Reviewerly/exHarmony huggingface dataset:
Motion Representation Using Residual Frames with 3D CNN

Recently, 3D convolutional networks (3D ConvNets) yield good performance in action recognition. However, optical flow stream is still needed to ensure better performance, the cost of which is very high. In this paper, we propose a fast but effective way to extract motion features from videos utilizing residual frames as the input data in 3D ConvNets. By replacing traditional stacked RGB frames with residual ones, 35.6% and 26.6% points improvements over top-1 accuracy can be obtained on the UCF101 and HMDB51 datasets when ResNet-18 models are trained from scratch. And we achieved the state-of-the-art results in this training mode. Analysis shows that better motion features can be extracted using residual frames compared to RGB counterpart. By combining with a simple appearance path, our proposal can be even better than some methods using optical flow streams.
Competitiveness of the University as a Hybrid Structure in the Regional Educational Space

Introduction. Managing the competitiveness of higher education organizations has been considered as a means of improving the quality of education and a tool for developing the innovative component of the domestic economy. The purpose of this paper, based on the materials of the conducted study, is to identify the factors determining the competitive position of the regional university and the opportunities to increase its competitiveness. Materials and Methods. The study employed the methods of logical, systemic, economic and statistical analysis, as well as the methods of sociological survey, expert assessments, structural analysis and design. The research methodology included comparison using the available data as well as graphical data visualization displaying the most common trends and showing the patterns of competitiveness of regional universities. Results. The regional university has been considered as a hybrid structure including horizontal and vertical connections of independent elements and interdependent ones. The phenomena of interaction, partnership and continuity of the organization of the regional education system have been analyzed. The effectiveness of the partnership between universities and secondary schools within the framework of hybrid educational systems formed by universities has been substantiated. Based on the empirical study, two functional models of the regional university have been developed which include its significant relationships in the regional educational space. Discussion and Conclusion. The study has confirmed the hypothesis of the importance of integrating the university into the regional educational space. The development of the university as a hybrid educational structure, its partnership with other educational organizations strengthens its competitive position. The functional models of the regional university as a hybrid structure and the methods for assessing its competitiveness, proposed by the author, may be useful for heads of educational organizations and regional authorities.
Research on Tibetan Speech Recognition Speech Dictionary and Acoustic Model Algorithm

Abstract This paper mainly conducts related research on the algorithm of the Tibetan acoustic model. Firstly, a Tibetan Lhasa pronunciation dictionary is constructed based on words and monossssyllables, and then compared. The experimental results show that the phonetic dictionary constructed by words is superior to the phonetic dictionary constructed by monosyllables. At the same time, taking phonemes and single syllables as the modeling unit of the acoustic model, the modeling unit of the acoustic model was studied and a comparative experiment was carried out. Experimental results show that phonemes are better than single syllables as acoustic model modeling units.
Research on Motion Blur Image of Infrared Target Deblurring Based on Wavelet Transform

Abstract Aiming At Removing the Motion Blur to Restore Images, a deblurring Method of Infrared Image Based on Wavelet Transform is Proposed. Determining Whether There is Motion Blur by Using Wavelet Transform to Extract and Analyze the High Frequency Information of Level Subband; Blur Direction and Blur Length Are Calculated by Rotating the Image; the Image Deblurring and Recovery Are Completed by the Optimization Program of Wiener Filtering Algorithm. the Experiments Show That the Proposed Method Can Effectively Removes Motion Blur, and Provide Clear Infrared Images for the Next Image Processing, It Has the Characteristics of Strong Robustness, Good Real-Time Capability and Higher Application Value.
An Albanian Text-to-Speech System for the BabelDr Medical Speech Translator.

In this paper we present work on creating and evaluating a Text-to-Speech system for the Albanian language to be used in the BabelDr medical speech translation system. Its quality was assessed by twelve native speakers who provided feedback on 60 prompts generated by the synthesizer and on 60 real human recordings across three dimensions, namely comprehensibility, naturalness and likeability. The results suggest that the newly created voice can be incorporated in the content creation pipeline of the BabelDr platform.
Cancer Treatment Classification with Electronic Medical Health Records (Student Abstract)

We built a natural language processing (NLP) language model that can be used to extract cancer treatment information using structured and unstructured electronic medical records (EMR). Our work appears to be the first that combines EMR and NLP for treatment identification.
Single-Shot 3D Detection of Vehicles from Monocular RGB Images via Geometry Constrained Keypoints in Real-Time

