Reviewerly/exHarmony huggingface dataset:
Στάσεις και απόψεις Ελλήνων της διασποράς σχετικά με το ορθογραφικό σύστημα της Eλληνικής και μια ενδεχόμενη αναθεώρησή του

Aim of the present paper is to explore the types of orthographic errors made by Greeks of the diaspora, specifically Greeks who live on the east coast of the U.S.A., as well the linguistic and extra-linguistic factors, which influence the shape, teaching and learning of the Greek orthographic system. The data stemming from two questionnaires distributed to the participants revealed that Greeks of the diaspora make less orthographic errors compared to Greeks who live in Greece. Greek of the diaspora prefer the preservation of historical orthography for reasons of national unity and recognize politics as a major factor affecting the shape of spoken and written language. Finally, they express their skepticism regarding a potential revision of the Greek orthography.
Deep learning for mortality prediction in patients with a de-novo or worsened heart failure

Abstract Background Heart failure (HF) is a heterogenous syndrome with complex pathophysiology. Biomarkers and clinical risk scores often fail to provide optimal patient-level precision in the prognostic stratification. As utilizing single observational timepoint, they do not capture the entire care pathway with variations in individual patient management. Electronic patient records provide an opportunity to develop new artificial intelligence (AI) strategies for comprehensive prognostic re-stratification reflecting diagnostic and therapeutic management. Purpose We sought to use deep artificial intelligence (AI) and develop an unbiased predictive algorithm for all-cause mortality in a cohort of patients hospitalized with a de novo or worsened HF. Methods In a cohort of 2449 HF patients hospitalized between 2011–2017, we utilized 151 451 patient exams from 422 parameters. They included clinical phenotyping, medication, ECG, laboratory, echocardiography, catheterization data or percutaneous and surgical interventions gathered on a routine clinical basis reflecting standard of care as captured in individual electronic records. The AI model development consisted of 101 iterations of repeated random subsampling splits into balanced training and validation sets. Results AI models yielded performance ranging from 0.83 to 0.89 AUC on the outcome-balanced validation set in predicting all-cause mortality at 30-, 90-, 180-, 360- and 720-day time-limits (Figure 1). The primary endpoint, 1-year mortality prediction model, recorded an 0.85 AUC accuracy. We observed stable model performance across all HF phenotypes: HFpEF 0.83 AUC, HFmrEF 0.85 AUC and HFrEF 0.86 AUC, respectively). Conclusion Our findings present a novel, patient-level, AI-based risk prediction of all-cause mortality in heart failure with a robust accuracy across its phenotypes. This suggests the potential of AI based predictive models in a point-of-care approach to guide clinical risk stratification. Funding Acknowledgement Type of funding sources: Foundation. Main funding source(s): VZW Cardiovascular Research Center Aalst
ON THE WAY TO THE PROFESSIONAL ACTIVITY OF A PSYCHOLOGIST

The article discusses the importance of the professional activity of a psychologist, its specifics, features, as well as types of psychological assistance, such as counseling, psychological rehabilitation, correction, psychotherapy, training, education, and prevention.
Research Guides: MUS 234: Harmony & Form IV: Find Web Resources

A guide for students in Dr. Stanziano's MUS 234 class composing in a particular musical style. Areas of interest
Comparative Analysis of Ranking Algorithms Used On Web

With the evolution in technology huge amount of data is being generated, and extracts the necessary data from large volumes of data. This process is significantly complex. Generally the web contains bulk of raw data and the process of converting this data to information mining process can be performed. At whatever point the user places some inquiry on particular web search tool, outcomes are produced with respect to the requests which are dependent on the magnitude of the document created via web information retrieval tools. The results are obtained using calculations and implementation of well written algorithms. Well known web search tools like Google and other varied engines contain their specific manner to compute the page rank, various outcomes are obtained on various web crawlers for a same inquiry because the method for deciding the importance of the sites contrasts among number of algorithm. In this research, an attempt to analyze well-known page ranking calculation on the basis of their quality and shortcomings. This paper places the light on a portion of the extremely mainstream ranking algorithm and attempts to discover a better arrangement that can optimize the time spent on looking through the list of sites.
Technology Enabled Learning Experience Among International Baccalaureate Students Through Experiential Mobile Learning App

