Reviewerly/exHarmony huggingface dataset:
SFU-Store-Nav: A Multimodal Dataset for Indoor Human Navigation

This article describes a dataset collected in a set of experiments that involves human participants and a robot. The set of experiments was conducted in the computing science robotics lab in Simon Fraser University, Burnaby, BC, Canada, and its aim is to gather data containing common gestures, movements, and other behaviours that may indicate humans' navigational intent relevant for autonomous robot navigation. The experiment simulates a shopping scenario where human participants come in to pick up items from his/her shopping list and interact with a Pepper robot that is programmed to help the human participant. We collected visual data and motion capture data from 108 human participants. The visual data contains live recordings of the experiments and the motion capture data contains the position and orientation of the human participants in world coordinates. This dataset could be valuable for researchers in the robotics, machine learning and computer vision community.
PREPARING FUTURE TEACHERS FOR EDUCATIONAL ACTIVITIES IN ORGANIZATIONS OF SECONDARY VOCATIONAL EDUCATION: THE CONATIVE-ACTIVITY COMPONENT

The problem of preparing future teachers for educational activities in the organizations of secondary vocational education is actualized. It is noted that the fact is conditioned by the increased importance of education in the teaching/learning process, specific cohort of college students, the necessity of forming soft skills by means of educational operations.The views of the Russian and foreign researchers on the problem of training future teachers for educational activities at the organizations of secondary vocational education are analyzed. The content of contative activity component of preparing future teachers for educational activities in the organizations of secondary vocational education is revealed. Keywords: preparation for educational activity, readiness for educational activity, future teacher, conative-activity component, organizations of secondary vocational education.
Brief Announcement: Game Theoretical Framework for Analyzing Blockchains Robustness

Blockchains systems evolve in complex environments that mix classical patterns of faults (e.g crash faults, transient faults, Byzantine faults, churn) with selfish, rational or irrational behaviors typical to economical systems. In this paper we propose a game theoretical framework in order to formally characterize the robustness of blockchains systems in terms of resilience to rational deviations and immunity to Byzantine behaviors. Our framework includes necessary and sufficient conditions for checking the immunity and resilience of games and a new technique for composing games that preserves the robustness of individual games. We prove the practical interest of our formal framework by characterizing the robustness of three different protocols popular in blockchain systems: a HTLC-based payment scheme (a.k.a. Lightning Network), a side-chain protocol and a cross-chain swap protocol.
BioNerFlair: biomedical named entity recognition using flair embedding and sequence tagger

Motivation: The proliferation of Biomedical research articles has made the task of information retrieval more important than ever. Scientists and Researchers are having difficulty in finding articles that contain information relevant to them. Proper extraction of biomedical entities like Disease, Drug/chem, Species, Gene/protein, can considerably improve the filtering of articles resulting in better extraction of relevant information. Performance on BioNer benchmarks has progressively improved because of progression in transformers-based models like BERT, XLNet, OpenAI, GPT2, etc. These models give excellent results; however, they are computationally expensive and we can achieve better scores for domain-specific tasks using other contextual string-based models and LSTM-CRF based sequence tagger. Results: We introduce BioNerFlair, a method to train models for biomedical named entity recognition using Flair plus GloVe embeddings and Bidirectional LSTM-CRF based sequence tagger. With almost the same generic architecture widely used for named entity recognition, BioNerFlair outperforms previous state-of-the-art models. I performed experiments on 8 benchmarks datasets for biomedical named entity recognition. Compared to current state-of-the-art models, BioNerFlair achieves the best F1-score of 90.17 beyond 84.72 on the BioCreative II gene mention (BC2GM) corpus, best F1-score of 94.03 beyond 92.36 on the BioCreative IV chemical and drug (BC4CHEMD) corpus, best F1-score of 88.73 beyond 78.58 on the JNLPBA corpus, best F1-score of 91.1 beyond 89.71 on the NCBI disease corpus, best F1-score of 85.48 beyond 78.98 on the Species-800 corpus, while near best results was observed on BC5CDR-chem, BC3CDR-disease, and LINNAEUS corpus.
Una estrategia metodológica para la optimización de procesos de producción de música POP, basada en modelos computacionales

The design of a methodological strategy composed of computational models, music technology and basic rules of harmonic composition is proposed. The strategy integrates different tools such as programming languages, design and reuse of algorithms and libraries for the extraction of strong characteristics to the samples produced by an interpreter, as well as the execution of discrete stochastic processes that generate melodies bounded by basic rules of music composition Pop. The fragments generated are converted into series that are subsequently reproduced in a controlled manner, by a MIDI device (Musical Instrument Digital Interface). To guarantee the integration of all the elements as a system that generates iterations, open control protocols are used between programming languages and tools that allow the interconnection and communication between the different technological components that make up the strategy. Once the melodic fragment generation process is completed, these are transmitted to an audio manager and copied to each channel of the manager in a standard MIDI type format.
HM4: Hidden Markov Model with Memory Management for Visual Place Recognition

