Miracle-dz/UniFAR-FTUs huggingface dataset:
Environment for Industrial Robot Performance Evaluation

Industrial robots and robotic systems have already become key components in various industry sectors. After a new industrial robot model is developed, robot manufactures have the responsibility to test it before the new model hits market. In this thesis, several technologies regarding industrial robot test are analysed, and a test environment for industrial robots is developed. ISO 9283 is the latest international standard for industrial robot tests. Robot test processes and test principles are described in this thesis. Questions and doubts about the standard are discussed. Laser tracker is one of the most advanced measuring instruments for industrial robot tests. The accuracy of laser tracker is essentially important for test results. Accuracy of laser trackers is analyzed in this thesis. Coordinate system calibration problem is discussed and solutions are shown. Two calibration methods are applied in this thesis for connecting different coordinate systems. Results of different calibration methods are compared. In data analysis, an accuracy verification test of the laser tracker is carried out. A data selection strategy is introduced by analysing raw data sequences. To verify functionalities of the test environment, an industrial robot is tested with the test environment. Pose accuracy and pose repeatability test results from the test environment are shown and analysed. Result error sources are discussed. The example test shows that the test environment is able to provide scientific results, which reflect robot performance characteristics.
Which Farm Animal Photos are Most Likely to Inspire People to Eat Vegan : A Reanalysis

This document presents a reanalysis of the data and the conclusions reported by Humane League Labs on January 25, 2015, in the blog post titled Report: Which farm animal photos are most likely to inspire people to eat vegan? Using regression analysis of the provided data, our reanalysis finds that photos of sick or injured animals, large groups of animals, pigs, and mother and baby animals are most likely to increase self-reported desire to stop consuming animal products. However, in the course of our reanalysis, we found the provided data likely represents only a subset of all respondents to the survey. As this may impart significant bias, substantial uncertainty is warranted around these conclusions. This research earned the Open Data badge for open science practices. All data is available on the Open Science Framework repository at https://osf.io/k67ge/. This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA. DOI 10.17605/OSF.IO/K67GE 1
LIP-TO-SPEECH SYNTHESIS USING LOCALITY-CONSTRAINT NON-NEGATIVE MATRIX FACTORIZATION

We propose in this paper a lip-to-speech conversion method that converts “unvoiced” lip movements to “voiced” utterances, where parallel lip movements and speech spectra are stored as a source dictionary and a target dictionary, respectively. An input lip image is decomposed into a linear combination of bases from the source dictionary, and its weight is estimated by Non-negative Matrix Factorization (NMF). The selected image bases are replaced with speech bases from the target dictionary, and the speech spectra are constructed. We assume this method will be an assistive technology for people who have speech disabilities. In this paper, NMF using β divergence is used as a cost function and introduced locality-constraint in order to increase sparsity in an activity matrix. The effectiveness of our method was confirmed by objective and subjective evaluations.
INFLATION FORECAST OR FORECAST ( S ) TARGETING ? 1

The paper refers to L.E. O. Svensson’s concept of inflation forecast targeting (IFT) and its implementation by central banks of Sweden, Norway and the Czech Republic. The study focuses on (1) inflation forecasts published by selected central banks, i.e. headline inflation and core or monetary policy-relevant (MPR) inflation, which are made on the assumption of endogenous instrument rate, (2) one-year consumer inflation expectations, and (3) repo rate decisions. The aim of the paper is to investigate whether MPR and core inflation forecasts (in addition to headline inflation forecasts) are useful tools in implementing IFT. The authors take into consideration differences between forecasts deviations from the inflation target, dependencies between forecasts and consumer inflation expectations and relationships between repo rate decisions and forecasts. The methodology used includes nonparametric tests and statistics (Sign Test, Wilcoxon Matched Pair Test, Nonparametric Correlation coefficients) and forecast errors analysis. The results are sufficiently positive to conclude that the implementation of IFT in central banking practice should be supplemented by forecasts of core inflation. The paper contributes to the literature on implementing monetary policy under the concept of IFT. It spotlights the importance of publication of core inflation forecasts that are not captured by other research undertakings, which tend to ignore the existence of them as such.
CHILDHOOD STROKE – THE UNKINDEST CUT OF ALL : A HISTORY OF CEREBROVASCULAR DISEASE IN CHILDHOOD

