Miracle-dz/UniFAR-FTUs huggingface dataset:
Regressive model approach to the generation of test trajectories

One aspect of system safety assurance is the application of large test sets. To aid in the development of test cases, researchers have investigated automated test generation systems which decrease the time and cost of acquiring new tests. Many automated systems currently exist, but few address the generation of trajectories of data. A trajectory is defined as a series of data points with each point relying upon the state of the system and previous point values. Examples of trajectories include an airplane's flight path or data describing a nuclear reaction. The paper describes an original approach to test trajectory generation using statistical regression models. An existing small set of trajectories is utilized to build regressive models. Then, the independent variables of the model can be perturbed, providing the basis for the use of the regressive model in the generation of new trajectories. A case study has been conducted within the scope of testing the sensor failure detection, identification, and accommodation (SFDIA) flight control scheme. We report and evaluate the results of this case study.
Human capital accumulation, long-run GDP growth and technological frontier

While initial education is at the heart of growth models, less work has been done on the influence of human capital accumulation on long-run growth. Our first step was to overcome the “human capital puzzle” by the introduction of the technological frontier as defined by Vandenbusshe, Aghion and Meghir (2006). The “human capital puzzle” means that the level of human capital has a significant positive effect on growth in countries where educational attainment is low and a significant negative effect in countries where educational attainment is high. We specified an aggregate long-run growth equation while taking account the limitations of the various approaches but without rejecting the contribution of endogenous theories. By combining the distance to technological frontier and the workhorse cross-country regression model, our coefficient on both the level and rate of accumulation of human capital are positive, and significant at the 1 and 10 percent level for the human capital predictors alone, and that the interaction between the rate of accumulation of human capital and distance to the technological frontier is also significant at the 5 percent level. This shows that the distance to the technological frontier significantly affects the relationship between human capital accumulation and economic growth, while cross-country differences in technology do not change the relationship between initial level of human capital stock and economic growth. Moreover, the effects of human capital accumulation on economic growth tend to increase with technological advancements of countries. According to our econometric results, the “human capital puzzle” is thus partially solved by taking into account cross-country differences in technological advancements, and their interaction with human capital proxies. To address the endogeneity of the human capital variable, we turn toward a simultaneous equations model (SEM) where accumulation of human capital is also caused by economic growth, and where accumulation of physical capital is allowed to be endogenous. Despite a less complete datasets (fewer countries), the both human capital level and accumulation have a positive and significant effect on long-term growth of GDP per capita. These first results were needed before investigating the relationship between human capital and economic development at a more granular level and could help to not underestimate the spillover effect of the investment in human capital accumulation on long-run GDP growth especially in countries close to the technological frontier.
Dynamic Knowledge Graph Based Construction of Quality Infrastructure System for Non-API Oil Country Tubular Goods

With the deep exploitation of oil and gas resources, the non-API oil country tubular goods (OCTG) adapted to specific environments are used widely. Therefore, how to effectively characterize the quality connotation of non-API OCTG to ensure their quality has become a challenge for the petroleum industry. We propose a dynamic knowledge graph of Quality Infrastructure (QI) to solve the problems of the diversity of non-API OCTG quality influencing factors, the concealment of the relationship, and the ambiguity of the mechanism of quality improvement. Firstly, a knowledge graph ontology framework of quality infrastructure is constructed, which realizes the effective combination of product characteristics and quality basic elements. Secondly, based on the professional dictionary in the field of OCTG, entity recognition adopts the entity recognition method of LDA-BiLSTM-CRF, which effectively improves the recognition accuracy of professional vocabulary. Finally, the relationship between entity types is defined as the edge of the knowledge graph; the graph embedding method is used to supplement the edge connection and calculation weight of the knowledge graph. The QI knowledge graph constructed with this technology can well describe the quality connotation of non-API OCTG, and provide opinions and methods for guaranteeing and improving the quality of non-API OCTG.
Conceptual Design and Analysis of Pipe Climbing Robot

