Reviewerly/exHarmony huggingface dataset:
Speech Recognition Technology for OPAC Service: An Innovative Idea for Indian Libraries

The information and communication technology-driven environment compelled to software engineers and professionals to work harder to meet out the expectations of the people needs and requirements. The smartphone savvy generation is more acquainted with application based software systems along with standard and smart search platforms. They are shifting from text-based search to voice search. ‘OK Google’ and ‘Hey Alexa’ are prominent voice services brought by Google and Amazon to attract their customers towards their products and make their life easy in searching and retrieving information. We found it equally good for library services. The talking Web-OPAC could be emerged as one of the innovative ideas to facilitate search services in the libraries. We are trying to highlight some issues and concerns over talking Web-OPAC in libraries.
Effect of Video Pixel-Binning on Source Attribution of Mixed Media

Photo Response Non-Uniformity (PRNU) noise obtained from images or videos is used as a camera fingerprint to attribute visual objects captured by a camera. The PRNU-based source attribution method, however, fails when there is misalignment between the fingerprint and the query object. One example of such a misalignment, which has been overlooked in the field, is caused by the in-camera resizing technique that a video may have been subjected to. This paper investigates the attribution of visual media in the context of matching a video query object to an image fingerprint or vice versa. Specifically this paper focuses on improving camera attribution performance by taking into account the effects of binning, a commonly used in-camera resizing technique applied to video. We experimentally show that the True Positive Rate (TPR) obtained when binning is considered is approximately 3% higher.
MEDIATION IN THE CONTEXT OF MULTILINGUAL EDUCATION IN UKRAINE

The importance of mastering several foreign languages is becoming increasingly important throughout the world and in Ukraine in particular.Knowledge of several languages provides a great opportunity to obtain useful information, valuable experience, high-quality education, opens new perspectives, it is the key to success in the modern world.Multilingualism is becoming a requirement today, that is why the countries of the world are introducing gradually multilingual education, striving to meet the demand for knowledge of foreign languages.The first recommendations for learning two foreign languages are found in the recommendations of the European Commission «White Paper» -«Teaching and learning.On the way to a cognitive society» in 1995 [5].Later, in 2003, the «Common European Framework of Reference for Languages: Study, teaching, assessment» (CEFR) introduced the concept of «plurilingualismknowledge of a number of languages or the coexistence of different languages in a given society» and substantiated its importance [1].Currently, the issue of introducing plurilingualism in education in Ukraine is especially relevant, as from September 1, 2022, in accordance with the Laws of Ukraine «On education» and «On complete general secondary education» the new State Standard of basic secondary education is introduced, according to which students will have the opportunity to learn two foreign languages.Also, general secondary education institutions may offer students «teaching one or more subjects (integrated courses) alongside the official language English or another official language of the European Union» [4; 7].The State Standard also states that the methods and techniques of bilingual and multilingual education may be used in the educational process.Taking into account the changes in the Ukrainian education system, special attention should be paid to the additional volume «Common European Recommendations on Language Education: Study, teaching, assessment» (2020), which does not change the 2001 edition but offers new descriptors as a means to improve teaching quality.and second/foreign language learning, as
Svandiela @ HaSpeeDe: Detecting Hate Speech in Italian Twitter Data with BERT

English.We describe the creation of HurtLex, a multilingual lexicon of hate words.The starting point is the Italian hate lexicon developed by the linguist Tullio De Mauro, organized in 17 categories.It has been expanded through the link to available synset-based computational lexical resources such as Mul-tiWordNet and BabelNet, and evolved in a multi-lingual perspective by semiautomatic translation and expert annotation.A twofold evaluation of HurtLex as a resource for hate speech detection in social media is provided: a qualitative evaluation against an Italian annotated Twitter corpus of hate against immigrants, and an extrinsic evaluation in the context of the AMI@Ibereval2018 shared task, where the resource was exploited for extracting domain-specific lexicon-based features for the supervised classification of misogyny in English and Spanish tweets.
A Comparative Study Of The Economic Crime In Uzbekistan And India: A Critical Analysis

This article discusses a comparative study of the economic crime in Uzbekistan and India: a critical analysis.
Integration of Library Data on Reference Books: with Service Oriented Architecture Implementation methods and (ESB) Enterprise Service Bus

