND-NOTCHED CHARACTERISTICS FOR UWB APPLICATIONS

This paper presents design analysis of a compact CPW-fed Wearable Textile Antenna with Dual Band notched characteristics for UWB applications. The proposed wearable textile antenna is designed on two different dielectric substrates; leather and denim with copper foil as conducting element. The performances of the designed textile antenna are compared on two substrates. Band-notched filtering characteristics are achieved by inserting semicircular split ring resonators on the conducting element. The first notch band is obtained from 2.3–2.5 GHz for Bluetooth application band, and the second notch band is obtained from 3.3–3.6 GHz for WiMAX application band. The simulated and measured frequency results show that the antenna has an impedance bandwidth of 1.8–10 GHz and reflection coefficient less than −10 dB, except at the two eliminating bands. The proposed antenna is designed and simulated using Ansys HFSS Electromagnetic Simulator. The prototype of the antenna has been developed on the denim substrate, and its performance is measured and compared with the simulated ones.
Multiport Interline Current Flow Controller for Meshed HVDC Grids

In meshed high voltage direct current grids, the current of each line cannot be controlled independently, since it depends on the resistances between nodes. Additional devices, such as current flow controllers (CFCs), may be needed to avoid bottlenecks or line overloads. This work presents a multiport dc–dc-based CFC topology to be connected to <inline-formula><tex-math notation="LaTeX">$n$</tex-math></inline-formula> lines with unidirectional current flows. The device is able to control the dc lines’ currents to the desired value by inserting variable voltage sources in series. First, the modeling of the generic <inline-formula><tex-math notation="LaTeX">$n$</tex-math></inline-formula>-port topology is presented and then, its modulation and control strategy are described. In the first case study, the concept is validated considering a 5-port CFC by means of dynamic simulations using different control methods. Finally, in the second case study, a 3-port CFC prototype is built and tested in an experimental platform in the laboratory considering different control modes.
Second Harmonic Beam Shaping and Sensing in Dielectric Bow-Tie Antenna via Convex Optimization Array Synthesis Approach

We propose a convex optimization approach for an array synthesis pattern to enhance the electromagnetic field in the gap region of a dielectric bow-tie antenna. This method allows the induction of the desired antenna modes by exploiting the concurrent excitation of the structure with plane waves with different propagation directions and complex amplitudes. By engineering the excitation coefficients of the array, different modes are excited in the bow-tie antenna and the radiation pattern of the generated second harmonic (SH) field is modified accordingly. Using our approach, we demonstrate both the feasibility of performing synthesis of the SH radiation pattern in dielectric antennas and the possibility of developing innovative sensing applications in photonics.
Maximum Entropy Derived Statistics of Sound-Speed Structure in a Fine-Grained Sediment Inferred From Sparse Broadband Acoustic Measurements on the New England Continental Shelf

Marginal probability distributions for parameters representing an effective sound-speed structure of a fine-grained sediment are inferred from a data ensemble maximum entropy method that utilizes a sparse spatially distributed set of received pressure time series resulting from multiple explosive sources in a shallow-water ocean environment possessing significant spatial variability of the seabed. A remote sensing seabed acoustics experiment undertaken in March 2017 off the New England Shelf was designed so that multiple independent analyses could infer the statistical properties of the seabed. The current analysis incorporates the measured horizontal variability from interpretations of a subbottom profiling survey of the experimental area. An idealized range- and azimuth-dependent parameterization of the seabed is derived from identification of horizons within the seabed that define multiple sediment layers. A sparse set of explosive charges were deployed on circular tracks with radii of about 2, 4, and 6.5 km with an acoustic array at the center to correlate a set of random measurements to physical acoustic processes that characterize the seabed. The mean values of a surface sound speed ratio and a linear sound speed gradient for the fine-grained sediment layer derived from 12 data samples processed in the 25–275-Hz band provide an estimate of the effective sound-speed structure in a 130-km$^2$ area. The inferred sediment sound speed values are evaluated by predicting measured time series data not used in the statistical inference, and are also compared to historical measurements. Finally, the low-frequency maximum entropy estimate of the sediment sound speed along with physical measurements derived from piston core measurements are utilized to estimate the sediment grain bulk modulus.
Trafic Signs Detection Based On Saliency Map Using Canny Edge

