Reviewerly/exHarmony huggingface dataset:
Development Of MAC-Based Smarthome Access Rights Authentication (Media Access Control) Address

This study seeks to understand the purpose of using the ESP32 module as a control center in the electronic equipment control system on Smarthome and to ascertain the outcomes of the application design by utilizing Mac Address as Authentication Access rights to control electronic equipment. A methods for gathering data utilized literary analysis. In this study, access rights authentication was conducted on the software, and two hardware test, manual mode testing and automatic mode testing, were applied. Software testing was done by registering the user and Mac address of the device by the admin, then the data is stored in the firebase. In software testing, three smartphones were used whose MAC addresses were registered by the administrator. Each registered device was tried to log in ten times, and the success rate was 100%. In contrast, three devices' MAC addresses were not registered, and they were unable to log in ten times, with a 100% failure rate. Hardware testing is carried out by manual testing mode, in manual model testing the input from the controller application is in accordance with the prototype output, while automatic mode testing is carried out based on conditions at room temperature, namely in room conditions &gt; 30 then the fan turns on automatically, the temperature room &lt;30 the lights turn on automatically, so the automatic mode test has been matched to the output of the prototype. Based on the results of the study, a control system was produced with a MAC Address as an id and a user to login to an application called “Controller” which can be used to control electronic equipment in the house.
The Law of Sedition: Implications for the Practice of Journalism in Nigeria

This study was conducted to examine the law of sedition and its implication for the practice of journalism in Nigeria. The study is premised on the tenets of the social responsibility theory while the secondary sources of data relevant to the discourse were relied upon for analysis. It was revealed that the freedom of expression is a fundamental human right enjoyed and protected by law in civilized and democratic societies, however this right is not absolute anywhere in the world as the fundamental human rights are restricted by the law of sedition which restricts journalists from publishing or undertaking actions that bring into hatred, ridicule or contempt to the government in power, or incite or provoke the citizens to rise against or seek to remove the government in power. It was also revealed that sedition is a punishable offense under the Nigeria law as journalists in Nigeria have been charged for various seditious offenses in the past. The study equally revealed that journalists charged for sedition have the right of defense through lawful excuse, prove that words used were not seditious as well as claim ignorance of the act. The study concludes that the law of sedition is a compromise to freedom of expression because constructive criticism is an indispensable tool especially in a democratic society. However, the law of sedition law has been used by the government as a tool to regulate citizens' opinions and indiscriminately wield power. The government uses the law to suppress the protesting views of the public and journalists alike. The study recommends that journalists should operate within the ambit of freedom of expression guaranteed by the fundamental human rights for a better society, journalists should observe the ethics of the profession as safety measures against being accused and charged for sedition and journalists should be conversant with laws that tend to inhibit their practice.
Artificial Intelligence in Acoustics of Library Functioning in Ukraine

The purpose of the study is to outline achievements, prospects for transformation and identify obstacles to the implementation of systems, elements of artificial intelligence (AI) and the algorithm for overcoming them in national library and information institutions. Research methodology: the principles of systematicity, generalisation, objectivity, and general methods of scientific research – analysis, synthesis, comparison, analytical monitoring of AI elements in libraries of the country – are applied. The scientific novelty of the work is to highlight, with an emphasis on key aspects, the obstacles to the addition of AI intellectual resources to the work of libraries in the realities of today. Conclusions. The article reflects the developments, main areas of use and reasons for limiting the intensive integration of AI systems and elements into library practice. Features of the application of AI components, practical potential of ultra-high-frequency technologies in national libraries. The above-mentioned practice in libraries is especially relevant during martial law and the times of profound changes. It will facilitate public access to information and self-education; access to advanced technological developments; allow further steps in the formation of a new digitalisation focus of libraries and modification of library activities; thoroughly form an approach to the vectors of the industry's influence on society; innovations in the model of library-user relations, taking into account civilisation challenges. The studied trends in the addition of intelligent systems and elements of artificial intelligence will contribute to the voluntarisation of technological proposals in library and information institutions. As a result of the study, the issue of compatibility of adding intellectual components to the work of the library industry with the realities of the country and the corresponding algorithm of actions for the long-term is considered.&#x0D; Key words: library, systems and elements of artificial intelligence, innovative technologies, transformation of intellectual resources, challenges of AI implementation in library practice.
Utilizing Multimedia Technology in Digital Learning Content Development

