Miracle-dz/UniFAR-FTUs huggingface dataset:
Probability of detection curve for the automatic visual inspection of steel bridges

The damage tolerant design philosophy is based on periodical inspections and provides safe bridge operation preventing fatigue cracks from growing up to a critical size. It is possible to optimize the management costs of a bridge throughout its life by designing the inspection frequency, which depends on the capabilities of the inspection method. However, such optimization requires knowledge about the performance of inspections that are envisioned to take place during the use of the bridge. Regular visual inspections is the most frequently applied type of inspection of bridge structures. Recent advances in computer vision technologies provide a strong basis for the development of automatic damage detection systems that can support regular visual inspection, thus increasing the reliability of the inspection. Several automatic crack detection systems have been developed in the past years. However, the performances of such systems have not been evaluated in the way as for traditional non‐destructive inspection methods, i.e. in terms of probability of detection curves and detectability limits. This restricts the applicability of automatic visual inspections for inspection planning and damage tolerant design. This paper proposes an encoder‐decoder neural network for segmentation of cracks on images of steel bridges. A probability of detection curve is calculated for this neural network.
Active disturbance rejection for the bipedal walk of a humanoid robot using the motion of the arms

A control system for the walking of a redundant biped robot in the swing phase is considered. The biped is a humanoid with 6DOF per leg and 3DOF per arm. The controller will be based on a full kinematic model of the robot to depict a more accurate behavior of the robot. The arms of the robot are used to compensate for disturbances the robot may experience during walking. Instead of controlling the robots ZMP, keeping it within the support polygon, all six foot support reaction components are controlled. First, a “shoe” with force sensors detect the forces and moments on the foot for feedback. The feedback from the joint servos provide position and velocity information. The support reaction and the joint position/velocities are fedback to a sliding mode controller, which makes adjustments to the arm links’ acceleration to compensate the shift in the reaction components. Simulations show the comparison of the ZMP shift when disturbances are applied with and without controlling the reaction forces to prove the effectiveness of the approach. NOMENCLATURE d Unknown actual disturbance vector D Upper bound of actual disturbance vector FR Actual force vector exerted by robot to ground FR(t) Desired force vector exerted by robot to ground Fs Actual force vector exerted by ground to robot Fx Longitudinal support force Fy Lateral support force Fz Vertical support force g Gravitational acceleration vector Gai Jacobian matrix for arm joint angular velocities Gbi Jacobian matrix for body/legs joint angular velocities Ii Link i moment of inertia matrix expressed in local frame Jai Jacobian matrix for arm joint linear velocities Jbi Jacobian matrix for body/legs joint linear velocities K Diagonal positive definite gain matrix Kv Row vector containing the diagonal elements of K mi Mass of link i MR Actual moment vector exerted by robot to ground MR(t) Desired moment vector exerted by robot to ground Ms Actual moment vector exerted by ground to robot Mx Support moment about the longitudinal axis My Support moment about the lateral axis Mz Support moment about the vertical axis q Joint variables of the robot’s limbs qa Vector containing arm joint positions qb Vector containing body/legs joint positions q(t) Desired joint variables of the robot’s limbs R0i Transformation from local frame of link i to inertial frame ri Position vector of the center of gravity of link i s Parameter defining the surface for sliding mode control u Control input vector containing arm joint accelerations y Actual control output y Desired control output z Double time integral of control output ω i Link i angular velocity vector expressed in global frame ω B i Link i angular velocity vector expressed in local frame 1 Copyright c © 2011 by ASME
Lindorm TSDB: A Cloud-native Time-series Database for Large-scale Monitoring Systems

Internet services supported by large-scale distributed systems have become essential for our daily life. To ensure the stability and high quality of services, diverse metric data are constantly collected and managed in a time-series database to monitor the service status. However, when the number of metrics becomes massive, existing time-series databases are inefficient in handling high-rate data ingestion and queries hitting multiple metrics. Besides, they all lack the support of machine learning functions, which are crucial for sophisticated analysis of large-scale time series. In this paper, we present Lindorm TSDB, a distributed time-series database designed for handling monitoring metrics at scale. It sustains high write throughput and low query latency with massive active metrics. It also allows users to analyze data with anomaly detection and time series forecasting algorithms directly through SQL. Furthermore, Lindorm TSDB retains stable performance even during node scaling. We evaluate Lindorm TSDB under different data scales, and the results show that it outperforms two popular open-source time-series databases on both writing and query, while executing time-series machine learning tasks efficiently.
AN ANALYSIS OF THE THIRD YEAR STUDENTS’ ABILITY IN ANSWERING SYNONYMOUS WORD QUESTIONS IN READING COMPREHENSION OF TOEFL LIKE TEST AT THE ENGLISH DEPARTMENT OF BUNG HATTA UNIVERSITY

