Reviewerly/exHarmony huggingface dataset:
Combining Hashing and Abstraction in Sparse High Dimensional Feature Spaces

With the exponential increase in the number of documents available online, e.g., news articles, weblogs, scientific documents, the development of effective and efficient classification methods is needed. The performance of document classifiers critically depends, among other things, on the choice of the feature representation. The commonly used "bag of words" and n-gram representations can result in prohibitively high dimensional input spaces. Data mining algorithms applied to these input spaces may be intractable due to the large number of dimensions. Thus, dimensionality reduction algorithms that can process data into features fast at runtime, ideally in constant time per feature, are greatly needed in high throughput applications, where the number of features and data points can be in the order of millions. One promising line of research to dimensionality reduction is feature clustering. We propose to combine two types of feature clustering, namely hashing and abstraction based on hierarchical agglomerative clustering, in order to take advantage of the strengths of both techniques. Experimental results on two text data sets show that the combined approach uses significantly smaller number of features and gives similar performance when compared with the "bag of words" and n-gram approaches.
An E-Learning Approach to Data Information Literacy Education

This paper presents the University of Minnesota Libraries' contributions to the ongoing Data Information Literacy project, an IMLS-funded project to educate the next generation of escientists through developing a library-run curriculum.Our project team at the University of Minnesota interviewed graduate students in Civil Engineering to determine their needs in data management and curation.We found many skill areas that were missing or needed support in the graduate program and proposed a list of learning outcomes that might be addressed through library training efforts.This paper will focus on our resulting approach to providing Data Information Literacy (DIL) instruction utilizing Google tools (Sites, Drive, YouTube) to present a self-paced, interactive online course.
Transitive Inference by Visual Reasoning

Two experiments are reported that investigated the influence of linear spatial organization on transitive inference performance. Reward/no-reward relations between overlapping pairs of elements were presented in a context of linear spatial order or random spatial order. Participants in the linear arrangement condition showed evidence for visual reasoning: They systematically mapped spatial relations to conceptual relation and used the spatial relations to make inferences on a reasoning task in a new spatial context. We suggest that linear ordering may be a “good figure”, by constituting a parsimonious representation for the integration of premises, as well as for the inferencing process. The late emergence of transitive inference in children may be the result of limited cognitive capacity, which – unless an external spatial array is available – constrains the construction of an internal spatial array.
Main directions of innovative transformations in higher education

The article highlights the main directions of innovative transformations in pedagogy. The methodological concept of research based on the following provisions is highlighted: implementation of a complex of approaches of a scientific and methodological direction in the professional training of future specialists; organization of the main directions of innovative transformations in higher education; determination of the principles of functioning of the educational process; determination of essential properties and features of the studied object of innovative transformations in higher education; determination of prospects for the development of the main directions of innovative transformations in higher education. The main directions of innovative transformations in higher education have been clarified. The essence of the content of innovative pedagogical technologies was considered, and the essential features and ways of development of pedagogical innovations were listed, divided into intensive and extensive. For the purpose of effective training of education seekers, the conditions for their innovative activities have been formulated. Distance learning is presented in the article as a set of information technologies that students need to: ensure the volume of material for their competitiveness in the labor market; for use in the learning process of interactive interaction of students and teachers; to enable students to work independently in order to master the material; for assessment during training and monitoring of their knowledge and skills.
Retracted: Prediction Algorithm of Young Students’ Physical Health Risk Factors Based on Deep Learning

[This retracts the article DOI: 10.1155/2021/9049266.].
Retracted: Optimization of Remote Public Medical Emergency Management System with Low Delay Based on Internet of Things

[This retracts the article DOI: 10.1155/2021/5570500.].
Retracted: An Ensembled Spatial Enhancement Method for Image Enhancement in Healthcare

[This retracts the article DOI: 10.1155/2022/9660820.].
The efficiency of the Saudi Capital Market from its weak - form during the Corona pandemic (COVID-19) "A comparative study between the business sectors listed in the Saudi Capital Market"

