Miracle-dz/UniFAR-FTUs huggingface dataset:
Annotated Example SDP for WebRTC

The Web Real Time Communications (WebRTC) family of protocols defines mechanisms for direct interactive rich communication using audio, video and data between two peers' web browsers. Within the WebRTC framework, the Session Description protocol (SDP) is used for negotiating session capabilities between the peers. Such a negotiation happens based on the SDP Offer/Answer exchange mechanism This document provides an informational reference in describing the role of SDP and the Offer/Answer exchange mechanism for the most common WebRTC use-cases.
MEDUSA: una nueva herramienta para el desarrollo de sistemas Brain-Computer Interface basada en Python

En este estudio se presenta MEDUSA, una nueva plataforma para la implementación de sistemas Brain-Computer Interface (BCI), utilizando como señal de control los potenciales evocados P300 generados mediante el paradigma odd-ball visual. Las principales características de MEDUSA son: i) diseño modular, conectando las distintas partes de la aplicación mediante estructuras simples; ii) arquitectura especialmente diseñada para entornos de investigación, que permite implementar nuevos paradigmas de estimulación, métodos de preprocesado de señal, o algoritmos de extracción, selección y clasificación de características de manera sencilla e integrarlos rápidamente en el flujo de ejecución; iii) desarrollo en Python: un lenguaje multiplataforma muy utilizado en investigación por su simplicidad y versatilidad, disponiendo además de gran cantidad de librerías que disminuyen el tiempo de desarrollo; iv) amplia documentación, con ejemplos de aplicación y código detalladamente comentado; v) interfaz gráfica atractiva y moderna, que permite modificar de manera sencilla gran cantidad de parámetros de la plataforma.
The effect on the wind power performance of different normalization methods by using multilayer feed-forward backpropagation neural network

Artificial Neural Networks is the most used machine learning approach today. It is a very successful method in terms of accuracy and reliability. It is widely used in classification and estimation calculations. In order to achieve the desired performance a model created with ANN, a series of processes such as selection of network structure, learning algorithms, input and output values adjustment and transfer functions determination needs to be implemented in a sensitive manner. Multilayer Feedforward Backpropagation Network, which is used most frequently in supervised learning approaches, was considered in this study. The effect on the prediction performance of the developed model was investigated by using different statistical normalization methods on the data to be used in the network. For this purpose, 4-input 1-output artificial neural networks model were operated with wind-based data taken from Osmaniye Korkut Ata University measuring station. Wind speed, Wind Direction, Humidity and Density data are defined as input values while wind power was defined as output value. Input and output data are calculated with different normalization methods and more than one network models are designed with calculated values. As a result, the study showed that artificial neural networks model which is established by sigmoid normalization method has the best performance value.
Generalized Frequency-Domain Filtered Single-Carrier Signal Transmission

Single-carrier (SC) transmission is a transmission equipped with frequency-domain equalization (FDE) is suitable for uplink transmission because of its low peak-to-average power ratio (PAPR) property. Square-root Nyquist filtering is widely used, where the filter shape is controlled by the roll-off factor  from 0 to 1. Nyquist filtering with =1 occupies twice bandwidth of the original signal. SC signal can be generated by inserting discrete Fourier transform (DFT) block in orthogonal frequency division multiplexing (OFDM). This realizes an introduction of various frequency-domain signal processing into SC signal transmission. In this paper, we introduce a generalized frequency-domain transmit filtering to SC transmission equipped with FDE (SC-FDE). The transmitted data is initially transformed to the frequency-domain signal and then copied over the available frequency spectrum before applying filtering. Any transfer function can be used and the filtered signal bandwidth can be arbitrary chosen in order to obtain more frequency diversity gain. The transmit filtering with >1 is equivalent to spread spectrum technique in the time-domain and frequency-domain. Performance of the proposed generalized filtered SC-FDE is evaluated by computer simulation in aspect of PAPR and bit-error rate (BER), and compared to the time-domain spread spectrum scheme. The advantages and disadvantages of the proposed generalized SC-FDE and the time-domain spread spectrum scheme are also discussed. Keyword Single-carrier (SC) transmission, transmit filtering, spread spectrum (SS)
Integrating word status for joint detection of sentiment and aspect in reviews

