Reviewerly/exHarmony huggingface dataset:
A Natural Language Interface for Querying Linked Data

The thesis introduces a proof of concept idea that could spark great interest from many industries. The idea consists of a remote Natural Language Interface (NLI), for querying Knowledge Bases (KBs ...
Some Theory for Texture Segmentation

In the context of texture segmentation in images, and provide some theoretical guarantees for the prototypical approach which consists in extracting local features in the neighborhood of a pixel and then applying a clustering algorithm for grouping the pixel according to these features. On the one hand, for stationary textures, which we model with Gaussian Markov random fields, we construct the feature for each pixel by calculating the sample covariance matrix of its neighborhood patch and cluster the pixels by an application of k-means to group the covariance matrices. We show that this generic method is consistent. On the other hand, for non-stationary fields, we include the location of the pixel as an additional feature and apply single-linkage clustering. We again show that this generic and emblematic method is consistent. We complement our theory with some numerical experiments performed on both generated and natural textures.
Pow-Wow: A Dataset and Study on Collaborative Communication in Pommerman

In multi-agent learning, agents must coordinate with each other in order to succeed. For humans, this coordination is typically accomplished through the use of language. In this work we perform a controlled study of human language use in a competitive team-based game, and search for useful lessons for structuring communication protocol between autonomous agents. We construct Pow-Wow, a new dataset for studying situated goal-directed human communication. Using the Pommerman game environment, we enlisted teams of humans to play against teams of AI agents, recording their observations, actions, and communications. We analyze the types of communications which result in effective game strategies, annotate them accordingly, and present corpus-level statistical analysis of how trends in communications affect game outcomes. Based on this analysis, we design a communication policy for learning agents, and show that agents which utilize communication achieve higher win-rates against baseline systems than those which do not.
Commento alla traduzione. Traduttori non sempre traditori

Starting from a statement of Pirandello concerning the art of translation, the essay aims to reflect on the concept of translator and on the frequent false attribution of traitor. In addition to this, the essay focuses on the Italian translation of the literary work of Adalberto Alves A presença dos dias / La presenza dei giorni.
Aplikasi Untuk Al-Qur’an Audio Juz 30 Bagi Penyandang Tunanetra Menggunakan Voice Recognition Berbasis Android

People with visual impairment are one of the community groups that need special attention from the surrounding area, because this group experiences difficulties in social life. Not only that, blind people also experience difficulties in their daily lives due to their disabilities, such as reading and memorizing the Qur'an juz 30. The current media does not make it easy for blind people to be able to choose surahs and verses of the Qur'an ' juz 30 that you want to memorize randomly. Application for Al-Qur'an Audio Juz 30 for people with visual impairment using Android-based Voice Recognition is a solution to overcome the above problems. Application for Al-Qur'an Audio Juz 30 for people with visual impairments using Android-based Voice Recognition equipped with a speech recognition system or Google Speech API developed by Google to recognize various kinds of human voices as input commands to the application and use the Arduino UNO module as the main controller in a tool for processing data on an SD card that can be read by the DFPlayer module so that it can recite the surah and verses contained in Al-Qur'an Juz 30. The voice command mode of calling the Qur'an juz 30 can be used in two modes, namely the selection mode per surah and selection mode per verse. Besides this application has a voice notification feature as a reminder for blind people to memorize the Qur'an juz 30 every day. Test results on these applications and tools show that applications and tools designed to function properly
Mechanical equipment fault detection applying data mining technology

Abstract Mechanical equipment fault detection in manufacturing enterprises has always been an important link in the manufacturing process. Along with the computer technology, artificial intelligence technology and various sensors are widely used in manufacturing industry, The amount of data produced by manufacturing machinery and equipment at all stages of the production process is also increasing rapidly, It is particularly important to analyze the data generated by these devices for fault detection and even prediction, Data mining technology provides advanced analysis methods for this purpose. This paper first introduces the basic concepts of Data Mining, Data Mining process and the key technology of Data Mining, and then focuses on the application of Data Mining in machinery fault detection, finally through the analysis of Data Mining in the field of top class meeting KDD2019, explored the could be applied to machinery fault detection of new technology, forecast the Data Mining technology in the fault detection of possible development trend.
Integration of mathematics and informatics by means of geometry in primary school

