Reviewerly/exHarmony huggingface dataset:
Seismic Event Automatic Detect Based on XGBoost

Disclaimer Text and Data Mining. Any automated analytical technique aimed at analysing text and data in digital form in order to generate information including - but not limited to - patterns, trends and correlations (so-called Text and Data Mining) may only be applied if it is done by a research organisation or cultural heritage institution solely for the purpose of (non-commercial) scientific research as mentioned in Clause 3 of Directive (EU) 2019/790 (the Digital Single Market Directive) and Clause 15n of the Dutch Copyright Act [Auteurswet]. Text and Data Mining for commercial purposes is not allowed; all rights in this respect are reserved pursuant to Clause 4 paragraph 3 of the Digital Single Market Directive and Clause 15o paragraph 1 of the Dutch Copyright Act.
Insider Threat Data Expansion Research using Hyperledger Fabric

This paper deals with how to implement a system that extends insider threat behavior data using private blockchain technology to overcome the limitations of insider threat datasets. Currently, insider threat data is completely undetectable in existing datasets for new methods of insider threat due to the lack of insider threat scenarios and abstracted event behavior. Also, depending on the size of the company, it was difficult to secure a sample of data with the limit of a small number of leaks among many general users in other organizations. In this study, we consider insiders who pose a threat to all businesses as public enemies. In addition, we proposed a system that can use a private blockchain to expand insider threat behavior data between network participants in real-time to ensure reliability and transparency.
Nested Named Entity Recognition from Medical Texts: An Adaptive Shared Network Architecture with Attentive CRF

Recognizing useful named entities plays a vital role in medical information processing, which helps drive the development of medical area research. Deep learning methods have achieved good results in medical named entity recognition (NER). However, we find that existing methods face great challenges when dealing with the nested named entities. In this work, we propose a novel method, referred to as ASAC, to solve the dilemma caused by the nested phenomenon, in which the core idea is to model the dependency between different categories of entity recognition. The proposed method contains two key modules: the adaptive shared (AS) part and the attentive conditional random field (ACRF) module. The former part automatically assigns adaptive weights across each task to achieve optimal recognition accuracy in the multi-layer network. The latter module employs the attention operation to model the dependency between different entities. In this way, our model could learn better entity representations by capturing the implicit distinctions and relationships between different categories of entities. Extensive experiments on public datasets verify the effectiveness of our method. Besides, we also perform ablation analyses to deeply understand our methods.
ICT Enabled Education to Empower Girls: Potentials for the Vulnerable Groups

Financial constraints, coupled with socio-cultural construct induce vulnerability among girls in Bangladesh. This leads to them entering the labor market without skills; thus, their career becomes constricted while their potential remains unexplored. For a worthwhile life they should be empowered, which can best be done by educating them without hindering their work life. Open and Distance Learning (ODL) with the use of Information and Communication Technology (ICT) can provide such a flexible learning arrangement to working women and girls. A wide range of electronic devices at different purchasing levels can provide flexibility in the use of ICT. A retrospection of COL’s Gender initiative’s virtual workshop, ‘Upskilling Girls in ICT through Mobile Application Development’, facilitated by the author in 2020 evoked ideas and generated interest for following up with the participants regarding their use of ICT. This endeavor helped conceptualize the idea that girls of the vulnerable groups can potentially be empowered by engaging them with ICT-enabled education which can transform their lives. This study has been conducted based on both primary and secondary sources of data. Secondary sources are research materials, scholarly articles, statistics from governmental websites and official publications. Primary data were collected in two stages. Firstly, data were collected from 74 girls through structured questionnaires and focus group discussions (FGDs), who represented nine rural areas of Bangladesh. Secondly, in light of the experience and findings of these data, a follow up study of the author’s previously conducted research among girl workers of six garment factories in Dhaka Metropolitan City was carried out through questionnaire survey and FGDs. The findings of this research can lead towards further educational explorations and help develop actionable plans to significantly empower girls of the vulnerable groups.
THE PHILOSOPHY OF EDUCATION OF J. BAUDRILLARD: SCREEN DISASTERS AND DISASTERS IN THE SOULS OF PEOPLE

