Reviewerly/exHarmony huggingface dataset:
A Study of Dispreferred Responses in Chinese Conversation Textbooks

This paper investigates several features of dispreferred responses, including their frequency, their distributional properties, their types, and their functions in conversations contained within Mandarin Chinese textbooks by level of difficulty, and it provides how dispreferred response should be reflected in Mandarin Chinese textbooks. The analysis in this paper are made into three aspects: (1) a detailed and complete study on the presence of dispreferred responses in the three textbooks; (2) a comparison of dispreferred responses among the three textbooks; (3) a comparison of dispreferred responses in naturally occurring spoken conversation in Chinese and those in Chinese textbooks. It is through the analysis that this paper shows that dispreferred responses in the three textbooks are defective in illustrating diverse types of dispreferred responses and delayed and structurally elaborated features. Account strategies are not frequently used in textbooks, while explaining strategies are most frequently used in naturally occurring conversations. The declination components of dispreferred responses does not truthfully reflect the entire circumstance of Chinese conversation. This paper proposes the improvements for integrating dispreferred responses into textbook study by level of difficulty. In the beginning level, Chinese conversation textbooks should introduce a variety of dispreferred response types. In the intermediate level, Chinese language textbooks need to show the interactional features of dispreferred responses based on the actual dispreferred responses of native Chinese speakers. In the advanced level, the textbooks should include the socio-culturally specific features of the dispreferred responses.
The Look of a Transprofessional Worker Through the Prism of the Educational Environment of the University

The problem of forming a transprofessional personality is becoming more and more relevant in the science and practice of the development of modern society. The article considers the characteristics of a transprofessional employee as the main subject of the development of the organization and the economy as a whole through the system of his professional and personal qualities and competencies, gives a generalized idea of the place of the studied characteristics in the labor potential of a transprofessional. The research is devoted to the study of ideas about the transprofessional worker in the educational environment. In the course of the study using the author's questionnaire, assessment scales and calculation of coefficients, data were obtained regarding the opinion of students and teachers about the degree of expression of the studied characteristics in transprofessionals, as well as – as a problem field – about the possibilities of forming and developing these characteristics in the process of studying at the University. At the final stage, a comparative analysis of the results by sample category is performed. The product of the study is a score table, as well as generalized graphs that reflect the opinion of respondents on the issues under study. The scientific novelty of the research consists in an attempt to identify the main patterns of understanding the phenomenon of transprofessionalism in order to find ways to form it most effectively. The practical significance of the research results can form the basis for the transformation of modern education systems and professional self-determination of young workers.
New Result Database for the Automotive Industry using Dynamic Columns

Scania is undergoing a transformation from being a supplier of trucks, buses and engines to a supplier of complete and sustainable transport solutions. Scania Test Rig Development (NLR) group is re ...
Enhancing, Correcting, and Working with Color

In this chapter, we’ll now learn about improving color images—both enhancing color and correcting color problems. We’ll also work with color by colorizing a grayscale (black-and-white image).
Adoption of Color Doppler Ultrasound in the Measurement of Fetal Hypoxia in Late Pregnancy

Objective : In order to improve the detection rate of fetal hypoxia in the third trimester and reduce the probability of adverse pregnancy outcome, color doppler ultrasound (CDU), and contractions were used to assess the severity of fetal hypoxia. Methods : The 61 pregnant women diagnosed with intrauterine hypoxia in South District of The Affiliated Hospital of Chengde Medical College from October 2017 to September 2019 were classified as the sick group. Meanwhile, the 61 normal pregnant women were selected as the control group. CDU was used to detect the relevant indexes of umbilical artery (UA) and middle cerebral artery (MCA) in the two groups, including pulse index (PI), resistance index (RI), systolic peak blood flow velocity (S) and diastolic peak blood flow velocity (D). The Apgar scale was used to score neonatal status. According to the score results, newborns were divided into Apgar ≤ 7 group and Apgar &gt; 7 group. The indexes of UA and MCA were compared between the two groups. The amniotic fluid status of pregnant women was assessed using the contractile stimulation test (CST). The rate of amniotic fluid pollution in pregnant women and the incidence of neonatal asphyxia were calculated. Pregnant women were grouped according to the CST score. The correlation between CST score and amniotic fluid pollution and neonatal asphyxia in pregnant women was analyzed. Results : First, the index of fetal UA was obviously higher than that of the control group, while the index of MCA was obviously lower than that of the control group ( P &lt; 0.05). Second, the indexes of fetal UA in Apgar ≤ 7 group were obviously higher than those in Apgar &gt; 7 group, while those in MCA were obviously lower than those in Apgar &gt; 7 group ( P &lt; 0.05). Third, the incidence of amniotic fluid pollution and neonatal asphyxia in low and middle groups of pregnant women was obviously higher than that in high groups ( P &lt; 0.01). Conclusion : This indicates that the CDU technology combined with uterine contraction stimulation experiment can assess the degree of intrauterine hypoxia in the late stage of pregnancy, which provides a feasible scheme for clinical detection of intrauterine hypoxia.
Generating Facial Expressions Associated with Text