In today’s world of digital technologies, the number of mobile apps used from the billions of users around the world appears to be increasing. However, keeping track of all these mobile apps on their efficiency and effectiveness becomes inevitable for any educational institutions that wishes to incorporate mobile apps as an avenue for Blended teaching and learning. During the process of implementing Blended learning, it is quite often for pedagogical community to decide on the best pedagogical approaches for the delivery of their teaching content to their students. Technology-Enabled Learning is one such feature that is taken to refer to the application of some form of digital technology to teaching and/or learning in an educational context. In this research study an attempt has been made to examine the BeEd Experiential Mobile Learning App for its acceptance among the two International Baccalaureate Schools with a population of 510 students. Students from Grade 5 until Grade 9 were asked to respond to the online survey questionnaire. Findings of this research study reports on the responses based on quantitative analysis received from the 275 students who had responded the survey questionnaire. The results of the analysis showed the student’s satisfactions towards the usage of the BeED Mobile App to be positive with respect to the three variables, Knowledge, Activity and Reflection.
Implications of equity theory on the job satisfaction levels of the academic staff at business faculties in Private Universities in Jordan

Motivation is viewed as one of the most dominant factors that affect human performance in carrying out tasks. Among various behavioral-motivational theories, the Equity Theory of Motivation has been examined in this paper in conjunction with employees‟ job satisfaction. The participants were the academic staff members of business faculties at six Jordanian private universities. Data were collected using a questionnaire survey that consisted of two parts. The outcomes of the study indicated that there is an immense support for a positive relationship and a robust correlation between the equity of the wage and incentive system, job satisfaction, and job satisfaction related variables (staff turnover, absenteeism, job performance and productivity, work engagement, and work relationship with superiors). The results also showed that there was statistically no significant evidence that indicated differences in the level of job satisfaction related to equity factor and demographics (gender, age, marital status, income, and academic ranking).
Generic Attention-Model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers

Transformers are increasingly dominating multi-modal reasoning tasks, such as visual question answering, achieving state-of-the-art results thanks to their ability to contextualize information using the self-attention and co-attention mechanisms. These attention modules also play a role in other computer vision tasks including object detection and image segmentation. Unlike Transformers that only use self-attention, Transformers with co-attention require to consider multiple attention maps in parallel in order to highlight the information that is relevant to the prediction in the model's input. In this work, we propose the first method to explain prediction by any Transformer-based architecture, including bi-modal Transformers and Transformers with co-attentions. We provide generic solutions and apply these to the three most commonly used of these architectures: (i) pure self-attention, (ii) self-attention combined with co-attention, and (iii) encoder-decoder attention. We show that our method is superior to all existing methods which are adapted from single modality explainability.
MHz2k: MPC from HE over $\mathbb{Z}_{2^k}$ with New Packing, Simpler Reshare, and Better ZKP

We propose a multi-party computation (MPC) protocol over \(\mathbb {Z}_{2^k}\) secure against actively corrupted majority from somewhat homomorphic encryption. The main technical contributions are: (i) a new efficient packing method for \(\mathbb {Z}_{2^k}\)-messages in lattice-based somewhat homomorphic encryption schemes, (ii) a simpler reshare protocol for level-dependent packings, (iii) a more efficient zero-knowledge proof of plaintext knowledge on cyclotomic rings \({\mathbb Z}[X]/\varPhi _M(X)\) with M being a prime. Integrating them, our protocol shows from 2.2x upto 4.8x improvements in amortized communication costs compared to the previous best results. Our techniques not only improve the efficiency of MPC over \(\mathbb {Z}_{2^k}\) considerably, but also provide a toolkit that can be leveraged when designing other cryptographic primitives over \(\mathbb {Z}_{2^k}\).
Analysis on Challenges and Responses of Library and Information Service in Digital Information Environment

In the context of the era of digital information, library and information services can provide readers with better, more diverse and more convenient services. While digital information promotes the perfect development of library and information services, it also faces many challenges in its services. Based on this, this article applies literature research and other methods to analyze the many development challenges faced by library and information services in the digital information environment, and explores strategies and specific methods for adapting to build a more complete library and information service system and improve its service quality. To promote the healthy and long-term development of the library industry.
Parental Support for Literacy Development of Early Grade Children during COVID-19 School Closures in Northern Nigeria