The article deals with the philosophical aspect of education in the teachings of the prominent French philosopher J. Baudrillard, who revealed the mechanism of creation and perception of the subject of modern education through the prism of simulacra, media images, which are the most important characteristics of the socio-cultural digital space, contribute to the “dehumanization” of a person, show the role of cinema and television in the educational process in solving the problem of “humanization of a dehumanized person”. The influence of screen disasters on the formation of a person’s personality is analyzed, the features of the figurative perception of reality on the educational process are revealed. J. Baudrillard showed that modern man can only “be” being “mediated”. Therefore, the main trends in the development of education are digitalization, informatization, mediation, communication, simulativeness, which is revealed through the teachings of J. Baudrillard.
Knowledge hiding in the COVID 19 Era: A Managerial Perspective

The COVID 19 pandemic has brought so many changes in workplaces and triggered knowledge hiding behaviours in employees as a result of increased job insecurity.This study was focused on enquiring how leadership in organizations discouraged knowledge hiding in their organizations.The research was more focused on this angle as many studies only focus on causes and effects of knowledge hiding.The study was based on a qualitative approach and face-to-face semi-structured interviews were conducted to collect the relevant data.Some secondary information was also used mainly in the form of company reports.The study revealed that job insecurity, power play and competition were among the causes of knowledge hiding.It also revealed that incentives, inclusion and an open culture were essential and proved methods of mitigating knowledge hiding tendencies.The implications of the study were that the leadership played a huge role in ensuring knowledge hiding in workplaces decreased.The researcher recommended that leadership had to be attuned to their employees' behaviour in order to pick up the knowledge hiding tendencies as well as deliver successful mitigation methods.
Classification of the Growth Level of Fungal Colonies in Solid Medium: A Machine Learning Approach

The measurement of colony growth in a solid medium is a common technique applied in phytopatology. The measurement procedures usually involve the visual identification and manual measurement of colonies in Petri dishes. Recently, some measurement techniques have been developed based on the segmentation of colony images by using digital image analysis and machine learning models. These approaches have in common: a highly controlled environment where the images were obtained; and a segmented image as output. In addition, few machine learning studies explore the importance of image features in the classification process and test a minimal range of algorithms. Thus, in this study, we propose a classification method of fungal growth based on machine learning, which performs this task using images obtained without any control of the luminosity conditions. An image dataset was created with a set of 537 images of Petri dishes incubated with Botrytis cinerea and obtained in the phytopathology laboratory of the UTFPR. The images were preprocessed, and a set of 97 feature descriptors extracted from them generated five different datasets. Experiments were carried out with 9 different classification algorithms trained through a repetitive cross-validation resampling. Induced models were compared in terms of the balanced accuracy metric e statistical significance verified through the Kruskal-Wallis test. From all trained models, 16 showed balanced accuracy above 0.8, and the top 11 showed no difference at 5% of significance by the statistical test. Among the evaluated features, the color channels were the most relevant, especially the standard deviation of the intensity channel.
MULTI-MODALITY IMAGE SUPER-RESOLUTION USING GENERATIVE ADVERSARIAL NETWORKS

Over the past few years deep learning-based techniques such as Generative Adversarial Networks (GANs) have significantly improved solutions to image super-resolution and image-to-image translation problems.In this paper, we propose a solution to the joint problem of image super-resolution and multi-modality image-to-image translation.The problem can be stated as the recovery of a high-resolution image in a modality, given a low-resolution observation of the same image in an alternative modality.Our paper offers two models to address this problem and will be evaluated on the recovery of high-resolution day images given low-resolution night images of the same scene.Promising qualitative and quantitative results will be presented for each model.
Research on the application of computer big data technology in English cognitive linguistics

With the continuous development of computer big data technology, our work, life and study are inseparable from computer big data technology, and we have gradually come to the era of big data. In such an era, we gradually apply big data technology to college English cognitive linguistics, and this paper mainly discusses the innovative strategies of college English cognitive linguistics analysis under the conditions of big data technology.
The Study of the Formation of Universal Educational Actions among Students in the Preparation of the Final Individual Project