A crucial task in sentiment analysis is aspect detection: the step of selecting the aspects on which opinions are expressed. This step anticipates the step of determining whether the opinions on aspects are positive or negative. This article proposes a novel probabilistic generative topic model for aspect-based sentiment analysis which is able to discover the latent structure of a large collection of review documents. The proposed joint sentiment-aspect detection model (SAM) is a generative topic model that incorporates the structure of review sentences for detecting aspects and sentiments simultaneously. The intuitions behind the SAM are that from generating documents by latent single- and multi-word topics, modelling the word distribution for each topic and learning of the prior distribution over topics in sentences of documents. SAM introduces word status so that the model can decide when to sample from a bigram distribution or a unigram distribution and integrates all these components into one combined model for aspect-based sentiment analysis. We evaluate SAM both qualitatively and quantitatively to show that the model is indeed able to perform the task effectively and improves significantly over standard joint sentiment-aspect models. The proposed model can easily be transformed between domains or languages and can detect the polarity of text data at various levels. However, for the quantitative analysis, we mainly focus on presenting the results for the document-level sentiment classification.
Learning Monotone Functions from Random Examples in Polynomial Time

We give an algorithm that learns any monotone Boolean function f : {−1, 1}n → {−1, 1} to any constant accuracy, under the uniform distribution, in time polynomial in n and in the decision tree size of f. This is the first algorithm that can learn arbitrary monotone Boolean functions to high accuracy, using random examples only, in time polynomial in a reasonable measure of the complexity of f. A key ingredient of the result is a new bound showing that the average sensitivity of any monotone function computed by a decision tree of size s must be at most √ log s. We generalize the basic inequality and learning result described above in various ways; specifically, to partition size (a stronger complexity measure than decision tree size), p-biased measures over the Boolean cube (rather than just the uniform distribution), and real-valued (rather than just Boolean-valued) functions. Some of this work was done while at the Institute for Advanced Study, supported by National Science Foundation under agreement No. CCR-0324906. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. Supported in part by NSF CAREER award CCF-0347282 and a Sloan Foundation Fellowship.
Inkjet printing of metal nanoparticles for green UHF RFID tags

Abstract. UHF RFID tags are nowadays widely and successfully implemented in many distinct applications, but unfortunately the traditional production process and incorrect disposal of such devices have a negative impact on the environment. In this work silver and gold nanoparticle inks were printed by a consumer inkjet printer on eco-friendly substrates like paper and PET in order to make the manufacturing process less harmful to the ecosystem. A dipole antenna with matching loop was designed for the RFID chip EM4325 from EM Microelectronics, which has an integrated temperature sensor, at the frequency of 866 MHz. Based on this design, simulations of the greener tags are presented and compared as a proof of concept, without optimizing the designs at first for the different materials. The printings with silver (unlike the gold) were conductive with self-sintering. IPL sintering was conducted to reduce the sheet resistance from the silver ink and to turn the gold ink conductive. First S11 parameter and read distance measurements are shown as well as the simulations with the optimized antenna designs.
Exploring the Designer-Constructor Teamwork Interface to improve Collaboration: A review of current literature