Robotics is one of the most emerging technologies in the current scenario. In this fast-growing technological world automation through robotics finds its place in almost all the fields. Climbing robots became more popular due to their versatile applications like inspection of tall buildings, tanks, structures, facade cleaning, fruits harvesting on tall trees (coconut) and many more. It became most adaptive as working on height may lead to dangerous incidents for human beings. Operations like visual inspection, crack detection of tall structures and pipes can be made possible with specially designed pipe climber robot. It finds its applications where human cannot reach, like hazardous applications. Specially design robots for a specific application also performs well with precision. This paper presents the novel design and analysis of pipe climbing robot for Chemical plant pipeline fault and leakage detection purpose. Design of all components of the robot is done with the basic mathematical consideration and then its analysis is carried out using FEA tools and MATLAB. Results of Forward and Inverse kinematic analysis of robot are obtained for certain specific points of trajectory. Dynamic analysis has been performed for motor selection and torque calculation. Presented conceptual design and analysis can be useful for pipe inspection purpose.
A Miniaturized 3 dB Branch-Line Hybrid

This letter presents a miniaturized 3 dB branch-line hybrid coupler with second harmonic suppression using high-impedance transmission lines and interdigitated shunt capacitors. By using the interdigitated capacitors shunt with the transmission lines, further minimization of the 3 dB branch-line hybridcouplercanbeachievedcomparedwithpreviouslyreported techniques. The design of the interdigitated shunt capacitors re- quires concurrent optimization of the capacitance to the ground and the edge-coupling interdigitated capacitance between the ports. For validation, a miniaturized 3 dB branch-line hybrid coupler at 836.5 MHz was designed and implemented. The pro- posed 3 dB branch-line hybrid coupler achieved a compact size of 27.75 mm 25.7 mm, or equivalently , where is the free-space wavelength. Moreover, the coupler can sup- press second harmonic components by 20 dB while maintaining similar measured performance compared to the conventional branch-line hybrid coupler.
Demand Peak Reduction of Smart Buildings Using Feedback-Based Real-Time Scheduling of EVs

Rapid urbanization leads to increasing electricity demand. The intraday high and low electricity consumption patterns further increase challenges for grid operation. This article proposes a real-time strategy to minimize peak demand of a building by optimally scheduling the energy consumption of electric vehicles (EVs) with bidirectional power transfer. The strategy also incorporates rooftop photovoltaics (PVs) in reducing the power consumption of the building. In this article, the randomness of PV output is handled using scenario modeling under a rolling time-horizon framework, where feedback regarding EV mobility is also utilized in real time. In addition, the degradation of EV batteries is limited by controlling the charging/discharging cycles required for peak reduction. To provide incentives for contributing to peak reduction, a cooperative game is presented, wherein the EVs are conceptualized to work in a coalition with the building’s energy management system. The payoffs in the game are decided based on the power extraction of EVs from the building combined with degradation costs incurred by individual EVs. The results demonstrate up to 40% reduction in demand peaks and 25% reduction in energy costs using the proposed energy management methods.
Shipboard machinery diagnostics and prognostics/condition based maintenance: a progress report

Developed a distributed shipboard system to perform diagnostics and prognostics on mechanical equipment (e.g. engines, generators, and chilled water systems) for the Office of Naval Research (ONR). This Condition Based Maintenance (CBM) system (called MPROS for Machinery Prognostics/Diagnostics System) consists of MEMS and conventional sensors on the machinery, local intelligent signal processing devices (called "Data Concentrators"), and a centrally located subsystem (called the PDME for Prognostics, Diagnostics, Monitoring Engine) which is designed so that it can run under shipboard monitoring systems such as ICAS (Integrated Condition Assessment System). MPROS includes and augments periodic vibration analysis by collecting data continuously from vibration and other sensors, including temperature, pressure, current, voltage, and so on. These data streams are integrated as necessary in the Data Concentrators (data fusion). A second level of integration (knowledge fusion) occurs in the PDME. At this level, the conclusions of different diagnostic and prognostic reasoning mechanisms are fused to yield the best possible analysis. In this paper, we discuss recent progress in design and implementation of the software and hardware required to support our system.
Judo Performance Tests Using a Pulling Force Device Simulating a Seoi-n age Throw

