Reviewerly/exHarmony huggingface dataset:
A Study on the Innovation Procurement System: Focusing on the diversification of procurement ways

Public procurement is the purchase of necessary goods, services, and construction by public institutions. Since public procurement uses taxes as a resource, efficiency should be prioritized in public procurement. However, considering that the purpose of public procurement is to promote the public interest, public entities can intervene in the market beyond the status of buyers.&#x0D; In the era of the 4th Industrial Revolution, it is important to preoccupy the early market. It is difficult to induce corporate innovation only with traditional policies, such as preferential treatment of SMEs in the public sector. Creating new demand in the market, such as the purchase of prototypes by the public sector, can lead to corporate innovation, which is the starting point for innovation procurement. Innovation procurement can induce private innovation, and the problems faced by the public sector can be solved using private innovative ideas.&#x0D; The current innovation procurement system of Korea focuses on ‘Pre-Commercial Procurement’(PCP)'. It is necessary to support from the R&amp;D stage of the product and create a new market by linking it with public procurement. Therefore, the 'Public Procurement of Innovation’(PCI) should be introduced in innovation procurement.
Implementing Cross-Platform Business Logic in Mobile Applications using Hexagonal Architecture

&lt;p&gt;Most modern mobile applications need to be available on iOS and Android. Frequent code sharing is desirable. While dedicated cross- and multiplatform development tools achieve this goal, there are also situations where more flexibility is necessary. If code for one platform already exists or if, for example, the UI needs to be highly platform-optimized, a high volume of shared business logic could be one of the main implementation goals. The Hexagonal Architecture is a global architecture, providing an extendable approach suitable for small and large projects and helping to achieve more independence from frameworks and external agencies and better testability. This paper discusses the use of the Hexagonal Architecture to simplify business logic sharing. &lt;/p&gt;
Advanced Image Compression Techniques for Medical Applications: Survey

The field of artificial intelligence has grown significantly in the past decade, with deep learning being a particularly promising technique due to its ability to learn complex feature representations from data. One area where deep learning has shown promise is in image compression, which is important for applications such as medical imaging, remote sensing, and video streaming. Traditional compression methods such as JPEG, JPEG200 and PNG have been used for decades, but recent advances in deep learning have led to innovative techniques that involve training deep neural networks to learn a compressed representation of the image data. This survey paper focuses on research-based applications of deep learning in image compression and reviews recent works on using deep learning techniques to compress and accelerate deep neural networks, including pruning, quantization, and low-rank factorization methods. In addition, we discuss the use of deep learning techniques to minimize compression defects, such as block artifacts and ringing, which can degrade image quality. The paper provides an overview of popular methods and recent works in the field, highlighting their characteristics, advantages, and shortcomings. We also discuss challenges and open research questions, such as the trade-off between compression efficiency and reconstruction quality, and the need for standardized evaluation metrics for comparing different compression methods. Overall, this survey aims to provide a comprehensive understanding of current trends in image compression using deep learning techniques and their potential to revolutionize the field. By exploring the advantages and limitations of these methods, we hope to facilitate further research and development in this exciting area.
Medical image super-resolution: A review, recent trends and techniques

The quality and resolution of medical images significantly impact the accuracy of clinical decisions. Preprocessing of medical images plays a crucial role in the performance of computer-aided diagnosis (CAD) systems, which helps to improve the quality of input images, remove noise, and enhance contrast. Medical images are often characterized by low resolution due to different constraints such as hardware limits and image acquisition time. To address this issue, researchers have proposed various super-resolution approaches to improve the resolution of medical imagesand therefore better image quality. Hence, the super-resolution (SR) process aims to reconstruct a high-resolution (HR) image from its low-resolution (LR) counterpart. Several techniques are suggested in the literature including interpolation-based methods, reconstruction-based methods and learning-based methods. In recent years, deep learning-based methods have shownpromising results in various medical image applications while preserving important features and structures. In this article, we present a review of different studies that have proven to be useful in medical image super-resolution including classical computer vision methods and deep learning based-methods.
A Computational Approach to Causality