The subject of the study is the methodology for the formation of universal educational activities that are trained in the process of implementing the final individual project. The object of the research is universal learning activities. In the course of the study, a model for the formation of universal educational activities was developed, as well as a form for studying the level of their formation. In the course of the study, the theoretical foundations of the process of forming skills and abilities were studied, the results of scientific works aimed at studying the use of final individual project as a form of attestation of students, as well as the provisions of the main legal acts that consolidate these theses, were used. The Federal State Standards consecrate the requirements for the results of the development of the main educational program, including the implementation of the final individual project. Concretizing the used theoretical provisions on universal educational activities, a pedagogical model of their formation in the process of creating final individual project was developed. This model is a practical understanding and consistent implementation of the theoretical vision of the process of their formation. The pedagogical model of the formation of universal educational activities can be used both in the phased implementation of the final individual project, and in the analysis of final works, at the stage of demonstrating and summing up the results of activities. Based on the methods used for organizing experimental work, a phased plan was implemented aimed at the formation of universal educational activities through the implementation of final individual project. A comparative analysis at the final stage of the experimental work revealed a positive dynamic in the formation of universal educational activities, which was confirmed by the results in the experimental group of students.
Weakly Supervised Named Entity Recognition for Carbon Storage Using Deep Neural Networks

Applying Transfer-Learning based on pre-trained language models has become popular in Natural Language Processing. In this paper, we present a weakly supervised Named Entity Recognition system that uses a pre-trained BERT model and applies two consecutive fine tuning steps. We aim to reduce the amount of human labour required for annotating data by proposing a framework which starts by creating a data set that uses lexicons and pattern recognition on documents. This first noisy data set is used in the first fine tuning step. Then, we apply a second fine tuning step on a small manually refined subset of data. We apply and compare our system with the standard fine tuning BERT approach on large amount of old scanned document. Those documents are North Sea Oil & Gas reports and the knowledge extraction would be used to assess the possibility of future carbon sequestration. Furthermore, we empirically demonstrate the flexibility of our framework showing that it can be applied to entity-identifications in other domains.
Development Guideline for Professional Education Administrators in the 21st Century of School Administrators in Loei Province

The objectives of this research were to study 1) desirable characteristics and development guidelines for Professional Education Administrators in the 21st Century, and 2) guidelines for developing Professional Education Administrators in the 21st Century. This is mixed methods research. The research population was the school administrators of the Loei Primary Education Service Area Office, District 1 for a total of 130 people. The researcher collected the data from the total population. The key informants were 30 school administrators in the Loei Primary Educational Service Area Office, District 1. The research instruments were questionnaires and interview forms. The statistics used in the research were percentage, mean, and standard deviation. The content analysis was the analysis of data obtained from interviews with key informants. The results showed that: 1. The results of the research on desirable characteristics and guidelines for developing professional education administrators in the 21st century found that the desirable characteristics and guidelines for developing professional education administrators in the 21st century were overall at a high level. When considering each aspect, it revealed that every aspect had a high level of opinions of desirable characteristics and guidelines that can be sorted in descending order: behavior and leadership, morality and ethics, skills, and roles and duties. 2. Results from research on the development of professional education administrators in the 21st century of school administrators in Loei Province is an era that has changed rapidly. There is the management of information technology in skills and abilities. There is a coordination initiative, innovation, and communication technology of 21st-century learning management skills. There is a coordination of supervision, monitoring, and performance assessment. School administrators can develop their potential in education administration independently, as well as support and promote the development of the morality and ethics of administrators. Moreover, school administrators must follow the moral principles as the basis, have good governance and professional ethics, and learn to develop themselves.
The Depiction of Hand Symbols (In) in Animated Series Naruto: Shippuden Episode 375

Naruto comics by Masashi Kishimoto are very popular comics. Besides Naruto comics are made in animated series films, and they are also available in the form of a game. Like the comicsâ€™ success, the Naruto animated series films were made up of hundreds of episodes. In the Naruto series, the most dominant element appears, namely the hand symbol. The hand symbol as part of the Ninja moves becomes an important element in this film and becomes an attraction for Naruto fans. In each episode of Naruto, there are depictions of hand symbols, one of which is in the Shippuden episode 375. This study aims to classify the types of hand symbols depicted on the characters of the animated film Naruto Shippuden episode 375 and the point of view of the depiction through descriptive methods. Data were collected through literature and observations of the animated series Naruto Shippuden episode 375. Hand symbols were collected through screenshots and tabulated. The results show that there are four depictions of hand symbols on the six figures. The character is depicted with six depiction points of view so that it affects the depiction of the hand symbol.
Igneability feature: an effective, easy and low-cost way to identify basic igneous rocks using wireline well logs in open hole wells

