Reviewerly/exHarmony huggingface dataset:
The Information and Communication Technology Infrastructure on University of Mines and Technology Campus and Its Impact on Library e-Resource Accessibility

Abstract&#x0D; The University of Mines and Technology (UMaT), Tarkwa, Ghana has a Local Area Network (LAN) infrastructure whose primary purpose is to facilitate research; teaching and learning; and information dissemination. The LAN infrastructure spans a maximum distance of 1.39 square-kilometers with an upload and download speed of 115 Mb/s and interconnects the administration block, faculties, library and halls of residence with high-speed ethernet links operating over a dedicated fiber optic backbone. The LAN infrastructure with connectivity to the internet impact operations in various sections of the University, notably, the University Library. The main purpose of the library is to interact with different information networks to make available e-resource materials to students, academic and non-academic staff. This can only be achieved over a dedicated LAN infrastructure. The introduction of Library Management Systems (Koha), Online Public Access Catalogue (OPAC) and the UMaT Space has improved library services such as document delivery, circulation and borrowing, amongst others. However, there exist a major challenge associated with library e-resources accessibility. This paper sought to investigate the factors hindering library e-resource accessibility for the purposes of improving research. Questionnaire was administered to respondents to solicit primary information while secondary information was obtained from published literature. 537 out of 855 participants responded to the questionnaire administered. 351 (65.36%) represented undergraduate students, 73 (13.60%) represented postgraduate students, 87 (16.20%), 21 (3.91%), 5 (0.93%) represented teaching, non-teaching and library staff respectively. The responses were analysed using simple tables and pie charts. Results from the study showed inadequate access points to enable users access these e-resource materials and lack of knowledge about the existence of these resources. The investigation further revealed the need for the library to embark on an information literacy drive for both students and academic staff. Various ways of improving e-resource accessibility was suggested.&#x0D; &#x0D; Keywords: Local Area Network, ICT Infrastructure, Online Public Access Catalogue (OPAC), E-Resources
An Adaptive Memory Multi-Batch L-BFGS Algorithm for Neural Network Training

Motivated by the potential for parallel implementation of batch-based algorithms and the accelerated convergence achievable with approximated second order information a limited memory version of the BFGS algorithm has been receiving increasing attention in recent years for large neural network training problems. As the shape of the cost function is generally not quadratic and only becomes approximately quadratic in the vicinity of a minimum, the use of second order information by L-BFGS can be unreliable during the initial phase of training, i.e. when far from a minimum. Therefore, to control the influence of second order information as training progresses, we propose a multi-batch L-BFGS algorithm, namely MB-AM, that gradually increases its trust in the curvature information by implementing a progressive storage and use of curvature data through a development-based increase (dev-increase) scheme. Using six discriminative modelling benchmark problems we show empirically that MB-AM has slightly faster convergence and, on average, achieves better solutions than the standard multi-batch L-BFGS algorithm when training MLP and CNN models.
A Hybrid GCN and RNN Structure Based on Attention Mechanism for Text Classification

Abstract In the field of deep learning, for problems and tasks that are sensitive to time series, such as natural language processing or speech recognition, the recurrent neural network is usually more suitable. Long short-term memory (LSTM) is a representative network structure in recurrent neural network. It is time-dependent and enables a global representation of features. However, some problems such as the network parameters of LSTMs limit the applicability of their solutions. This paper proposes an improved hybrid structure of graph convolutional neural network and recurrent neural network. In the input layer, a two-dimensional convolutional neural network is used to build a text corpus map. Graphic embedding is used to preserve the global structure of the entire text graph structures. The LSTM layer and attention mechanism are used to fully implement text classification and improve the computational efficiency. The test results show that the hybrid network structure has better operation speed on the IMDb dataset.
Improving keyword extraction in multilingual texts

The accuracy of keyword extraction is a leading factor in information retrieval systems and marketing. In the real world, text is produced in a variety of languages, and the ability to extract keywords based on information from different languages improves the accuracy of keyword extraction. In this paper, the available information of all languages is applied to improve a traditional keyword extraction algorithm from a multilingual text. The proposed keywork extraction procedure is an unsupervise algorithm and designed based on selecting a word as a keyword of a given text, if in addition to that language holds a high rank based on the keywords criteria in other languages, as well. To achieve to this aim, the average TF-IDF of the candidate words were calculated for the same and the other languages. Then the words with the higher averages TF-IDF were chosen as the extracted keywords. The obtained results indicat that the algorithms’ accuracis of the multilingual texts in term frequency-inverse document frequency (TF-IDF) algorithm, graph-based algorithm, and the improved proposed algorithm are 80%, 60.65%, and 91.3%, respectively.
Design of Dayak Kanayatn Language Learning Mobile Applications Using Gamification