The article outlines the relevance of using geometric material as a means of integrating elementary school mathematics and computer science education. Peculiarities of teaching junior schoolchildren elements of geometry are considered. The analysis of mathematics and informatics programs in terms of geometric material content in the elementary mathematics course is carried out. The criteria for selecting the content of geometric material aimed at integrating elementary mathematics and computer science selected in the research process have been illustrated. A set of geometric tasks is presented, aimed at optimising the learning process and improving the quality of knowledge in the subject area of „Mathematics and Computer Science” when integrating primary school mathematics and computer science teaching. The study was based on an analysis of the psychological, pedagogical and methodological literature on the problem under study. The possibility of integrating mathematics and informatics by means of geometry in primary schools to make inter-subject connections was theoretically justified and practically confirmed. The integration of mathematics and computer science contributes to the implementation of inter-subject connections, since the student simultaneously uses knowledge from the field of mathematics, computer science, and computer knowledge. This leads to the formation of a scientific worldview.
MOTIVASI PEMANFAATAN E-LEARNING PADA GURU DI SEKOLAH KABUPATEN GOWA

The objectives to be achieved in this Partnership Program are: (1) Teachers and students use the internet as a public communication tool that optimally supports the learning process. (2) Using moodle learning as an interactive forum for students (3) Teachers have knowledge of how to build moodle-based e-learning classes. The expected outputs from community services are: (1) 20 Teachers understand the basic concepts of e-learning so that they can go further in applying online-based computer technology. (2) 20 teachers are motivated to use e-learning as a medium for the learning process. (3) 20 Teachers can apply e-learning so that students can be active in elaborating information obtained creatively and skillfully without being limited by time and space. The results in implementing community services consist of: (1) Participants can design e-learning classes using moodle. (2) Participants are able to manage classes in the learning process using E-learning. (3) Participants already have insight into E-learning. The conclusions of this PKM activity are: (1) Participants can design e-learning classes using moodle. (2) Participants have been able to manage classes in the learning process using E-learning. (3) the results of the study are based on the results of the distributed motivation questionnaire analysis, based on the results of the participant motivation questionnaire in SMP Negeri 1 Bontonompo 1, the success rate with a high category of 10 or 100%. Whereas Based on the results of the participant's motivation questionnaire in SMP Handayani, the success rate with a high category was 9 or 90%. While the success rate is in the medium category of 1 or 10%. Therefore the suggestion from this activity is that this activity should continue to be developed and applied widely among teachers because it can help increase motivation, effectiveness and efficient learning.
Multichannel Saliency Detection Based on Visual Bionics

Inspired by the visual properties of the human eyes, the depth information of visual attention is integrated into the saliency detection to effectively solve problems such as low accuracy and poor stability under similar or complex background interference. Firstly, the improved SLIC algorithm was used to segment and cluster the RGBD image. Secondly, the depth saliency of the image region was obtained according to the anisotropic center-surround difference method. Then, the global feature saliency of RGB image was calculated according to the colour perception rule of human vision. The obtained multichannel saliency maps were weighted and fused based on information entropy to highlighting the target area and get the final detection results. The proposed method works within a complexity of O(N), and the experimental results show that our algorithm based on visual bionics effectively suppress the interference of similar or complex background and has high accuracy and stability.
Extending the Classifier Algorithms in Machine Learning to Improve the Performance in Spoken Language Understanding Systems Under Deficient Training Data

One of the open domain challenges for Spoken Dialogue System (SDS) is to maintain a natural conversation for rarely visited domain i.e. domain with fewer data. Spoken Language Understanding (SLU) is a component of SDS that converts user utterance into a semantic form that a computer can understand. If we scale SDS open domain challenge toSLU then it should be able to convert user utterance to a semantic form even if less data is available for the rarest visited domain.The SLU reported in literature incorporate classifiers for the task of identifying the domain of user utterance, understanding the intent of the user, and filling slots-value pair.Thus, to address open domain challenges, classifiers in SLU must be robust to scarce training data.This paper presents investigations to improve the performance of SLU to convert user utterance into semantic form even if less training data is available.Eleven classification algorithms from machine learning have experimented under deficient data.The evaluation matrices used are accuracy, f-score, and inter crossentropy.Comprehensive experimentation is carried out on the two publicly available datasets DSTC2 and DSTC3 were carried out.The accuracy for Support Vector Machine (SVM) , Stochastic Gradient Descent (SGD) and Decision tree are 0.940, 0.960 , 0.955 for DSTC2 and 0.916, 0.900, 0.901 for DSTC3 database respectively.The F-score for SVM, SGD and Decision tree are 0.855, 0.868, 0.849 for DSTC2 dataset and 0.725, 0.715, 0.700 for DSTC3 database, respectively.The ICE for SVM and SGD are 1.191,1.100for DSTC2 dataset and 3.180,2.999for DSTC3 database, respectively.The performance of SLU based on SVM and SGD was found to be the best among all.The worst performance in terms of all three evaluation metrics was displayed by SLU incorporating Automatic Relevance Determination (ARD) and Relevance Vector Machine (RVC) classifier.
Monadification of attribute grammars

