Reviewerly/exHarmony huggingface dataset:
Robust adaptive graph learning with manifold constraints for subspace clustering

Subspace clustering aims at grouping data into a number of partitions, which has become one of the most powerful tools to analyze and interpret big data, particularly for clustering high-dimensional data. Although a series of related approaches have been proposed, real data are often corrupted leading to the learned graph is inexact or unreliable. Meanwhile, constructing an informative graph is one of the most important steps, which can greatly affect the final performance of clustering approaches. To learn a robust graph, this paper presents a novel data representation approach called Robust Adaptive Graph Learning with Manifold Constraints (RAGLMC) for subspace clustering. RAGLMC introduces the <i>l</i>2,1-norm constraint on sparse coding coefficients for ensuring the learned coding coefficients would be optimal as adaptive graph weights. Moreover, in order to reduce the influence of noise points on the local structure in graph construction, we combine <i>l</i>2,1-norm with manifold constraints on the coding coefficients to learn a locality and smoothness representation. Therefore, the proposed approach can estimate the graph from data alone by using manifold constraint on coding coefficients, which is independent of a prior affinity matrix. Extensive experiments verify the effectiveness of the proposed approach over other state-of-the-art approaches.
Experimenting with Assamese Handwritten Character Recognition

While Optical Character Recognition has become a popular tool in business and administration, its use for Assamese character recognition is still in early stages. Therefore, we have experimented with multiple neural network architectures, applied to this task, to establish general understanding of their performance. For the experiments, we have generated an Assamese script dataset, with over 27k images. To this dataset, LeNet5, AlexNet, ResNet50, InceptionV3, DenseNet201, and hybrid LSTM-CNN models have been applied. Next, geometric transformations that included shifting image horizontally and vertically, and rotating them, were applied, to augment the available dataset. The augmented dataset was used in experiments and accuracy of applied methods has been studied. Best accuracy, obtained on the test data, reached 96.83%.
A Study on the Conversion of Nominals and Adverbs in Korean

본고에서는 사전에 명사류(명사, 대명사, 수사)와 부사의 품사 통용으로 등재된 항목을 퍼지(fuzzy) 문법적 관점에서 명사류에 가까운지 혹은 부사에 가까운지. 아니면 두 개의 품사적 속성을 모두 지닌 전형적 품사 통용어인지를 분석하였다. 먼저 명사성과 부사성을 검증하기 위한 문법적 규준들을 상세히 논의하였다. 그리고 이를 통하여 분석한 결과를 도식화하여 입체적인 그래프로 나타냄으로써 명사류와 부사 통용어가 갖는 품사성의 분포를 구체적으로 확인할 수 있도록 하였다. 본고의 분석 대상이 된 216개 명사류-부사 통용어 중 전형적 품사 통용어로 볼 수 있는 항목은 100개(46%), 명사류에 가까운 항목은 37개(17%), 부사에 가까운 항목은 79개(37%)로 나타났다. 본고는 명사성 검증 규준, 부사성 검증 규준을 정도성의 관점에서 매우 상세한 수준까지 고찰하였다는 점과 명사-부사 품사 통용어들의 세 유형 및 유형별 비율을 제시하였다는 점에서 그 의의를 찾을 수 있다.In this paper, we researched whether the Korean words registered as words of nominals-adverb conversion are close to nominals or adverb, or typical word class conversions based on various properties of both word class (that is nominals and adverb) from the perspective of fuzzy grammar. First, we discussed grammatical criteria for verification of the properties of noun and adverb. Furthermore, we showed the results of the analysis with three-dimensional graphs, so that the distribution of the words of nominals-adverb conversion can be recognized in detail. Among the 216 nominals-adverb conversion analyzed in this paper, 100 (46%) words can be classified as typical word class conversion, 37 (17%) words are close to nominals, and 79 (37%) words are close to adverbs. This paper is significant in that we researched very minutely the properties of noun and adverbials as criteria for verification of nominals or adverb from the perspective of fuzziness and showed 3 types and ratios by the 3 types of the words of the noun-adverb conversion.
Versions and Revisions

As we change and improve our backend applications over time, add new features and remove some others, we might come to a point where we have to make changes to the backend APIs as well. Some of them might be breaking changes and require an API consumer to change code on the client side, while other changes are non-breaking changes where API consumers can decide whether they want to change the client side and eventually use a new feature or not.
The Electroweak Theory