This paper proposed Canny edge detection to detected saliency map on traffic sign. The edge detection functions by identifying the bounds from an object on an image. The edge of an image is an area that has a strong intensity of light.The pixel intensity of an image changes from low to high values or otherwise. Detecting the edge of an image significantly will decrease the amount of data and filters insignificant information by not deleting necessary structure from the image. The image used for this paper is a digital capture of a traffic sign with a background. The result of this study shows that Canny edge detection creates saliency map from the traffic sign and separates the road sign from the background. The image result tested by calculating the saliency distance between a tested image and trained image using normalized Euclidean distance . The value of normalized Euclidean distance is set between 0 to 2. The testing process is done by calculating the nearest distance between the tested vector features and trained vector features. From the examination as a whole, it can be concluded that road sign detection using saliency map model can be built by Canny edge detection. From the whole system examination, it resulted a accuracy value of 0,65. This value shows that the data was correctly classified by 65%. The precision value has an outcome of 0,64, shows that the exact result of the classification is 64%. The recall value has an outcome of 0,94. This value shows that the success rate of recognizing a data from the whole data is 94%.
MIMO‐OFDM‐radio over fiber system incorporating higher‐order space‐time block codes

Radio over fiber (RoF) is an indispensable technology for the amalgamation of microwave‐ and optical communication, which facilitates a flexible access‐network infrastructure proficient to endow with broadband wireless connectivity over an extensive assortment of applications. Achieving ample spectral efficiency in conjunction with excellent link reliability is the austere menace to the design of such prospect‐integrated systems. Moreover, amalgamation of multiple‐input multiple‐output (MIMO) technology with multicarrier multiplexing (MCM) such as orthogonal frequency division multiplexing (OFDM) is a proficient contender for supporting such next‐generation RoF‐based static‐ and mobile‐wireless systems. Earlier, the MIMO‐based multicarrier RoF systems are limited to the use of fourth‐order spatial diversity (2 × 2 antenna package) using the Alamouti code. Subsequently, the authors investigated the aptness and impetus of such integrated multicarrier RoF systems to provide a reliable and spectrally efficient system and proposed an orthogonal space‐time block code (OSTBC) equipped MIMO‐OFDM‐RoF system by incorporating higher order spatial diversity in conjunction with QAM (Quadrature Amplitude Modulation) schemes. The proposed work is carried out for NLOS (non‐line of sight) and LOS (line of sight) scenarios. Furthermore, the demonstrated work elucidates a relative QoS (Quality of Service) explorations of sixth (3 × 2 antenna package) and ninth order spatial diversity (3 × 3 antenna package) and recommend the optimal antenna package as per the requirements of the proposed integrated system in the demonstrated scenarios.
Production data analysis system using novel process capability indices-based circular economy

Purpose The purpose of this paper is to establish mechanisms for process improvement so that production efficiency and product quality can be expected, and create a sustainable development in terms of circular economy. Design/methodology/approach The authors obtain a critical value from statistical hypothesis testing, and thereby construct a process capability indices chart, which both lowers the chance of quality level misjudgment caused by sampling error and provides reference for the processes improvement in poor quality levels. The authors used the bottom bracket of bicycles as an example to demonstrate the model and methods proposed in this study. Findings This approach enables us to plot multiple quality characteristics, despite varying attributes and specifications, onto the same process capability analysis chart. And it therefore increases accuracy and precision to reduce rework and scrap rates (reduce), increase product availability, reduce maintenance frequency and increase reuse (reuse), increase the recycle rates of components (recycle) and lengthen service life, which will delay recovery time (recovery). Originality/value Parts manufacturers in the industry chain can upload their production data to the cloud platform. The quality control center of the bicycle manufacturer can utilized the production data analysis model to identify critical-to-quality characteristics. The platform also offers reference for improvement and adds the improvement achievements and experience to its knowledge management to provide the entire industry chain. Feedback is also given to the R&D department of the bicycle manufacturer as reference for more robust product designs, more reasonable tolerance designs, and selection criteria for better parts suppliers, thereby forming an intelligent manufacturing loop system.
A Hybrid Domain Adaptation Approach for Identifying Crisis-Relevant Tweets

Huge amounts of data generated on social media during emergency situations is regarded as a trove of critical information. The use of supervised machine learning techniques in the early stages of a crisis is challenged by the lack of labeled data for that event. Furthermore, supervised models trained on labeled data from a prior crisis may not produce accurate results, due to inherent crisis variations. To address these challenges, the authors propose a hybrid feature-instance-parameter adaptation approach based on matrix factorization, k-nearest neighbors, and self-training. The proposed feature-instance adaptation selects a subset of the source crisis data that is representative for the target crisis data. The selected labeled source data, together with unlabeled target data, are used to learn self-training domain adaptation classifiers for the target crisis. Experimental results have shown that overall the hybrid domain adaptation classifiers perform better than the supervised classifiers learned from the original source data.
Evaluation of Printed P(VDF-TrFE) Pressure Sensor Signal Quality in Arterial Pulse Wave Measurement