The construction industry has been criticised over several decades for functioning and producing output with low levels of productivity when compared to other manufacturing-based industries. One possible solution to improve productivity is the adoption of collaborative working practices by project teams, particularly designers and constructors during the design phase. Arguments in support of the need to manage the design process effectively during a construction project are well documented. Issues such as providing the client with a sustainable, affordable, quality design that adds value to their business needs, requires attention. Managing the interpersonal interface between designers and constructors during the design phase is a vital requirement of design management practice. Design management is a discipline that requires a thorough understanding of the nature and culture of the different professionals to improve the social behaviours and performance of teams, which in turn may improve project outcomes and thus industrial productivity. The current study, which is part of an ongoing project, presents the position of the design management literature focused on the interpersonal behaviour between designers and constructors. Following a strategically focused review of the extant literature, current themes relevant to Teamwork Quality (TWQ), specific to the designer-constructor interface, are presented. The findings confirm the presence of 14 articles that explore collaborative teamwork behaviour between designers and constructors and that survey methods dominate publications in this area. Few studies capture the power of space and place by observing ‘live' industry practice, particularly from a longitudinal perspective. Recommendations include the identification of research themes worthy of future exploration that may assist in teamwork performance concerning productivity. An increase in the use of alternative methodological approaches such as ethnographic and action research is also justified and discussed.
Vulnerability Based Seismic Assessment and Retrofit of One- and Two-Family Dwellings (ATC-110 Project)

The California Earthquake Authority (CEA) and the Federal Emergency Management Agency (FEMA), through the Applied Technology Council’s ATC-110 Project series, have sponsored development of a prestandard for seismic assessment and retrofit of cripple wall, house-overgarage, and hillside vulnerabilities in residential wood dwellings. Although simplified for the purposes of implementation, methodologies are being developed using best available numerical tools and performance objectives consistent with the philosophies of current seismic codes and standards. After almost three years of work, prestandard provisions and prescriptive plan sets for assessment and retrofit are nearing completion. This paper discusses the project methodology, illustrates retrofit approaches and interim numerical study results, and shares insights gained. 1 Structural Engineer, Buehler & Buehler, San Carlos, CA 94070 (cblaney@bbse.com) 2 Structural Engineer, Hohbach-Lewin, Inc., 296 East 5th Ave. Suite 302, Eugene, Oregon 97401 (vbourcier@hohbach-lewin.com) 3 Structural Engineer, Wiss Janney Elstner Assoc. , Emeryville, California 94608 (kcobeen@wje.com) 4 Professor, Department of Civil, Structural and Environmental Engineering, University at Buffalo, State University of New York, Buffalo, NY 14260 (af36@buffalo.edu) & University School for Advanced Studies IUSS Pavia, Italy (andre.filiatrault@iusspavia.it) 5 Post-doctoral researcher, Department of Civil and Environmental Engineering, Stanford University, Stanford, CA 94305 (dpwelch523@gmail.com) 6 Graduate Student, Glenn Department of Civil Engineering, Clemson University, Clemson, SC 29634 (mwstone@g.clemson.edu) 7 Associate Professor, Glenn Department of Civil Engineering, Clemson University, Clemson, SC 29634 (wpang@clemson.edu) 8 Staff Engineer, Hohbach-Lewin, Inc., 296 East 5 Ave. Suite 302, Eugene, Or 97401 (tvincent@hohbachlewin.com) Eleventh U.S. National Conference on Earthquake Engineering Integrating Science, Engineering & Policy June 25-29, 2018 Los Angeles, California Vulnerability Based Seismic Assessment and Retrofit of Oneand Two-Family Dwellings (ATC-110 Project) C. Blaney, V. Bourcier, K. Cobeen, A. Filiatrault, D. Welch, M. Stoner, W. Pang, and T. Vincent
Design Methodology of a High- $Q$ Tunable Coaxial Filter and Diplexer