A summary is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.
Design of the “XingSong” Song-Based Learning Application Prototype and Its Implementation in Chinese Language Learning Activity

Researchers sparked the idea of designing a song-based learning application concept to get responses in the form of input from research samples to develop better learning applications in the future.Learning media in the form of songs have been used in classroom learning.Digital transformation in education into music technology as an innovative learning media.The research was conducted using a qualitative-descriptive method that begins with depth interviews, distributing questionnaires, and then using the data obtained from the user experience.Based on the results of the initial user survey, it is known that there are four classifications of learning difficulties in Mandarin, including problems in remembering Han characters, grammatical errors, difficulties in pronouncing Han characters, and challenges in hearing recorded Mandarin conversations.Based on the needs survey, the initial design of the songbased application prototype, XingSong, features a song list and music player, vocabulary list, practice, and quiz (including Pinyin Writing, fill in the blanks, and reading), speech recognition, and downloadable PDF writing practice.The XingSong application received a positive response from respondents as an innovation in Chinese learning applications.Based on testing the XingSong application prototype, researchers received input on application development regarding design aesthetics and content that can adapt to each user's Chinese language skills.
Impact of China’s Foreign Direct Investment on The Rwandan Economic Growth

The purpose of this study was to investigate the exact impact in quantitative terms of China’s FDI on the Economic development of the African continent with reference to Rwanda. The target population comprised 10 staff members of National Institute of Statistics of Rwanda, Rwanda Development Board, Ministry of Trade and Industry, Ministry of Finance and Economic Planning, United Nations (UN) Statistics, and World Bank's World Development Indicators. The sample size was 10 key informants. The researcher used questionnaire, interview guide and desk review as data analysis tools. The SPSS was used to analyze data into descriptive and inferential statistics. Results discover that in Rwanda a foreign direct investment depends on the consumer prices index. The study found out that 54.3% agreed with the consumer prices index, foreign direct investment is influenced by owner-occupiers' housing costs as it was evidenced by 62.8%, it was seen the retail prices index, where 56.7% agreed. Correlation analysis between the Owner-occupiers' housing costs and economic growth show a significant correlation between owner-occupiers' housing costs and job creation (r=.206; p-value=.000). This was statistically correlated given the p value was &lt;0.005 proposing that increase in owner-occupiers' housing costs has led to a job creation in Rwanda. The study demonstrated that 64.6% agreed that the nominal effective exchange influence foreign direct investment, 45.1% strongly agreed with the real effective exchange rate. Correlation results felt that choice of price or cost felt that it is significantly correlated with a growth domestic product (r=0.123*; p value=0.034). The study sought to evaluate the effect of Balance of Trade on the economic growth of Rwanda. The study evidenced that participants agreed that the financial account statements by 55.5% while the study found that capital account is affecting foreign direct investment. It was shown by 53.0%. Results show a significant correlation between capital account and poverty reduction (r=0.105, p-value=0.071). The correlations were statistically significant given that the p value was &lt; 0.05 proposing that an increase in capital account was insignificant with the economic growth and vice versa. The study concludes that inflation rate, exchange rate and balance of trade and thus FDI, have a significance effect on the economic growth in Rwanda. The study recommends that foreign direct investment strategies could be adopted in everyday activities. It would be appropriate to consider most favored nation and trade liberalization and investment as a criteria of exporting companies for improving economic growth. Future research can be conducted using longitudinal research to identify factors which contribute to economic growth. Keywords: Foreign Direct Investment, Economic Growth, Rwanda.
Digital resources on the Uralic languages of Siberia: an overview, evaluation and application

The paper reviews digital resources on the Uralic languages of Siberia, defining their scope and testing applicability for different tasks in linguistic studies. We focus on the resources featuring at least one Uralic language of Siberia. A short case-study for Nenets outlines applicability of the resources and the types of data that can be obtained from all the mentioned resources, helping researchers to navigate between them.
Impact of Professional Background on Inter-Annotator Variability and Accuracy During Annotation of Clinical Notes

