Reviewerly/exHarmony huggingface dataset:
An approach for generating square Hmong characters using intelligent derivation mechanism

In order to reduce the storage capacity of fonts and improve the display quality of characters, this study proposes an approach to generate square Hmong characters using intelligent derivation mechanism. In the proposed approach, the process of generating square Hmong characters is transformed into the process of solving the bounding box of components using binary tree. Thus, various square Hmong characters can be generated by repeatedly performing topological transformation of limited components. A corresponding intelligent derivation model is developed to get square Hmong characters based on the glyph data of objective components obtained by intelligent derivation. Meanwhile, deterministic finite automata is also used to represent the square of square Hmong characters. Testing results of the editing software developed based on this model demonstrate that the square Hmong characters generated by the proposed intelligent derivation mechanism can meet the needs of practical applications.
DEEP LEARNING–BASED FORMULA RECOGNITION FOR SMART EDUCATION

Motivation: Mathematical formula recognition has a wide range of applications in smart teaching tasks, such as photo search for questions, automatic scoring, and question bank construction. Most of the mathematical formulas in these applications exist in the form of pictures. Therefore, identifying mathematical formulas in pictures has become one of the most critical research issues in smart education. Due to the complex structure of the mathematical formula structure, the recognition of mathematical formulas from pictures is much more complicated than ordinary isolated symbol recognition. Current research mostly uses methods based on machine learning. Traditional mathematical formula recognition technology requires complex recognition processes, and the recognition accuracy is not high. To solve these problems, we propose a method of end-to-end handwritten mathematical formula recognition to recognizes two-dimensional mathematical formula pictures and outputs them with one-dimensional character sequences in LaTeX, which is an edited format for easier human-computer interaction.Method: In this paper, we introduce a neural network model of the attention-based end-to-end. Convolutional neural network (CNN) as a feature extractor maps formula images to high-level features. The decoder is a Gated Recurrent Unit (GRU) that converts these high-level features into output sequences, word by word. For each predicted word, the attention mechanism built into the decoder scans the entire input formula image and chooses the most relevant region to describe a predicted digit or symbol. Moreover, the decoder and the encoder are jointly trained, the decoder could provide contextual information to tune the encoder and guide the attention.Result: We validated the proposed method on the data released by the CROHME competition. Results showed that the proposed method achieves the best-reported results with an expression recognition accuracy of 61.16% on CROHME 2014 and 57.02% on CROHME 2016. Conclusions: The paper proposed a deep learning-based formula recognition method for smart education. The proposed method will be applied to smart education for artificial intelligence technology to solve the problems existing in teaching tasks further, such as low accuracy when searching for questions with photos and low efficiency in automatic scoring and question bank construction.
Resource-efficient energy test and parameter estimation in continuous-variable quantum key distribution

Symmetry plays a fundamental role in the security analysis of quantum key distribution (QKD). Here we review how symmetry is exploited in continuous-variable (CV) QKD to prove the optimality of Gaussian attacks in the finite-size regime. We then apply these results to improve the efficiency, and thus the key rate, of these protocols. First we show how to improve the efficiency of the energy test, which is one important routine in a CV QKD protocol aimed at establishing an upper bound on the effective dimensions of the otherwise infinite-dimensional Hilbert space of CV systems. Second, we show how the routine of parameter estimation can be made resource efficient in measurement-device independent (MDI) QKD. These results show that all the raw data can be used both for key extraction and for the routines of energy test and parameter estimation.
Discovering Robust Convolutional Architecture at Targeted Capacity: A Multi-Shot Approach

Convolutional neural networks (CNNs) are vulnerable to adversarial examples, and studies show that increasing the model capacity of an architecture topology (e.g., width expansion) can bring consistent robustness improvements. This reveals a clear robustness-efficiency trade-off that should be considered in architecture design. In this paper, considering scenarios with capacity budget, we aim to discover adversarially robust architecture at targeted capacities. Recent studies employed one-shot neural architecture search (NAS) to discover robust architectures. However, since the capacities of different topologies cannot be aligned in the search process, one-shot NAS methods favor topologies with larger capacities in the supernet. And the discovered topology might be suboptimal when augmented to the targeted capacity. We propose a novel multi-shot NAS method to address this issue and explicitly search for robust architectures at targeted capacities. At the targeted FLOPs of 2000M, the discovered MSRobNet-2000 outperforms the recent NAS-discovered architecture RobNet-large under various criteria by a large margin of 4%-7%. And at the targeted FLOPs of 1560M, MSRobNet-1560 surpasses another NAS-discovered architecture RobNet-free by 2.3% and 1.3% in the clean and PGD-7 accuracies, respectively. All codes are available at https://github.com/walkerning/aw\_nas.
Sign Gesture Recognition from Raw Skeleton Information in 3D Using Deep Learning

