Reviewerly/exHarmony huggingface dataset:
Miniaturization of borescopic fringe projection systems for the inspection in confined spaces: a methodical analysis

The rapid developments in the micro camera industry, driven by the smartphone sector, offer a wide range of innovations with respect to the performance and miniaturization of endoscopic instruments. For the fast 3D inspection of inaccessible components such as turbine blades in partially disassembled aircraft engines, a borescopic fringe projection system was developed. This study provides a methodology for the comparison of different camera and projection configurations within borescopic fringe projection. Furthermore, the current limits for the use of multimedia sensors in metrological applications are shown and quantified. The projection unit of the developed measuring system is based on a digital micromirror device, which generates structured light that is imaged into the measurement scene by means of an objective lens and a borescope. Threedimensional, high-resolution reconstructions are carried out via chip-on-the-tip miniature cameras based on the MIPI interface by forming a triangulation base with the projection unit. To enable inspections in confined spaces, the cameras are connected to external framegramer boards. In this study, 1/6” and 1/4” sensors with fixedfocus lenses are evaluated to assess the trade-off between the physical sensor size and the possible reconstruction accuracy. Typical camera parameters such as the sensitivity with respect to the signal-to-noise ratio are determined by means of a standardized test setup. In addition, the application in the triangulation system is evaluated through the modulation signal strength as well as the suitability for typical system calibrations based on the widely used pinhole camera model in combination with a distortion polynomial correction according to the approach of Conrady and Brown. Finally, the sensors are compared regarding 3D reconstructions of calibrated geometric features in accordance with ISO/IEC Guide 98-3:2008 and VDI/VDE 2634-2.
Mineral exploration in the glaciated terrain using upper soil horizon geochemistry and compositional statistical data analysis

&amp;lt;p&amp;gt;Vulnerable nature in northernmost Europe requires development of new, environmentally friendly sampling and analyses techniques for mineral exploration. Those areas are typically covered by transported glaciogenic sediments where the glacial till is most dominant. To offer an alternative for conventional basal till and bedrock sampling with heavy machines, the use of different surface geochemical sampling media and techniques which are quick and cost-effective have been actively applied during the last decade. Particularly, the development of selective and weak leach techniques for the upper soil (Ah and B) horizons&amp;amp;#8217; geochemistry has been intensive, but the reliability needs to be improved and testing is required in different glaciogenic environments.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;In this research, carried out under the project New Exploration Technologies (NEXT), funded by the European Union&amp;amp;#8217;s Horizon 2020 research and innovation programme under grant agreement No 776804, we used stratified random sampling strategy for choosing sampling locations and developed novel compositional statistical data analysis for the interpretation of geochemical data obtained by surface geochemical techniques. The test area is located in the Rajapalot area, Ylitornio, northern Finland, where an active project is carried out by Mawson Oy for Au-Co exploration. The thickness of till cover varies from some metres to 5 m and the glacial morphology is composed of the ribbed moraine ridges with peatlands in between. A sampling network for the Ah and B horizon samples was comprised of 89 routine samples and 10 field replicates acquired of mineral Podsol-type soils. The chemical analyses methods used were Ultratrace 1:1:1 Aqua Regia leach and 0.1 M sodium pyrophosphate leach for the Ah horizon samples, and Ionic leach and Super Trace Aqua Regia leach methods for the B horizon samples. The laboratory analyses were supported by the portable X-Ray Fluorescence (pXRF) analyses done directly in the field. The statistical analysis was based on log-ratio transformations of the geochemical compositions to avoid spurious results. In addition, the response ratios were calculated to measure the degree of enrichment in each element per sample.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The preliminary results of the soil geochemistry show a significant response to many elements (e.g. Au, Co, Cu, Mo, Sc, Te and W) with known mineralized bedrock targets observed in the drill core data. Elemental distribution is also reflecting the lithological variations of the rock units in the bedrock. Based on the results, it is obvious that a) there is good or moderate correlation for several elements between the surface geochemical data and underlying bedrock, and b) soil analysis method using certain soil sampling procedure and selective extraction is an effective, environmentally friendly geochemical exploration technique in the glaciated terrains.&amp;lt;/p&amp;gt;
Target Detection in NAO Robot Golfing

Abstract In robot golfing games, how to identify and track small balls is a critical step for scoring. Considering uneven illumination and intensity, irregular distribution, and blurred borders, an integrated detection method based on the random Hough transform and the Kalman filter is presented to improve the recognition accuracy, i.e., guaranteeing the detection accuracy and the stability in shooting. Experiment on the NAO robot is performed to show the effectiveness of the proposed detecting method. Both theoretical and experimental results suggest that the proposed recognition method can reduce the calculation time of the Hough transform and has a certain degree of robustness against uncertain environments.
Hitting sets and reconstruction for dense orbits in VPe and ΣΠΣ circuits