The study aimed to identify the level of efficiency of the Saudi capital market and the business sectors included in it during the Corona pandemic, with a comparison between these sectors. The daily indices values of the capital market and the business sectors included in it were relied upon during the pandemic period from 2020 to 2022. The indicators were described through the arithmetic mean, standard deviation, and a graphical display of the trend graph for each indicator. To test the efficiency of the capital market and the sectors included in it, the Jarque – Bera test was used to test the Normality, the Run test to test the random walk of the indices values, and Augmented Dickey Fuller test (ADF) to test the stationary of the indices values series during the study period. The most important results of the study were the inefficiency of the weak form of the Saudi capital market and the sectors included in it during the pandemic period. The study also found that the sectors most affected by the pandemic are the transportation sector, the construction sector, public utilities, the entertainment sector, and the retail sector for luxury goods. While the sectors least affected by the pandemic are the pharmaceutical sector, health care, food, energy, and the telecommunications sector. The most important recommendations were that the individual investor should be careful when investing financially in business sectors that work in the field of entertainment and luxury goods in periods of natural crises, and it is preferable to invest in basic goods and services sectors, and the Capital Market Authority should educate investors on how financial investment is made in light of crises , while achieving high transparency, and fully providing data to investors so that no unusual returns or losses are achieved.
Penerapan Model Pembelajaran Kooperatif Tipe TGT (Teams Games Tournaments) Terhadaphasil Belajar dan Motivasi Belajar Siswa

This research was motivated by the low learning outcomes and learning motivation of grade VIII students of SMPN 1 IV Jurai, Pesisir Selatan Regency. The purpose of this study was to determine the influence of the application of the Teams Games Tournaments learning model on mathematics learning outcomes and motivation of grade VIII students of SMPN 1 IV Jurai, Pesisir Selatan Regency. The type of research used in this study is experimental research with research design is post-test only control group design. The population of this study was all grade VIII students of SMPN 1 IV Jurai, South Coast District. The sampling technique used in this study was random sampling so that class VIII4 was selected as an experiment class with twenty-one students and class VIII1 as a control class with twenty-two students. The instruments used are learning outcomes tests and student learning motivation questionnaires.
Teacher training before and during the Covid19 pandemic in higher education

In teacher training there is a before and after the pandemic (Picón, et al., 2020). Although there was a scheme before covid-19 (Mendiola et al., 2020), it has now been detected that said training that was given in person (Suárez, 2020) was insufficient (Cardona et al., 2020) since the health emergency (Garavito et al., 2020) had a precedent that showed a different reality. This research determines the training provided before (Prieto et al., 2020) and after the pandemic (Zavala et al., 2020), the characteristics of groups of teachers who, framed in a digital divide (Fernández et al. , 2020) were adapting to forced marches with digital and virtual scenarios (Argandoña et al., 2020) for which they were not prepared (Trejos et al., 2020) and that generated teaching and learning problems with students who claimed to be knowledgeable. of technology (Ardini et al., 2020) but who also attended the paradigm of digital youth who only knew about social networks but not about educational platforms (Sarobe et al., 2020). Studies were carried out on 80 teachers from two higher education institutions and 104 students through probabilistic, homogeneous, expert, systematic random sampling, by quotas, of which 80% were not prepared for virtual classes, 20% who If he considered himself prepared, it is because he was already teaching online classes, among other relevant data declared in this document. This through a cross-sectional study conducted in 2019 and 2020. Therefore, it is considered essential that all teachers and students are always trained on digital educational platforms even when the subjects are face-to-face. Teachers must always be up to date to provide quality education and show that a teacher should always be the best student by being up to date.
Construction of College Students’ Management Informatization Ecosystem Based on Data Analysis Technology

College students’ management informatization ecosystem can help college students better manage information and resources, thus improving learning and life efficiency. It’s important to introduce data technology into the college student management informatization ecosystem, which can better realize the extraction of student behavior fluctuation information and achieve more targeted student management decisions. The current research lacks consideration of its future development trend, such as the impact of the application of technologies, including artificial intelligence, big data Fenix, and the Internet of Things. This paper studies the construction of college students’ management informatization ecosystem based on data analysis technology. Firstly, the design of the data fusion scheme applied to the college students’ management informatization ecosystem is carried out, and the idea of the scheme is given. Aiming at the big data of students’ learning and living behaviors, this paper digs deep into the value of data information, and extract historical student behavior characteristics, providing a basis for short-term student behavior prediction and management decision-making planning and implementation for the college students’ management informatization ecosystem. Based on historical student behavior data and its characteristic data, the XGboost algorithm is used to quantify and extract the importance of each influencing factor on student behavior fluctuations. Experimental results verify the effectiveness of the method proposed in this paper.
BLOCKCHAIN BASED TRUST SYSTEM FOR COUNTERFEIT PRODUCT DETECTION

