Miracle-dz/UniFAR-FTUs huggingface dataset:
Humor prediction with bi-directional long-short term memory

Humor prediction based on the statistical architecture aims to automatically judge whether a sentence/dialogue is laughing-provoking or not. Due to the complexity of the humor prediction, it is necessary to consider the contextual relevance on the text data when conducting semantic analysis, and the accuracy of Humor detection or comparison need to be further improved. This paper presents to the usage of Bi-directional Long-Short Term Memory (BiLSTM) to predict humor on textual data, and the predictions are reflected in the form of the comparison of humor between the two texts. In order to compare the two sentences in a mathematic way, the sentences are projected into vector space and the sentences are represented at the word-level granularity by using Global Vectors for Word Representation. To strengthen the influential factors of specific words in humor prediction, the similarity of humor vector (SoHV) is introduced as an additional feature, which is calculated from the Cosine similarity between the edit words and the original words in sentences. BiLSTM is compared with Convolutional Neural Network (CNN) on Humicroedit to illustrate its effectiveness in dealing with textual data. The experimental results illustrate that the proposed method significantly outperforms CNN by obtaining the accuracy of 51% and 34.2%, respectively. The effectiveness of BiLSTM is further verified on SemEval-2020 Task 7, which assesses Humor in Edited News Headlines. We are ranked 46th and 64th as to subtask-1 (classification task) and subtask-2 (regression task). Our analyses show that some particular words do have huge impact on the degree of humor in whole sentences and the BiLSTM model can have better cognition capacity by utilizing SoHV.
Creating ties of affection andmaintaining the language:elements of culturally competentcare for indigenous people

Objective: to interpret the perception of public health nurses when they provide the Embera Chami Indians with culturally competent care. Materials and Method: interpretative ethnography with participant observation and ethnographic interviews. The participants were three public health nurses who work in an intercultural Institution providing health services. The analysis followed Leininger’s proposal with support from Atlas ti and Excel. Results: the category “happy nurses with their work, extending this feeling to the personal field by creating bonds of affection with the indigenous Embera Chami” emerged and it was sustained with three subcategories. Conclusion: the public health nurses enjoy the work activities specified by the intercultural Institutions providing health services, they also enjoy the daily life offered by the work environment and the municipal situation characterized by the presence, socialization and interrelation with the Embera Chami indigenous people.
A Low-Noise L-Band Dielectric Resonator Stabilized Microstrip Oscillator

Design and performance of a unique microstrip L-band bipolar transistor dielectric resonator stabilized oscillator (DRO) is described which achieves ultralow single-sideband phase noise (-163 dBc/Hz at 100 kHz offset frequency), low I/f noise corner frequency of 12 kHz, with near-constant frequency (1280 +- 0.06 MHz) and power (12.55 +- 0.15 dBm) over -50° to 75°C. Circuit details to minimize noise as well as transistor selection criteria and measurements are presented. Back-to-back varactors provide 350 kHz electronic tuning range for phase-locking applications without any increase of noise.
Stripline Triplexer for Use in Narrow-Bandwidth Multichannel Filters (Short Papers)

Design techniques and equivalent circuits are presented for constructing a printed-circuit narrow-bandwidth complementary triplexer filter. The techniques and circuits described allow the construction of contiguous-band multichannel filters using printed circuits with no shorted stubs. A unit was designed and constructed to give a three-percent relative bandwidth for each separate channel. The agreement between theory and experiment was in the range of measurement accuracy.
A New Use for an Old Medicine: Dextromethorphan to Prevent Postoperative Sore Throat

Postoperative sore throat (POST) is a well‐recognised complication after general anaesthesia (Incidence: 21–65%). [1] POST is caused by trauma after airway instrumentation, leading to aseptic inflammation with congestion, oedema of pharyngolaryngeal mucosa, and raised biochemical markers, especially interleukin‐6. [2] POST may cause significant postoperative morbidity and dissatisfaction with symptoms like pain, soreness, hoarseness, and dysphagia. Prophylactic management to decrease its frequency and severity will improve the quality of anaesthesia care.
Modeling effects of system frequency variations in induction motor dynamics using singular perturbations