Sign Language Recognition (SLR) minimizes the communication gap when interacting with hearing impaired people, i.e. connects hearing impaired persons and those who require to communicate and don’t understand SLR. This paper focuses on an end-to-end deep learning approach for the recognition of sign gestures recorded with a 3D sensor (e.g., Microsoft Kinect). Typical machine learning based SLR systems require feature extractions before applying machine learning models. These features need to be chosen carefully as the recognition performance heavily relies on them. Our proposed end-to-end approach eradicates this problem by eliminating the need to extract handmade features. Deep learning models can directly work on raw data and learn higher level representations (features) by themselves. To test our hypothesis, we have used two latest and promising deep learning models, Gated Recurrent Unit (GRU) and Bidirectional Long Short Term Memory (BiLSTM) and trained them using only raw data. We have performed comparative analysis among both models and also with the base paper results. Conducted experiments reflected that proposed method outperforms the existing work, where GRU successfully concluded with 70.78% average accuracy with front view training.
Strategies in Raising Speaking Performance for Communication Students: A Case Study at Universitas Bunda Mulia

Nowadays communication is a very important. Communication helps people to understand other people from around the world. If we communicate, it means we can understand their language because people usually use language to communicate. As a result, mastering English is also one of keys to compete and to face global competitions for students in finding the best job in the world.  English is a foreign language for Indonesian students. Therefore, the students have difficulties in learning English. The reason is that they only learn English only in the classroom. The materials they get in the classroom are only grammar. Therefore, the students only learn English theoretically. They do not have much time to practice their English both inside and outside the class. The objectives of this study are first, to find out the problem they face when learning English Subject. Second, to find out the strategies in raising English performance for Communications students in Universitas Bunda Mulia. This is a case study at Universitas Bunda Mulia.
Improving Reward Functions in Robots Playing Capture the Flag Using Q-Learning

This paper builds on previous work that used Q-Learning to teach simulated marine robots to play capture the flag against an unintelligent enemy robot. This paper will focus on the improvement of reward functions to achieve two goals: make the attacking robot more tactical in its approach to the flag, and rid the attacking robot of its indifference to the enemy's location (which often leads to the attacking robot being captured). This paper alters reward function components (dependent on the distance from the attacking robot to the nearest boundary, enemy, and enemy flag) and contributes two new components (dependent on the robot's angle to the enemy flag and the robot's angle to the enemy's heading, known as the deviation angle). This paper then trains four models with variations of reward function components to improve capture the flag behavior of the attacking robot. The models were successful in finding more efficient approaches to the flag than the previous project, although the attacking robot did not capture the flag as many times as the previous project. However, the findings give potential to follow-on work to achieve better results than the parent project. This paper will be continued in hopes of finding more efficient reward functions to increase the intelligence of the attacking robot's approach. Future work will focus on teaching multi-robot teams to capture the flag from an intelligent adversary.
Literary Planning and Development in Indonesia Through The Local Literature Community (LLC): A Challenge

Planning and fostering literature in Indonesia is very important as an effort to preserve it, especially regional literature and develop its existence. This is important because literature has a noble function, namely voicing the heart and phenomena that occur in society. We see that the development of literature in Indonesia such as "living reluctantly to death does not want", is in a situation and condition of concern. Attention from the government and the community is still very minimal. Even though literature in Indonesia still seems to exist, it is solely due to literary activists, both individuals and communities who still care and love literature. This presents a challenge. Challenges in planning and developing literature in Indonesia. It is time for literary issues in Indonesia to be seriously designed by involving people or people who have concerns. Does not always depend on the country. Therefore, independence is needed in discussing the planning and development of literature in Indonesia. In this case the direct involvement of activists / local literary communities is needed. This thinking originated from several existing communities and can survive and even flourish in producing writers and developing literary works in Indonesia. Thus, it is not impossible if the Local Literature Community will provide encouraging results on the development of literature in Indonesia.
An Integer Linear Programming-Based Method for the Extraction of Ontology Alignment

The Semantic Web uses ontologies to cope with the data heterogeneity problem. However, ontologies become themselves heterogeneous; this heterogeneity may occur at the syntactic, terminological, conceptual, and semantic levels. To solve this problem, alignments between entities of ontologies must be identified. This process is called ontology matching. In this paper, the authors propose a new method to extract alignment with multiple cardinalities using integer linear programming techniques. The authors conducted a series of experiments and compared them with currently used methods. The obtained results show the efficiency of the proposed method.
A Study on the Semantic Functions and co-occurrence component of the ‘Yiding(一定)’ in Mandarin