Reading class seriously, pay attention to the lecturer’s explanation, and do more exercise to answer those types of questions. Last but not least, the future researchers are suggested to conduct the related study to overcome the students’ problems in any section of TOEFL Like test. It is suggested to the further researchers to find out the cause of students’ low ability in answering TOEFL Like test.
Structural cumulative survival models for estimation of treatment effects accounting for treatment switching in randomized experiments

Treatment switching in a randomized controlled trial occurs when a patient in one treatment arm switches to another arm during follow‐up. This can occur at the point of disease progression, whereby patients in the control arm may be offered the experimental treatment. It is widely known that failure to account for treatment switching can seriously bias the estimated treatment causal effect. In this paper, we aim to account for the potential impact of treatment switching in a reanalysis evaluating the treatment effect of nucleoside reverse transcriptase inhibitors (NRTIs) on a safety outcome (time to first severe or worse sign or symptom) in participants receiving a new antiretroviral regimen that either included or omitted NRTIs in the optimized treatment that includes or omits NRTIs trial. We propose an estimator of a treatment causal effect for a censored time to event outcome under a structural cumulative survival model that leverages randomization as an instrumental variable to account for selective treatment switching. We establish that the proposed estimator is uniformly consistent and asymptotically Gaussian, with a consistent variance estimator and confidence intervals given, whose finite‐sample performance is evaluated via extensive simulations. An R package ‘ivsacim’ implementing all proposed methods is freely available on R CRAN. Results indicate that adding NRTIs versus omitting NRTIs to a new optimized treatment regime may increase the risk for a safety outcome.
Capital Account Liberalization and Economic Growth : The Empirical Relationship Revisited

This paper reexamines the eﬀects of capital account liberalization on economic growth using various measures and methods. We ﬁnd the evidence that capital account liberaliza‑ tion promotes economic growth temporarily in panel regressions that use more sophisticat‑ ed indexes for ﬁnancial opening. We also examine the conditional eﬀects of capital account liberalization on economic growth. There is a nonlinear relationship between its growth ef‑ fects and the level of growth in cross‑country regressions. The short‑run growth eﬀects of capital account liberalization in panel regressions are larger in a country that has lower
Distance Education in Library and Information Science Discipline: The Valdosta State University Case

The library and information science discipline in the United States has thoroughly embraced distance education to deliver its courses and other curricular offerings. Courses ha ve been or are offered through a variety of mechanisms, some with deep historical roots, others are dependent upon new and emerging Internet technologies. Different distance education methods offer different opportunities but also diffe rent problems. This paper discusses the approach taken at one university – asynchronous Web course delivery – and the lessons we have learned from those experiences. Given our circumstances and opportunities, we have at times adopted alternatives to technological solutions, including hybrid courses and cross-listing of courses at sister institutions to meet student needs.
Analytical investigations of seismic performance of different joint details for composite RCS frames

Composite RCS frames, comprising of Reinforced Concrete (RC) column and Steel (S) beam are gaining popularity as an attractive alternative to traditional steel moment frames for mid to high‐rise buildings as well as conventional RC construction for low‐rise buildings. The prime concerns with RCS frames are constructability and load transfer at beam‐column connections. Over the last 30 years, several joint details, viz. face bearing plates, erection steel columns, vertical joint reinforcement, and steel band plates have been proposed for RCS frames. The moment‐rotation behavior of these joints was established through quasi‐cyclic experimental programme. The moment‐rotation characteristics of RC column‐S steel beam joint significantly affect seismic performance of the overall frame. The objective of this paper is to evaluate the seismic performance of low and mid‐rise RCS moment resisting frames with different connection details, available in published literature. The nonlinear analyses of differently jointed RCS moment resisting frames is carried out and performance assessed in terms of collapse capacity and the available response reduction factor, Ravl. Seismic collapse risk of RCS frames is estimated to understand performance under uncertain ground motion.
Deep Neural Network Direct Stiffness Method: Fundamental Steps into Beam Design

This paper presents a novel approach for performing beam element analysis that considers the nonlinear deformation behavior of various RHS and SHS sections made of mild to high‐strength steel: the Deep Neural Network Direct Stiffness method (DNN‐DSM), which uses Deep Neural Networks (DNN), a subset of machine learning algorithms and more general artificial intelligence approaches, to predict the nonlinear stiffness matrix terms in a beam element formulation for implementation in the direct stiffness matrix (DSM). These predictions are made using trained DNN models drawn from an extensive pool of geometric‐material nonlinear simulations with additional imperfections (GMNIA) using shell‐based models. Initial implementations of this method are able to predict the nonlinear load‐displacement and moment‐rotation behavior of various cross sections with high accuracy. This combines the precision of shell analysis with the computational efficiency of beam element analysis. Previous publications have already demonstrated the suitability and advantages of this method, albeit on a small scale for local buckling prediction. This work goes beyond previous studies and focuses on finite beam element design. This includes a review of the modeling approaches of DNN‐DSM using experimental and numerical results from literature.
Aircraft tracking based on fully conventional network and Kalman filter