In this paper we study polynomials in VPe (polynomial-sized formulas) and in ΣΠΣ (polynomial-size depth-3 circuits) whose orbits, under the action of the affine group GLaffn (F) (the action of (A, b) ∈ GLaffn (F) on a polynomial f ∈ F[x] is defined as (A, b) ο f = f (AT x + b)), are dense in their ambient class. We construct hitting sets and interpolating sets for these orbits as well as give reconstruction algorithms. Specifically, we obtain the following results: 1. For [EQUATION], where the lis are linearly independent linear functions, we construct a polynomial-sized interpolating set, and give a polynomial-time reconstruction algorithm. By a result of Bringmann, Ikenmeyer and Zuiddam, the set of all such polynomials is dense in VPe [14], thus our construction gives the first polynomial-size interpolating set for a dense subclass of VPe. 2. For polynomials of the form ANFΔ (l1(x),..., l4Δ(x)) where ANFΔ(x) is the canonical read-once formula in alternating normal form, of depth 2Δ, and the lis are linearly independent linear functions, we provide a quasipolynomial-size interpolating set. We also observe that the reconstruction algorithm of [35] works for all polynomials in this class. This class is also dense in VPe. 3. Similarly, we give a quasipolynomial-sized hitting set for read-once formulas (not necessarily in alternating normal form) composed with a set of linearly independent linear functions. This gives another dense class in VPe. 4. We give a quasipolynomial-sized hitting set for polynomials of the form f(l1(x),..., lm(x)), where f is an m-variate s-sparse polynomial. and the lis are linearly independent linear functions in n ≥ m variables. This class is dense in ΣΠΣ. 5. For polynomials of the form Σsi=1 Πdj=1 li,j (x), where the li,js are linearly independent linear functions, we construct a polynomial-sized interpolating set. We also observe that the reconstruction algorithm of [45] works for every polynomial in the class. This class is dense in ΣΠΣ. As VP = VNC2, our results for VPe translate immediately to VP with a quasipolynomial blow up in parameters. If any of our hitting or interpolating sets could be made robust then this would immediately yield a hitting set for the superclass in which the relevant class is dense, and as a consequence also a lower bound for the superclass. Unfortunately, we also prove that the kind of constructions that we have found (which are defined in terms of k-independent polynomial maps) do not necessarily yield robust hitting sets.
Segmentation Technique for Nucleus Detection in Blood Images for Chronic Leukaemia

Abstract leukaemia is a disease which develops in the bone marrow, causing a large formation of abnormal cells and usually affected adults. The process of inspecting visually on the microscopic images is time consuming and a tiring process. The developed technique is aimed at assisting the haematologists upon identifying the presence of nucleus in blood cell images. Therefore, this technique is hoped to aid the haematologists in early and fast identification of leukaemia. This paper will be focusing on Acute Myeloid Leukaemia (AML). This research work proposed a combination of methods for the detection of Leukaemia using image processing techniques such as L*A*B colour-based thresholding algorithm, Sobel edge detection algorithm, and watershed distance transform to identify the nucleus blasts of leukaemia cells from blood cells image. The developed technique shows that it is able to produce the image of segmented nucleus blasts.
A Quantitative Analysis of Student Solutions to Graph Database Queries

As data grow both in size and in connectivity, the interest to use graph databases in industry has been growing rapidly. However, there has been little research on graph database education. In response to the need to introduce college students to graph databases, this paper is the first to analyze students' errors in their submissions writing different types of queries in Cypher, the query language for Neo4j--the most prominent graph database. Based on 40,093 student submission from homework assignments in an upper-level computer science database course at University of Illinois at Urbana-Champaign, this paper provides qualitative insights and quantitative analysis about students' learning when solving graph database problems. The data shows that writing more complex queries initially takes students more time and more attempts to write more complex queries correctly. Additionally, students struggle to correctly use Cypher's WITH clause to define variable names before referencing in the WHERE clause, and these errors persist over multiple homework problems requiring the same techniques.
Android Application for Crime Prevention with GPS Integrated Technology

Abstract Vigilance is a top priority in carrying out daily activities considering the number of various crimes that arise due to the increasingly rampant social conflicts regardless of economic class. During 2019, the crime rate in the Labuhanbatu police area (Labuhanbatu, Labuhanbatu Selatan, Labuhanbatu Utara) increased by approximately 10 percent from the previous year, and is still dominated by criminal theft with ballast, motor vehicle theft and drug cases, as for the case data in 2018 there were 4,412 cases and in 2019 4,663 cases. Based on the case, the researcher wants to help the community and the police in preventing crime, especially in Labuhanbatu. The research method used is descriptive method that is research based on actual data by comparing theories and then drawing conclusions. This research will create an Android-based application that helps the community and the police in preventing or overcoming crime. This crime alarm application makes it easy for people who use when a crime occurs because it can be accessed directly on the phone and help the police in handling crime.
Kindergarten Big Data System Solution Architecture