Summary form only given as follows. This paper presents an application of singular perturbation theory to modeling induction motors in system simulations. The focus is on model approximations and their impact on a motor's response to changes in system frequency as well as voltage. The fast states associated with the motor stator and rotor dynamics are eliminated from a full motor model using singular perturbations with a first order correction factor added. This leads to a reduced order motor model referred to as the singularly perturbed model. The starting performance of this model is compared to that of a full model, and to that of a simple model in which the fast states are modeled by neglecting the rates of change of the fast variables. The response of the singularly perturbed model is much closer to that of the full model than is that of the model which neglects the rates of change of the fast variables completely. It is also noted that a corrected first-order slip model of the induction motor can yield a more accurate speed response than a conventional uncorrected first-order slip model during frequency and voltage changes. The response of models are also compared to disturbances applied to a two-area four-machine power system and again the singularly perturbed model performance is closer to that of the full model than is the model with the rates of change of the fast states neglected completely. While the simulation time using the singularly perturbed model is longer than that using the simple model, it is considerably less than that of the full model.
n-Dimensional Polynomial Chaotic System With Applications

Designing high-dimensional chaotic maps with expected dynamic properties is an attractive but challenging task. The dynamic properties of a chaotic system can be reflected by the Lyapunov exponents (LEs). Using the inherent relationship between the parameters of a chaotic map and its LEs, this paper proposes an <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula>-dimensional polynomial chaotic system (<inline-formula> <tex-math notation="LaTeX">$n\text{D}$ </tex-math></inline-formula>-PCS) that can generate <inline-formula> <tex-math notation="LaTeX">$n\text{D}$ </tex-math></inline-formula> chaotic maps with any desired LEs. The <inline-formula> <tex-math notation="LaTeX">$n\text{D}$ </tex-math></inline-formula>-PCS is constructed from <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> parametric polynomials with arbitrary orders, and its parameter matrix is configured using the preliminaries in linear algebra. Theoretical analysis proves that the <inline-formula> <tex-math notation="LaTeX">$n\text{D}$ </tex-math></inline-formula>-PCS can produce high-dimensional chaotic maps with any desired LEs. To show the effects of the <inline-formula> <tex-math notation="LaTeX">$n\text{D}$ </tex-math></inline-formula>-PCS, two high-dimensional chaotic maps with hyperchaotic behaviors were generated. A microcontroller-based hardware platform was developed to implement the two chaotic maps, and the test results demonstrated the randomness properties of their chaotic signals. Performance evaluations indicate that the high-dimensional chaotic maps generated from <inline-formula> <tex-math notation="LaTeX">$n\text{D}$ </tex-math></inline-formula>-PCS have the desired LEs and more complicated dynamic behaviors compared with other high-dimensional chaotic maps. In addition, to demonstrate the applications of <inline-formula> <tex-math notation="LaTeX">$n\text{D}$ </tex-math></inline-formula>-PCS, we developed a chaos-based secure communication scheme. Simulation results show that <inline-formula> <tex-math notation="LaTeX">$n\text{D}$ </tex-math></inline-formula>-PCS has a stronger ability to resist channel noise than other high-dimensional chaotic maps.
Asset information for FMEA-based maintenance