Aircraft tracking is a significant technology for military reconnaissance, but there is no efficient algorithm to solve this particular problem. Recently, research based on deep learning for object tracking has developed rapidly, and the performance is greatly improved compared to the traditional methods, so the authors refer to relevant work and make an improvement on the previous research to improve the performance on aircraft tracking. They first learn the idea from region-based fully convolutional networks to perform detection on each frame of video. To avoid the target drift due to the failure of object detection on a certain frame, then they employ Kalman filter (KF) and extended KF together to predict the moving trajectory of the target. Beyond that, this method can confine the valid range based on the size of a target object, which increases the speed of detection. This approach can also correct the bounding box on adjacent frames. The steps are not complicated but have an excellent performance. Through the experiment, it is clear that the proposed method is reasonable and more precise.
Stiffness of L‐stubs loaded in compression

The stiffness of T‐stubs in compression is generally assumed infinite except for column base plates. For bolted circular flange connections and double web angle connections, the stiffness of L‐stubs and T‐stubs in compression should be determined to accurately calculate the position of the center of compression. Simple expressions have been recently proposed for these components in contact with a rigid foundation. However, the end‐plate can be in contact with a flexible foundation.
Proposing of Single Entity Design Pattern in Big Agricultural Positioned Data Sets (ADS)

With emerging usage of positioned devices such as drones, cell phones or IoT, the amount of data that can be collected expands drastically. At any given time, there is usually at least one nearby device that has positioning capabilities. Smart phones, smart TVs, personal computers, or even cars contain localization features. These vast amounts of data require a lot of effort in analysis and understanding in order to be properly utilized, which is especially true for the field of agriculture, where proper analysis can yield tremendous improvements in terms of production. Current computer technologies offer plenty options for such analysis. However, not every agricultural subject has access to a mainframe with performance in petaflops to perform complicated analyses of such big data in a timely manner. The defined design patterns for creation of data offers potential for speeding up the analysis of ADS on personal computers. This article describes known and used creational patterns and compares their benefits regarding ADS and offers possible usage and improvements.
Agris on-line Papers in Economics and Informatics

This study compares the performance of the tea industry of Assam and West Bengal of India between two time stretches each spanning over six years; one ending in 2006-07 the pre-reform regime and the other beginning in the next yearthe post-reform regime. The basic question addressed is whether reform policy led to improvement in technical efficiency of the tea industries of these states. The study uses stochastic frontier approach and introduces heterogeneity of tea gardens. Consideration of both Assam and West Bengal tea gardens adds unique flavour to this study. The study the study concludes that rehabilitation package of Indian government in the form of reform has paid off even within the existing framework of the tea gardens. JEL Classification: C01, Q17, Q19
The Relationship between Technological Pedagogical Content Knowledge and Web 2.0 Self-Efficacy Beliefs

Available online 10.01. 2019 The aim of the present study was to investigate the development of technological pedagogical content knowledge (TPACK) and Web 2.0 self-efficacy beliefs (W2SEB) and to determine the relationship between them for middle school pre-service mathematics teachers through their involvement in a course designed using a Web 2.0 tools. To achieve this aim, thirty pre-service teachers participated in forty two hours of the course in which they could interact with Web-based applications. In the course, pre-service mathematics teachers were requested to develop and present e-content related to the use of these applications for learning outcomes determined in 5-8th grade mathematics curriculum. In order to collect the required data, the TPACK and W2SEB scale were applied to pre-service teachers at the beginning and end of the course. The data obtained from these scales were quantitatively analyzed. Within this scope, while there were positive developments in terms of the technological pedagogical knowledge levels and self-efficacy beliefs, there was a significant relationship identified between them. Additionally, when the regression results related to the post-test are investigated, the TPACK sub-factors of technological and mathematical knowledge were shown to be significant predictors of Web 2.0 rapid content development self-efficacy beliefs. © 2019 IOJES. All rights reserved
Prevalence and Predictors of Substance Use Support Programming Among U.S. Religious Congregations

We conducted a cross-sectional secondary analysis of data from the 2012 National Congregation Study, a nationally representative survey of religious congregations in the United States (N = 1,331). Multivariate logistic regression was used to identify congregational characteristics associated with providing substance use support programing. Nearly one-third (38%) of U.S. congregations indicated that they provided substance use support programming; approximately half (52%) of all congregational attendees were in a congregation that provided some type of substance use support. The internal factors associated with a congregation providing substance use programming include having members who are unemployed and younger, being conservative Protestant, engaging in the practice of speaking in tongues, and having the resources to support social services. The analysis also identifies external factors (i.e., assessing community needs and hosting social service speakers) as being associated with a congregation’s likelihood of providing substance use programming. Findings identify factors associated with congregations providing substance use support.
UvA-DARE (Digital Academic Does anger help or harm leader effectiveness? The role of competence-based versus integrity based violations and abusive supervision.