The Standard Model of particle physics is an amazingly successful theory describing the fundamental particles and forces of nature. This text, written for a two-semester graduate course on the Standard Model, develops a practical understanding of the theoretical concepts it's built upon, to prepare students to enter research. The author takes a historical approach to demonstrate to students the process of discovery which is often overlooked in other textbooks, presenting quantum field theory and symmetries as the necessary tools for describing and understanding the Standard Model. He develops these tools using a basic understanding of quantum mechanics and classical field theory, such as Maxwell's electrodynamics, before discussing the important role that Noether's theorem and conserved charges play in the theory. Worked examples feature throughout the text, while homework exercises are included for the first five parts, with solutions available online for instructors. Inspired by the author's own teaching experience, suggestions for independent research topics have been provided for the second-half of the course, which students can then present to the rest of the class.
Developing a Successful Bomberman Agent

In this paper, we study AI approaches to successfully play a 2-4 players, full information, Bomberman variant published on the CodinGame platform. We compare the behavior of three search algorithms: Monte Carlo Tree Search, Rolling Horizon Evolution, and Beam Search. We present various enhancements leading to improve the agents' strength that concern search, opponent prediction, game state evaluation, and game engine encoding. Our top agent variant is based on a Beam Search with low-level bit-based state representation and evaluation function heavy relying on pruning unpromising states based on simulation-based estimation of survival. It reached the top one position among the 2,300 AI agents submitted on the CodinGame arena.
Study about Interpersonal Communication for Development

This paper is aimed at extolling the overwhelming synergy between interpersonal communication and development while establishing that interpersonal communication is a must for meaningful and sustained development to take place. Specifically, basic concepts were defined, explained and appropriate examples given for better comprehension of the discourse. The paper goes further to discuss types of interpersonal communication, interpersonal communication in relationship, elements of interpersonal communication, and noise in communication as doing a great damage to the communication process. The paper adopted content analytical method whereby scholarly articles from books, journals and internet were analyzed. The authors advocate for channel mix whereby interpersonal communication can be mixed with the mass media and the social media for more effective sustainable development to be achieved. Finally, certain inferences and conclusions were made.
Construction method of fire emergency rescue communication network based on mixed organization and self-organization

Tother article first discusses the severe situation of the emergency communication requirements of the fire rescue team at the emergency rescue site, and then analyses the current situation and existing problems of the current fire emergency rescue communication network. In response to the problem, a fire emergency communication network based on a mixture of other organizations and self-organizations is proposed, and the network structure, construction method, networking process and network status change rules are elaborated in detail. Finally, the fire emergency communication network construction method constructed in tother paper is compared with the traditional emergency communication network construction method.
THE ROLES OF MANAGERS AND EMPLOYEES IN THE USE OF ORGANIZATIONAL IDEATION PLATFORMS

Leader to LeaderVolume 2022, Issue 104 p. 66-68 FROM THE FRONT LINES THE ROLES OF MANAGERS AND EMPLOYEES IN THE USE OF ORGANIZATIONAL IDEATION PLATFORMS First published: 18 February 2022 https://doi.org/10.1002/ltl.20638Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Volume2022, Issue104Spring 2022Pages 66-68 RelatedInformation
A Study on Image Restoration and Analysis

Image restoration and analysis are the technique and methodology to recover degraded images through prior knowledge, which includes degradation functions, modeling, and inverse process. This technique can process in two domains. Those domains are spatial domain as well as frequency domain. The various noise models and techniques are improved using MATLAB for the filtering methodology in spatial and frequency domains. We can analyze the different restoration methods given in image enhancement with the help of mean squarer error (MSE) estimation as well as the estimation of signal-to-noise ratio (SNR). Goals for image restoration to determine the types of noise analyze the techniques and determine how the restoration works. Image restoration methodology is distinct with respect to the methodology of image enhancement. Image enhancement uses to emphasize the basic features of an image which enhances an image more presentable for observation. It is not always possible to develop factual data in the prospect of scientific observation. Image enhancement technology is generally provided by imaging packages which are used without an a-priori model to process and produce the image. The book chapter presents the adequate fundamental concepts to enhance the noise reduction technique and resolution loss for image processing.
Multi-channel medical image segmentation method in Hessian domain

Medical image segmentation is an important technique in surgical navigation, tumor quantification, computer-aided diagnosis and detection, etc. To enhance the accuracy of its performance, the image contrast among different tissues in multi-modality plays an important role and is still a great challenge. In this paper, we proposed an image segmentation method by merging multi-channels which are defined in Hessian domain. Every domain owns individual properties and is only sensitive to a few specific tissues, which should be an essential complement for other domains. The contrast between two neighboring tissues in their merging results provides more sensitive boundary information than the original images. Moreover, we also notice some weak boundaries are the major barrier in the processing of image segmentation. An unsupervised local segmentation scheme is proposed to combat this challenge by dividing the whole volume into small patches which are overlapped with each other. Our method is testified over five different organs with two major modalities and three noise levels, and yields very promising results. After comparing, our method exhibits its great superiority over slic and level set, two state-of-the-art methods with more accurate contours and boundaries.
A Novel Emoji Based Deep Super Learner (EDSL) for Sentiment Classification