Preservation of regional languages is very important in the current globalization era. The longer the erosion of regional languages will make the younger genera-tion do not know the language inherited from their ancestors. The fewer the speakers and interest in learning will make the Regional Language endangered. The purpose of this study is to design the learning of regional languages, espe-cially for children aged 9-10 years with the principles of pedagogy. The method of gamification uses a mobile-based application in the form of video, quiz games, and visual images. This regional language learning design is called Enggang Ka-nayatn Quiz (EKQ). The lesson material will be given first, then continued with a quiz. The material in the form of daily sentences and the introduction of cultural wisdom. The result is a mobile-based application that can be used by children for the learning of regional languages with the pedagogy principle. The collected points will get an attractive reward. The contribution made through this paper is to motivate children to learn regional languages so that they will maintain cultural wisdom and regional language dances, especially Dayak Kanayatn.
A Multi-Modular Approach for Gesture Recognition and Text Formulation in American Sign Language

The most important thing in communication is hearing what isn't being said, this goes for the people who are deaf and mute.Sign language is the most natural means of exchanging information amongst these people.The deaf and mute people have to rely on an interpreter or some sort of visual communication while communicating with the rest of society.So, to bridge the gap between the deaf and dumb community and the rest of the world, there is the need for the translation system that will make the entire process of communication fluent.American Sign Language (ASL) is a visual and gestural language i.e. the brain processes linguistic information through eyes.This paper proposes a system that interprets the gestures in sign language enacted by the person to plain text.It is a robust as well as real-time Intelligent Translation System ensuring that none of these two parameters are compromised.This application would capture a live video stream of the user performing ASL from the webcam which then translates the gestures to corresponding text using Image Processing techniques and Deep Learning Models.It is then combined to form words that are passed to the spell checker and then combined to form sentences.The proposed solutions would thus enable quick and effective communication between the deaf and mute community and the rest of the society.
Dynamic Interactive Artificial Intelligence: Sketches for a Future AI Based on Human-Machine Interaction

We propose to designate as dynamic interactive artificial intelligence (dAI) a cross-section of existing work in artificially designed and artificially evolved systems meant for minimal forms of in...
High-quality quantum process tomography of time-bin qubit’s transmission over a metropolitan fiber network and its application

We employ quantum state and process tomography with time-bin qubits to benchmark a city-wide metropolitan quantum communication system. Over this network, we implement real-time feedback control systems for stabilizing the phase of the time-bin qubits, and obtain a 99.3% quantum process fidelity to the ideal channel, indicating the high quality of the whole quantum communication system. This allows us to implement field trial of high performance quantum key distribution using coherent one way protocol with average quantum bit error rate and visibility of 0.25% and 99.2% during 12 hours over 61 km. Our results pave the way for the high-performance quantum network with metropolitan fibers.
The Model Development of Picture Story Books Sumbang Kurenah Through Minangkabau Culture Literacy for Early Childhood Character Building

This study aims to develop a model picture book "Sumbang Kurenah" through literacy Minangkabau culture to build the character of early childhood especially in Group B. Sumbang kurenah designed in the form of picture books using the Minangkabau language aims to introduce children about the teaching culture, Minangkabau culture is faded away and being replaced by advanced technology and not many of Minangkabau culture story books have been published so storybook sumbang kurenah story books can be used as a reference for educators in shaping the character of children from an early age.This type of research is the research and development (Research and Development), with model Borg and Gall.Based on language test validation research result data, illustrator pictures and lay out of the book gained an average of 90.81%.Teacher questionnaire responses obtained with an average of 81.8%, children's character value is 68.39%.Based on these results it can be concluded that the development model of sumbang kurenah in form of story book to build the early childhood character is very valid, practical and effective.In other words, the use of model development sumbang kurenah picture books can be effective in shaping the character of the child, and make a positive contribution in the learning process in group B in Bukittinggi-Agam.
Implementation of the Algorithm Fisher Yates Shuffle on Game Quiz Environment