The development of information and communication technology is growing rapidly. Many positive impacts are obtained, especially in the field of education. Teachers and students find it easy to do the learning process in the classroom. If they use technology in digital learning. Access to new knowledge, information from various parts of the world, learning methods that suit student needs, and others can be reached with just one tap of the finger. It is so easy to compete in this globalization era. One of them is by utilizing multimedia technology in the development of digital learning content, so that if utilized optimally, it will get great benefits. The results of content creation are more interesting and favored by the audience. The purpose of this research is to facilitate the development of digital learning content by utilizing multimedia technology as much as possible, so that learning objectives for students can be achieved properly and optimally. For example, by creating educational content about one of the learning materials on YouTube which contains direct explanation by the teacher in an interesting place. And the content is supported by features that are interesting and not boring. The method used in this research is quantitative method. Data obtained through distributing questionnaires to students. The questionnaire was created by utilizing Google form. The results of this study explain that utilizing multimedia technology properly in creating digital learning content will provide benefits for teachers and students in the learning process. The conclusion of this study is that the utilization of multimedia technology has a positive influence and provides space for teachers to provide digital learning content easily and creatively. The limitation of this study is that researchers only conducted research at the school or madrasa level which in fact requires the use of multimedia technology in learning.
Prerequisites and Methodological Principles of Digital Library Creation in the State Scientific and Technical Library of Ukraine

The purpose of the article is to substantiate the relevance, prerequisites and methodological foundations for creating an electronic library of scientific and technical information in the State Scientific and Technical Library of Ukraine (SSTL). The research methodology is based on a combination of general scientific methods of analysis, synthesis and forecasting, as well as on the use of systemic, informational, structural and functional, comparative, and terminological approaches. The scientific novelty of the study lies in the further development of views on the creation and functioning of an electronic scientific and technical library in the context of the implementation of the principles of open science and open access to scientific and informational resources. Conclusions. The development and implementation of the project on the creation of an electronic scientific and technical information library in the SSTL of Ukraine will contribute to solving a number of important issues, in particular: optimization and expansion of remote access of domestic and foreign users to the documents of the library collection, implementation of virtual reconstruction of scattered collections and funds; informational support for scientific, educational, and production projects; providing access to unique materials – rare books, archival documents, including their special types – patent, regulatory and technical, unpublished; preservation of originals that are at risk of disappearance or damage.&#x0D; Key words: State Scientific and Technical Library (SSTL) of Ukraine, electronic information resources, electronic library, electronic catalogue, full-text databases, scientific and technical information, open access, open science.
Higher Art Education at Civilisational Crossroads: Creative, Personal, and Social Needs

The purpose of the article is to consider current issues of national higher art education in the context of meeting creative, personal, and social needs. Research methodology. To achieve the goal, general scientific (analysis and synthesis, generalisation) and special research methods were used. The systematic-analytical method made it possible to determine the features of modern art education, and the axiological method helped to identify the value priorities of art education, taking into account the needs of society and the artist. The method of theoretical generalisation was used to establish the specifics of the functioning of art education in modern conditions. The scientific novelty of the obtained results lies in the theoretical understanding of modern processes in art education, taking into account its personal, creative, and social potential. Conclusions. In general, the organisation of higher education in Ukraine provides a comprehensive approach to the training of an artist. The level of higher art education largely reflects the state of national education in general, the ability of students to act as producers of material and spiritual values, which characterises them as the spiritual potential of Ukraine. In order to address the issue of artistic education's relevance to contemporary civilisational challenges, its structure should be systematically modernised, taking into account the national educational experience gained. Traditional art education should be aimed at educating not only a producer of material values, but also a specialist capable of passing on his experience to a new generation, promoting spiritual values and interest in artistic activity among society by his own example. On the other hand, art education should enable artists to fulfil their creative and professional needs, which, in turn, should coincide with the development goals and needs of society.&#x0D; Key words: art education, artist, art, professional realisation, creativity, hermeneutics.
Exploration of Ethical Leadership in Teachers in Government High Schools of Lahore