With increase in new products, there is always a problem of counterfeits in almost every industry.It is essential to have a system which can check details of product and identify whether the product is genuine or counterfeit.Counterfeit plays vital role in today's world as it can affect many industries resulting in loss of sales, reputation, profits, ideas.In order to fight these counterfeit products, we have used blockchain technology.Blockchain technology is a decentralized, distributed ledger that stores transactions in the form of blocks in many databases that are interlinked to each other via chains.Blockchain is stable and secure as it has immutable property due to which the data once stored in blockchain nodes cannot be modified.By using blockchain technology, there is no need for customers to rely on third party for confirming product originality.Our project uses QR (Quick Response) codes to combat the problem of counterfeit.QR code scanner will be used by the buyer to scan the product for genuineness, as the QR code of each product is connected to our blockchain.System will check product's unique code with the entries in our blockchain database.If code matches, the notification will pop out to customer stating product is genuine.If not, customer will receive notification that product is counterfeit.
Analysis of University Student Motivation in Cross-Border Contexts

The development of the personality of university students can determine their affinities for certain disciplines; therefore, it is important to know their specific socio-demographic and motivational profile, what motivates them to start a certain university degree and what encourages them to continue with it, which can help to adapt the teaching methodology. A total of 292 university students from the University of Granada (Ceuta and Melilla campuses) participated in this quantitative study with a descriptive, cross-sectional design, in which motivation and social skills were analysed. Among the results, it can be highlighted that the student population is mainly female, with a higher level of motivation. Sociability, communication, thinking (optimistic or pessimistic), empathy and self-confidence are skills that affect university students’ motivation levels. This study highlights the importance and impact of students’ motivation on their learning and the development of their social competence, so it is essential to carry out educational interventions that promote these types of skills, especially in cross-border contexts, which can be demotivating environments.
Techno-pedagogical Skills of Prospective Teacher Educators

In teacher education, Techno-pedagogical skills involves the development of knowledge and skills for using general computer applications, learning specific software programs and internet tools confidently and competently. Directly or indirectly teacher education programme will benefit from techno pedagogical skills. Technological pedagogical content knowledge extends beyond proficiency with technology for personal use to an understanding of how technology can be integrated with subject matter and the technology itself. Therefore, the teachers of the present generation should not only have content and pedagogy knowledge, they also should be well versed in technology and to transact knowledge to the students of the current digital society. In the present study the investigator is intended to study the Techno-pedagogical skills of Prospective Teacher Educators. The investigator used purposive random sampling technique for selecting the sample. The sample of the study is Prospective Teacher Educators studying in the M. Ed. colleges affiliated to Tamil Nadu Teachers Education University, Chennai, Tamil Nādu. The percentage analysis shows that the Level ofT echno-Pedagogical skills of Prospective Teacher Educators is average. The ‘t’ test results reveal that there is no significant difference in the Techno-Pedagogical skills of the Male and Female Prospective Teacher Educators, but the female Prospective Teacher Educators are slightly better than the male Prospective Teacher Educators. It is also found out there is no significant difference in the Techno-Pedagogical skills of the Under-graduate and Post-graduate Prospective Teacher Educators. Further, it is therefore concluded that the Under-graduate Prospective Teacher Educators are slightly better than the Post-graduate Prospective Teacher Educator sintheir Techno-Pedagogical skills. Therefore, it is imperative that teachers should be competent enough to use ICT effectively in the classroom situation. Digital technology helps a teacher for being an effective technology user, a lifelong learner in advanced ways, make effective technological pedagogical content knowledge as well as an effective mentor and facilitator.
Locals’ Perceptions Towards English For Local Tourism Industry

