Reviewerly/exHarmony huggingface dataset:
Crypto World: Unleashing the Power of Digital Space

A crypto currency is virtual money of tomorrow which that has cryptography for security. It is tough to forge this asset since the transactions are secure. Crypto currencies are classified as a subgroup of digital currencies and are also classified as a subset of alternative currencies and virtual currencies. It helps to eliminate a lot of hassle, and it behaves as the exchange for wallets, and traditional banks must catch up with the trending technology. It has the following incredible benefits. Prevention of fraudulent activities helps in immediate settlement, tracking identity theft and to provide access to everyone, with decentralization facility. Also it possess some of the disadvantage like Scalability, cyber security issues Price volatility and lack of inherent value, Built in deflation, no physical form, no valuation guarantee. The impact of crypto currency is Power to the Dark Web, speculations, politicization of money, apprehension among the central banks, the emergence of new markets. This research paper is a conceptual paper focusing on crypto currency as an alternative option to physical currency, its impact on the economy of the nation and issues and challenges associated with it
Full field strain measurement of braided composite structures

Braided composites consist of continuous fibers embedded in a matrix. Braid mechanical properties are influenced through selection of matrix and fibers and by modifying the braid manufacturing process. Control of braiding parameters allows for tailorable mechanical properties. The objective of this work is to utilize full-field strain measurement approaches for the assessment of braided composite structures. Two full-field strain measurement methods will be utilized (1) Three Dimensional Digital Image Correlation- 3D DIC and (2) Digital Volume Correlation-DVC. 3D DIC is an optical stereo camera based strain measurement method while DVC is an x-ray based tomographic approach that allows for volumetric strain measurement. The two correlation methods utilized in this study provide both surface and volumetric strain data for braided composite structures. The approaches outlined in this work are a critical first step towards better understanding the internal and external deformation and strains that occur within braided composite structures and results will be used towards analytical and numerical models for braided composites.
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Adaptive Adversarial Logits Pairing

Adversarial examples provide an opportunity as well as impose a challenge for understanding image classification systems. Based on the analysis of the adversarial training solution—Adversarial Logits Pairing (ALP), we observed in this work that: (1) The inference of adversarially robust model tends to rely on fewer high-contribution features compared with vulnerable ones. (2) The training target of ALP does not fit well to a noticeable part of samples, where the logits pairing loss is overemphasized and obstructs minimizing the classification loss. Motivated by these observations, we design an Adaptive Adversarial Logits Pairing (AALP) solution by modifying the training process and training target of ALP. Specifically, AALP consists of an adaptive feature optimization module with Guided Dropout to systematically pursue fewer high-contribution features, and an adaptive sample weighting module by setting sample-specific training weights to balance between logits pairing loss and classification loss. The proposed AALP solution demonstrates superior defense performance on multiple datasets with extensive experiments.
COVID-19: el efecto en la gestión educativa

COVID-19 constitutes a turning point that will mark a before and after, due to the global dimension that it reached in a short time since it was detected in Wuhan, China, on December 31, 2019 and the declaration made by the World Organization of Health (WHO) on March 11, 2020 when classifying it as a pandemic due to the speed of its spread in all countries. The medium and long-term impacts are not yet clearly seen, however, within those that are already visible, the impacts have been felt immediately in all dimensions of social life, including: political, economic, labor, legal, family, environmental, health and education. The unprecedented nature of this epidemiological contingency faces us with new challenges. In the field of educational management, it requires new practices that are imperative to innovate on the part of institution representatives, teachers, students and the family. Moreover, it also requires new participation schemes and action protocols with a perspective of anticipation and prevention. The purpose of this article is to reflect on the impact of this health emergency on educational management, some implemented actions and scenarios to consider the social responsibility of the educational system and training centers.
Result-oriented project management as a soft skills development methodology for students studying optical communication systems

The meaning of project management, soft skills concepts is analyzed. Various theoretical and methodological approaches to the soft skills topics are presented. The psychological and pedagogical study findings made from 2016 to the present are analyzed, indicating the adjustment methods and programs for soft skills and hard skills development levels. The indicators of emotional intelligence and critical thinking as important components in the structure of the soft skills set have been reviewed. A blueprint of soft skills development through result-oriented project management program for students studying optical communication systems is proposed.
Knowledge Sharing, Organizational Rewards and Life Satisfaction of Employees: A Study of Knowledge Intensive Firms