The current technological development of science and knowledge can easily be provided through various media. Learning media have become part of the learning and teaching process. In its use these media can be anything such as videos, motion animations, power points, including games. Educational games can be used as learning media in schools so that learning activities can be more interesting and enjoyable. Games made as learning media are certainly not merely entertainment but must contain elements and educational values. The purpose of this research is to make an educational game of natural science where the questions / questions in the quiz section can be scrambled by themselves. The design of the construction of this environmental quiz game uses the method of Multimedia Development Life Cycle (MDLC) and Fisher Yates Shuffle algorithm for randomization of questions. This environmental game contains natural science lessons about the organization of life systems, the interaction of living things with the environment and environmental pollution. Components in this game are in the form of material and quiz games, puzzles and drag and drop. In this study there are 10 questions that will be randomized to each quiz. The result of the implementation of the Fisher Yates Shuffle algorithm in this quiz section is that the quiz questions that come out can be scrambled, so the questions / questions that come out are different and the user does not easily guess the next question.Keywords: Quiz Game, Adobe Flash, Actionscript, Fisher Yates Shuffle
Local certification of graphs with bounded genus

Naor, Parter, and Yogev [SODA 2020] recently designed a compiler for automatically translating standard centralized interactive protocols to distributed interactive protocols, as introduced by Kol, Oshman, and Saxena [PODC 2018]. In particular, by using this compiler, every linear-time algorithm for deciding the membership to some fixed graph class can be translated into a dMAM(O(logn)) protocol for this class, that is, a distributed interactive protocol with O(logn)-bit proof size in n-node graphs, and three interactions between the (centralized) computationally-unbounded but non-trustable prover Merlin, and the (decentralized) randomized computationally-limited verifier Arthur. As a corollary, there is a dMAM(O(logn)) protocol for recognizing the class of planar graphs, as well as for recognizing the class of graphs with bounded genus. We show that there exists a distributed interactive protocol for recognizing the class of graphs with bounded genus performing just a single interaction, from the prover to the verifier, yet preserving proof size of O(logn) bits. This result also holds for the class of graphs with bounded non-orientable genus, that is, graphs that can be embedded on a non-orientable surface of bounded genus. The interactive protocols described in this paper are actually proof-labeling schemes, i.e., a subclass of interactive protocols, previously introduced by Korman, Kutten, and Peleg [PODC 2005]. In particular, these schemes do not require any randomization from the verifier, and the proofs may often be computed a priori, at low cost, by the nodes themselves. Our results thus extend the recent proof-labeling scheme for planar graphs by Feuilloley et al. [PODC 2020], to graphs of bounded genus, and to graphs of bounded non-orientable genus.
The Ability of Word Embeddings to Capture Word Similarities

Distributed language representation has become the most widely used technique for language representation in various natural language processing tasks.Most of the natural language processing models that are based on deep learning techniques use already pre-trained distributed word representations, commonly called word embeddings.Determining the most qualitative word embeddings is of crucial importance for such models.However, selecting the appropriate word embeddings is a perplexing task since the projected embedding space is not intuitive to humans.In this paper, we explore different approaches for creating distributed word representations.We perform an intrinsic evaluation of several state-of-the-art word embedding methods.Their performance on capturing word similarities is analysed with existing benchmark datasets for word pairs similarities.The research in this paper conducts a correlation analysis between ground truth word similarities and similarities obtained by different word embedding methods.
An Intelligent Recommendation Drilling Platform for Online Computer Education

The continuous innovation of Internet technology makes online education an important way for IT talents to learn. Although many computer learning platforms can provide users with massive online education resources, they do not meet the individual needs of different users well, lacking drilling and interactive links. We implemented an intelligent recommendation drilling platform, striving to personalize learning resources, and integrate learning and drilling. The platform provides functional modules such as question bank learning, competition world, online Q & A, and excellent note section. In the recommendation module, the platform's original data is processed as data sets, and a hybrid recommendation model is trained to provide users with more accurate and valuable recommendations.
A Timeliness-Enhanced Traffic Identification Method in Airborne Network