This research aims to study the locals’ perceptions towards English in association with the local tourism destination development. Since language and tourism are interwoven, the use of language is linked to the likelihood of its popularity or infamy. It is undeniable that Indonesia requires English in all tourism sectors. The problem is that Indonesian's English proficiency in general is still in the lowest position among the members of the MEA. This has become one of the obstacles to make local tourism sites more competitive in the international sphere. Recognizing the communities’ perceptions to English would be a meaningful step to advance the potentials of the local tourism destination. Therefore, two issues that this research is concerned about are: the locals’ perceptions and the problems that might pose if English were introduced. The descriptive qualitative method employed. This research is located in Langgher Dhatang, Dusun Pogag, Desa Palalang, Kec. Pakong, Kab. Pamekasan, Madura. We interviewed thirteen local people living around the location. The participants’ involvement decision was made based on the assumption that they will have a direct impact for its language planning. We designed a questionnaire in a Google Form to ask and marked the answers in accordance with the participants’ responses. The research shows various attitudes towards English: most of them (76,9%) believe that English is important for Langgher Dhatang. 15,4% of the participants who have no idea either English will have a positive impact or not for local tourism development. The rest (7,7%) sees that English is inconsequential to its promotion. The problems that could arise include a low level of motivation in learning (15,4%), a low level of education (69,2%), and the youth ignorance in tourism site development (7,7%).
Fast Fingerprinting of Cloud-based NISQ Quantum Computers

Cloud-based quantum computers have become a reality with a number of companies allowing for cloud-based access to their machines with tens to more than 100 qubits. With easy access to quantum computers, quantum information processing will potentially revolutionize computation, and superconducting transmon-based quantum computers are among some of the more promising devices available. Cloud service providers today host a variety of these and other prototype quantum computers with highly diverse device properties, sizes, and performances. The variation that exists in today‘s quantum computers, even among those of the same underlying hardware, motivate the study of how one device can be clearly differentiated and identified from the next. As a case study, this work focuses on the properties of 25 IBM superconducting, fixed-frequency transmon-based quantum computers that range in age from a few months to approximately 2.5 years. Through the analysis of current and historical quantum computer calibration data, this work uncovers key features within the machines, primarily frequency characteristics of transmon qubits, that can serve as a basis for a unique hardware fingerprint of each quantum computer.
The Economics of Cryptocurrencies: Finance in Digital Era

Global economic markets are encountering apprehensions and susceptibilities after the pandemic of COVID-19. Investment patterns are becoming restrained because of uncertain global scenarios and reduced GDP worldwide. World economies are moving towards digital era and investors are becoming more open towards the newest forms of investments. Due to the uncertain scenarios, investors globally are looking forward to some lucrative forms of investments and cryptocurrencies are the ray of hope for global investors. The present study is attempt to explore the changing dynamics of cryptocurrencies with the market uncertainties. Volatility of five cryptocurrencies, namely Bitcoin, Ethereum, XRP, Chainlink and Bitcoin Cash are analysed using the Generalised AutoRegressive Conditional Heteroskedasticity Model. Results showed that the investors preferred taking cautious decisions and invested more in famous bitcoin rather than other cryptocurrencies.
A Decentralized and Privacy-Preserving Data Sharing Framework using Blockchain Technology

Sharing data has evolved into an essential component of today's society as a direct result of the proliferation of new technologies and the growing prevalence of digitalization. Traditional methods of data sharing, on the other hand, frequently encounter considerable hurdles in terms of both privacy and security.With its immutability and indestructibility, blockchain technology has emerged as the most reliable all-in-one cryptosystem for protecting online transactions. Some businesses, IT managers, and programmers have taken an interest in the blockchain network because of its potential as a decentralized infrastructure. In addition to safeguarding transactions from modification, this solution also serves as a historical audit trail for the network. This paper presents a decentralized data sharing architecture that uses blockchain technology and protects users' privacy. The goal is to address the problems that have been identified. The framework that has been proposed makes use of a combination of cryptographic methods and the technology of blockchains in order to enable secure, efficient, and decentralized data sharing while still maintaining users' anonymity. In order to improve data privacy and scalability, the framework makes use of a hybrid blockchain method. This technique incorporates the positive aspects of both public and private blockchains. The usefulness of the suggested framework in maintaining data privacy and security while also enabling efficient and decentralized data exchange is demonstrated by the results of an evaluation that uses a prototype implementation as the basis for the evaluation.
Human Pose Estimation Using Deep Learning Models

In the last decade, there has been a lot of research into recovering 3D human poses from images. The current datasets need to address frequent exposure estimation problems adequately. However, these are shared resources to assess, inform, and contrast various models. Deep learning models are widely utilized and perform at high levels in many branches of research and engineering. So these models are used in this study with the help of the OpenCV and Keras libraries, which are open-source programs. Providing significant improvements in diversity and difficulty, the MPII Human Pose dataset is used to train and test the ResNet50 and VGG16 models. The validation rate of the dataset is shown to evaluate the model's performance.