Visual place recognition needs to be robust against appearance variability due to natural and man-made causes. Training data collection should thus be an ongoing process to allow continuous appearance changes to be recorded. However, this creates an unboundedly-growing database that poses time and memory scalability challenges for place recognition methods. To tackle the scalability issue for visual place recognition in autonomous driving, we develop a Hidden Markov Model approach with a two-tiered memory management. Our algorithm, dubbed HM$^4$, exploits temporal look-ahead to transfer promising candidate images between passive storage and active memory when needed. The inference process takes into account both promising images and a coarse representations of the full database. We show that this allows constant time and space inference for a fixed coverage area. The coarse representations can also be updated incrementally to absorb new data. To further reduce the memory requirements, we derive a compact image representation inspired by Locality Sensitive Hashing (LSH). Through experiments on real world data, we demonstrate the excellent scalability and accuracy of the approach under appearance changes and provide comparisons against state-of-the-art techniques.
Study of Groundwater Quality in Magelang City Due to the Impact of Domestic and Industrial Waste

This study aims to determine the current condition of groundwater quality in the city of Magelang due to the disposal of domestic and industrial waste. The analysis used was to measure physical, chemical, and biological parameters in situ and ex-situ. The research method used purposive sampling and then analyzed descriptively using water quality standards. The results showed that the physical parameters were still in good condition, while the values (TSS) of Total Suspended Solid and Total Dissolved Solid was 3.7 mg / L and 227.95 mg / L. On the other hand, there was a fluctuation in the pH value at several water stations which showed a tendency to be acidic. Furthermore, the nitrate levels at research stations 1,6,7 and 9 showed values that exceeded the established threshold of 10 mg/L. Furthermore, for the BOD value that has a value of more than 2 mg / L as a requirement for entering class 1, groundwater quality is safe for hygienic, Chemical Oxygen Demand has a value that exceeds the maximum requirement of 10 mg/L in all research station and is categorized as heavy pollution. The total coliform value that exceeds the water quality standard for sanitation hygiene according to Permenkes No. 32 of 2017 at 50 MPN / 100ml. The quality of groundwater in the Magelang can be used for drinking water, provided that its use must go through the cooking process first.Keywords: Groundwater quality, waste, Magelang
Image Out painting with GANS

The difficult task of image out painting (extrapolation) has received relatively very little attention in respect to its cousin, image-inpainting (completion). Consequently, we tend to present a deep learning approach supported [4] for adversarial perceive a network to comprehend past image boundaries. We use a three-phase training schedule to stably train a DCGAN design on a set of the Places365 dataset. In line with [4], we additionally use native discriminators to reinforce the standard of our output. Once trained, our model is ready to out paint 256Ã—256 color images relatively realistically, thus allowing algorithmic out painting. Our results show that deep learning approaches to image out painting are each possible and promising.
I connettivi perché e weil come introduttori di enunciati autonomi nei giornali di oggi

The aim of this paper is, first of all, to outline the contemporary uses of causal structures in Italian writing, focusing on some less canonical syntactic and textual manifestations. These non-prototypical constructs will be, then, compared with the corresponding ones in German. The analysis that will be presented are based on qualitative and quantitative data derived from corpora of Italian and German newspaper writing. As far as the Italian language, the paper will focus on the causal connective perché: after presenting its frequency of use compared to the other causal connectives, we will discuss some of its most common syntactic and informative-textual configurations, with particular reference to the case in which perché introduces an independent utterance, preceded by a strong punctuation mark. Right this last use will be observed also in German newspapers, thanks to a preliminary survey that will focus on the causal connective weil. For both languages we will consider the frequency of this peculiar use, as well as its possible forms and textual functions, in order to highlight analogies and differences between German and Italian.
A comparative study between Round Robin technique and Talking Chip technique in improving speaking achievement and students’ attitudes toward the techniques