Any filter of order <inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> can be readily tuned for a constant absolute bandwidth (BW) using <inline-formula> <tex-math notation="LaTeX">$2N+1$ </tex-math></inline-formula> independent tuning elements. This significantly increases the size and the cost, and also adds to the complexity of the tuning control mechanism. This article demonstrates the feasibility of realizing a high-<inline-formula> <tex-math notation="LaTeX">$Q$ </tex-math></inline-formula> tunable coaxial filter, which is tuned by a single rotational tuning element irrespective of the filter order. The proposed filter has low variations in the absolute BW and insertion loss (IL) over a relatively wide tuning range. A prototype four-pole filter is developed at 2.5 GHz with a fractional BW of 4% to verify the concept. The measured tuning range of the filter is 20%, within which the BW variation is better than ±10% and IL variation is better than 0.05 dB. The proposed concept is easily expandable to filters with higher order. Furthermore, the concept is adopted to design a tunable diplexer which can be tuned using a single tuning mechanism. The proposed high-<inline-formula> <tex-math notation="LaTeX">$Q$ </tex-math></inline-formula> tunable filter is promising for use in the frequency-agile communication architecture at the cellular base-station and aerospace applications.
Spatio-Radio Resource Management and Hybrid Beamforming for Limited Feedback Massive MIMO Systems

In this paper, a joint spatio–radio frequency resource allocation and hybrid beamforming scheme for the massive multiple-input multiple-output (MIMO) systems is proposed. We consider limited feedback two-stage hybrid beamformimg for decomposing the precoding matrix at the base-station. To reduce the channel state information (CSI) feedback of massive MIMO, we utilize the channel covariance-based RF precoding and beam selection. This beam selection process minimizes the inter-group interference. The regularized block diagonalization can mitigate the inter-group interference, but requires substantial overhead feedback. We use channel covariance-based eigenmodes and discrete Fourier transforms (DFT) to reduce the feedback overhead and design a simplified analog precoder. The columns of the analog beamforming matrix are selected based on the users’ grouping performed by the K-mean unsupervised machine learning algorithm. The digital precoder is designed with joint optimization of intra-group user utility function. It has been shown that more than 50 % feedback overhead is reduced by the eigenmodes-based analog precoder design. The joint beams, users scheduling and limited feedbacK-based hybrid precoding increases the sum-rate by 27 . 6 % compared to the sum-rate of one-group case, and reduce the feedback overhead by 62 . 5 % compared to the full CSI feedback.
DC-Link Voltage-Balancing Strategy Based on Optimal Switching Sequence Model Predictive Control for Single-Phase H-NPC Converters

In this article, a model predictive control (MPC) strategy based on the optimal switching sequence (OSS) concept for a single-phase grid-connected H-bridge neutral-point-clamped (H-NPC) power converter is presented. The proposed OSS-MPC algorithm considers both the grid current tracking error and the dc-link capacitor voltage balance. Special emphasis is placed on the power converter control region in order to design suitable switching sequence candidates for this multiobjective control problem. Additionally, based on an analysis of the weighting factor effect over closed-loop performance, it is possible to demonstrate that this controller parameter is relatively easy to adjust. In fact, the weighting factor only affects the peak current during transients, with no effect over the steady-state performance. As a result, the proposed OSS-MPC provides a fast closed-loop dynamic to the H-NPC converter, which operates with a fixed switching frequency at all times. This predictive control strategy is experimentally validated in a 3.5-kVA laboratory setup.
Comparative Study Between Daubechies and Coiflets Wavelet Decomposition Mother Families in Feature Extraction of BCI Based on Multiclass Motor Imagery Discrimination

Brain-computer interface (BCI) is a method of direct communication between the human brain and the computer without the need for the use of other physical organs such as peripheral muscles, where the interface allows the human to order any electronic device using brain activity only. Multiclass discrimination of motor imagery movements is one of the BCI applications that uses electrical signals measured from brain or muscles; these signals were filtered and processed using time, space, and frequency feature extraction techniques, and machine learning algorithms to construct a system achieve best performance. The objective of this research was to make a comparative study between different wavelet Daubechies and Coiflets families mother functions used as feature extraction to discriminate between 4 classes of imagined movements. The coefficients of different Wavelet Daubechies (2-20) and Coiflets (1-5) were examined in calculating common spatial filters to discriminate between 4 imagined classes, where 4 detail levels of the wavelet coefficients were calculated; support vector machine was used as a classifier that enables the classification of imagined movements. The algorithms applied to the BCI competition IV data set 2a. Result yields performance of 0.53 and 0.52 average &kgr; coefficients using Db2 and Coif1, respectively.
A Novel Method for Feature Extraction and Automatic Recognition of Tire Defects Using Independent Component Analysis