A pulling force device (PFD) is used to carry out monthly performance tests on 12 judo squad athletes (8 male, 4 female, aged 19.4 ± 4.3 years) of the Olympic Center in Linz (Austria) to see the progress over a training period of six months. The variation of a friction brake simulates the resistance of the opponent in the throwing technique Seoi-Nage, which consists of three phases: balance breaking (kuzushi), fit-in (tsukuri) and throw (kake). Force and velocity over time are measured, and the parameters maximum force F max , time to maximum force t(F ), maximum force derivative dF max and maximum velocity v max are calculated with use of the software LabView. Displaying force and velocity curves together with the recorded videos of a synchronous 2x 2D motion analysis in Dartfish in a special graphic user interface (GUI) provides a helpful visualization and feedback for athletes and trainer and shows imperfections in technical skills in more detail. The relevant investigations comprise the position of center of mass (COM), knee and elbow angles, body axis, trunk rotation as well as chain pullout. Longitudinal studies, standardized by weight category, show improvements in all 4 parameters, especially t(F max ) has decreased by 64 %. The PFD has proven to be a valid method of determining specific abilities of judokas. The gained knowledge and experience will be used in optimizing individual motion structure and training. An improved, mobile PFD should also be used as a training device.
An Efficient Radio Map Learning Scheme Based on Kernel Density Function

Training an accurate and up-to-date radio map has always been a primary concern for implementing a WiFi fingerprint-based localization system. This paper presents a novel radio map learning scheme for online learning a set of kernel density functions, which function like a traditional radio map in WiFi fingerprint-based localization systems. To be specific, each kernel density function corresponds to one specific access point (AP) and predicts the probability of having a received signal strength (RSS) measurement from this AP at any position. In the offline phase, a set of coarse-grained kernel density functions are initially established by the Multivariate Kernel Density Estimation (MKDE) through a fast site survey. In the online phase, these kernel density functions are recursively refined through Incremental-MKDE (IMKDE) using freshly crowdsourced fingerprints, which essentially fuses the historical features in the previous kernel density functions and up-to-date features in the current fingerprints. A compression technique is applied to improve the computation and storage efficiency. In addition, pedestrian dead reckoning (PDR) is leveraged to calibrate the location labels of crowdsourced fingerprints. Extensive experiments are carried out in a real scenario of nearly 1000 $m^2$ for five months, and a comparison made between the IMKDE based method and several existing popular solutions confirms the superiority of the proposed IMKDE in terms of both computational complexity and localization accuracy.
Sensorless Control With Fault-Tolerant Ability for Switched Reluctance Motors

This paper presents a new sensorless control strategy with the fault-tolerant ability for switched reluctance motors (SRMs). Nowadays, many rotor position detection methods are utilized, but most of them increase the system cost due to the additional hardware or complex calculations. To address this problem, various methods of using phase inductance to estimate the rotor position and speed have been proposed. However, the traditional inductance detection method will cause signal distortion due to the presence of interference signals and the unbalanced phase inductance. In particular, the turn-ON angle is advanced. To further improve the stability of the control system, the interference signals are eliminated via establishing the reference time of the inductance characteristic point and the error band in this work. When the position signal disappears, the inductance characteristic points of adjacent phases will be adopted for signal compensation to realize fault-tolerant control. Finally, an SRM drive system is used to verify the effectiveness of the proposed control strategy.
Modeling and analysis of wideband power transmission line transformers