Tujuan dari penelitian ini adalah untuk mencari perbedaan dari Round Robin Technique dan Talking Chip Technique dalam meningkatkan prestasi berbicara siswa dan untuk mencari hubungan antara sikap siswa tehadap teknik belajar dan pencapaian berbicara. Subjek penelitian terdiri dari 30 siswa di kelas XI MIA 4 dan 33 siswa di kelas XI MIA 6 MAN 1 Bandar Lampung. Tes berbicara dan kuisioner digunakan untuk mengumpulkan data. Penelitian ini menggunakan Independent T-test dan Product Moment Correlation. Hasil dari penelitian ini menunjukan tidak ada perbedaan yang signifikan antara Round Robin Technique dan Talking Chip Technique dalam meningkatkan pencapaian berbicarakarena p>0.05 (P=0,072 and 0,069). Selain itu, hasil penelitian menunjukkan bahwa ada hubungan yang signifikan antara sikap siswa terhadap teknik dan pencapaian berbicara dengan tingkat signifikan (0,000 600 (r = 0,738 dan 0,678). Dapat disimpulkan bahwa teknik apa pun yang digunakan oleh guru, sikap siswa akan selalu memiliki pengaruh pada pencapaian berbicara. Semakin banyak siswa memiliki sikap yang baik terhadap teknik, semakin mereka berusaha terlibat dalam diskusi dan mereka akan mendapatkan skor yang lebih baik.  The objectives of this research were to find out the difference between Round Robin Technique and Talking Chip Technique in improving speaking achievement and to find out the correlation between students’ attitudes toward the techniques and speaking achievement. The subjects were 30 students of XI MIA 4 and 33 students of XI MIA 6 in MAN 1 Bandar Lampung. Speaking tests and questionnaires were used to collect the data. This study employed Independent T-test and Product Moment Correlation. The result showed that there was no significant difference between Round Robin Technique and Talking Chip since p>0.05 (P=0.072 and 0.069). Furthermore, the result showed that there was a significant correlation between students’ attitudes toward the techniques and speaking achievement with the significant level (0.000 600 (r= 0.738 and 0.678). It can be concluded, whatever techniques that are used by the teacher, students’ attitude would always influence speaking achievement. The more students had a good attitude toward the techniques, the more they would have an effort to be involved in the discussion and they would get better scores.  Keywords:Round Robin Technique, Talking Chip Technique, Speaking Achievement, Students’ Attitudes
The Solar Eclipse: A Perfect Variable Irradiance Source. An Investigation of the Linearity Properties of Photovoltaic Devices

A detailed study of photovoltaic devices and their response to natural sunlight is difficult since the experimental conditions, i.e. illuminated area, uniformity, spectral stability and distribution of the light source, can be very demanding to reproduce. Conventional laboratory approaches such as varying the intensity of the lamp or using neutral density filters do not provide satisfactory repeatability of the above conditions. Additionally, outdoor characterisation maintains ideal and consistent conditions only within a limited irradiance level. Total irradiance varies during the day between a large range but unfortunately so does the air mass. A rare event such as a solar eclipse combines two remarkable characteristics: the total irradiance varies while the spectral distribution remains virtually the same, and it exhibits an excellent spatial uniformity. These characteristics have been exploited to perform a study on photovoltaic devices and irradiance sensors of different technologies and their relative mismatch.
Bayesian Fusion of Data Partitioned Particle Estimates

We present a Bayesian data fusion method to approximate a posterior distribution from an ensemble of particle estimates that only have access to subsets of the data. Our approach relies on approximate probabilistic inference of model parameters through Monte Carlo methods, followed by an update and resample scheme related to multiple importance sampling to combine information from the initial estimates. We show the method is convergent in the particle limit and directly suited to application on multi-sensor data fusion problems by demonstrating efficacy on a multi-sensor Keplerian orbit determination problem and a bearings-only tracking problem.
Neural text normalization leveraging similarities of strings and sounds

We propose neural models that can normalize text by considering the similarities of word strings and sounds. We experimentally compared a model that considers the similarities of both word strings and sounds, a model that considers only the similarity of word strings or of sounds, and a model without the similarities as a baseline. Results showed that leveraging the word string similarity succeeded in dealing with misspellings and abbreviations, and taking into account the sound similarity succeeded in dealing with phonetic substitutions and emphasized characters. So that the proposed models achieved higher F$_1$ scores than the baseline.
Research on the Importance of Chinese Traditional Music Education in the Process of Higher Vocational Aesthetic Education Based on Computer-aided

Abstract With the comprehensive development of quality education in our country, Chinese traditional music education attaches more and more importance to aesthetic education. Based on computer-aided analysis, Chinese traditional music education has been greatly developed in the past two decades, but there are still many shortcomings. How to improve the role of Chinese traditional music education in aesthetic education in higher vocational colleges has become the main direction. This paper first analyses the important content and means of aesthetic education of Chinese traditional music. Then, based on computer-aided analysis, this paper analyses the important function of Chinese traditional music education to aesthetic education. Finally, this paper puts forward some suggestions for some problems.
To Push or To Pull: On Reducing Communication and Synchronization in Graph Computations