The kindergarten big data system is designed based on the practical problems of insufficient pre-school education resources, inadequate regulatory systems and mechanisms, and the need to improve the quality of childcare, and the management needs of the kindergarten urgently need to improve the science, flexibility, efficiency, and safety, developing. It includes three major aspects of network system architecture, environment system and management system. The kindergarten big data system is based on modern information technology and can eventually achieve "intelligent connection with government authorities" to facilitate supervision. The kindergarten big data system can "integrate intelligently the various affairs of the kindergarten" for effective management; "monitor children's health information at all times" to ensure safety. It also can "real-time interact with parents and share children's information" to achieve home-school co-education; "develop games, learning environment and resources" to provide personalized services and other functions for kindergarten teachers.
Implicit data recommendation based on refined classification and ranking learning

With the exponential growth of data, it becomes more and more difficult to quickly obtain valuable information from massive amounts of data. Clicking and browsing of such non-scoring implicit data has also attracted more and more attention from scholars. Recommendations for implicit data generally use bayesian personalized ranking algorithm (BPR). The algorithm focuses on the difference in preferences between item pairs, and believes that users prefer items that have interacted with items that have never interacted. However, this assumption is still not specific enough for analyzing the relationship between users' items. Therefore, this paper expands the single pairwise sorting algorithm into a more detailed pair-level parallel sorting. First, the non-interactive item set is refined into two categories through the concept of frequent item sets: uncertain feedback and negative feedback. Secondly, the algorithm of fusion of BPR and list sorting is used to relax the assumptions of independence, and two sets are analyzed separately. This also alleviates the sparsity problem of implicit data due to natural imbalance. Finally, a simulation experiment was performed on the public data set. The experimental results show that the refined BPR algorithm has a better improvement than the baseline algorithm.
An Analysis of the Factors Related to EU GMP Non-compliance - Focusing on Active Substance, Human Medicinal Product -

To export medicinal products to Europe, EU Good Manufacturing Practices (GMP) inspection is a critical step. Using the EudraGMDP database from 2009 to 2019, this study was conducted to determine factors influencing noncompliance in the EU GMP inspection. The results revealed that the number of EU GMP inspections has steadily increased in both EU and non-EU countries. The latter showed higher non-compliance rates compared to the former. For active substances, analysis of observations from non-compliance inspections indicated that “Documentation and records,” “Quality management,” and “Equipment” are common items observed as non-compliant. For human medicinal products, “Pharmaceutical quality system,” “Production,” and “Premises and equipment” are frequently observed as non-compliance items. “Building and facilities” and “Contract manufacturing” were found to be significant factors causing GMP qualification failure for active substances. For human medicinal products, “Quality control” was found to be a significant factor in GMP qualification failure. This study confirmed that non-compliance rates for OECD and non-OECD countries were significantly different.
Acts of Requesting as Realized by English for Specific Purposes Students

The success of language learners’ intercultural communication highly depends on their acquisition of not only grammatical knowledge but also pragmatic aspects of the target language. However, research examining English for specific purposes (ESP) learners’ request realization, as a crucial indicator of pragmatic competence, still remains a paucity of evidence. Addressing this issue, the present study aims to examine English for specific purposes (ESP) students’ most frequently used request strategy and their reasons behind the selected strategy. To this end, 36 ESP students of a public university in Surakarta Indonesia were involved in a descriptive qualitative study. A set of Discourse Completion Test (DCT), role-play, and semi-structured interview were employed as a means of data collection. The data were analyzed based on Blum-Kulka and Olshtain’s Cross-Cultural Study of Speech Act Realization Patterns (CCSARP) and followed by thematic content analysis for the interview responses. The results depicted that conventionally indirect requests were the most frequently used strategy by the students than other strategies, i.e. direct request, and non-conventionally indirect request. The semi-structured interview further revealed that cultural factors, degree of politeness, and social distance among the interlocutors became the primary reasons for the students’ massive selection of conventionally indirect strategies. These results offer fruitful insights for English language teaching stakeholders as an effort to equip ESP students with satisfactory pragmatic and cross-cultural knowledge.Keywords: acts of requesting, pragmatics, request strategies,
Effect of Holding Time on Optical Structure Properties of Ba(Zr0.5Ti0.5)O3 Thin Film Using Sol-Gel Method