This paper examines the semantic functions of ‘Yiding(一定)’ in Mandarin Chinese, and analyzes the characteristics of VP that co-occurs with ‘Yiding(一定)’.<BR> First, divides the semantic functions of the polysemous word ‘Yiding(一定)’ into three: ‘presume’, ‘intensify’, and ‘promise’. In usage, it is found that when ‘Yiding(一定)’ expresses ‘intensify’, auxiliary verbs need to appear together or be used in imperative sentences. To express the ‘promise’ function requires the speaker and the acting subject to be consistent. If this condition is met, the subject can be the first person or the third person, and even the subject is allowed to not appear.<BR> Second, by investigating the actual corpus, it is found that when expressing the three semantic functions of ‘Yiding(一定)’, there is a restriction on the choice of co-occurring VP. If the VP contains aspect marks and the main predicate in the VP are ‘Shi(是), You(有), adjective’ or ‘combinatorial predicate-complement’, then ‘Yiding(一定)’ expresses the epistemic modality of ‘presume’ semantics; If the VP contains the deontic modal verbs ‘Yao(要), Dei(得)’, then ‘Yiding(一定)’ expresses the non-modality that ‘intensify’ the semantics; If VP contains the auxiliary verb ‘Hui(会)’, ‘Yiding(一定)’ expresses the epistemic modality, and the first-person subject will express the deontic modality of ‘promise’ semantics.
Enriching Attack Models with Cyber Threat Intelligence

As cyber threats continue to grow and expertise resources are limited, organisationsneed to find ways to evaluate their resilience efficiently and takeproactive measures against an attack from a sp ...
FACTORS AFFECTING THE CHOICE OF MODES OF LEARNING BY EMPLOYEES TO ACQUIRE DIGITAL SKILLS

A. Wong 1, D. Lee2 1Hong Kong Polytechnic University (HONG KONG) 2Hong Kong Polytechnic University, School of Professional Education and Executive Development (HONG KONG)
COMPARISON OF PARSING METHODS FOR THE ANALISYS OF A NATURAL LANGUAGE SENTENCE

When constructing machine translation systems, an important task is to represent data using graphs, where words act as vertices, and relations between words in a sentence act as edges. One of these tasks at the first stage of the analysis is the classification of words as parts of speech, and at the next stage of the analysis to determine the belonging of words to the sentence members’ classes. The article discusses methods of parsing both on the basis of rules determined in advance by means of traditional object-oriented programming, and on the basis of analysis by means of graph convolutional neural networks with their subsequent training. Online dictionaries act as a thesaurus.
HOME OFFICE E A SEGURANÇA DA INFORMAÇÃO EM TEMPOS DE PANDEMIA

We are living in a time of great changes, both Brazil and other countries around the world are facing the coronavirus pandemic (COVID-19). In this scenario, there are several challenges, and one of the areas that most require attention is information security in the home office, as many companies have had to adopt this work model due to the necessary social isolation. Therefore, this article aims to inform and present practices that can assist in maintaining cybersecurity in the home office, using the literature review as methodology.Keywords: Home office, pandemic, security, information technology
Korelasi, Motivasi, dan Prospek terhadap Hasil Belajar Bahasa Indonesia Mahasiswa Amerika di Program BIPA

&lt;p&gt;&lt;strong&gt;Abstract:&lt;/strong&gt; This research aims to describe the motivation, prospect, and correlation between the two factors in learning Indonesian for American students in BIPA UM. The hypothesis underlying this study is that “there is a positive and significant influence of American students’ learning motivations towards their learning outcomes in BIPA UM”. This study employs sequential mix methods research design with sequential status or two steps design. The results of this research show that a positive and significant correlation on motivation and students’ prospect towards students’ learning outcome in BIPA UM.&lt;/p&gt;&lt;strong&gt;Abstrak:&lt;/strong&gt;&lt;em&gt; &lt;/em&gt;Penelitian ini bertujuan mendeskripsikan wujud motivasi, prospek, dan korelasi mahasiswa Amerika dalam belajar bahasa Indonesia di program BIPA UM. Penelitian ini menggunakan desain &lt;em&gt;sequential mix methods&lt;/em&gt; dengan status berurutan atau desain dua tahap. Hasil dari penelitian ini menunjukkan bahwa terdapat korelasi yang positif dan signifikan antara motivasi dan prospek terhadap hasil belajar mahasiswa Amerika di program BIPA UM.
Topical Problems of Training Modern Creative Teacher of Preschool Educational Institution

This article discusses the specific pedagogical and psychological features of the preparation of future preschool education professionals for innovative occupational activities. The semantic aspects characterizing the process of creativity in the work of a teacher, as well as the criteria that characterize this process, are highlighted. It also outlines the issues of pedagogical practice, advanced experiences and cooperation with parents to prepare future preschool education professionals for innovative career.
Andor Technology Ldt.: Intelligent and multi-modal spectroscopy with Andor Kymera 328 spectrograph