In order to extract the features of tire defects in X-ray images, Linear transformation is often performed on the images. However, Gabor and wavelet transformation are predefined and unchangeable, and their basic functions can’t be adapted to the characteristics of defect images. So we propose a new approach using Independent Component Analysis (ICA) and Topographic Independent Component Analysis (TICA) reconstruction algorithm to extract the features of tire defects and apply automatic recognition of tire defects. First, the basis functions and filters which adapt to the characteristics of defect images are estimated adaptively using ICA and TICA from the tire defect library. Then, the tire defect images are filtered to extract features. Finally, the samples are classified by a nonlinear support vector machine (SVM). Experimental results show that the proposed algorithm has very high recognition rates for shape defects, texture defects and other defects. Its total recognition rate can be as high as 95.76%.
A Static Balancing Method for Variable Payloads by Combination of a Counterweight and Spring and Its Application as a Surgical Platform

Stackable mechanism architecture has demonstrated effective gravity-balancing over entire workspaces. Adjustable balancing is required when balancing is broken due to changing the payload at the distal end of a mechanism. In this paper, adjustable balancing of the stackable mechanism for a variable payload is investigated. For this, balancing conditions for three adjustable balancing methods are suggested, and a new balancing method combining a spring and counterweight is considered as an effective means of adjustable balancing for variable payloads. The excellent performance of the system is proven through experiments. Electromyography (EMG) sensors are employed to measure the amount of energy expenditure during the drilling task. It was verified through several tests that an operator holding a drill mounted at the distal end of a stackable arm felt less energy compared to an operator holding the drill directly in free space. The developed balancing arm was successfully applied during a mastoidectomy. A 3-step warning algorithm along with a braking function was found to be effective for safe surgery.
Ultraefficient Green LEDs Using Quantum Dots in Liquid Matrix

Green spectral range, which has the highest human eye sensitivity, is one of the most fundamental colors in lighting and display. Quantum dots (QDs) offer exceptional optical properties including high quantum yield (QY), strong absorption, and narrow emission linewidths for efficient green-emitting diodes. In this article, we demonstrated QD-based light-emitting diodes (QD-LEDs) that operate at a luminous efficiency (LE) level of 95 lumens per electrical watt, the luminous efficacy of optical radiation of 409 lumens per optical watt, and external quantum efficiency (EQE) of 23.3% in the green spectral region. For that, we synthesized 1-octanethiol-capped CdSe/ZnS QDs with an absolute QY of 91% and integrated them in a liquid matrix that allows conservation of the QD efficiency in device architecture. Our simulations were in agreement with the performance of the fabricated QD-LEDs, and they showed that the QD-LEDs can be further improved to reach LE levels over 250 lm/W.
A Conceptual Survey of Sturucture, Security and Advantages in Virtual Private Network

There is an increasing request nowadays to connect to core networks from different places. Workers regularly need to connect to internal private networks over the Internet from home, hotels, airports or from other external networks. Security becomes a main attention when staff or business partners have constant access to internal networks from insecure external locations. Currently, such a secured access is realized with Virtual Private Network (VPN) connections. Although operational, the current VPN solutions suffer of severe limits. Most of the VPN solutions are not satisfactorily secured since they are using weak authentication. The more secured ones are quite often expensive and require the usage of security tokens that demand administration from the service provider. On the user's side there is a need for additional care and attention since he/she has to carry an extra device. In this paper, the focus is to examine the structure, security, and benefits of VPNs.