The ferroelectric thin film material of barium zirconium titanate (BZT) on the fluorine-doped tin oxide (FTO) glass substrate was successfully prepared using the sol-gel method. The purpose of this study was to determine the effect of crystal size on the variation of holding time. The lattice parameter data has a value of a = b of 3.918 A and for c it is 4.01 A. The results of this study indicate that the crystal structure of BZT is tetragonal because the lattice parameter has the same values a and b but not equal to c. To obtain the bandgap energy, a thin film plot method of Ba(Zr0,5Ti0,5)O3 was used at a temperature of 700 °C with a holding time of 30 minutes, 1 hour, 1 hour 30 minutes, and 2 hours. The optical thin layer bandgap energy of Ba(Zr0.5Ti0.5)O3 was calculated using the Tauc plot. The absorbance values obtained were 3.277 a.u, 3.0654 a.u, 3.323 a.u, and 3.424 a.u. The maximum transmission (TM) occurs at 1 hour holding time which gives a percentage of TM1 44.477% and TM2 20.568%. While the 2 hour hold time gives a minimum transmission (Tm) of Tm1 10.859% and Tm2 7.759%, respectively.
Integrating Automated Segmentation and Glossing into Documentary and Descriptive Linguistics

Any attempt to integrate NLP systems to the study of endangered languages must take into consideration traditional approaches by both NLP and linguistics. This paper tests different strategies and workflows for morpheme segmentation and glossing that may affect the potential to integrate machine learning. Two experiments train Transformer models on documentary corpora from five under-documented languages. In one experiment, a model learns segmentation and glossing as a joint step and another model learns the tasks into two sequential steps. We find the sequential approach yields somewhat better results. In a second experiment, one model is trained on surface segmented data, where strings of texts have been simply divided at morpheme boundaries. Another model is trained on canonically segmented data, the approach preferred by linguists, where abstract, underlying forms are represented. We find no clear advantage to either segmentation strategy and note that the difference between them disappears as training data increases. On average the models achieve more than a 0.5 F1-score, with the best models scoring 0.6 or above. An analysis of errors leads us to conclude consistency during manual segmentation and glossing may facilitate higher scores from automatic evaluation but in reality the scores may be lowered when evaluated against original data because instances of annotator error in the original data are “corrected” by the model.
Contextual Dropout: An Efficient Sample-Dependent Dropout Module

Dropout has been demonstrated as a simple and effective module to not only regularize the training process of deep neural networks, but also provide the uncertainty estimation for prediction. However, the quality of uncertainty estimation is highly dependent on the dropout probabilities. Most current models use the same dropout distributions across all data samples due to its simplicity. Despite the potential gains in the flexibility of modeling uncertainty, sample-dependent dropout, on the other hand, is less explored as it often encounters scalability issues or involves non-trivial model changes. In this paper, we propose contextual dropout with an efficient structural design as a simple and scalable sample-dependent dropout module, which can be applied to a wide range of models at the expense of only slightly increased memory and computational cost. We learn the dropout probabilities with a variational objective, compatible with both Bernoulli dropout and Gaussian dropout. We apply the contextual dropout module to various models with applications to image classification and visual question answering and demonstrate the scalability of the method with large-scale datasets, such as ImageNet and VQA 2.0. Our experimental results show that the proposed method outperforms baseline methods in terms of both accuracy and quality of uncertainty estimation.
SASI: a metric for Salt Body Reconstruction

Summary We propose a new metric called Spatial Aware Similitude Index (SASI) to compute quality of prediction and models that contain salt bodies. The metric is more informative than traditional general metrics such as SSIM or Jaccard.
Subject Identification Across Large Expression Variations Using 3D Facial Landmarks

In this work, we propose to use 3D facial landmarks for the task of subject identification, over a range of expressed emotion. Landmarks are detected, using a Temporal Deformable Shape Model and used to train a Support Vector Machine (SVM), Random Forest (RF), and Long Short-term Memory (LSTM) neural network for subject identification. As we are interested in subject identification with large variations in expression, we conducted experiments on 3 emotion-based databases, namely the BU-4DFE, BP4D, and BP4D+ 3D/4D face databases. We show that our proposed method outperforms current state of the art methods for subject identification on BU-4DFE and BP4D. To the best of our knowledge, this is the first work to investigate subject identification on the BP4D+, resulting in a baseline for the community.
Believe The HiPe: Hierarchical Perturbation for Fast and Robust Explanation of Black Box Models.

Understanding the predictions made by Artificial Intelligence (AI) systems is becoming more and more important as deep learning models are used for increasingly complex and high-stakes tasks. Saliency mapping - an easily interpretable visual attribution method - is one important tool for this, but existing formulations are limited by either computational cost or architectural constraints. We therefore propose Hierarchical Perturbation, a very fast and completely model-agnostic method for explaining model predictions with robust saliency maps. Using standard benchmarks and datasets, we show that our saliency maps are of competitive or superior quality to those generated by existing black-box methods - and are over 20x faster to compute.