Deep learning has revolutionized the way valuable insights are discovered from the data in predictive modelling. It exploits the features in the dataset by gradually moving up the granularity level in each iteration feeding the results to the immediate upper layer resulting in significant performance boost. Though deep neural networks ace in the field of predictive modelling yet it has several shortcomings which need to be catered to. The black box nature of neurals, plethora of hyper-parameters to tune and its reluctance to converge faster on smaller datasets renders it discouraging sometimes. Surface classifiers address these issues though with a compromise on the performance. Considering the shortcomings of the two aforementioned techniques, super learners harness the power of both the techniques by developing an amalgam of diverse learning algorithms. Inspired by this notion, this paper proposes a novel EDSL (Emoji based Deep Super Learner) that fits surface classifiers in a deep learning architecture to perform emoji based sentiment classification. It exploits the simplicity of surface classifiers and the power of deep neural networks achieving performance competitive to the later. Experiments prove that the proposed approach is highly adaptable and has better performance over individual surface learners and deep neural networks to classify text having emojis as key features.
Is German more nominal than English? Evidence from a translation corpus

Recent corpus studies comparing the frequency of nouns in English and German have produced inconclusive evidence. All existing studies have certain methodological limitations in that they rely on automatic part-of-speech tagging, which involves diverging tokenization based on contrastive spelling differences. Alternatively, counting is based on human categorization, thus avoiding the problems of spelling differences, but using a problematic sampling method. This paper aims at determining nominality in English and German while avoiding both types of problems. The distribution of normal nouns is counted in three random samples of 100 sentences from three different registers drawn independently of the word count, thus foregoing spelling-related differences. The sample is taken from a corpus containing originals and translations in the language pair. Since the corpus also includes alignment of matching translations, translation equivalents are taken into consideration as a tertium comparationis, thus offering the opportunity to assess the impact of translation-related decisions. In fact, a tendency of translations to deviate from originals can be observed at least in one register. The general results do not reveal any statistically significant difference in the frequency of nouns between the two languages. This rectifies informal claims that nouns are more frequent in German and contributes to a more accurate characterization of English and German. These findings are of relevance for language learners and translators, whose task is often to conform to target language patterns.
Manipulator Posture Estimation Method Based on Multi-eye Vision and Key Point Detection

Image recognition is combined with multi-eye stereo vision technology to estimate the pose of the robot arm which can improve the flexibility of the robot arm control and reduce the immobilization of the control mode. Multiple cameras illuminate the robotic arm to form a multi-eye vision model. At the same time, the HRNet key point detection model detects the key points of the robotic arm in the picture, establishes a space line equation set, and obtains the coordinates of the key points of the robotic arm in space, so as to realize the pose estimation. The experimental results show that when the key points of the HRNet model are detected correctly, the pose of the robotic arm can be estimated well. The method has research significance and practical value.
Minsel. An etymological database for lexemes of Arabic origin in Maltese

Minsel is a digital etymological database for lexemes of Arabic origin in Maltese which is currently being compiled at the Department of Oriental Studies of the University of Malta. Minsel is still in its initial stages and researchers are currently in the editing phase. Once this online platform is launched, it will contribute towards the study of the Maltese lexicon in particular and Arabic dialectology in general.
A New Semi-Automated Method for Service Identification

Service identification plays a key role in the design of service-oriented systems. There are non-model-based and model-based methods for extracting services from business processes. These methods suggest a set of mostly descriptive solutions that do not pay sufficient attention to service design guidelines and the conceptual relations between tasks. The challenge is to develop an algorithm to automatically identify services from business processes to simplify the analysis and reduce the gap between information technology and business needs. In this paper, we develop a semi-automated service identification method that addresses this gap. This method incorporates the Goal, Data, and Business Process Models (BPM) to identify services based on related tasks, shared data, and business requirements. It advances previous methods by simultaneously considering both semantic and structural relations between tasks which permits better and more accurate identification of services. Moreover, the proposed method considers the principles of service design such as internal cohesion of service methods, loose coupling of services, and reusability of the identified services.
The TORNARE-periphrasis in Italo-Romance