FMEA (Failure Mode and Effects Analysis) is een methode die het gevolg van mogelijk falen op een product of een proces onderzoekt en analyseert. Het doel is preventieve constructie- of procesmaatregelen te treffen. Het promotieonderzoek van Jan Braaksma heeft als doel bij te dragen aan het informatiemanagement voor het onderhoud van kapitaalgoederen in de procesindustrie. Onderhoud heeft een belangrijke rol in het waarborgen van de integriteit van kapitaalgoederen en dus in het waarborgen van betrouwbaarheid, veiligheid en duurzaamheid van deze kapitaalgoederen. Een conclusie van het onderzoek is dat feedback op de informatie die gebruikt wordt in de FMEA’s verbeterd dient te worden. Daarbij wordt voorgesteld informatie van kritieke installaties anders te behandelen dan van niet-kritieke installaties. Het proefschrift omvat verder voorstellen de effectiviteit van kapitaalgoedinformatie te verhogen voor het gebruik in FMEA.
Network link prediction based on machine learning methods

Network analysis can help discover latent information on graph-structured data, and one of the major topics in link prediction [1]. Given the current state of a graph, the main task of link prediction is to predict the emergence of currently non-existing associations between nodes [2]. This project handles this problem with a machine learning-based method, where we compute a series of network parameters, feed them to a simple neural network and obtain the likelihood label for each non-existing edge. In the topic of connection prediction, this paper focuses on the application effect of mainstream machine learning algorithms, finds the key statistical parameters in the algorithm, and compares the prediction efficiency with deep learning. The test data I used came from Facebook. A complex network with 4000 nodes and 88000 links is constructed as the test object, and the influence of test sample data selection on test results is analyzed.
The Usability of Terrestrial 3D Laser Scanning Technology for Tunnel Clearance Analysis Application

After building underground constructions, spatial parameters monitoring is essential due to safety and statuary reasons. Therefore after completion of work in tunnels often supervision projects follow which include cross sections measurements, as well as ground and secondary wall layer deformations monitoring during consolidation era. Conventional approaches to achieve this type of documentations are different, however their downside is often that they are time consuming and even with combination of independent contractors, collected data is often deficient and corrupted with rough interpolations. Terrestrial 3D laser scanning (TLS) represents alternative approach to conventional monitoring methods [1]. With engineer planning approach, field work and data interpretation, TLS technology allows systematical and fast acquisition of shape and spatial orientation of complex objects and all their components. In case of shorter railway tunnels (up to 360 m) data for clearance analysis in correlation of standard cargo and tunnel surface, was captured with terrestrial 3D laser scanning method. Control of tunnel clearance is usually performed analogously and on conventional low equidistant cross section survey method. Considering that in this article we deal with relative old tunnels, in which there is no constant transversal profile but huge amount of geometric anomalies, simulation verification could be performed only with hi-grid definition survey method. With TLS larger amount of tunnels were measured and clearance analysis simulations for real case of standard cargo profile was made, based on radius and railway inclination of the tunnel. Standard or non-standard cargo transport planning with computer simulation now can be done in relatively short time. In this article is presented integration of TLS in case study of short railway tunnels with focus on clearance analysis applications with interactive and user friendly visualization for data interpretation. Other methods for different spatial parameters interpretations in underground constructions are presented as well.
Evaluation and modelling of a passive hydraulic steering for locomotives

During the past few decades, substantial improvements were made to rail infrastructure worldwide. This was necessary to accommodate the ever increasing transportation demand and requirements. Nowadays, trains are required to transport heavier loads and to travel at higher speeds. One of the major improvements was achieved by the development of the off-flange curving bogie designs to reduce wheel and rail wear. Off-flange designs include passive steering and actively controlled steering. The development and implementation of self-steering bogies on locomotives was promoted in the early 1980’s by two major locomotive manufacturers. Up to date, thousands of these locomotives, with built-in self-steering bogies, have been manufactured and taken into service (Swenson, 1999). Most self-steering bogies have mechanical linkage systems to steer the wheel sets. As an alternative to the mechanical linkage system, the DCD Group (a South African manufacturer of rail and mining equipment) initiated the development of a Passive Hydraulic Steering (PHS) system. First PHS prototype systems, developed by DCD, have proven that huge wear reduction possibilities exist on both, rails and wheels. In addition the prototype systems also significantly decreased noise and vibration levels when negotiating tight corners (Swenson & Scott, 1996 and DCD Rolling Stock, 2012). However, existing prototype solutions require further improvements and development for optimisation. To be able to identify and implement improvements, the need exists to perform modelling and testing of the systems to obtain a better understanding of the operation and suitability of a complete unit.
The effect of credit risk management and bank-specific factors on the financial performance of the South Asian commercial banks