Libraries have an important role in mastering science and technology as well as a center for information activities. Currently, the library extends its services not only in hardcopy but also in softcopy and provides faster information retrieval capabilities. Service Oriented Architecture (SOA) provides better multi-platform integration through network infrastructure. This job is to implement SOA in a Library Information System based on Glassfish Enterprice Service Bus and MySQL database. The methods for implementing library application design using SOA and ESB are built using a business process approach with several stages (M. Weske, 2006). The application of the methodology to be implemented with SOA and ESB is built using a business process approach with the following stages: The first stage, map design for integration of library requirements, the second stage is service interface design, the third stage builds relationships between services combine services that have been previously created by interaction with other services. The fourth stage is determining the logic flow that will evaluate the service logic flow that has been created with existing business processes. The fifth stage builds scenarios for shared perceptions and refining existing processes. The results show that the design has faster search capabilities that match the needs of the library.
Experiential Meaning Breadth Variations of the English-Bahasa Indonesia Alice in Wonderland Movie Texts

Research on experiential meaning breadth of bilingual analysis is rarely performed. The research aims at describing (1) the experiential meaning breadth variations of Alice in Wonderland English- Bahasa Indonesia movie texts, (2) the contextual factors that motivate the occurrence of meaning and realization variations, and (3) the contextual effects of the meaning and realization variations in question on the context in reference to the target readers of the texts. The research used descriptive qualitative approach to make the interpretation and the research findings. The data were taken from Alice in Wonderland (2010) movie texts then measured and validated in terms of quantitative research then analyzed through several steps: classifying the data into realized and unrealized expressions, classifying the data into the categories or degrees of variations, classifying the higher degree of each clause compared, giving number of clauses and their process type, contrasting each analysis result, and drawing conclusions. Research results indicate that the most prominent degree of experiential meaning breadth variations falls into the â€œlowestâ€ category of variation with 57.54%. This means that the Target Text is closely related to the Source Text and/ or the translator of Target Text applied source- based translation as regards experiential meaning breadth complexity. It is also strengthened by the average degree in each of the analysis falling in â€œvery lowâ€ category. The contextual factors that motivate the occurrence of the variations consist of inter- textual and situational context (field, mode, and tenor). The contextual effects in reference to the target readers are related to two aspects; the readability and the purpose of creating the texts. The Target Text is readable for the target readers of the text, target readers feel entertained by interpreting the text. The purpose for creating the Target Texts is for education and gives effects for the target readers to enrich their vocabularies and improve their English skills.
Variable Length Memory Chains: Characterization of stationary probability measures

Variable Length Memory Chains (VLMC), which are generalizations of finite order Markov chains, are an essential tool to modelize random sequences in many domains, as well as an interesting object in contemporary probability theory. The question of existence of stationary probability measures leads us to introduce a key combinatorial structure for words produced by a VLMC: the Longest Internal Suffix. This notion allows us to state a necessary and sufficient condition for a VLMC to admit a unique invariant probability measure. This condition turns out to get a much simpler form for a subclass of VLMC: the stable VLMC. This natural subclass, unlike the general case, enjoys a renewal property. Namely, a stable VLMC induces a semi-Markov chain on an at most countable state space. Unfortunately, this discrete time renewal process does not contain the whole information of the VLMC, preventing the study of a stable VLMC to be reduced to the study of its induced semi-Markov chain. For a subclass of stable VLMC, the convergence in distribution of a VLMC towards its stationary probability measure is established. Finally, finite state space semi-Markov chains turn out to be very special stable VLMC, shedding some new light on their limit distributions.
Service User Inclusion in Social Work Education, a Factor Analysis

Based on the Principle Component Analysis extraction method using the Varimax with Kaiser Normalization rotation method, the Rotated Component Matrix gleans three extracted factors that were then examined for loading. Analysis finds Component 1 (C1) pertains to student development, Component 2 (C2) pertains to professional development and Component 3 (C3) pertains to service user compensation, with linear regression showing all three components as statistically significant, each with a significance of 0.000. C1, student development, has an unstandardized beta of 5.690 and a standardized beta of 0.783, C2, professional development has an unstandardized beta of 3.016 and standardized beta of 0.415 and C3, service user compensation has an unstandardized beta of 3.040 and standardized beta of 0.419.
Construction of Brand Identity through Language in the Video Advertisements of Pakistani Telecom Companies