In this paper we propose a novel 3D single-shot object detection method for detecting vehicles in monocular RGB images. Our approach lifts 2D detections to 3D space by predicting additional regression and classification parameters and hence keeping the runtime close to pure 2D object detection. The additional parameters are transformed to 3D bounding box keypoints within the network under geometric constraints. Our proposed method features a full 3D description including all three angles of rotation without supervision by any labeled ground truth data for the object's orientation, as it focuses on certain keypoints within the image plane. While our approach can be combined with any modern object detection framework with only little computational overhead, we exemplify the extension of SSD for the prediction of 3D bounding boxes. We test our approach on different datasets for autonomous driving and evaluate it using the challenging KITTI 3D Object Detection as well as the novel nuScenes Object Detection benchmarks. While we achieve competitive results on both benchmarks we outperform current state-of-the-art methods in terms of speed with more than 20 FPS for all tested datasets and image resolutions.
Research on a convolution operation method based on domain transformation in deep learning

Abstract In deep learning, convolution operation is an important part of convolutional neural network. Various transformations have been used to deal with convolution problems, but complex number operation and the inability to carry out convolution in the DCT domain have been introduced. In this paper, the relationship between DCT transform of output matrix and DCT transform of input matrix is found. At the same time, in view of the reality of partitioning operation in the case of large matrix, the method of overlapping of blocks is introduced. Finally, experiments on LeNet show that the proposed method can achieve the accuracy of the traditional method and can be used in practical applications.
Building Low-Resource NER Models Using Non-Speaker Annotation

In low-resource natural language processing (NLP), the key problems are a lack of target language training data, and a lack of native speakers to create it. Cross-lingual methods have had notable success in addressing these concerns, but in certain common circumstances, such as insufficient pre-training corpora or languages far from the source language, their performance suffers. In this work we propose a complementary approach to building low-resource Named Entity Recognition (NER) models using ``non-speaker'' (NS) annotations, provided by annotators with no prior experience in the target language. We recruit 30 participants in a carefully controlled annotation experiment with Indonesian, Russian, and Hindi. We show that use of NS annotators produces results that are consistently on par or better than cross-lingual methods built on modern contextual representations, and have the potential to outperform with additional effort. We conclude with observations of common annotation patterns and recommended implementation practices, and motivate how NS annotations can be used in addition to prior methods for improved performance. For more details, http://cogcomp.org/page/publication_view/941
Involving Users and Creating Symbols for Tangible Programming: a Case Study with TaPrEC

INTRODUCTION: Participatory Design is an approach that is characterized by the active participation of users as part of the design team, thus reflecting their perspectives and needs in the product design. BrainDraw is a participatory technique for use in the design phase of product creation. This article investigates the use of participatory practices with elementary school teachers, aiming at the redesign of the programming blocks of TaPrEC, a tangible programming environment for children. OBJECTIVE: This work aimed at the redesign of symbols for the repetition blocks of TaPrEC involving the main stakeholders. METHOD: A Case Study in an educational space that offers activities during out-of-school hours to children was carried out using the BrainDraw technique with a group of elementary school teachers to redesign the symbols of the repetition blocks of the TaPrEC. The experimentation and evaluation of the created symbols were carried out by the same teachers and a group of elementary school children. We also applied the Self-Assessment Manikin form to assess the participants' affective responses during participatory activities. RESULTS: The results of the workshops highlight that the symbols created by the teachers have been better accepted by teachers and children. This positive acceptance may result from the fact that the participatory solutions proposed by the teachers suggest associations with everyday elements such as traffic signs and the symbol of multiplication. CONCLUSION: Participatory Design is a process that involves researchers and end-users in creating products for their use. Using this approach, we studied different symbol proposals for representing and understanding the repetition blocks of TaPrEC, a tangible programming environment, to promote a solution that had the participation of stakeholders and reached a solution that made sense to them.
QUESTIONNAIRE SURVEY ON ACTUAL CONDITION OF INSPECTION OF TRANSPORT PIPES ATTACHED TO CONCRETE PUMPING VEHICLE WITH BOOM

In order to clarify the actual state of the inspection method of the transport pipes attached to the concrete pump with a boom, this study carried out a questionnaire survey for Japan concrete pumping association. The main points of the results are as follows. The inspection method differs depending on the type of steel pipe, and hoses are visually inspected. The inspection frequency is once a month for steel pipes and docking hoses, and every time before work for tip hoses. The records of inspection results and reports to general contractors are more for steel pipes than for hoses.
Analysis of landslide vulnerability in Sibolangit area using Geographic Information System (GIS)