Leaders development and manufacture of high performance scientific digital cameras and spectrographs from hard X-ray to SWIR for academic, industrial and government applications
Label-Based Diversity Measure Among Hidden Units of Deep Neural Networks: A Regularization Method

Although the deep structure guarantees the powerful expressivity of deep networks (DNNs), it also triggers serious overfitting problem. To improve the generalization capacity of DNNs, many strategies were developed to improve the diversity among hidden units. However, most of these strategies are empirical and heuristic in absence of either a theoretical derivation of the diversity measure or a clear connection from the diversity to the generalization capacity. In this paper, from an information theoretic perspective, we introduce a new definition of redundancy to describe the diversity of hidden units under supervised learning settings by formalizing the effect of hidden layers on the generalization capacity as the mutual information. We prove an opposite relationship existing between the defined redundancy and the generalization capacity, i.e., the decrease of redundancy generally improving the generalization capacity. The experiments show that the DNNs using the redundancy as the regularizer can effectively reduce the overfitting and decrease the generalization error, which well supports above points.
On The Gap Between Software Maintenance Theory and Practitioners' Approaches.

The way practitioners perform maintenance tasks in practice is little known by researchers. In turn, practitioners are not always up to date with the proposals provided by the research community. This work investigates the gap between software maintenance techniques proposed by the research community and the software maintenance practice. We carried out a survey with 112 practitioners from 92 companies and 12 countries. We concentrate on analyzing if and how practitioners understand and apply the following subjects: bad smells, refactoring, software metrics, and change impact analysis. This study shows that there is a large gap between research approaches and industry practice in those subjects, especially in change impact analysis and software metrics.
XRJL-HKUST at SemEval-2021 Task 4: WordNet-Enhanced Dual Multi-head Co-Attention for Reading Comprehension of Abstract Meaning

This paper presents our submitted system to SemEval 2021 Task 4: Reading Comprehension of Abstract Meaning. Our system uses a large pre-trained language model as the encoder and an additional dual multi-head co-attention layer to strengthen the relationship between passages and question-answer pairs, following the current state-of-the-art model DUMA. The main difference is that we stack the passage-question and question-passage attention modules instead of calculating parallelly to simulate re-considering process. We also add a layer normalization module to improve the performance of our model. Furthermore, to incorporate our known knowledge about abstract concepts, we retrieve the definitions of candidate answers from WordNet and feed them to the model as extra inputs. Our system, called WordNet-enhanced DUal Multi-head Co-Attention (WN-DUMA), achieves 86.67% and 89.99% accuracy on the official blind test set of subtask 1 and subtask 2 respectively.
Editor for pronunciation dictionaries

A web application for the editing of pronunciation dictionaries. The tool offers detailed annotation of entries, e.g. on compounds, prefixes, dialects and part-of-speech. Exports dictionaries in .tsv format for use in speech applications.Vefviðmot til þess að vinna með framburðarorðabaekur. Tolið býður upp a að merkja upplýsingar með hverju orði, t.d. hvort orðið se samsett, byrji a forskeyti, framburðartilbrigði og orðflokk. Unna orðalista er svo haegt að flytja ut a .tsv formi til notkunar i taltaeknihugbunaði.
An analysis of Students Ability in Skimming and Scanning in Reading Class of English Department FTIK IAIN LANGSA

The purposes of this study were to find out the ability of students in Skimming and Scanning and to investigate how the students apply the procedure in Skimming and Scanning in Reading class. This study applied a descriptive qualitative approach. The writer used purposive sampling. The writer had nine respondents. The writer used documentation and observation as the instrument. Based on the results, indicated that in skimming, the students made a question, some also looked at the table of contents, they read or browsed at high speed, but some students were still affected to Look at reading topics. Then all students stopped when they found the topic they were looking for. but some students were not careful when text a reading. In scanning, the students also saw the table of contents first, but some students directly browsed to the page they wanted to find, besides, the students also read the background, and they also read the conclusions at a glance.
Social Role of the Librarians of the Federal Institute of Education, Science and Technology

The study was carried out through the theoretical foundation about the conceptions and objectives of the Federal Institute of Education, Science and Technology, and also on the social role of the librarians of this educational institute. These Federal Institutes were created in Brazil in 2009 and they offer basic and higher education. This study aims at investigating, analyzing, and understanding if the librarians of the Federal Institutes of Education, Science, and Technology recognize their social roles as professionals that can contribute to the development of cognitive skills with regards to the information in the library’s users. A case study was carried out with all the librarians of the Federal Institutes and questionnaires were the method used for collecting data. It should be noted in the librarians’ answers that they recognize their social roles, and they act according to what they recognize. In their everyday practices, these librarians try to minimize the difficulties that the library’s users face in relation to the search, location, use, assessment, dissemination, and understanding of information.