This research explored the construction of brand identity in the video advertisements of Pakistani telecom companies. Brand identity is constructed mainly by showing competitor’s submissive and weaker image rather than by using creative and unique advertising techniques. Data for this research was collected from five advertisements of five telecom companies. Positioning theory was applied on these advertisements. The data showed that all cellular companies of Pakistan were using positioning techniques to make their advertisements and construct the language of their ads to communicate with the society at large. The cellular companies have engaged in such kind of social communication due to the competition in the market of cellular services. This type of positioning in the language of advertisements is helpful in the conflicting and competitive business environment and explicitly or implicitly promotes competition. The research found that the cellular companies are using second order acknowledgement status and putting competitors in the third order status in their advertisements. The study found that Ufone is the company using this language technique mostly in its advertisements.
Sentiment classification of review data using sentence significance score optimisation

A significant amount of work has been done in the field of sentiment analysis in textual data using the concepts and techniques of natural language processing (NLP). In this work, unlike the existing techniques, we present a novel method wherein we consider the significance of the sentences in formulating the opinion. Often in any review, the sentences in the review may correspond to different aspects which are often irrelevant in deciding whether the sentiment is positive or negative on a topic. Thus, we assign a sentence significance score to evaluate the overall sentiment of the review. We employ a clustering mechanism followed by the neural network approach to determine the optimal significance score for the review. The proposed supervised method shows a higher accuracy than the state-of-the-art techniques. We further determine the subjectivity of sentences and establish a relationship between subjectivity of sentences and the significance score. We experimentally show that the significance scores found in the proposed method correspond to identifying the subjective sentences and objective sentences in reviews. The sentences with low significance score corresponds to objective sentences and the sentences with high significance score corresponds to subjective sentences.
Learning Model-Blind Temporal Denoisers without Ground Truths

Denoisers trained with synthetic noises often fail to cope with the diversity of real noises, giving way to methods that can adapt to unknown noise without noise modeling or ground truth. Previous image-based method leads to noise overfitting if directly applied to temporal denoising, and has inadequate temporal information management especially in terms of occlusion and lighting variation. In this paper, we propose a general framework for temporal denoising that successfully addresses these challenges. A novel twin sampler assembles training data by decoupling inputs from targets without altering semantics, which not only solves the noise overfitting problem, but also generates better occlusion masks by checking optical flow consistency. Lighting variation is quantified based on the local similarity of aligned frames. Our method consistently outperforms the prior art by 0.6-3.2dB PSNR on multiple noises, datasets and network architectures. State-of-the-art results on reducing model-blind video noises are achieved.
Partial Feature Aggregation Network for Real-Time Object Counting

Object counting has become an important task in computer vision for its practical applications in surveillance system. Previous methods for object counting have achieved promising results in accuracy, but few researchers focus on the real-time performance of counting methods. In this paper, we propose an efficient and accurate light-weight network for object counting, called Partial Feature Aggregation Network (PFANet). In this novel method, a Partial Feature Aggregation (PFA) structure is designed to accelerate networks and improve the utilization of multi-scale features. Moreover, PFANet uses the dilated convolution to enlarge the receptive-filed of network. Experiments on two datasets indicate our network exceeds the existing real-time counting networks in both accuracy and efficiency.
Conceptual Framework for ICT Development and Foreign Direct Investment Inflows as Drivers for Sustainable Economic Growth: Evidence from China and Malaysia

Development of information and communication technology (ICT) plays a crucial role in catalysing economic growth.This paper proposed a conceptual framework for ICT development and foreign direct investment inflows as driver for economic growth in China and Malaysia.Although some studies have found evidence of the positive effect on economic growth of ICT development and FDI, others have revealed the opposite outcome.Policymakers are expected to implement specific policies that enhance the penetration of ICT in countries such as providing low pricing and improving ICT infrastructure.In addition, policy makers should develop policies to strengthen the macroeconomic position that leads to a stable financial sector and the use of foreign investment.
Mathematics Students’ Ability in Understanding Text

This study aims to obtain a description of the students’ ability in understanding text. To achieve the objective, the study selected 216 mathematics students in a proportionate stratified random sampling. The students were asked to answer questions from a text that was designed and validated by a linguist. The samples were asked to fill out a questionnaire. The results show that there was a relationship between the length of studying mathematics (semester level) and the student’s ability to understand the idea of a text, the ability to determine conclusions from the given text, and the student’s ability to determine the relationships of paragraphs. This study also found that factors such as Grade Point Average (GPA), reading habits, and reading preferences cannot be assumed to have correlations with students’ ability to understand texts.&#x0D; &#x0D; Received: 15 February 2021 / Accepted: 29 March 2021 / Published: 10 May 2021
On English Vocabulary Teaching under the Construction Mode of Mobile Learning Community