How will you react to the next post that you are going to read? In this paper we propose a learning system that is able to artificially alter the picture of a face in order to generate the emotion that is associated with a given input text. The face generation procedure is function of further information about the considered person, either given (topics of interest) or automatically estimated from the provided picture (age, sex). In particular, two Convolutional Networks are trained to predict age and sex, while two other Recurrent Neural Network-based models predict the topic and the dominant emotion in the input text. First Order Logic (FOL)-based functions are introduced to mix the outcome of the four neural models and to decide which emotion to generate, following the theory of T-Norms. Finally, the same theory is exploited to build a neural generative model of facial expressions, that is used create the final face. Experimental results are performed to assess the quality of the information extraction process and to show the outcome of the generative network.
RADSSo: An Automated Tool for the multi-CASH Machine Learning Problem

The increasing application of machine learning techniques to different disciplines has driven the research in the field towards the creation of algorithms able to construct the best model with the optimal hyperparameter configuration for a particular problem, without the need of user’s expert knowledge. This is well-known as the Combined Algorithms Selection and Hyperparameter Optimization problem. In this work, we develop the open-source tool RADSSo in order to solve a multi-scenario of combined algorithms selection and hyperparameter optimization in which only one datastore is available containing many different machine learning problems. Then, several models need to be computed, at the same time, in an automated way. The tool is deployed in a modular form that allows to modify it and to customize the configuration files to adapt the tool to any context. The underlying model is a mathematical formula that scores each machine learning model providing the best one for each subsample of the datastore. This score is based on the suitability of the model, different metrics from the confusion matrix and the capability of the generalization by the learning curves. In addition, RADSSo provides intuitively reports with all the essential information.
Analysis of Wasted Computing Resources in Data Centers in terms of CPU, RAM and HDD

Despite the vast benefits offered by the data center computing systems, the efficient analysis of the wasted computing resources is vital. In this paper we shall analyze the amount of wasted computing resources in terms of CPU, RAM and HDD.
What do CNNs gain by imitating the visual development of primate infants

This research is supported by A*STAR under its Human-Robot Collaborative AI for Advanced Manufacturing and Engineering (Award A18A2b0046) and theNational Research Foundation Singapore under its AI Singapore Programme (Award Number: AISG-RP-2019-010).
Dynamic Trajectory for Visual Perception of Abnormal Behavior

Computer vision and intelligent analysis technology has been extensively applied to video surveillance and security system. Motion trajectory feature is used to detect abnormal motion behavior. Because the trajectory mainly reflects the spatial change of the moving object in the foreground, there are some limitations to reflect the time information. In this paper, a time encoding method for particle trajectory is proposed, which is based on the information of temporal and spatial changes of particle motion. Based on the trajectory of motion, it describes how the object moves and its position changes in space, reflecting the spatial distribution of motion mode and energy. Based on the dynamic particle trajectory, the video motion evolution pattern is presented in the form of visual behavior template, and the performance of visual features is enhanced by pseudo color coding. Compared with the spatial motion trajectory, the proposed time encoding trajectory method can effectively improve the recognition performance.
Application of VR Technology in Teaching Archery

Objective: This paper aims to explore the effectiveness of using VR in archery teaching, and to accumulate experience in order to promote the integration of physical education and information technology in tertiary education, improve the teaching effect, and further promote the reform of physical education. Methods: In this study, literature review, questionnaire and experiments were used to establish an experimental group and a control group of 20 subjects each. The experimental group used VR technology in archery teaching and relaxation exercises, whereas the control group used traditional teaching methods. Results: the results show that compared with the control group, the relevant data of the experimental group is significantly stronger. A significant difference exists in the students’ learning interest and control of heart rate. The P value is less than 0.05. There is a very significant difference in the acceptability of teaching methods. The P value is less than 0.01. conclusion: the use of VR technology in archery teaching plays an important role in enhancing students’ learning interest and acceptability of teachers’ teaching methods, inspiring students’ potential and enhancing their ability to regulate their own heart rate. VR technology can very effectively assist archery teaching.
ANALISIS PENGGUNAAN MEDIA AUDIO VISUAL DALAM MENGATASI KESULITAN MEMBACA SISWA KELAS RENDAH DI SD MBS PRAMBANAN