High dynamic topology and limited bandwidth of the airborne network make it difficult to provide reliable information interaction services for diverse combat mission of aviation swarm operations. Therefore, it is necessary to identify the elephant flows in the network in real time to optimize the process of traffic control and improve the performance of airborne network. Aiming at this problem, a timeliness-enhanced traffic identification method based on machine learning Bayesian network model is proposed. Firstly, the data flow training subset is obtained by preprocessing the original traffic dataset, and the sub-classifier is constructed based on Bayesian network model. Then, the multi-window dynamic Bayesian network classifier model is designed to enable the early identification of elephant flow. The simulation results show that compared with the existing elephant flow identification method, the proposed method can effectively improve the timeliness of identification under the condition of ensuring the accuracy of identification.
The Quality of E-Learning Based on Learning Media Using Moodle LMS on Text of Observation Reports of Grade 10th Students of Vocational School Telkom Shandy Putra Medan

The aims of this study to find out the quality of E-learning based on learning media using Moodle LMS on text of observation. This type of research is development research in the field of education known as Research and Development (R&amp;D). Development research (development research) is research that is used to produce certain products and test the effectiveness of these products (Tegeh and I.M, 2013). The result of this study show that The quality of e-learning based learning media using LMS Moodle which was developed as a learning media on the observation report text material is stated to be a useful and effective contribution in improving the quality of learning outcomes of 10th grade TJA1 Vocational School Telkom Shandy Putra Medan. This is because there is a significant difference in the learning outcomes of the average value of students before using e-learning based learning media (pre-test) ie 57.0 or only about 52% are able to exceed KKM and after using e-based learning media learning using LMS Moodle (post-test) the average value of students increased to 77.0% or can be interpreted as 100% of students able to exceed the KKM. Based on these data the difference is increased by 20% or can be interpreted student learning outcomes increased by 58%.
Accurate localization method for subaperture stitching interferometry in aspherical optics metrology

Aspherical optics have superior performance in many applications. However, precision metrology for an aspherical surface is a key stage in its manufacture. Subaperture stitching interferometry (SSI) is one of the mainstream testing methods for aspherical metrology. In many cases, Annular Stitching Subaperture Interferometry (ASSI) is more suitable for components having rotational symmetry because, compared to SSI, the number of motion directions that need to be adjusted is less. Although motion only along the optical axis is of concern in ASSI, inaccurate localization for subapertures may also occur due to the machining error at the optical center of the optics under test and errors in Cat's eye location, thereby leading to measurement errors. To overcome these problems, an accurate localization method for subaperture stitching is proposed. It is based on the maximum asphericity information between the reference spherical wavefront and the test aspherical surface. First, by using the test aspherical formula and theoretical spherical wavefront, we can calculate the minimum peak-to-valley (PV) value of maximum asphericity. The theoretical location of an optimal reference sphere, which corresponds to this value, can be obtained. Then, we perform a practical test, which starts at the initial zero position, and find an actual minimum PV value near its theoretical location. The difference between the theoretical location and the actual one is the compensation quantity. Finally, we execute ASSI measurement to aspherical optics. The location coordinate of each subaperture is compensated with the acquired quantity. Through the experiments, it can be concluded that the proposed method can improve the measurement accuracy of ASSI in terms of error elimination. The results produced by the new method are more desirable than those of the conventional one.
Corrections to “Enhancing BERT Representation With Context-Aware Embedding for Aspect-Based Sentiment Analysis”

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PENGEMBANGAN MODEL PEMBELAJARAN VIRTUAL (MPV) BERBASIS VIDEO E-LEARNING MOODLE

This study aims to develop a learning model by using web-based moodle e-learning videos to support student learning outcomes in Computer subject. This research is motivated by the development of technology increasing rapidly, the demand for efficiency is increasing. Video e-learning media is a very good breakthrough, and demands for modernization in the world of education. The research method in this study was conducted using the R and D method. The study began with preparing teaching materials that were previously used, preparing teaching materials from the latest sources, collaborating old teaching materials with new teaching materials, reviewing instructional materials that have been compiled, refining materials teach according to directions, make video tutorials based on teaching materials, tutorial videos that have been uploaded to youtube, video links that have been uploaded on youtube are combined with e learning, the final step is done by perfecting the web-based e learning video teaching material by doing several test times , evaluating, and correcting as needed. Keywords: learning models, video learning, moodle e-learning