The success of knowledge intensive firms is dependent on knowledge management practices in the firm. A better knowledge management system comprises feasible strategies to identify, react and overcome problems inherited in knowledge resources. Employees of knowledge intensive firms are considered the prime resource in terms of knowledge creation, accumulation, sharing and protection. This research examines the impact of knowledge sharing intentions on the life satisfaction of employees working in knowledge intensive firms in Sri Lanka. A questionnaire was used to collect data from employees who are working in IT oriented firms in Sri Lanka. Respondents from different job categories and companies for the sample were selected using a stratified sampling method. Descriptive and correlation analysis of the respondents and responses were done to identify basic features of the sample. Study findings indicated that knowledge sharing in the profession by employees of knowledge intensive firms has strong positive influenced on their life satisfaction. Further, the analysis confirmed that organizational rewards mediate the relationship of knowledge sharing and life satisfaction. Findings of the study have contributed immensely to both theory and practice.
Designing Methodological System of Teachers` Personalized Training for Networking Activities

The research problem is related to the emerging need to prepare teachers for careers in the context of globalization and digitalization of education. The purpose of the study is to design and substantiate a methodological system of personalized training of teachers for network project activities that will foster their readiness to work in a digital school. The main components of the methodological system of personalized training of teachers have been presented and the modular polyvariant content of the training program has been proposed. Materials of this paper carry a practical value for teachers of pedagogical universities, as well as for employees of institutes of professional development of teachers.
A Study of State Management System in Manufacturing Processes using IoT

In the market increased diversification and globalization, manufacturing companies are making efforts to improve their business operations to enhance competitiveness. Business management, such as visualizing and analyzing business operations, is indispensable in such activities. Also, management to support manufacturing activities requires the utilization of IT technology such as IoT. However, we could not find any concept and framework of an information system that is for management by using state of manufacturing processes based on domain concepts in a manufacturing company's activity area and cooperates with their existing equipment. Therefore, we propose an easy-to-reconfigure state management system by using IoT based loosely coupled software components. We aim to realize that users of the system can manage and improve their activities by using states defined by their specific concepts, and acquired and visualized from manufacturing tools they have. In this paper, we propose a state management system model, and then we describe a method and results that we have demonstrated the system by using some manufacturing tools at a real manufacturing factory. Furthermore, based on the results, we discuss the usefulness of the state management system.
Phoneme Boundary Analysis using Multiway Geometric Properties of Waveform Trajectories.

Automatic phoneme segmentation is an important problem in speech processing. It helps in improving the recognition quality by providing a proper segmentation information for phonemes or phonetic units. Inappropriate segmentation may lead to recognition falloff. The problem is essential not only for recognition but also for annotation purpose also. In general, segmentation algorithms rely on training large data sets where data is observed to find the patterns among them. But this process is not straight forward for languages that are under resourced because of less availability of datasets. In this paper, we propose a method that uses geometrical properties of waveform trajectory where intra signal variations are studied and used for segmentation. The method does not rely on large datasets for training. The geometric properties are extracted as linear structural changes in a raw waveform. The methods and findings of the study are presented.
Modelling Frequency and Attestations for OntoLex-Lemon

The OntoLex vocabulary enjoys increasing popularity as a means of publishing lexical resources with RDF and as Linked Data. The recent publication of a new OntoLex module for lexicography, lexicog, reflects its increasing importance for digital lexicography. However, not all aspects of digital lexicography have been covered to the same extent. In particular, supplementary information drawn from corpora such as frequency information, links to attestations, and collocation data were considered to be beyond the scope of lexicog. Therefore, the OntoLex community has put forward the proposal for a novel module for frequency, attestation and corpus information (FrAC), that not only covers the requirements of digital lexicography, but also accommodates essential data structures for lexical information in natural language processing. This paper introduces the current state of the OntoLex-FrAC vocabulary, describes its structure, some selected use cases, elementary concepts and fundamental definitions, with a focus on frequency and attestations.
Study on Obstacles and Countermeasures of Curriculum Reform of E-commerce Specialty

The curriculum reform is affected by many factors, the rapid development of our country's social economy, higher education from elite to popular transformation of the key period, the reform of e-commerce curriculum is imperative, this paper analyzes the current e-commerce curriculum reform is facing obstacles, and points out its reform strategy.
Progress in the Construction of Marine Observation Data Sources on the Western Route of the Maritime Silk Road