Introduction Depictions and descriptions of children who have had a stroke (or apoplexy or acute hemiplegia) have been around for millennia. The concept of children at any age suffering and even dying from a stroke appears anachronistic, given our own experiences that it is typically a disease of the elderly. It is perhaps this very incongruity that has made the occurrence of stroke in childhood the more striking to medical observers often better known for other contributions. Understanding of aetiology had to await the development of the concepts of the systemic and cerebrovascular circulation in adults from the seventeenth century onwards, the distinction between upper and lower motor lesions and therefore between spinal (usually poliomyelitis) and cerebral paralysis, the emergence of the concept of childhood and the later twentieth century focus on differences between diseases of children and those of adults and therefore their needs in terms of investigation and rehabilitation. The increase in research into childhood health and disease in general has at long last started to redress the deficiency.
Speech Prosody Conversion using Sequence Generative Adversarial Nets with Continuous Wavelet Transform F 0 Features

In the voice conversion tasks, the spectral and F0 features can affect the acoustic and prosodic features, respectively. Particularly in emotional VC tasks where the prosody plays an important role in conveying various types of non-linguistic information that represent the mood of the speaker, such as identity, intention and, attitude. Previous studies (ex. [1]) have shown that prosody conversion is affected by both shortand long-term dependencies in different temporal levels such as the phones, syllables, and words, within an utterance. The LG-based method is insufficient to convert prosody effectively because of constraints of their linear models and lowdimensional F0 features. In recent years, it has been shown that the CWT method can effectively model F0 in different temporal scales and significantly improve speech synthesis performance. Our earlier work [2] systematically captures the F0 features of different temporal scales using AS-CWT, which transforms F0 features into high-dimensional CWT-F0 features containing more specifics. Thus, building on top of the success of using CWT-F0 features for prosody conversion, in this study, we want to go one step further to generate emotional voice more similar to target emotion using a generative model. In this study, inspired by the success of Generative Adversarial Networks (GAN) model in VC tasks, we propose an emotional VC framework that using the GAN model. The effectiveness of GAN is due to the fact that an adversarial loss forces the generated data to be indistinguishable from real data. This is particularly powerful for image generation tasks. So, before training in the GAN model, we segmented the voice features such as the spectral features and CWT-F0 features to the suitable size matrices for training. However, a generative adversarial model only discriminates between “real” and “fake” features, it has
Scalable and Secure Message Recovery through Identity Based Secured Cryptographic System

Cryptography is the art and science of concealing the messages to introduce secrecy in information security This paper focuses on scalable and secure message encryption, message storage and recovery from cloud based storage system. Here we are using advanced Identity Based Secured Cryptographic System for message encryption in which we are using RSA algorithm for key generation, Diffie Hellmann algorithm for Key exchange, Elliptic curve cryptography for encryption and decryption process. For storage in cloud one have to pay charges, so we are using Huffman coding for compression and decompression procedure which makes the size of message less. The scheme prevents replay attacks and privacy preserving access control for securing data in clouds. We are representing the response time of storage through a graph; we also calculate total costs for storage.
RESPONSE OF ACACIA FORAGE YIELD AND ITS QUALITY TO WATER STRESS AND CUTTING HEIGHT

Shrubs of acacia dispersed over clay or sandy regions of arid and semi-arid lands due to its tolerance to salinity. In order to re-vegetate acacia plants in the desert sand saline soils and its forage dry matter production. Two experiments accompanied during 2014, 2015 and 2016 seasons. The purposes of this investigation aimed to (1) investigate water deficit effects, i.e. irrigation at Evaporation rates 1.00, 0.67 and 0.33 ET, (2) study the effect of three stubble-heights, i.e. 20, 40 and 60 cm (3) schoolwork the interaction effects on forage dry matter yield, its quality, water use efficiency and desert re-vegetation. The tallest plant, thick stems, highest weight of green forage yield/ha, highest weight of dry forage yield/ha and the highest values of water use efficiency obtained from the first cut. While, uppermost ether extract as well as ash percentage and ash yield/ha created from the second cut. The tallest plant, thick stem, the highest green and dry matter forages yield/plant, forage, green and dry yield/ha, protein%, nitrogen free extract%, Yield/ha of protein, fiber, ether extract, ash and nitrogen free extract created for irrigation at 1.00 ET. Irrigation at 0.67 ET produced the highest water use efficiency. Irritation at 0.33 ET created the highest ether extracts, crude fiber and ash percentage. Cutting at 40 cm height produced the tallest plant, thick stems, the highest weight of green and dry foraged yield/plant, green and dry matter forage yields/ha, the highest values of water use efficiency, the highest percentages of protein and ash, yield/ha of protein, fiber and ether extract. For the moment, cutting at 60 cm height recorded the highest percentage of crude fiber and ether extract. In general, cutting at 40 cm with irrigation at 100% ET gets the great forage dry matter yield/ha, its quality and water use efficiency.
On GMM Estimation and Inference with Bootstrap Bias-Correction in Linear Panel Data Models