Abstract Natural disasters are a natural phenomenon that can occur at any time causing material and immaterial losses. Sibolangit is one of the subdistricts in the Deli Serdang Regency with relief of sloping hills between 60° – 90° with high rainfall so that the Sibolangit subdistrict has the potential for landslides. Geographic Information System can connect spatial and non-spatial data so that maps and information analysis can be made in a digital form. This study aimed to determine the level of landslide vulnerability in Sibolangit subdistrict, where the data used include types of rocks, types of soil, slope, rainfall, and land use. The analysis used in the study was the Geographic Information System with Puslittanak Modelling 2004. The study results obtained four criteria for landslide vulnerability in Sibolangit subdistrict, namely low landslide-prone areas which were 7 villages (32.65 km 2 or 18.84%), moderate landslide-prone areas which were 13 villages (77.93 km 2 or 44.96%), high landslide-prone areas which were 8 villages (46.43 km 2 or 28.96%), and very high landslide-prone areas which were 2 villages (16.31 km 2 or 10.17 %).
A Study on the Interactive Design and Aesthetics of Website Interface Based on Augmented Reality

Abstract With the development of computer technology and the upgrading of human-computer interaction equipment, interactive media technology has been widely applied in daily life, among which augmented reality is the hot focus. In this paper, augmented reality, interactive interface and interactive design are overviewed to summarize the trend of the blending of the three and research and analysis on the aesthetics created is carried out.
Mapping quantum random walks onto a Markov chain by mapping a unitary transformation to a higher dimension of an irreducible matrix

Here, a new two-dimensional process, discrete in time and space, that yields the results of both a random walk and a quantum random walk, is introduced. This model describes the population distribution of four coin states |1&gt;,-|1&gt;, |0&gt; -|0&gt; in space without interference, instead of two coin states |1&gt;, |0&gt; .For the case of no boundary conditions, the model is similar to a Markov chain with a stochastic matrix, i.e., it conserves the population distribution of the four coin states, and by using a proper transformation, yield probability distributions of the two quantum states |1&gt;, |0&gt; in space, similar to a unitary operator. Numerical results for a quantum random walk on infinite and finite lines are introduced.
Comparison of Rice Price Forecasting Using the ARIMA Method on Amazon Forecast and Sagemaker

Rice is one of the main commodities of trade in Indonesia. PT Food Station as the management company of Cipinang Rice Main Market every day publishes data on price, type of rice and the amount of rice that enters and exits Jakarta area. This study aims to forecast rice prices in the Jakarta area using data held by PT FoodStation during the 2016-2018 data period. Rice price prediction is carried out for the next 30 days using the Auto Regressive Integrated Moving Average (ARIMA) method on the Amazon Forecast and Amazon Sagemaker platforms. The ARIMA model is a form of regression analysis that measures the strength of one dependent variable that is relatively influential on other change variables. The ARIMA model is a special type of regression model in which the dependent variable is considered stationary and the independent variable is the lag or previous value of the dependent variable itself and the error lag. ARIMA is a combination of auto-regressive and moving average processes. The final result obtained in this experiment is that the ARIMA model on Amazon Sagemaker cloud computing is superior when compared to Amazon Forecast. From the experimental results obtained the results of Amazon Sagemaker RMSE (313.379941) are smaller than Amazon Forecast (322.4118029). So it can be concluded that the ARIMA model run at Amazon Sagemaker is more accurate than Amazon Forecast for forecasting the price of rice for 30 days at the Cipinang Rice Main Market
Metacognitive Competence as a Factor of Self-Regulation of Students' Educational Activity

The article is devoted to the problem of metacognitive competence formation and self-regulation. The aim of the work is to identify the features of self-regulation of educational activity in metacognitively competent students. The concepts of “metacognitive competence”, “metacognitive knowledge”, “metacognitive regulation”, and “self-regulation” are clarified in the article. Methods of research. The study was conducted at the Institute of Pedagogy and Psychology of FSBEI of HE “Petrozavodsk State University” with freshmen and second year students, studying in the program 44.03.02 “Psychological and pedagogical education”. Methods of studying metacognitive competence and self-regulation were used to test the hypothesis; the data obtained were processed according to the F-test. Analysis of the results of the research showed that metacognitive competent students have a high level of development of the self-regulation system and regulatory properties of personality. The author outlines that among the stylistic features of self-regulation of metacognitive competent students are high level of independence and flexibility, the predominance of orientation to achieve success, activity in setting goals, etc. It is concluded that the results obtained can be used to determine the directions for further study of the relationship between metaprocesses and self-regulation, and the development of programs for the development of self-regulation of students' educational activities.
A Facial Approach for Detection of Irregularly Entangled Copper Wire during Twining by Machine Vision