PurposeAmong all of the world's continents, Asia is the most important continent and contributes 60% of world growth but facing the serving issue of high nonperforming loans (NPLs). Therefore, the current study aims to capture the effect of credit risk management and bank-specific factors on South Asian commercial banks' financial performance (FP). The credit risk measures used in this study were NPLs and capital adequacy ratio (CAR), while cost-efficiency ratio (CER), average lending rate (ALR) and liquidity ratio (LR) were used as bank-specific factors. On the other hand, return on equity (ROE) and return on the asset (ROA) were taken as a measure of FP.Design/methodology/approachSecondary data were collected from 19 commercial banks (10 commercial banks from Pakistan and 9 commercial banks from India) in the country for a period of 10 years from 2009 to 2018. The generalized method of moment (GMM) is used for the coefficient estimation to overcome the effects of some endogenous variables.FindingsThe results indicated that NPLs, CER and LR have significantly negatively related to FP (ROA and ROE), while CAR and ALR have significantly positively related to the FP of the Asian commercial banks.Practical implicationsThe current study result recommends that policymakers of Asian countries should create a strong financial environment by implementing that monetary policy that stimulates interest rates in this way that automatically helps to lower down the high ratio of NPLs (tied monitoring system). Liquidity position should be well maintained so that even in a high competition environment, the commercial is able to survive in that environment.Originality/valueThe present paper contributes to the prevailing literature that this is a comparison study between developed and developing countries of Asia that is a unique comparison because the study targets only one region and then on the basis of income, the results of this study are compared. Moreover, the contribution of the study is to include some accounting-based measures and market-based measures of the FP of commercial banks at a time.
A dual‐band and wideband planar inverted‐F antenna for WLAN applications

A dual‐band planar inverted‐F antenna (PIFA), presented here, covers both 2.4‐ and 5‐GHz bands used in all IEEE 802.11 WLAN standards. Computed and measured return loss and radiation patterns of the antenna are presented and are in reasonable agreement. Experimental results indicate a very wide 32.5% operational bandwidth in the 5‐GHz band. © 2007 Wiley Periodicals, Inc. Microwave Opt Technol Lett 50: 138–141, 2008; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.23016
A neural approach to product demand forecasting

This paper develops an artificial neural network (ANN) model to forecast the optimum demand as a function of time of the year, festival period, promotional programmes, holidays, number of advertisements, cost of advertisements, number of workers and availability. The model selects a feed-forward back-propagation ANN with 13 hidden neurons in one hidden layer as the optimum network. The model is validated with a furniture product data of a renowned furniture company. The model has also been compared with a statistical linear model named Brown's double smoothing model which is normally used by furniture companies. It is observed that ANN model performs much better than the linear model. Overall, the proposed model can be applied for forecasting optimum demand level of furniture products in any furniture company within a competitive business environment.
Bridge Deck Inspection Using Small Unmanned Aircraft Systems Based Airborne Imaging Techniques

Traditional bridge deck inspection is primarily conducted on the ground by having inspectors either visually inspect the surface condition or interpret the acoustic feedback from hammer sounding or chain dragging method to determine the subsurface condition. These traditional methods are expensive, time-consuming, laborintensive, unsafe, can exhibit a high degree of variability, and require specialized staff on a regular basis. In recent years, many remote sensing technologies have shown promise in bridge deck inspection. This project will focus on using small unmanned aircraft systems (sUAS) based airborne imaging techniques and image analysis techniques to develop a complete data acquisition and analysis system to accurately and rapidly detect bridge deck surface and subsurface distresses at a low cost. This project will also develop a guidebook for the implementation of the proposed bridge deck inspection system to assist transportation agencies with workforce development and professional training.
Multiplexing Invited Paper