The ability that must be possessed by the lower classes in Elementary School is the ability to read, but low grade students or novice readers usually have difficulty reading at low levels. To overcome this, it is necessary to have effective learning media in order to overcome reading difficulties in lower classes. This study aims to analyze the effectiveness of audio-visual learning media in overcoming the reading difficulties of low grade students at SD MBS Prambanan. The method used in this research is descriptive approach method, data obtained from research subjects are analyzed according to the statistical method used and interpreted by this type of qualitative research. Data collection was carried out by interviewing class II teachers at SD MBS Prambanan and distributing questionnaires to 15 low grade students. reading then analyzed using descriptive statistics with visual analysis techniques in the form of diagrams. The results showed that there was an increase in the level of reading difficulty after using audio visual learning media. This data can be strengthened by data from the results of the distribution of questionnaires that have been obtained. The data is in the form of a diagram which has a percentage of 90.9%, 100%, 90.9%, 100%, 100%, 81.8%, and 81.8% which, if averaged, is 92.2%. Based on this data, it can be concluded that the use of audio-visual learning media is quite effective in overcoming reading difficulties for low-grade students at SD MBS Prambanan.
VAE for NLP: novel architectures and possible applications

Natural Language Processing consist in the study of how to automatically process information conveyed in Natural Language, that is, human language.This thesis is interested in a subset of this domain called Text Generation which consist in the elaboration of computational system capable of generating text comprehensible by humans.More specifically, it is interest in explore a specific model named Variational Autoencoders, which is one of the most popular models in the academia in the time of elaboration of this work. In the context of the VAE, this thesis aims to accomplish two sets of goals.The first is: to improve the overall performance of the VAE in the text generation task, the understanding of the most new techniques and reflect upon how to evaluate Text Generation Models. This shall be done by combining recent advances in the VAE architectures and by proposing a new technique. The recent advances consist in performing Aggressive Training, using Length as a feature and adding a Bag of Word loss. The new technique consist in splitting the representation of the VAE in two disentangled vectors: one for content and other for grammar. The second set of goals is to explore the applications of the text generation system to other tasks, analyzing its performance and giving guidance to future work in the application of VAEs and Text Generation Systems. The applications in question are Information Retrieval and Text Autocomplete. The goal is not to make tailored system, but explored how a VAE could be used in such context.
Maze path planning of mobile robots by gradient map rendering and gradient follow

Path planning for a human being is very easy to reach a desired location in a room, by avoiding obstacles on the way, by generating a mental map and uses this map to find the optimal path. This is a difficult task in case of a robot. In order to make the robot adapt, the system is fed with different obstacle arrangement in the same room and allow the robot to finalise the optimal path avoiding the obstacles. To achieve, the gradient map rendering algorithm is proposed with successful simulation results in MATLAB. The new map produced has given a gradient again using the same algorithm. After the rendering process is completed, the robot climbs up or down the gradient using the maximum or minimum local gradient technique respectively, to find its way to the destination cell. Gradient surface plots are obtained for a variety of mazes to give a visualisation of how the gradient is being formed. Results are obtained after maze simulation successfully shows the most optimised path in any kind of maze.
Multi-resolution Steganalysis of JPEG Images Using the Contrast of DCT Coefficients

This paper proposes a novel JPEG steganalytic scheme, which combines the designing of feature called as the Contrast of Discrete Cosine Transform (DCT) coefficients, multi-resolution decomposition. Unlike the conventional steganalytic schemes, without using the co-occurrence to show directly the correlation between the DCT coefficients, the original JPEG image is decompressed into spatial domain and, applying the Fast Discrete Curvelet Transform (FDCT), the spatial version is resolved into several multi-resolution subimages. After transforming all the spatial subimages into JPEG image, the contrast of two DCT coefficients is turned into an angle and the l2 norm is used as the weight of the angle. Therefore, the new feature is seen as a union of the first-order statistics of weighted angle. On modern stegnographic algorithm JPEG Universal Wavelet Relative Distortion (J-UNIWARD), we demonstrate the proposed scheme achieves more accurate detection than Cartesian-calibrated feature (CFstar) and is superior to the Cartesian-calibrated JPEG Rich Model (CC-JRM) at lower embedding rate.
Blockene: A High-throughput Blockchain Over Mobile Devices