This paper proposes a simple bootstrap-bias correction (BBC) of the rstdi¤erenced (DIF) and system (SYS) GMM estimators, and investigates their nite sample behaviour, especially with many instruments and under the weak instrument problem. It is found that the BBC DIF and SYS estimators have much less bias, and that among variants of DIF estimators, the BBC DIF estimator can be a reliable alternative in terms of mean square errors. Also, a t-test based on bootstrap standard errors of BBC estimator is proposed. The evidence shows that the proposed t-test of BBC DIF estimator can outperform the standard bootstrap t-test of DIF estimator. Nonetheless, the crude SYS estimator outperforms other BBC estimators considered here, in terms of root mean square errors. Therefore, in the applications where the additional mean stationarity assumption for the validity of SYS estimator are not believed to be satis ed, the BBC DIF estimator together with the proposed bootstrap t-test, can be a reliable alternative. Key Words: method of moments; dynamic panel data; bootstrap; bias-correction. JEL Classi cation: C12, C13, C23. I am grateful to Frank Windmeijer for helpful comments. yCorresponding author. E-mail address: ty509@york.ac. uk
Robust, real-time eye movement classification for gaze interaction using finite state machines

Fixations and saccades are commonly used in gaze-based interfaces. State-of-the-art algorithms for eye movement segmentation work well for high speed and accurate eye trackers, which are still too expensive and bulky for most gaze interaction applications. For low-end eye trackers running at 30 to 60 Hz and with accuracy of about 1 degree, such algorithms do not perform as well. We propose a robust, real-time method to classify eye movement data into four categories: fixations, saccades, drifts, and none. The classifier is based on a finite-state machine (FSM) and is robust to missing data and blinks. The approach first filters raw gaze data to recover missing samples and smoothes the data. The current filtered sample is then classified by computing spatial dispersion and absolute eye velocity using a small number of recent gaze samples and the current state of the machine. Qualitative evaluation have shown evidence that FSM reduces latency after blinks, reduces the number of refocusing events and improves user experience during the interaction compared with a simple fixation detector based on a running average window. The source code is publicly available at https://bitbucket.org/diaztula/gaze_movements_fsm/.
Image rejection and match verification to improve surface-based localization

The capability to localize is paramount for many mobile robots and autonomous vehicles. Key attributes of localization systems include reliability, accuracy, low-latency, minimal cost and robustness to variation in environmental conditions. Typical approaches by self-driving car systems incorporate some combination of LiDAR, camera, radar and GPS sensing technologies; which are all suboptimal with respect to one or more of the aforementioned key attributes. This paper presents new research that translates previous work on surface-based positioning systems, which have appealing latency and accuracy properties, to road networks in the context of autonomous car positioning. To achieve the required performance and robustness to appearance change caused by phenomena such as day-night cycles, we develop two new data-driven statistical and learning-based techniques. One performs self-evaluation with regards to the suitability of the current camera query image, while the other retrospectively determines the quality of the query-reference image comparison outcome. Multiple new road surface datasets spanning day and night cycles were utilized to evaluate the system. Results show that both contributions significantly improve place recognition performance, decreasing the median estimated image position error from 24m to 0:26m. The strengths and limitations of our approach and how it could complement current positioning techniques to improve vehicle positioning capability are discussed.
Social media adoption challenges of small businesses: the case of restaurants in the Cape Metropole, South

Regardless of the claim that there is a large uptake of social media, it is reported in both scholarly and mainstream media that more than half the world’s population remains offline. Several fingers point in the direction of the high cost of devices, lack of infrastructure, and poor/intermittent supply from providers and many more as reasons for the low uptake. A major concern that emanates from this state of affairs, especially for small firms that have to embrace technology for its acclaimed virtues, is that they have to find creative ways of reaching out to their customers, expand their customer base and generally improve their businesses. Worryingly, considering the value of small businesses in a developing economy such as South Africa, there should be sustained inquiry into the factors that prevent small businesses from blossoming. This study examines social media adoption challenges of small businesses. The purpose of pursuing a study of this kind was based on, among others what is generally considered as: (1) the necessity of social media in business, and (2) the inevitability of social media. Specifically focusing on restaurants in the Cape metropole, the study applied the quantitative method to obtain data which were analysed using the Statistical Package for the Social Sciences (SPSS). Perhaps surprising, the results suggest that access to the internet in this digital age is one of the most prominent factors that inhibit the adoption of social media by the restaurants surveyed. Other factors include a limited understanding of the role of social media, the capacity of social media, marketing strategies and lack of interest. While there is the urge to associate non-adoption of information technology to limited education, this was not the case as most of the respondents were moderately educated with specific insights in marketing. With digital technology driving marketing efforts nowadays, clearly businesses that choose to ignore or optimally deploy this new media may suffer or continue to suffer excruciating losses.
RELATIONSHIP BETWEEN SHOOT AND ROOT NUTRIENT CONCENTRATIONS FOR A RANGE OF TEMPERATE PASTURE AND CEREAL SPECIES