Abstract In this study, a computer vision-based inspection system is designed to detect the presence of irregularly entangled copper wire during twining for industrial processing. With the assistance of high speed industrial camera, the images of copper wire during twining would be recorded in real-time. All lines in the images are detected by Hough transform. According to the calculated slope of all lines detected in the images, a threshold is artificially set to distinguish between the regularly coiled and irregularly entangled copper wire. This defect detection system could greatly improve the efficiency of industrial production.
Research on Virtual Roaming Technology of Urban Scene Based on Multi-mode Human-Computer Interaction

Abstract Virtual reality technology refers to the use of computer multi-body technology to simulate the environment from many aspects, such as human smell, vision, touch and hearing, so that people can have a sense of being in it in the virtual environment constructed by computer, and can obtain all kinds of information with the help of human-computer interaction.By combining virtual reality with somatosensory interaction using gesture recognition, speech recognition and other modes, this paper develops an immersive urban scene roaming system based on Unity3D multi-mode human-computer interaction, which gives users a near-real scene roaming and somatosensory interaction experience.
Solvability of a Bounded Parametric System in Max-Łukasiewicz Algebra

The max-Łukasiewicz algebra describes fuzzy systems working in discrete time which are based on two binary operations: the maximum and the Łukasiewicz triangular norm. The behavior of such a system in time depends on the solvability of the corresponding bounded parametric max-linear system. The aim of this study is to describe an algorithm recognizing for which values of the parameter the given bounded parametric max-linear system has a solution—represented by an appropriate state of the fuzzy system in consideration. Necessary and sufficient conditions of the solvability have been found and a polynomial recognition algorithm has been described. The correctness of the algorithm has been verified. The presented polynomial algorithm consists of three parts depending on the entries of the transition matrix and the required state vector. The results are illustrated by numerical examples. The presented results can be also applied in the study of the max-Łukasiewicz systems with interval coefficients. Furthermore, Łukasiewicz arithmetical conjunction can be used in various types of models, for example, in cash-flow system.
Social Recommendation in Heterogeneous Evolving Relation Network

The appearance and growth of social networking brings an exponential growth of information. One of the main solutions proposed for this information overload problem are recommender systems, which provide personalized results. Most existing social recommendation approaches consider relation information to improve recommendation performance in the static context. However, relations are likely to evolve over time in the dynamic network. Therefore, temporal information is an essential ingredient to making social recommendation. In this paper, we propose a novel social recommendation model based on evolving relation network, named SoERec. The learned evolving relation network is a heterogeneous information network, where the strength of relation between users is a sum of the influence of all historical events. We incorporate temporally evolving relations into the recommendation algorithm. We empirically evaluate the proposed method on two widely-used datasets. Experimental results show that the proposed model outperforms the state-of-the-art social recommendation methods.
Modelling Contextual Data for Smart Environments. Case Study of a System to Support Mountain Rescuers

Context-aware pervasive systems are complex, due to the need to gather detailed environmental information and to perform a variety of context reasoning processes in order to adapt behaviours accordingly. These operations are merged seamlessly. We show the feasibility and vitality of a fully designed system for mountain rescue operations, with various aspects of the contextual processing in middleware, as well as analyse its context life cycle. The system is verified through intensive experiments with a rich set of categorised context data. The contextual processing is shown in different weather scenarios. The service is geared towards software development, converging IoT (Internet of Things) and cloud computing with specific reference to smart application scenarios.
Spoken English Repetitive Correction Retrieval Based on Syllable Unit WFST Web Search Filter

Abstract Aiming at the difficulty in computer-assisted language teaching of repeated correction and error detection in spoken English, a fault-tolerant alignment and search filtering algorithm based on the syllable unit WFST (weighted finitestate transformer) network is proposed. This algorithm uses the script corresponding to the adjacent matching words in the recognition results to establish the above grammatical network for fault-tolerant alignment under secondary recognition. The candidate modified parts and replacement parts are used as the query and template for search filtering. In the end, the result of repeated correction error detection is determined by the confidence of the search filtering algorithm. To this end, the k-difference algorithm based on sequential assumptions and the n-gram algorithm based on random assumptions are proposed. Experiments show that the multi-n-gram hybrid search filtering with syllables as the modeling unit achieves relatively optimal results without using quadratic fault-tolerant alignment; when using quadratic fault-tolerant alignment, F-measure can obtain 3 to 4 Further increase in percentage.