The modeling and analysis of wideband transmission line transformers (TLTs) are presented in this paper. The innovative transmission-line impedance-based methodologies are proposed to evaluate the significant parameters of the transmission line first. The complete equivalent models of the basic 1:1 isolating TLT and high turns ratio TLTs are presented and the validity of this proposed model is confirmed by the excellent match between the simulated results and experimental data. Some important characteristics of high turns ratio isolating TLTs are discovered and discussed in this paper.
EXTENSION OF THE YONAPAVE METHOD FOR DETERMINING FLEXIBLE PAVEMENTS OVERLAY THICKNESS FROM FALLING- WEIGHT DEFLECTOMETER DEFLECTIONS

YONAPAVE, a direct and simple method for evaluating the structural needs of flexible pavements, was presented at the 2003 Annual Meeting of the Transportation Research Board (TRB) in Washington D.C. The method uses falling-weight deflectometer (FWD) deflection basins to determine the effective structural number and the equivalent subgrade modulus of the pavementsubgrade system without previous knowledge of the layer thicknesses above the subgrade. An extension of YONAPAVE is hereby presented to determine the asphalt concrete (AC) overlay required to account also for the fatigue of the AC layer under future traffic loadings. The scheme is based on commonly accepted relationships between AC fatigue cracking and the radial tensile strain at the bottom of the AC layer. The real layered pavement is characterized by an equivalent twolayer system which is determined from the measured FWD deflection basins. Thus, no coring operations are needed since the whole scheme remains basically independent of layers thicknesses. YONAPAVE algorithms can be solved using a spreadsheet or a handheld PC making it suitable to handle large amounts of data, even in field conditions. The extended method can be used at the network level for the evaluation of the flexible pavement overall structural capacity and the AC overlay needed to accommodate future traffic. With local calibration and experience YONAPAVE can be also used at the project level. YONAPAVE has been used successfully in numerous pavement evaluation and rehabilitation projects providing reasonable and useful results.
Manufacture in town and country before the factory: From manor to mill: the West Riding in transition

List of illustrations Acknowledgements 1. Manufacture in town and country before the factory Maxine Berg, Pat Hudson and Michael Sonenscher 2. Political economy and the principles of manufacture 1700-1800 Maxine Berg Part I. The Structure of Manufacture: 3. Variations in industrial structure in pre-industrial Languedoc J. K. J. Thomson 4. Seasonal fluctuations and social division of labour: rural linen production in the Osnabruck and Bielefeld regions and the urban woollen industry in the Niederlausitz, c.1770-c.1850 Jurgen Schlumbohm 5. From manor to mill: the West Riding in transition Pat Hudson Part II. 'Work' and 'Wages': 6. Work and wages in Paris in the eighteenth century Michael Sonenscher 7. Embezzlement, industry and the law in England, 1500-1800 John Styles Index.
Multi-expert tracking algorithm based on improved compressive tracker

Object tracking is a challenging task in computer vision. Most state-of-the-art methods maintain an object model and update the object model by using new examples obtained incoming frames in order to deal with the variation in the appearance. It will inevitably introduce the model drift problem into the object model updating frame-by-frame without any censorship mechanism. In this paper, we adopt a multi-expert tracking framework, which is able to correct the effect of bad updates after they happened such as the bad updates caused by the severe occlusion. Hence, the proposed framework exactly has the ability which a robust tracking method should process. The expert ensemble is constructed of a base tracker and its formal snapshot. The tracking result is produced by the current tracker that is selected by means of a simple loss function. We adopt an improved compressive tracker as the base tracker in our work and modify it to fit the multi-expert framework. The proposed multi-expert tracking algorithm significantly improves the robustness of the base tracker, especially in the scenes with frequent occlusions and illumination variations. Experiments on challenging video sequences with comparisons to several state-of-the-art trackers demonstrate the effectiveness of our method and our tracking algorithm can run at real-time.
Towards “Explorable” AI: Learning from ML Developers’ Sensemaking Practices