The relationships between shoot and root nutrient concentrations were determined using regression analysis for a range of temperate pastures species and cultivars grown in low ionic strength solution culture. Results from cereals were also included as a comparison. There were significant (P<0.05) differences in the relationships between the grass and cereal species, and the leguminous species. For a given shoot concentration, the root concentrations were higher in legumes for N, P, S, K, Mn, and Zn. Generally, the range of measured shoot concentrations from grass/cereal and legumes were similar (Figure 1). The exceptions were Ca, Mg and B, where legumes had higher shoot concentrations than the grasses/ cereal. For N, S, P, Mn, Zn, Cu, and Fe within the leguminous species, root concentrations for a given shoot concentration were lower when root K concentrations were <3%. Including other nutrients did not significantly improve the relationship except in wheat, where increasing root Ca concentrations increased root Mg concentrations, and increasing root Mg concentrations increased root Ca concentrations. The results from this study give an empirical method for estimating the root nutrient concentrations from shoot nutrient concentrations when modelling nutrient flows in pasture. Introduction Within a pastoral system, plant roots can be a sink (via uptake) or source (via senescence) of nutrients. In order to model the relative contribution of roots within a pastoral system, information on root mass and root nutrient concentrations is required. Since shoot concentrations are regularly measured in pastures, one approach is to estimate root concentrations from an empirical relationship with shoot concentrations. Solution culture techniques for growing plants allow easy harvest of roots without problems due to soil contamination, and hence could give good estimations of root nutrient concentrations in actively growing roots. A wide range of pasture species and cultivars have been screened for Al tolerance using a low ionic strength solution culture technique (see Table 1). The nutrient concentrations used in the experimental soil solution mimicked those found in soil solution extracts from fresh soils (Edmeades et al., 1985; Blamey et al., 1991) as these have been shown to be important for the study of plant responses on acid soils (Edmeades et al., 1995). The majority of experiments with pasture species had varying solution Al concentrations. Thus the range in nutrient concentrations obtained were due to between experiment variation, or to variation when solution Al concentrations were varied. There were a series of experiments with wheat using the same technique where several factors relating to Al tolerance were investigated (see Table 1). These experiments give an indication of what factors may affect the relationship between shoot and root concentrations, and were also included in the analysis. In addition, the results from a set of experiments
Growth and physiological changes during metamorphosis of Senegal sole reared in the laboratory C

The metamorphosis of Solea senegalensis was studied in larvae reared at 20 C and fed four different feeding regimes. A, Artemia (4 nauplii ml ); B, Artemia (2 nauplii ml ); C, mixed diet (2 nauplii ml 1 and 3 mg ml 1 microencapsulated diet); and D, microencapsulated diet (3·7 mg ml ). Rotifers were also supplied in all cases during the first days of feeding. These feeding regimes supported different growth rates during the pre-metamorphosis period (regime A, G=0·376 day ; regime B, G=0·253 day ; regime C, G=0·254 day ; regime D, G=0·162 day ). Larvae started metamorphosis 9 days after hatching (DAH) when fed the regime A, 13 DAH with regime B, 11 DAH with regime C and 15 DAH with regime D. A minimum 5·6–5·9 mm LT was required under all feeding regimes to initiate the metamorphosis. Eye translocation was completed when the larvae reached 8·6–8·7 mm LT (regimes A, B and C), but only 7·3 mm LT with regime D. 4·4–6·2 days were required to complete eye migration under the regimes A, B and C, and 18·3 days under the regime D. This transformation is concomitant with changes in body reserves, and with the pattern of some digestive enzymes.
How Judo Economics can help small firms to survive Bertrand competition : evidence from the lab

The theory of ”judo Economics” describes an optimal strategy for small enterprises to enter a market. By limiting its capacity, the entrant forces a dominant enterprise to accommodate entry. In our paper we find experimental evidence supporting this theory. Collusive behavior, which can be observed in the basic model, is destroyed when price competition among multiple dominant firms is introduced. In contrast, a cost advantage strengthens the small enterprise in a competitive environment while it hurts collusive interaction with one single dominant enterprise. Using these results, we are able to derive strategies for entrants as well as incumbents in different market environments.