The COVID-19 pandemic that began in early 2020 has had consequences for children's education globally, as schools closed and parents found themselves playing the role of teacher, alongside their economic and other community roles. This study aims to explore the experiences of parents in northern Nigeria as they attempted to support their primary school children's reading development while schools were closed. We conducted in-depth qualitative interviews with 15 middle- and low-socioeconomic status parents in Kano State, Nigeria. Using thematic analysis, we identified challenges faced by parents as well as unexpected positive effects of the pandemic. Challenges included the lack of textbooks and other appropriate learning materials, time pressures, and lack of knowledge of strategies to teach reading. However, parents noted that the extra time they had spent together during lockdowns had led to improved relationships in the household, and that they had been able to spend more time discussing moral development and discipline with their children. In summary, this sample of parents believed that the pandemic would not have severe impacts on their own children, as they were making efforts to support learning at home. However, they had concerns for children in Nigeria more broadly, particularly those whose parents were not literate, as they would have little access to learning outside school. Recommendations for the Nigerian government and other stakeholders include making learning materials available for home use, increasing the use of educational radio and television programming, and developing simple literacy assessments for parents to monitor children's progress.
Blood Vessels Extraction from MRA Images by a Region Growing Algorithm Based on a New Nonlinear Contrast Stretching Function and Shearlets Frame

Region growing, in a simple version, is a segmentation process, which having pixels as seeds, pixels with the same intensities and connected them are added to the area gradually, and finally presents a binary image that contains the object or objects of the target. So far, many binary segmentation techniques have been developed to extract target objects, with the common disadvantage that they do not perform the extraction task completely. Frames as the generalization of orthogonal bases are used scarcely in these algorithms. In this paper, a new nonlinear contrast stretching function is introduced, and then, based on the contrast stretching function andshearlets frame, correct initialization seeds are extractedand then the region growing algorithm applyto the image. The results presented on synthetic images and real medical images show the advantages of our technique to those recently proposed.
A Comparative Study on Teaching Writing Through Task Based Instruction and Group Investigation Method: A Quasy-Experimental Study

This paper explains the result of the research conducted in order to find out: (1) whether there is a significant difference in writing achievement between the students taught using Task-Based Instruction and Group Investigation method; and (2) which method has a better result in writing, the group taught using Task-Based Instruction or using Group Investigation method. The method used within this research is quasi-experimental design. This research was led at SMA BATIK 2 Surakarta in the academic year of 2018/2019. The population of this research is the eleventh grade of SMA BATIK 2 Surakarta. The samples of this research are the XI IPA 3 as the experimental class which consists of 28 students and XI IPA 1 as the control class which consist of 28 students. The data within this experiment were gathered by the usage of mechanism to collects it. The data were analyzed using t-test formula. The calculation of the t-test data shows that t observation (to) = 2.02 is higher than t table (54, 0.05) = 1.960. Thus it can be concluded that there is a significant difference in writing achievement between the students taught using Task-Based Instruction and those taught using the Group Investigation method. The average score of the students taught using the Group Investigation is 77.64. Meanwhile, the average score of the student taught using Task-Based Instruction is 75.80. Therefore, it can be concluded that Group Investigation method has a better result in writing than Task-Based Instruction method.
The asymmetric effect of internet access on economic growth in sub-Saharan Africa: Insight from a dynamic panel threshold regression

This article investigates the asymmetric effect of internet access (index of the internet) on economic growth in 42 sub-Saharan African (SSA) countries over the period 2008-2018. The estimation procedure is obtained following a dynamic panel threshold regression technique via 1000 bootstrap replications and the 400 grids search developed by Hansen (1996, 1999, 2000). The investigation first explores the presence of inflection points in the relationship between internet access and economic growth through the application of Hansen's threshold models. The finding from the nonlinearity threshold model revealed a significant internet threshold-effect of 3.55 percent for growth. The article also examines the linear short-run effect of internet access on economic growth while controlling for the effects of private sector credit, trade openness, government regulation, and tariff regimes. The marginal effect of internet access is evaluated at the minimum, and the maximum levels of government regulation and tariffs regime are positive. On the other hand, the minimum and maximum levels of private sector credit and trade openness are negative via the interaction terms. The article advances the literature by its nonlinear transformation of the relevance of internet access on economic growth by exploring interactive mechanisms of: internet access versus financial resource, internet access versus trade, internet access versus government regulation, and internet access versus the tariff regimes from end-user subscriptions. In policy terms, the statistical significance of the joint impact of government regulations and tariff regimes is relevant in the operation of the telecommunication industry in SSA countries.
Video Is Graph: Structured Graph Module for Video Action Recognition