We reduce the cost of communication and synchronization in graph processing by analyzing the fastest way to process graphs: pushing the updates to a shared state or pulling the updates to a private state.We investigate the applicability of this push-pull dichotomy to various algorithms and its impact on complexity, performance, and the amount of used locks, atomics, and reads/writes. We consider 11 graph algorithms, 3 programming models, 2 graph abstractions, and various families of graphs. The conducted analysis illustrates surprising differences between push and pull variants of different algorithms in performance, speed of convergence, and code complexity; the insights are backed up by performance data from hardware counters.We use these findings to illustrate which variant is faster for each algorithm and to develop generic strategies that enable even higher speedups. Our insights can be used to accelerate graph processing engines or libraries on both massively-parallel shared-memory machines as well as distributed-memory systems.
Modelchecking Safety Properties in Randomized Security Protocols

Automated reasoning tools for security protocols model protocols as non-deterministic processes that communicate through a Dolev-Yao attacker. There are, however, a large class of protocols whose correctness relies on an explicit ability to model and reason about randomness. Although such protocols lie at the heart of many widely adopted systems for anonymous communication, they have so-far eluded automated verification techniques. We propose an algorithm for reasoning about safety properties for randomized protocols. The algorithm is implemented as an extension of Stochastic Protocol ANalyzer (Span), the mechanized tool that reasons about the indistinguishability properties of randomized protocols. Using Span, we conduct the first automated verification on several randomized security protocols and uncover previously unknown design weaknesses in several of the protocols we analyzed.
Conceptual Cues Facilitate Encoding in Visual Working Memory

A growing body of evidence suggests that viewing words with implicit spatial associations can facilitate the processing of information at compatible spatial locations. Like other types of spatial cues, these conceptual cues are thought to produce spatial shifts of attention. If this is the case, viewing words with implicit spatial associations should also facilitate the encoding and retrieval of information from visual working memory. To test whether this is the case, participants viewed a word with an upward (e.g., God, hat), downward (e.g., Devil, boots), or neutral (e.g., table, chair) spatial association, followed by an array of four colored squares. The colors of the squares could be selected from either a set of seven discriminable colors or a continuous color wheel. After a brief retention interval, a probe square was presented at the location of one of the four squares, and participants were asked to identify whether the color of this square was the same as the square that was originally at that location. To ensure that participants processed the central word, they were only asked to complete the visual working memory task when a non-furniture word was presented. Participants were faster at identifying the color of the probe square when it was presented at a compatible spatial location, suggesting that conceptual cues can influence the encoding of information in visual working memory. However, participants were also faster at identifying the color of the probe square when it was presented at a horizontal spatial location, suggesting that processing the central word may have involved lateral shifts of attention. Together, these findings indicate that viewing words with implicit spatial associations can facilitate the encoding of information in visual working memory, and provide further evidence that these conceptual cues may produce spatial shifts of attention.
A New Algorithm for Identifying and Quantifying of Latent Classes

Processing large amounts of data can be greatly simplified if this data is divided into approximately homogeneous groups. Splitting into such groups is the task of cluster analysis. However, the question of constructing an objective, natural partition into clusters remains open. The paper considers a modern approach to the search for such an objective cluster structure by highlighting the indicator of a common essential part from the set of characteristics that define objects (we call them the forming ones). When this indicator is fixed, the remains of the forming characteristics become independent or close to such. The resulting independent residuals are interpreted as a kind of information noise, and the latent cluster variable, the common fixed part that provides such a transformation, can be a reason for the objective integration of objects into clusters. A new algorithm for the formation of a cluster partition based on the proximity or coincidence of the values of a latent cluster variable with the simultaneous quantification of its values is proposed. The algorithm is based on the targeted search of partitions, the transition from the start one to the partition, more close to the objective. The algorithm proposed in the paper can be easily modified to the case of non-numeric categorized characteristics.
Internships as a Factor in Developing the Company’s Social Potential

The article examines the role of internship in the development of the social potential of the company. One of the factors of this development is a two-level system for improving the professional qualities of trainees, each component of which has its specific characteristics. The authors give conceptual definitions and analyze the features of such forms of training young personnel as internship and mentoring. While there are certain common features, these phenomena still have significant differences in moral, administrative, temporal and legal aspects. We used the method of sociological diagnostics to analyze the effectiveness of organizing internships in one of the largest companies in the pharmaceutical market. In the course of the study, we made a grouping, and a hierarchy of varieties of knowledge and skills was built based on the respondents’ self-esteem. The result of the work was the identification of the factors of the weak development of the internship phenomenon in modern Russia with a sufficiently large potential.