The idea of ethics is frequently discussed in educational settings because it is part of daily life for ethical leadership students. Ethical leadership is someone who adheres to the rules because they are significant to him. The purpose of the research was explore the perception of SSTs regarding ethical leadership (EL) as well as the difference in it with respect to demographic characteristics of SSTs. The research was quantitative and descriptive approach was employed. Cross sectional survey was conducted to collect the quantitative data. Head teachers working in Government High Schools of Lahore made up population of the study. 375 head teachers selected randomly participated in the study. Instrument developed by Langlois (2005) was modified with the researcher's consent. In ELs, a six-point rating scale was employed. School administrators' opinions on ethical leadership (EL) and its supporting variables were found to be above average, which is considered to be a positive rating. On the basis of qualification, there was no discernible variation in EL, but there were considerable differences on the basis of age and experience. The current study demonstrated the need of taking into account the advantages of moral leadership while creating an efficient educational system. The results of this study have an impact on daily activities in educational settings.
Journal of the Society for Information Display

Abhishek Kumar Srivastava Editor in Chief JSID's Impact Factor increases to 2.3 Upcoming JSID issues feature articles from the International Conference on Display Technology (ICDT) 2022 and exciting articles on micro-electromechanical systems (MEMS) shutter display, quantum dot (QD)-microdisplay, E-paper, liquid crystals, and thin-film transistors (TFTs). Visit JSID's website to discover the latest display-related research: https://sid.onlinelibrary.wiley.com/journal/19383657. High-performance MEMS shutter display with metal-oxide thin-film transistors and optimized MEMS element | Sheikh Abdullah Al Nusayer et al. | DOI: 10.1002/jsid.1252. Holographic waveguide display with large field of view based on volume holographic grating | Chuang Wang et al. | DOI: 10.1002/jsid.1197. Solution-processed high-performance organic light-emitting diodes containing a green-emitting multiresonant thermally activated delayed fluorescent dendrimer | Sen Wu, Dianming Sun, & Eli Zysmanl-Colman | DOI: 10.1002/jsid.1204. JSID is published monthly by Wiley. Subscription fees apply, but SID members and student members have free online access via sid.org/Publications.aspx. Many universities also have an institutional subscription. JSID is indexed in the Web of Science. Submit your original manuscript online via mc.manuscriptcentral.com/sid. Author guidelines can be found on the Journal's homepage: tinyurl.com/jsidhome. Editorial board: tinyurl.com/jsideb. Please direct any questions about JSID to its editor in chief at [email protected]. EarlyView: Accepted papers about to be published can be accessed online via tinyurl.com/jsidev. The Journal is soliciting review papers on any display-related topic. If you have a great idea for a review paper, please contact the editor at [email protected]. Page charges for invited review papers will be waived.
RedPenNet for Grammatical Error Correction: Outputs to Tokens, Attentions to Spans

The text editing tasks, including sentence fusion, sentence splitting and rephrasing, text simplification, and Grammatical Error Correction (GEC), share a common trait of dealing with highly similar input and output sequences. This area of research lies at the intersection of two well-established fields: (i) fully autoregressive sequence-to-sequence approaches commonly used in tasks like Neural Machine Translation (NMT) and (ii) sequence tagging techniques commonly used to address tasks such as Part-of-speech tagging, Named-entity recognition (NER), and similar. In the pursuit of a balanced architecture, researchers have come up with numerous imaginative and unconventional solutions, which we’re discussing in the Related Works section. Our approach to addressing text editing tasks is called RedPenNet and is aimed at reducing architectural and parametric redundancies presented in specific Sequence-To-Edits models, preserving their semi-autoregressive advantages. Our models achieve F0.5 scores of 77.60 on the BEA-2019 (test), which can be considered as state-of-the-art the only exception for system combination (Qorib et al., 2022) and 67.71 on the UAGEC+Fluency (test) benchmarks. This research is being conducted in the context of the UNLP 2023 workshop, where it will be presented as a paper for the Shared Task in Grammatical Error Correction (GEC) for Ukrainian. This study aims to apply the RedPenNet approach to address the GEC problem in the Ukrainian language.
Stabilized In-Context Learning with Pre-trained Language Models for Few Shot Dialogue State Tracking

Prompt-based methods with large pre-trained language models (PLMs) have shown impressive unaided performance across many NLP tasks. These models improve even further with the addition of a few labeled in-context exemplars to guide output generation. However, for more complex tasks such as dialogue state tracking (DST), designing prompts that reliably convey the desired intent is nontrivial, leading to unstable results. Furthermore, building in-context exemplars for dialogue tasks is difficult because conversational contexts are long while model input lengths are relatively short.To overcome these issues we first adapt a meta-learning scheme to the dialogue domain which stabilizes the ability of the model to perform well under various prompts. We additionally design a novel training method to improve upon vanilla retrieval mechanisms to find ideal in-context examples. Finally, we introduce a saliency model to limit dialogue text length, allowing us to include more exemplars per query. In effect, we are able to achieve highly competitive results for few-shot DST on MultiWOZ.
PriMeSRL-Eval: A Practical Quality Metric for Semantic Role Labeling Systems Evaluation