We describe a monadification process for attribute grammars for more concisely written attribute equations, closer to the style of inference rules used in traditional typing and evaluation specifications. Inference rules specifying, for example, a typing relation typically consider only typable expressions, whereas well-defined attribute grammars explicitly determine attribute values for any term, including untypable ones. The monadification approach lets one represent, for example, types as monadic optional/maybe values, but write non-monadic equations over the value inside the monad that only specify the rules for a correct typing, leading to more concise specifications. The missing failure cases are handled by a rewriting that inserts monadic return, bind, and failure operations to produce a well-defined attribute grammar that handles untypable trees. Thus, one can think in terms of a type T and not the actual monadic type M(T). To formalize this notion, typing and evaluation relations are given for the original and rewritten equations. The rewriting is total, preserves types, and a correctness property relating values of original and rewritten equations is given. A prototype implementation illustrates the benefits with examples such as typing of the simply-typed lambda calculus with Booleans, evaluation of the same, and type inference in Caml Light.
Correction to: Mechanism to capture learner’s interaction in VR-based learning environment: design and application

An amendment to this paper has been published and can be accessed via the original article.
Research on anti plagiarism technology for manuscript washing and false original

With the rapid development of the digital economy, traffic has become the key to the profitability of self-media, and some self-media use script-washing software to generate pseudo-original content in batches to seek improper benefits, which has seriously damaged the content creation intellectual property ecology. Aiming at the problem that it is difficult to detect pseudo-original manuscripts, this article discusses from a technical level, proposes an anti-plagiarism technology based on the fusion of semantic similarity and emotional tendency, uses topic mining technology to obtain text topic distribution, calculate topic similarity, and uses text representation technology Calculate the semantic similarity of the text, use the sentiment analysis technology to calculate the difference in the emotional tendency of the text, and merge the topic similarity, semantic similarity and emotional tendency to detect plagiarism. The experiment was conducted by collecting data on a public platform. The results show that the accuracy of this method to judge plagiarism is 91.9%, which has certain practical significance in the technical practice of anti-plagiarism.
Multiple Subspace Model and Image-Inpainting Algorithm Based on Multiple Matrix Rank Minimization

This paper proposes an image inpainting algorithm based on multiple linear models and matrix rank minimization. Several inpainting algorithms have been previously proposed based on the assumption that an image can be modeled using autoregressive (AR) models. However, these algorithms perform poorly when applied to natural photographs because they assume that an image is modeled by a position-invariant linear model with a fixed model order. In order to improve inpainting quality, this work introduces a multiple AR model and proposes an image inpainting algorithm based on multiple matrix rank minimization with sparse regularization. In doing so, a practical algorithm is provided based on the iterative partial matrix shrinkage algorithm, with numerical examples showing the effectiveness of the proposed algorithm.
An Approach to Hide an Audio File in Image Using LSB Technique

Recently, the world is interested in moving data between various devices. When The data transfer over the internet, maybe it attacks and reads or modifies on containing it. So, Data transmission must be encrypted before sending it to read and interpret by the intended receiver. Thus, information security is more critical than it used to be. This paper reflects the implementation of the two Least Significant Bit (LSB) techniques is named sequential LSB and sorted LSB. It is done by embedding a secret audio file into a cover file of the image using the LSB techniques with an approach to choose the hiding index. The work proposed uses the conventional approach to the LBS techniques under the name sequential LSB as the basic steganography model to compare my algorithm which called sorted LSB. Based on results, the sorted LSB produces is the same sequential LSB in which the stego image is not recognized by human eyes, but the security more complex than the LSB sequential.
Scientific Potential Of Teachers Of Secondary Vocational Education In Their Professional Communication

The contemporary stage of development of secondary vocational education featured an increasing demand for training specialists in this field, with a focus on their professional development, the use of their scientific potential, in particular in their professional activities, including in practical communication in teaching. In solving the problem of training teachers of secondary vocational education, the authors proceed from the competence approach and the need to develop research skills as universal and promising competencies. The level of development of these skills can be used to assess the scientific potential of workers, preparedness to change, ability to quickly and adequately respond to external situations, see and identify problems in professional activities and find ways to solve them, evaluate the results of their work, observe and analyze educational phenomena and facts, and choose the most effective ways to achieve teaching objectives. The authors conducted a comparative review of the experience of training specialists of secondary vocational education for innovative activities in teaching future students, for active use of the scientific potential of teachers in the training process, and for increase of their professional level in the system of non-formal and informal education in different countries (Russia, UK, USA, Canada, Australia, New Zealand). It allows to conclude that professional communication based on dialogue and professionals' need for interaction, mutual help and mutual enrichment is among the most effective forms of pedagogical support of development of the scientific potential of vocational education workers for successful use of their promising research competences in their activities.
A valuable deep dive into unpublished works