In this contribution, we evaluate the performance of an additively fabricated piezoelectric poly(vinylidenefluoride-co-trifluoroethylene) (P(VDF-TrFE)) based dynamic pressure sensor in non-invasive arterial pulse wave (PW) measurement. Additively fabricated piezoelectric sensors have high potential for the realization of affordable and unobtrusive PW measurement systems which could enable the long-term monitoring of patients with cardiovascular diseases (CVDs). However, the accuracy and reliability of such sensors have not been extensively studied before. We propose an additive fabrication process for a P(VDF-TrFE) PW-sensor, measure PW from the radial artery at the wrist from 22 healthy volunteer subjects, calculate clinically relevant parameters based on the PW waveform and compare their values to the values obtained from concurrent measurement with an electromechanical film (EMFi) based reference sensor, used earlier in several clinical studies. We show that the signals recorded with the two sensors, as well as the radial augmentation index (rAIx) and the stiffness index (SI) calculated from them, are in good agreement with each other. These results demonstrate that the additively fabricated P(VDF-TrFE) PW sensors can reach a suitable level of accuracy and reliability for clinical use.
Torque Ripple Mitigation of T-3L Inverter Fed Open-End Doubly-Salient Permanent-Magnet Motor Drives Using Current Hysteresis Control

A torque ripple mitigation and current hysteresis control for T-type three level (T-3L) inverter fed open-end doubly-salient permanent-magnet motor (DSPM) drives is proposed in this paper. The structure, principle, and characteristics of the DSPM are studied and analyzed and a T-3L inverter fed open-end three-phase DSPM drive configuration is proposed in this paper. Then, this paper introduces a novel commutation strategy to reduce the torque ripple during phase commutation. Furthermore, the multi-loop hysteresis current controller and DC-link voltage balancing algorithm are presented. The effectiveness of the proposed control schemes is verified by both simulation and experimental results.
Stable camera position control of unmanned aerial vehicle with three‐degree‐of‐freedom manipulator for visual test of bridge inspection

This paper describes a camera position control with aerial manipulator for visual test of bridge inspection. Our developed unmanned aerial vehicle (UAV) has three‐degree‐of‐freedom (3‐DoF) manipulator on its top to execute visual or hammering test of the inspection. This paper focuses on the visual test. A camera was implemented at the end of the manipulator to acquire images of the narrow space of the bridge such as bearings, which the conventional UAV without the camera‐attached manipulators at its top cannot achieve the fine visual test. For the visual test, it is desirable that the camera is above the body with enough distance between the camera and the body. As obvious, the camera position in the inertial coordinate system is effected by the movement of the body. Therefore we implement the camera position control compensating the body movement into the UAV. As a result of an experiment, it is assessed that the proposed control reduces the position error of the camera comparing the one of the body. The mean position error of the camera is 0.039 m that is 51.4% of the one of the body. Our world‐first study enables to acquire the image of the bearing of the bridge by a camera mounted at the end effector of aerial manipulator fixed on UAV.
Detection of hidden data attacks combined fog computing and trust evaluation method in sensor‐cloud system

With the popularity of Sensor‐Cloud, its security issues get more attention from industry and academia. Especially, Sensor‐Cloud underlying network is very vulnerable to internal attacks due to its limitations in computing, storage, and analysis. Most existing trust evaluation mechanisms are proposed to detect internal attack issues from the behavior level. However, there are some special internal attacks in the data level such as hidden data attacks, which are normal in the behavior level but generate malicious data to lead user to make wrong decisions. To detect this type of attacks, we design a fog‐based detection system (FDS), which is based on the trust evaluation mechanism in the behavior level. In this paper, three types of scenes (the redundant data, the parameter curve characteristic, and the data validation) are defined, and three detection schemes are given. Some experiments are conducted, which manifest that FDS has certain advantages in detecting hidden data attacks.
Source Separation for Enabling Dialogue Enhancement in Object-based Broadcast with MPEG-H

Dialogue Enhancement (DE) is one of the most promising applications of user interactivity enabled by object-based audio broadcasting. DE allows personalization of the relative level of dialogue for intelligibility or aesthetic reasons. This paper discusses the implementation of DE in object-based audio transport with MPEG-H, with a special focus on source separation methods enabling DE also for legacy content without original objects available. The user-benefit of DE is assessed using the Adjustment/Satisfaction Test methodology. The test results demonstrate the need for an individually adjustable dialogue level because of highly-varying personal preferences. The test also investigates the subjective quality penalty from using source separation for obtaining the objects. The results show that even an imperfect separation result can successfully enable DE leading to increased end-user satisfaction.