We introduce Blockene, a blockchain that reduces resource usage at member nodes by orders of magnitude, requiring only a smartphone to participate in block validation and consensus. Despite being lightweight, Blockene provides high throughput and scales to millions of participants. Blockene consumes negligible battery and data in smartphones, enabling millions of users to participate in the blockchain without incentives, to secure transactions with their collective honesty. Blockene achieves these properties with a novel split-trust design based on delegating storage and gossip to untrusted nodes. We demonstrate, with a prototype implementation, that Blockene provides a throughput of more than 1000 transactions per second, and can run with very low resource usage on smartphones, pointing to a new paradigm for building trustworthy, decentralized applications.
On Chinese Translation of English Proverbs—A Dynamic Equivalence Perspective

Mainly derived from daily life of common people, English proverbs, as a highly condensed encyclopedia of the English-speaking nations and their cultures, cover the widest possible fields of the society ranging from the universal deepest philosophic contemplation to the commonest daily activities. English proverb translation has always been heatedly discussed in language field, and many scholars have made great contribution to it. They put forward different translation methods from different views. The paper attempts to discuss the Chinese translation methods on the basis of the dynamic equivalence theory.
Quadratic Planning Method for Eliminating Driving Collision and Path Tortuosity

In the scene of intelligent warehousing and automatic production line, the automatic guidance vehicle (AGV) needs to work continuously among multi-objective points, but the existing path planning algorithm has the problems of driving collision and path tortuosity. Therefore, this paper proposes a quadratic planning method for eliminating driving collision and path tortuosity, which includes two parts: collision elimination and path winding elimination. Firstly, according to the characteristics of collision points on the path, a description model is established, and an algorithm for eliminating collision is given. Then, an algorithm for eliminating redundant tortuosity is developed based on collision elimination. Finally, the procedure of quadratic planning method for eliminating driving collision and path tortuosity is given. The simulation results show that the contact times between the path and the obstacles after the quadratic programming are 0, and the AGV can save 24.4% of driving time.
Concept of Digital Literation Based on Value of Local Wisdom Piil Pesenggiri in History Learning in the Industrial Revolution 4.0

Literacy is one of the abilities that are considered important in facing the 21st-century world. The distinctive character of the 21st-century world is the industrial revolution of 4.0. The impact of the industrial revolution 4.0 has been felt by anyone in every aspect of life, including aspects of education. The low condition of Indonesia's digital literacy capability must be overcome immediately. For this reason, this study aims to propose a thesis on the concept of digital literacy based on value of local wisdom piil pesenggiri in learning history in the era of the industrial revolution 4.0. Local wisdom piil pesenggiri is the behavior and outlook on life of Lampung people who are still held firm to this day. It is hoped that through this strategy the historical awareness of the students at Public High School 2 Kalianda in Lampung Province will increase amidst the current of Industrial Revolution 4.0. This study used qualitative research methods. Data collection was conducted in January and February 2020 with natural conditions, primary data sources and more data collection techniques in participant observation, in-depth interviews, and documentation. The results show that there must be a change in conventional history learning resources to a digital history book that can understand current students without losing their cultural identity.
Priberam at MESINESP Multi-label Classification of Medical Texts Task

Medical articles provide current state of the art treatments and diagnostics to many medical practitioners and professionals. Existing public databases such as MEDLINE contain over 27 million articles, making it difficult to extract relevant content without the use of efficient search engines. Information retrieval tools are crucial in order to navigate and provide meaningful recommendations for articles and treatments. Classifying these articles into broader medical topics can improve the retrieval of related articles []. The set of medical labels considered for the MESINESP task is on the order of several thousands of labels (DeCS codes), which falls under the extreme multi-label classification problem []. The heterogeneous and highly hierarchical structure of medical topics makes the task of manually classifying articles extremely laborious and costly. It is, therefore, crucial to automate the process of classification. Typical machine learning algorithms become computationally demanding with such a large number of labels and achieving better recall on such datasets becomes an unsolved problem.This work presents Priberam’s participation at the BioASQ task Mesinesp. We address the large multi-label classification problem through the use of four different models: a Support Vector Machine (SVM) [], a customised search engine (Priberam Search) [], a BERT based classifier [], and a SVM-rank ensemble [] of all the previous models. Results demonstrate that all three individual models perform well and the best performance is achieved by their ensemble, granting Priberam the 6-th place in the present challenge and making it the 2-nd best team.