mobile learning community is a virtual learning community established in wireless environment, which can effectively guide and stimulate the role consciousness of learners in the community, and plays an important role in students' autonomous learning, collaborative learning and self-management. As a new learning mode, mobile learning community can make full use of mobile devices for knowledge construction, communication and cooperation. With the support of a variety of media technologies, the construction of mobile learning community constitutes a specific mode, which is widely used in education and teaching activities, especially in English vocabulary teaching. Based on this, this paper expounds the concept and characteristics of mobile learning community and its significance to English vocabulary teaching, and puts forward various strategies for reference.
Correction to “Nonlinear Regression via Deep Negative Correlation Learning”

Reports on changes to the author information presented in the above named paper.
Dynamic Obstacle Avoidance Based on A Dynamic Space-Time Grid Map for Mobile Robots

In this study, a dynamic space-time grid map is proposed to dynamic obstacles avoidance for the mobile robot in the navigation environment. In the constructed dynamic space-time grid map, the detected objects will be recognized as the static and the dynamic obstacles. The trajectory of the dynamic obstacles can be predicted in the dynamic spatio-temporal map, and then, the possible collision for the mobile robot can be prevented if there is any target dynamic obstacle that will cross the moving path of the robot. The experimental results demonstrate the feasible behavior of obstacle avoidance for the mobile robot.
Rule Injection-Based Generative Adversarial Imitation Learning for Knowledge Graph Reasoning

Knowledge graph reasoning is a crucial part of knowledge discovery and knowledge graph completion tasks. The solution based on generative adversarial imitation learning (GAIL) has made great progress in recent researches and solves the problem of relying heavily on the design of the reward function in reinforcement learning-based reasoning methods. However, only the semantic feature is considered in existing GAIL-based methods, which is not enough to assess the quality of reasoning paths. While logical rules contain rich factual logic that can be used for reasoning. Thus, we introduce the first-order predicate logic rule in our model called Rule Injection-based Generative Adversarial Path Reasoning. The key idea is to train the generator to learn reasoning strategies by imitating the demonstration from both semantic and rule levels. Particularly, we design a path discriminator and a logic rule discriminator to distinguish paths respectively from these two levels. Furthermore, both discriminator feedback to the generator a self-adaptively reward by assessing the quality of the generated reasoning path. Extensively experiments on two benchmarks show that our method improves the performance than the state-of-the-art baseline and some cases study also confirmed the explainability of our model.
Problem statement and presentation of results of scientific research in dissertation works in tech-nical sciences

Problem. When writing dissertations, applicants face a serious problem of correct presentation of the results. Consequently, the quality of dissertations decreases significantly, even if the level of their research and development is very high. Goal. The purpose of the article is to provide knowledge on the justification and formulation of the problem and the presentation of scientific information in dissertations, which are the key criteria in ensuring their quality. Methodology. Analytical methods of research of dissertations concerning their quality of presentation were used. Results. The paper presents the general requirements for the delivery of the problem and the presentation of research results in dissertations of the technical area. The methodical recommendations concerning the formation of the purpose were formalized, as well as the novelty of the work and conclusions. To facilitate the use of these recommendations, keywords, typical phrases, clarifying words and examples of wording are provided. The structure and interrelation of the main components of the problem statement and evaluation of research results are presented. Originality. Clear instructions on the choice of topic, description of the object and subject of research, and research technology are provided. Practical value. This work is intended not only for those who are working on a dissertation (master's degree, doctor of philosophy (PhD), doctoral), but also for those who prepare research reports and for the authors of scientific articles.Key words: scientific research, dissertation work, requirements, education, higher educational institution, applicant, quality of dissertations.
Adaptable Multi-Domain Language Model for Transformer ASR

We propose an adapter based multi-domain Transformer based language model (LM) for Transformer ASR. The model consists of a big size common LM and small size adapters. The model can perform multi-domain adaptation with only the small size adapters and its related layers. The proposed model can reuse the full fine-tuned LM which is fine-tuned using all layers of an original model. The proposed LM can be expanded to new domains by adding about 2% of parameters for a first domain and 13% parameters for after second domain. The proposed model is also effective in reducing the model maintenance cost because it is possible to omit the costly and time-consuming common LM pre-training process. Using proposed adapter based approach, we observed that a general LM with adapter can outperform a dedicated music domain LM in terms of word error rate (WER).