This paper describes the process to build marine observation data sources of the National Marine Environment Forecast Center of the Ministry of Natural Resources through various channels, which has been relying on China's national basic marine observation system since 2013 and taking the western route of the Maritime Silk Road as the target through a variety of diplomatic channels and international cooperation channels, as well as scientific and technological cooperation and information technology methods. The data sources on the western route of the Maritime Silk Road are in a chain structure, including South China Sea ocean observation system which is autonomous, perfect and efficient, North Indian Ocean observation network which is autonomous, international cooperated, sharing, exchange with other forms of integration and initial formation system; rapid developing Mediterranean ocean observation system and loose Atlantic Ocean observation framework. This vast ocean observation data source project has not only made an important contribution to the disaster prevention of the Maritime Silk Road, but also laid a solid data foundation for the development of China's global ocean forecasting technology. There is no end to the Maritime Silk Road, and the exploration of the ocean observation data sources for the Maritime Silk Road is endless.
Advanced Data Structures

At some point while writing Perl code (most likely often), you will need to have to deal with large amounts of data. As you likely know, there is always more than one way to perform a task in Perl. That means there is always a "good" way and a "bad" way. Good might mean faster or less memory usage. In any event, this chapter will introduce you to different techniques you can use to deal with data.
Augmented reality in plastic surgery: recent applications and developments

Augmented reality(AR)is a technique that superimposes continuous computer-generated images onto real scenes. With the collaborative work of tracking module, registration module and display module, real-time fused images can be composed and shown. In recent years, AR has been applied in several medical fields, such as medical education, remote medical aid, navigation system, etc.Latest applications and developments of AR in plastic surgery was reviewed in this article.Key words: Augmented reality; Navigation system; Plastic surgery; Computer-assisted surgery
Clinical value of delayed percutaneous coronary intervention in the treatment of acute ST segment elevation myocardial infarction at different time windows

ObjectiveTo analyze the efficacy and safety of surgically clipped aneurysm neck for the treatment of intracranial aneurysm rupture.MethodsA total of 102 patients with intracranial aneurysm rupture treated in Weihai Central Hospital from May 2011 to May 2019 were selected. According to the treatment plan, they were divided into two groups, with 51 cases in each group. The control group underwent interventional therapy, and the observation group underwent surgical clamping of the aneurysm neck. The related efficacy indicators, functional indicators and complications were compared between the two groups.ResultsThe modidied Rankin scale score of the control group was 1.14±0.34, and that of the observation group was 0.83±0.26. The difference between the two groups was statistically significant (t=5.172, P<0.05). The recurrence rate of aneurysm in the control group was 23.53% (12/51), and that in the observation group was 7.84% (4/51). The difference between the two groups was statistically significant (χ2=4.74, P<0.05). The scores of physiological function, physiological function and emotional function of the observation group were higher than those of the control group (P<0.05). The incidence of complications such as cerebral infarction, cerebral edema, hydrocephalus and intracranial hemorrhage in the observation group was lower than that in the control group (P<0.05).ConclusionsSurgical clipping of the aneurysm neck can effectively treat the rupture of intracranial aneurysms with fewer complications and lower recurrence rate.Key words: Intracranial aneurysm; Operation clamping; Intervention
The Emerging Role of New Technologies in Vocational Education

Abstract The paper presents some essential tools in the field of 3D modelling for vocational education. The purpose of vocational training is to adequately prepare students for the needs of the industry. Over the last decade, the appearance of low-cost virtual reality (VR) technology has enabled it to be deployed across a broad range of educational institutions. VR as a system allows intuitive human-computer interaction and offers great benefits in many application areas important for educational process. In this paper, two VR studies in educational field were compared.
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Evaluation of mammography calcification detection system based on deep learning

ObjectiveTo evaluate the performance of a deep learning (DL) based mammogram calcification detection system.MethodsScreening digital mammographic examinations with standard cranio-caudal (CC) and medio-lateral oblique (MLO) views were performed in 1 431 women (5 488 mammogram images) who were enrolled between January and December in 2013. The DL system and a radiologist detect calcifications separately, and then both results are reviewed by a moreexperiencedradiologist. Sensitivities of the DL model and radiologist were compared. Different calcification morphology, distribution, BI-RADS categories, breast density and patient age were investigated by χ2 tests.ResultsFor DL system, sensitivity of all kinds of calcifications were 96.76% (7 649/7 905). The average false positive was 1.04 per image (5 706/5 488), 3.99 per case (5 706/1 431). The false positive rate was 42.73% (5 706/13 355). There was no significant differences for DL system with different calcification distribution, BI-RADS categories, breast densities and patient ages (P>0.05).ConclusionDeep learning based mammogram calcification detection system shows high sensitivity and stability, which may help to reduce the missing rate of calcification (especially the suspicious ones).Key words: Mammography; Suspicious calcification; Detection; Deep learning
Analysis of characteristics of highly cited papers in nursing management published in 12 nursing core journals from 2015 to 2017