The correct identification of igneous rocks is of fundamental importance during drilling and to the quality of the initial assessment of their role in the petroleum systems. These rocks show characteristics in geophysical well logs that are distinct from those of sedimentary rocks. After calibrating with laboratory data, we propose a method to identify and characterize igneous rocks using basic geophysical logs. This method consists of a crossover between bulk density and photoelectric factor logs to identify basic igneous rocks in sedimentary sections, named "igneability feature". This log feature consists in using the bulk density log on the scale 2.0 to 3.0 g/cm³ in the same track as the photoelectric factor log on the inverted scale, from 12 to 2 b/e. Then, when the density log is to the right of the photoelectric factor, it denotes the presence of basic igneous rocks.Acid igneous rocks were also studied and characterized by a complementary method, which consists in a crossover between the gamma ray log and a factor calculated from the bulk density and photoelectric factor log curves. Thus, this method covers most of the varieties of igneous rock found in the Brazilian basins, such as Santos, Parnaíba and Paraná.
Research on Salient Reasoning for Commonsense Knowledge

Salient reasoning of commonsense knowledge can help search engines better understand users’ search intentions and improve users’ search experience with intelligent product recommendation. Existing reasoning methods only use triple classification to determine the rationality of different entities in the knowledge graph, ignoring the significant changes between entities due to different search scenarios, and thus cannot infer the user’s true search intent. In order to solve the above problems, this paper tries various methods to improve the performance of the salient commonsense reasoning model, and proposes a multi-task learning model based on entity type discrimination and entity commonsense saliency reasoning, and at the same time proposes a Prompt-based commonsense saliency inference model. The model proposed won the first place in both the preliminary and semi-finals in the commodity commonsense knowledge saliency reasoning track of the 2022 China Conference on Knowledge Graph and Semantic Computing.
Research on obstacle avoidance method Of in-situ blades grinding robot based on improved RRT

To solve the problems that existing grinding equipment and methods cannot grind the back of aeroengine blades, an in-situ grinding robot is proposed to maintain aeroengine blades through borescope. Meanwhile, path planning algorithm is improved from these aspects: adding bias strategy, improving sampling method and path smoothing to overcome shortcomings caused by standard rapidly exploring random tree algorithm (RRT). Consequently, simulation results show that the robot can avoid obstacles and reach the specified position quickly and smoothly to finish the grinding work on the back of blade. Simulation results also show that the improved RRT algorithm improves the path exploration efficiency and reduces the unnecessary oscillation in the motion of the robot. Moreover, the average path planning time is shortened and the average path length is cut down.
Pure-state certification by undoing Hamiltonian evolution leading to local thermalization

In a quantum-photonic experiment with an integrated quantum photonics network, we observe a quantum state locally evolve towards a thermal state. By undoing the evolution with the inverse network, we recover the input pure state.
The probabilities of the cut distribution laws

The limit measurement errors in the geodesy are determining for the normal distribution law, But the errors, exceeding the limits are throw aside and accidental errors are obey the cut law. Cut laws are not study enough. The article is leading the results of calculate the probabilities hit accidental measurements errors for intervals σ, 2σ, 2,5σ, 3σ for cut normal and cut logical distribution laws. The analysis was accomplished.The probabilities of the cut normal and normal laws is different immaterial. 0,043 - maximum of the different. The normal law replace to the cut normal law is not recommending. Probabilities of the cut law may to use, when it is allowing to avoid the repetition of the field measurements.
The Digital Revolution with NESAS Assessment and Evaluation

The Network Equipment Security Assurance Scheme (NESAS) is a security assurance framework for improvements in the mobile industry, and it includes a common requirement for security assessments of network equipment and evaluation of equipment vendors. Moreover, it ensures the security base to prove that network equipment has been designed according to legal guidelines. In this article, the authors overview NESAS definitions, explanation, and importance. In addition, the 5G Digital Revolution and its concepts, risk aspects, and the possible future enhancements. Finally, the authors discuss the European Union Cyber Risk Assessment over the recent years, which contains; a 5G risk assessment in the EU countries, the most significant threat in the EU, and some suggestions about governments’ action; there is a vital need for a proper technique to produce security evaluation and guarantee telecoms infrastructure and systems throughout the offering lifecycle focusing on developing security systems in all sectors and businesses and maintain the continuity of improvement.