As its title suggests, this book is about unpublished works in the realm of common-law copyright. Its aim is to consider whether the often stouter and longer protection enjoyed by unpublished works is justified; it looks at that question through a variety of prisms, including historical, normative and legal. Its specific geographical focus is on unpublished works in the UK but it also casts a net to other common-law jurisdictions. Dr Masiyakurima, in my view, does a dexterous analytical job with his topic which, at first blush, seemed rather narrow to me but, after reading his treatment, clearly touches on an array of important themes in copyright, including, of course, the real meaning of ‘publication’ in our current era, but also pulling in such difficult issues as orphan works. It also raises important questions in legal spaces other than copyright, such as privacy law, and the author’s discursive style permits...
Loss Function Considering Multiple Attributes of a Temporal Sequence for Feed-Forward Neural Networks

Deep neural network (DNN)-based speech synthesis became popular in recent years and is expected to soon be widely used in embedded devices and environments with limited computing resources. The key intention of these systems in poor computing environments is to reduce the computational cost of generating speech parameter sequences while maintaining voice quality. However, reducing computational costs is challenging for two primary conventional DNN-based methods used for modeling speech parameter sequences. In feed-forward neural networks (FFNNs) with maximum likelihood parameter generation (MLPG), the MLPG reconstructs the temporal structure of the speech parameter sequences ignored by FFNNs but requires additional computational cost according to the sequence length. In recurrent neural networks, the recursive structure allows for the generation of speech parameter sequences while considering temporal structures without the MLPG, but increases the computational cost compared to FFNNs. We propose a new approach for DNNs to acquire parameters captured from the temporal structure by backpropagating the errors of multiple attributes of the temporal sequence via the loss function. This method enables FFNNs to generate speech parameter sequences by considering their temporal structure without the MLPG. We generated the fundamental frequency sequence and the mel-cepstrum sequence with our proposed method and conventional methods, and then synthesized and subjectively evaluated the speeches from these sequences. The proposed method enables even FFNNs that work on a frame-by-frame basis to generate speech parameter sequences by considering the temporal structure and to generate sequences perceptually superior to those from the conventional methods.
OPPORTUNITIES AND RESTRICTIONS OF SOCIO-PEDAGOGICAL ACTIVITY IN THE COUNTRYSIDE

The relevance of the research materials presented in the article is determined by the need to organize high-quality socio-pedagogical activities to form and develop students’ social competence in rural society. This type of activity in rural school as one of the main institutions of students’ socialization involves the creation of pedagogical conditions that contribute to the social adaptation, social integration and social autonomy of young people. The article considers possibilities and restrictions of sociopedagogical activity taking into account the peculiarities of students’ socialization in rural society. The results of aerobatic socio-pedagogical study of potentials and limitations of socio-pedagogical activity in rural areas are presented, which was carried out in 2020 in three educational organizations of Nekrasovsky and Yaroslavsky districts of the Yaroslavl region,. The study involved 398 respondents, including 140 two rural schools, 217 parents of students of two rural schools and pupils of one rural preschool educational organization, 41 teachers and seven leadership personnel of these educational organizations. The results of the work of four focus groups of the problem group «Modern problems of rural schoolchildren’s socialization in modern conditions and ways to solve them» of the interregional laboratory «Pedagogy in rural school» of the Scientific Center of the Russian Academy of Education at Yaroslavl State Pedagogical University named after K. D. Ushinsky are presented. The interest of all categories of respondents to the problem of the development of integrated social and pedagogical activities in the countryside and the interest of students’ parents, teachers and leaders in the implementation of interaction with organizations and institutions of rural society was revealed. The study showed the «reference points for the development» of sociopedagogical activities in the countryside, updated the problem of the need for systematic coordinated socio-pedagogical activities in rural society, studying its capabilities and limitations, improving the forms and methods of organizing this type of activity (sociopedagogical complexes, coordination councils, headquarters, socio-pedagogical monitoring, etc.), as well as the need to prepare specialists for high-quality support of socio-pedagogical activities in rural society.