The question of how leaders ’ expressions of anger influence their effectiveness has long intrigued researchers and practitioners. Drawing on emotions as social information theory, we suggest the effects of leaders ’ expressions of anger depend on both the type of violation about which anger is expressed and the type of leader who expresses it. We test this in a series of studies using experimental and field methods. Study 1 shows that a leader ’ s anger expression in response to followers ’ integrity-based violations enhances observers ’ perceptions of leader effectiveness, whereas anger in response to followers ’ competence-based violations diminishes observers ’ perceptions of leader effectiveness. Study 2 shows that these divergent effects occur because anger in response to integrity-based violations elicits beneficial inferential reactions among followers who observed the anger, whereas anger in response to competence-based violations provokes harmful affective reactions. Study 3 demonstrates that the negative effects of anger expressed toward competence-based violations are exacerbated, and positive effects of anger expressed toward integrity-based violations weakened, when a leader is perceived as abusive. These findings help reconcile divergent perspectives on the effects of leader anger expression, suggesting that anger can enhance perceived leader effectiveness when expressed in the right situation and by the right person. A colleague failing to meet [Amazon CEO] Bezos ’ s exacting standards will set off a nutter. If an employee does not have the right answers or tries to bluff, or takes credit for someone else ’ s work, or ex-hibits a whiff of internal politics, uncertainty, or frailty in the heat of battle — a blood vessel in Bezos ’ s forehead bulges and his filter falls away. He ’ s capa-ble of hyperbole and harshness in these moments the years has
ACTI Task Report – Transformer-basedConspiracy Theory Identification

English. In this work, we participated in the Automatic Conspiracy Theory Identification (ACTI) competition, which involved two sub-tasks: identifying whether an input text is a conspiracy theory and recognising the specific conspiracy theory it discusses. Our approach involved fine-tuning two BERTmodels, one in Italian and one multilingual, and combining them in an ensemble. The results were promising, and we achieved a position among the top participants in the challenge. This work contributes to the advancement of automatic conspiracy theory identification and highlights the effectiveness of fine-tuned BERTmodels in this domain. Italiano. In questo lavoro, abbiamo partecipato alla competizione di Identificazione Automatica delle Teorie Cospiratorie (Automatic Conspiracy Theory Identification, ACTI), che si compone due sotto-problemi: identificare se un dato testo riguarda una teoria del complotto e riconoscere a quale teoria del complotto in particolare si fa riferimento nel testo. Il nostro approccio prevedeva l’adattamento di due modelli BERT, uno in italiano e uno multilingue, e la loro combinazione in un ensemble. I risultati sono stati promettenti e abbiamo raggiunto una posizione tra i primi partecipanti nella sfida. Questo lavoro contribuisce allo sviluppo dell’identificazione automatica delle teorie del complotto e mette in evidenza l’efficacia dei modelli BERT adattati in questo ambito.
Hydrodynamic pressure and effective mixing length in vegetated free-flow region

Submerged vegetation acts as large-scale roughness element that changes flow structure and promotes flow subdivision, thereby affecting scalar transport and energy transfer in the river. This article explores vertical distributions of both the hydrodynamic pressure P D and effective mixing length L in vegetated free- flow region through flume experiments. Firstly, formulas have been proposed in the present study to calculate the P D and L values by some theoretical analyses. Then, we discuss the P D and L profiles under different vegetation density λ, submergence degree H/h v and mean bulk velocity U m conditions. The P D value is positive and attains its vertical maximum around the middle position of this region, indicating that shear turbulence promotes the upwards release of the hydro pressure. The vertical variation coefficient for P D is nearly 1.15 and independent of λ and U m in this study. The dimensionless L value varies little in the lower part of this region and increases linearly upwards in the upper part, reflecting vertical variation of shear turbulence movement. Since the vegetation density λ and submergence H/h v control turbulence coherent motion, the P D and L/(h o - h v) values change monotonically with them in this study. The high-velocity flow accelerates turbulence waves and promotes an increase in P D.