Semantic role labeling (SRL) identifies the predicate-argument structure in a sentence. This task is usually accomplished in four steps: predicate identification, predicate sense disambiguation, argument identification, and argument classification. Errors introduced at one step propagate to later steps. Unfortunately, the existing SRL evaluation scripts do not consider the full effect of this error propagation aspect. They either evaluate arguments independent of predicate sense (CoNLL09) or do not evaluate predicate sense at all (CoNLL05), yielding an inaccurate SRL model performance on the argument classification task. In this paper, we address key practical issues with existing evaluation scripts and propose a more strict SRL evaluation metric PriMeSRL. We observe that by employing PriMeSRL, the quality evaluation of all SoTA SRL models drops significantly, and their relative rankings also change. We also show that PriMeSRLsuccessfully penalizes actual failures in SoTA SRL models.
Discourse Structure Extraction from Pre-Trained and Fine-Tuned Language Models in Dialogues

Discourse processing suffers from data sparsity, especially for dialogues. As a result, we explore approaches to infer latent discourse structures for dialogues, based on attention matrices from Pre-trained Language Models (PLMs). We investigate multiple auxiliary tasks for fine-tuning and show that the dialogue-tailored Sentence Ordering task performs best. To locate and exploit discourse information in PLMs, we propose an unsupervised and a semi-supervised method. Our proposals thereby achieve encouraging results on the STAC corpus, with F1 scores of 57.2 and 59.3 for the unsupervised and semi-supervised methods, respectively. When restricted to projective trees, our scores improved to 63.3 and 68.1.
ERATE: Efficient Retrieval Augmented Text Embeddings

Embedding representations of text are useful for downstream natural language processing tasks. Several universal sentence representation methods have been proposed with a particular focus on self-supervised pre-training approaches to leverage the vast quantities of unlabelled data. However, there are two challenges for generating rich embedding representations for a new document. 1) The latest rich embedding generators are based on very large costly transformer-based architectures. 2) The rich embedding representation of a new document is limited to only the information provided without access to any explicit contextual and temporal information that could potentially further enrich the representation. We propose efficient retrieval-augmented text embeddings (ERATE) that tackles the first issue and offers a method to tackle the second issue. To the best of our knowledge, we are the first to incorporate retrieval to general purpose embeddings as a new paradigm, which we apply to the semantic similarity tasks of SentEval. Despite not reaching state-of-the-art performance, ERATE offers key insights that encourages future work into investigating the potential of retrieval-based embeddings.
Exploiting Language Characteristics for Legal Domain-Specific Language Model Pretraining

Pretraining large language models has resulted in tremendous performance improvement for many natural language processing (NLP) tasks. While for non-domain specific tasks, such models can be used directly, a common strategy to achieve better performance for specific domains involves pretraining these language models over domain specific data using objectives like Masked Language Modelling (MLM), Autoregressive Language Modelling, etc. While such pretraining addresses the change in vocabulary and style of language for the domain, it is otherwise a domain agnostic approach. In this work, we investigate the effect of incorporating pretraining objectives that explicitly tries to exploit the domain specific language characteristics in addition to such MLM based pretraining. Particularly, we examine two distinct characteristics associated with the legal domain and propose pretraining objectives modelling these characteristics. The proposed objectives target improvement of token-level feature representation, as well as aim to incorporate sentence level semantics. We demonstrate superiority in the performance of the models pretrained using our objectives against those trained using domain-agnostic objectives over several legal downstream tasks.
A Hybrid Detection and Generation Framework with Separate Encoders for Event Extraction

The event extraction task typically consists of event detection and event argument extraction. Most previous work models these two subtasks with shared representation by multiple classification tasks or a unified generative approach. In this paper, we revisit this pattern and propose to use independent encoders to model event detection and event argument extraction, respectively, and use the output of event detection to construct the input of event argument extraction. In addition, we use token-level features to precisely control the fusion between two encoders to achieve joint bridging training rather than directly reusing representations between different tasks. Through a series of careful experiments, we demonstrate the importance of avoiding feature interference of different tasks and the importance of joint bridging training. We achieved competitive results on standard benchmarks (ACE05-E, ACE05-E+, and ERE-EN) and established a solid baseline.