This chapter examines verbal periphrases involving the originally transitive Latin verb TORNARE ‘turn’ in Italo-Romance. The emergence in late Latin of intransitive uses of TORNARE as a verb of motion meaning ‘return, go back’ prepared the way for early Romance collocations with an infinitive, ‘go back to doing’. The gradual grammaticalization of such periphrases involved semantic and syntactic reanalysis that produced an aspectual auxiliary with restitutive, continuative, and repetitive meanings according to the context, e.g., It. <italic>torno a dire</italic> ‘I say again, I repeat’. Whereas the lexical unaccusative motion verb selects the expected perfective auxiliary BE, the aspectual periphrasis displays in some dialects an unusual type of auxiliary shift (BE &gt; HAVE), when the infinitive involved is transitive or unergative. This account of the morphosyntactic development of the periphrasis also contributes to recent typological and semantic investigations regarding the expression of ‘again’.
ACCtic Master Programme on STEAM + SciArt

A new master university programme on STEAM + SciArt is presented. It will be taught in University of Seville (Spain).
Assessing Students’ Vocabulary through Mobile Technologies on Vocabulary Mastery for English Foreign Language Students

English learning for foreign language learners is very necessary to get the learning process with or through technology that is developing at this time especially in the current Covid-19 pandemic. This procedure becomes a compulsory protocol of learning for the teachers, especially an English teacher in this pandemic situation era. This will be very meaningful and have a positive impact on effective learning especially in maintaining social distance as an anticipatory step in dealing with a pandemic. The aim of the research was to find out the influence of the use of Edmodo program multimedia and technology in teaching vocabulary as learners of English as a Foreign Language Learning. Total of 42 high school students in Serang City, Banten Province, Indonesia were taken as samples in this study which were divided into 2 groups. The vocabulary is chosen as many as 87 words taken from the textbook. Edmodo program content and multimedia were used in this research. Vocabulary tests and student responses were examined and the results analyzed with 61.23 pretest and 71.01 posttest with [t (39) =2.745, p&lt;0.05*]. For the conclusion from this research, it was found that the students 'vocabulary skills improved from pre-test and post-test and students' responses about the use of multi-media technology using Edmodo program received a positive response. As the implication from this research, the teachers should be aware of their roles as guides and facilitators of their learners’ learning and the teachers should find the ways that technology can help them towards learner-centered instruction as opposed to teacher-centered instruction. Learners should use technology to enhance their language skills because it has as a crucial role in developing learners’ creativity and provides them with interesting, enjoyable, and exciting alternatives to study English language teaching situation.
The Mediating Effect of Smartphone Addiction in the Relationship between Basic Psychological Needs and Learning Flow in University Students

Purpose: This study aimed to examine the mediating effect of smartphone addiction in the relationship between basic psychological needs and learning flow of university students during the COVID-19 pandemic. Methods: Participants comprised 170 university students, and data were collected from web surveys conducted from June 30 to July 10, 2021. Data were analyzed using Pearson’s correlation coefficients, multiple regression analysis, and a Sobel test with SPSS/WN 23.0 software. In order to verify the mediating effect, hierarchical regression analysis and the Sobel test were conducted. Results: There was a positive correlation between learning flow and basic psychological needs (r=.67, p<.001). Smartphone addiction was negatively correlated with learning flow (r=-.24, p=.002) and basic psychological needs (autonomy; r=-.25, p=001, relatedness; r=-.18, p=021, competence; r=-.31, p<.001). Smartphone addiction had a partial mediating effect between relatedness and learning flow. Conclusion: The results suggest that to increase learning flow, strategies to meet basic psychological needs and reduce smartphone addiction should be provided to learners during the COVID-19 pandemic.
Recognition of Disparaging Phrases in Social Media

Social media provides a space for individuals, where they can share their view or opinion very easily. The use of social media is growing at a rapid pace. Users can communicate more swiftly through social media platforms like Twitter, Facebook, and YouTube. The content of social media texts is generally made up of code-mixed comments/posts and replies, and it may contain harmful or non- offensive words. Sentiment analysis on social media provides businesses with a quick and effective approach to monitor public opinion on their brand, business, goods, and other topics. In recent years, a variety of features and approaches for training sentiment classifiers for fetched datasets have been investigated, with mixed results. Twitter is a popular social media platform. It provides businesses with a quick and efficient way to assess customers’ viewpoints on issues that are crucial to their performance in the marketplace. Expanding a sentiment analysis software is a way to utilise computers to measure consumer perceptions. Analyze the sentiment from employee tweets regarding work from home is the main goal. The employees work from home tweets dataset as input was collected from twitter. Then, to analyse the sentiment the NLP techniques, text classification and deep learning algorithm were used. The experimental results shows the performance metrics such as accuracy and analyse the sentiment based on sentiment analyser into positive, negative and neutral.