In the field of action recognition, video clips are always treated as ordered frames for subsequent processing. To achieve spatio-temporal perception, existing approaches propose to embed adjacent temporal interaction in the convolutional layer. The global semantic information can therefore be obtained by stacking multiple local layers hierarchically. However, such global temporal accumulation can only reflect the high-level semantics in deep layers, neglecting the potential low-level holistic clues in shallow layers. In this paper, we first propose to transform a video sequence into a graph to obtain direct long-term dependencies among temporal frames. To preserve sequential information during transformation, we devise a structured graph module (SGM), achieving fine-grained temporal interactions throughout the entire network. In particular, SGM divides the neighbors of each node into several temporal regions so as to extract global structural information with diverse sequential flows. Extensive experiments are performed on standard benchmark datasets, i.e., Something-Something V1 & V2, Diving48, Kinetics-400, UCF101, and HMDB51. The reported performance and analysis demonstrate that SGM can achieve outstanding precision with less computational complexity.
Agile: Can the Wrong Tool Derail Your Transformation?

When it comes to agile tools, one size does not fit all. Here are three common mistakes and how to avoid them
Penerapan Model Pembelajaran Problem Based Learning Untuk Meningkatkan Hasil Belajar Ipa Kelas 2 Sdn 16 Timbulun

The purpose of this study was to improve science learning outcomes for grade 2 students of SDN 16 Timbulun, Tanjung Gadang District, Sijunjung Regency, West Sumatra. The research method used is the classroom action research method (CAR) which was carried out at SDN 16 Timbulun in the 2019/2020 school year for 25 Class 2 students. The research design used is classroom action research. This research was carried out for two actions (cycles). Each action includes planning, implementation, observation and reflection. Data collection techniques through learning outcomes tests. The results showed that there was an increase in learning outcomes through the use of the problem based learning model for class 2 SDN 16 Timbulun. The results showed that the application of the Problem Based Learning (PBL) learning model can improve the learning outcomes of grade 2 students starting from pre-action, cycle I and cycle II, namely 69.65 in the pre-action stage increased to 79.65 in the first cycle and again increased to 82 ,86 in cycle II. The conclusion of this study is that the application of the Problem Based Learning (PBL) learning model can improve the learning outcomes of grade 2 students at SDN 16 Timbulun in science subjects.
VLSI Architecture of Modified S-Box with 256-bit Key for High Speed FPGA-IOT Applications

The enhancement of the VLSI based circuit structure and parameter performance is going on to meet the requirement of the 5th generation FPGA internet of things applications. The security is major concern as developing the application under 5G-IOT. FPGA technology is upgrading to enhance the performance of latency and area. Many of the security algorithm is already developed but its less perform under advance FPGA-IOT constraints. The advance encryption standard is one of the best security algorithm and using in real time high secure application but its need to modify for FPGA-IOT applications. This paper proposes a high performance and area-efficient VLSI architecture of Modified S-Box with 256-bit Key. Modified-AES algorithm is a fast lightweight encryption algorithm for advance security with low latency. Simulation is performed using the Xilinx ISE 14.7 Software with verilog language. The simulation results are verified using Isim simulator in Xilinx test bench.
A New Ecosystem for Digital Identity Verification Using Blockchain

Digital data collection and sharing provide tremendous opportunities for fraud offenders through the digitalization of infrastructure. Identity theft is one such fraud which has created a need for new security approaches. Modern technologies such as blockchain can provide solutions to many problems with a centralized identification system. In addition, it improves data transparency, facilitates the self-execution of Know Your Customer (KYC), improves efficiency, and can improve customer experience. In this chapter, we propose a decentralized model to ensure data security and privacy and provide a collaborative ecosystem design for single KYC verification among different service providers. More specifically, we propose a first of its kind decentralized data model alongside blockchain technology to ensure security against identity theft. Thus, our model solves repetitive and costly independent KYC processes for different service providers. The design increases the users’ ease by enabling them to control their data and remove the need to verify the same details repeatedly.
MODERN EDUCATIONAL TECHNOLOGIES IN THE TEACHING OF ENGINEERING AND COMPUTER SCIENCES

Article has survey character and is based on the discussion on technologies for teaching computer and engineering Sciences through the use of modern digital tools and best practices to engineering courses in the period of the pandemic. Experts from Finland, Croatia and France took part in the discussion. The discussion was held within the framework of a foresight session organized by the Foundation “center for strategic research” North-West “ in partnership with the International scientific and methodological center of MEPhI. The article deals with the following topics: collecting a digital trace, features of interaction with students online, psychological aspects of distance learning. also, attention is paid to various platforms and SOFTWARE for providing a remote learning process.