ObjectiveAnalyze the distribution of high-cited papers on nursing management from 2015 to 2017, understand the research hotspots of nursing management in recent years, provide further reference for nurses to conduct research in this field in the future.MethodsBibliometrics method and visualization techniques were used to analyze the distribution of journals, fund support, thematic distribution, regional distribution of nursing management highly cited papers published in 12 nursing core journals.ResultsThere were 422 highly cited papers in nursing management from 2015 to 2017, and the total cited frequency was 4 709 times, and the average cited frequency was 11.16 times. Among them, 187 papers were funded, and the frequency of citation is 11.63 times. There are 235 non-fund articles, and the average frequency of citation is 10.79 times. The highest number of highly cited papers published in the  Research was 63, followed by 61 articles in the Chinese of Nursing and the Journal of Science . The research focuses on nursing human resource management, nursing quality management, nursing safety management and so on. The high cited papers were funded by provincial (municipality) level, and the average fund paper ratio was 44.31%. The authors are distributed in 28 regions.ConclusionsNursing personnel caught the attention of the hot spots of clinical research and paid attention to teamwork, which played an active role in promoting the overall level of nursing management.Key words: Nursing management; High-cited papers; Bibliometrics; Cited frequency; Visual analysis
Hybrid Naive Bayes with Pigeon Optimization for Classification of Opinion Mining

Twitter is a common way to express yourself and connect with others in the online world. Therefore, Twitter is measured a tremendous source of info for decision making and emotional analysis. When predicting the polarity of words, the analysis refers to a classification problem and then categorizes them into positive and negative emotions, in order to identify attitudes and opinions expressed in some way or form. Mental analysis through Twitter provides organizations with a quick and effective way to monitor public attitudes towards their brand, and directors. Recent research has focused on the different aspects and methods used to train sentiment classifiers for a set of Twitter data with different results. The main problems of the previous techniques are the accuracy of the classification, the sharpness of the data and the ridicule, since most of the tweets categorize and neutralize a high ratio of tweets. This study focuses on these issues and presents an algorithm for rating Twitter feed based on a hybrid approach. In our scheme is applies to different stages of pre-processing before placing the text in the classifier. The research notes show that the projected method has exceeded the previous limits and performs better compared to the corresponding measures.
Nonpartisan election information

2020 is an election year in the United States. As we know from both past elections and the current election season, mudslinging, hyperbole, misinformation campaigns, and fake news proliferate the media landscape. Finding and recognizing reliable, accurate, nonpartisan election information can be challenging. Fortunately, several websites offer reliable, accurate, nonpartisan, and balanced information on the election and about voting. Some sources include information on how to register to vote, who can register to vote, and explain voting rights. Other sources provide links to or compile information on candidate voting records, where candidates get their funding, where they stand on issues, and fact check their statements. And, still others allow voters to get personalized information about what will be on their specific ballots, such as all the candidates running for local, state, and national offices, as well as bond measures, propositions, and other ballot initiatives. The reviews included in this issue’s column comprise a sampling of reliable election websites spanning the various election topics mentioned above. Librarians can feel confident recommending these sites to their patrons looking for accurate, balanced, reliable election and voting information.
Research on the Intelligent Classroom Teaching Mode in Colleges and Universities under the Mobile Internet

In the actual college classroom, the phenomenon of students' low attention, low attendance, lack of interest in learning, old teaching methods, and teachers' lax supervision of students occur frequently, which reduces the effectiveness of college teaching. This paper analyzes the problems existing in the teaching of intelligence classroom in Universities under the background of information integration, big data and Internet plus education. At the same time, it also expounds the way of constructing smart classroom based on ＂rain classroom＂ technology, aiming at improving the effectiveness of teaching in universities.
Data Types in Ring

In the course of my career as a programmer and a manager of programming teams, I have observed a common symptom of low-quality code: poor mastery of data type systems. Data types are the foundation of any programming language. They are part of a “language inside the language,” and they define the nomenclature of what is possible to say in the language and the range of what is possible to do through its features. Unfortunately, data types are not deeply addressed in the majority of programming books and documentation. Decidedly, that won’t be the case of this Ring book.