In this note, we report on a qualitative design study in the field of machine learning (ML) and in particular on the sensemaking practices of ML developers as they interact with the interface of a novel adversarial AI method. This paper makes contributions to discourses on interpretable or explainable AI (XAI) systems through an empirical understanding of ML developers’ sensemaking practices. These findings make salient the concept of “explorability” as an alternative design metaphor for interactive AI systems – instead of a focus on explainability or interpretability as fixed qualities of AI systems, explorability focuses on emergent meanings and ways in which they might be enabled or constrained through practice.
Evaluating the carrying capacity of a subsurface drainage network based on a spatially varied flow regime

The carrying capacity of a subsurface drainage network based on spatially varied flow with increasing discharge and the presence of a free surface is examined and reported. The discharge capacity of a subsurface drainage network depends on the hydraulic and geometric parameters of the network components which should be clearly identified. In this regard a prototype scale experimental set‐up was prepared to determine the major head loss of the corrugated pipes employed in these networks and to investigate the minor head losses of different network junction types. According to the compiled data average values for the major and minor head loss coefficients were proposed and employed for modelling the flow condition within a subsurface drainage network. The model determines the network discharge capacity based on the real flow condition i.e. a free surface spatially varied flow regime. Comparison between the outputs of the applied model with that of the traditional relationships indicated a large discrepancy. The results revealed that applying existing formulations in the design process would likely pressurize significant portions of the network which could affect the water depletion period from the plant root zone. Copyright © 2010 John Wiley & Sons Ltd.
Neoplasms In Equine Species In Sharkia Governorate, Egypt

| Few studies and very limited published data concerning the spread of neoplasia among Equidae in Egypt are available, therefore, the present study was carried out to investigate the prevalence and types of neoplasia among Equidae in Sharkia Governorate, Egypt, and to assess the efficacy of some available biomarkers as a diagnostic tools. This work was investigated 35 clinical cases of equine neoplasms (23 donkeys, 10 horses, and 2 mules) out of 1513 total examined cases admitted from different clinics in Sharkia Governorate, from May 2019 to October 2020. Depending upon gross and histopathological findings; the neoplastic growths include 12 cases of sarcoids, 9 cases of fibroma, 4 cases of squamous cell carcinoma, 3 cases of papilloma, 2 cases of fibropapilloma, 1 case of fibrosarcoma,1 case of myxoma, 1 case of of myxosarcoma, 1 case of myxoid liposarcoma, and 1 case of ovarian teratoma. Immunohistochemically, cytokeratin5 (CK5), MDM2, and S100 biomarkers were used to confirm the diagnosis of certain neoplasms. The Overall prevalence of equine neoplasms was 2.31 %. The diagnosed cases were linked with animal species and sex and the significance (p < 0.05) of differences among age, seasons, and location of the neoplasms were evaluated. The prevalence rates in domestic donkeys, horses, and mules were 2.66 %, 1.94%and 1.22% respectively. The rate of affected animals over 3 years was (3.38 %) in comparison with animals less than 3 years (0.19 %). Females (2.64%) were more affected than males (2.28%) and mules (1.42%). The prevalence rate was 5.56% in summer, 1.6 % in spring, 1% in autumn, and 0.85 % in winter. A higher rate of neoplasms was reported in extremities and trunk (1.25%), 0.52% in the head, neck, 0.19% back, ventrum, 0.19% in eye, related skin, 0.13 % in genital organs.
Fringing field of finite parallel-plate capacitors

The effect of finite plate width on the fringing field of a parallel-plate capacitor is determined, and an exact expression is derived for the total capacitance by applying conformal transformation to a finite parallel-plate configuration. With small values of the plate-width/plate-separation ratio, finiteness of plate width is shown to have a predominant effect on the correction factor for capacitance as well as on the fringing field. The analysis is extended to shielded parallel plates and expressions are derived for capacitance and field distribution as functions of shield separation, plate width and plate separation. The effect of shielding on capacitance and fringing field is determined.