This paper presents the GFDM system, a gen- eralized digital multi-carrier transceiver concept. GFDM is based on traditional filter bank multi-branch multi- carrier concepts which are now implemented digitally. Our GFDM approach exhibits some attractive features which are of particular importance for scenarios exhibit- ing high degrees of spectrum fragmentation. Spectrum fragmentation is a typical technical challenge of digital dividend use cases, exploiting spectrum white spaces in the TV UHF bands which are located in close proximity to allocated spectrum. Specifically, the GFDM features are a lower PAPR compared to OFDM, a ultra-low out-of- band radiation due adjustable Tx-filtering and last but not least a block-based transmission using cyclic prefix insertion and efficient FFT-based equalization. GFDM enables frequency and time domain multi-user scheduling comparable to OFDM and provides an efficient alternative for white space aggregation even in heavily fragmented spectrum regions.
How Airport Context and Service Are Related to General Aviation Aircraft Operations

Nationwide, there is an effort to improve small airport facilities for reducing demand and congestion at primary commercial airports. Identifying the factors that are associated with operations can help decision makers select new airport sites, choose between airport improvement alternatives, and anticipate future service needs. There are many local benefits to attracting aircraft traffic, as operations are often associated with positive economic impacts. This research seeks to identify airport service and contextual variables that have strong associations with general aviation aircraft operations, in which an operation is defined as one aircraft landing or departing. It builds on the existing literature by incorporating aspects of land use, ground access, economic productivity, and regional transportation factors into a robust operations model. Data from multiple sources were combined using a geographic information system to create a unique longitudinal data set providing a comprehensive view of 41 North Carolina airports over a 12-year period, from 1988 to 1999. Fixed- and random-effects regression models were estimated, and many of the hypothesized factors associated with operations, including local population, surrounding commercial development, and available aviation services, were found to be statistically significant. Understanding these factors is useful for airport system planning, from anticipating future demand to attracting general aviation operations away from congested, primary airports.
Ultrasonic Мeasurements and its Evaluation for the Monitoring of Saccharomyces cerevisiae Cultivation

The monitoring and supervision of batch Saccharomyces cerevisiae cultivations are presented by ultrasonic velocity measurements. The measurements are performed in a by-pass to reduce the influence of bubbles. Using these signals the typical phases of such cultivations can be identified. Applying a multi-linear regression model the ultrasonic veloc- ity can be estimated by the biomass, the glucose and the ethanol concentration with a mean estimation error of 1.6 m/s. The multi-linear regression model has also been used to predict one of the three process variables by the other two and the ultrasonic velocity. Here the mean error of prediction is 0.6 g/L, 2.3 g/L and 1.5 g/L for biomass, glucose and ethanol concentration respectively. Using a Kalman filter theses variables have been estimated with mean errors of 0.6 g/L, 1.8 g/L and 1.6 g/L.
Perspective Traffic Display Format and Airline Pilot Traffic Avoidance

Part-task experiments have examined perspective projections of cockpit displays of traffic information as a means of presenting aircraft separation information to airline pilots. Ten airline pilots served as subjects in an experiment comparing the perspective projection with plan-view projections of the same air traffic situations. The pilots' task was to monitor the traffic display in order to decide if an avoidance maneuver was needed. Pilots took more time to select avoidance maneuvers with a conventional plan-view display than with an experimental perspective display. In contrast to previous results, if the pilots selected a maneuver with the perspective display, they were more likely to choose one with a vertical component. Tabulation of the outcomes of their initial avoidance decisions with both perspective and plan-view displays showed that they were more likely to achieve required separation with maneuvers chosen with the aid of perspective displays.