The aging population's need for treatment of chronic diseases is exhibiting a marked increase in urgency, with heart failure being one of the most severe diseases in this regard. To improve outpatient care of these patients and reduce hospitalization rates, the telemedical disease management program HerzMobil was developed in the past.This work aims to analyze the inter-annotator variability among two professional groups (healthcare and engineering) involved in this program's annotation process of free-text clinical notes using categories.A dataset of 1,300 text snippets was annotated by 13 annotators with different backgrounds. Inter-annotator variability and accuracy were evaluated using the F1-score and analyzed for differences between categories, annotators, and their professional backgrounds.The results show a significant difference between note categories concerning inter-annotator variability (p<0.0001) and accuracy (p<0.0001). However, there was no statistically significant difference between the two annotator groups, neither concerning inter-annotator variability (p=0.15) nor accuracy (p=0.84).Professional background had no significant impact on the annotation of free-text HerzMobil notes.
Machine Learning Approach for Phishing Attack Detection

Phishing is the easiest method for gathering sensitive information from unwary people. Phishers seek to get private data including passwords, login information, and bank account details. Cyber security experts are actively seeking for trustworthy and effective ways to identify phishing websites. In order to distinguish between legal and phishing URLs, we used machine learning (ML) technology. In this research work using ML technology extraction and analysis of both types of URLs was performed. Extreme Gradient Boosting (XGBoost), Decision Tree (DT), Logistic Regression (LR), Random Forest (RF), and Support Vector Machine (SVM) were used to identify phishing websites. The goal was to identify phishing URLs and determine the most effective ML technique by comparing the accuracy rates of each algorithm. In this, proposed methodology two datasets were used. The accuracy of models was calculated on Phishtank and UCI dataset using kfold, feature selection and hyperparameter tuning method. Performance measures precision, recall and F1-score and Receiver Operating Characteristics (ROC) curve were calculated. RF provided an accuracy of 98.80% and 97.87% on the Phishtank dataset and UCI respectively. Highest precision, recall, F1-score value was 99% each and AUC-ROC value was 99.89% with Phishtank dataset. Validation with other researchers showed better results with proposed methodology. Therefore this methodology can be of help to identify phishing websites.
«Book Culture in the Digital Era»: the Results of the All-Russian (with International Participation) Scientific and Practical Conference. The Republic of Buryatia, November 24-25, 2022

The results of the All-Russian (with international participation) scientific and practical conference “Book Culture in the Digital Age”, organized by the Department of Library and Information Resources of the East Siberian State Institute of Culture within the framework of the implementation of the comprehensive scientific topic, are summarized. The reports presented at the plenary and sections sessions, panel discussion are characterized, and the recommendations formulated by the participants of the event are summarized.
Constructive Alignment Approach: Enhancing Learning and Teaching

The main focus of this paper is grounded in the assumption that the constructivist approach to learning and teaching is absent from the educational practices of a reasonable number of higher education (HE) institutions. Learning and teaching practices in some of these institutions are still based on the traditional approach (Livingstone, 2014). Teacher-centered strategies are still employed, where the teachers impart knowledge and students are passive learners and therefore they are not given the opportunity to have autonomy over their learning. In this way, students are not experiencing enough chances to interact and communicate while doing their defined assignments. Accordingly, this paper outlines/pinpoints the specifications of the constructive alignment approach which could be used to put an end to this daunting situation in HE organizations through designing/developing the existing programs to meet the 21st century cognitive skills perspectives. In my experience, constructive alignment framework could enable educational practitioners to create /develop programs based on the actual needs of the target learners in different contexts. Also, the involved staff could plan learning and teaching activities applying this approach in the given daily lessons. Furthermore, Biggs and Tang (2011) note that quality learning ensures that learners use the right cognitive skills required to gain knowledge and this could pave the way for their lifelong learning.&#x0D;
Usability Testing of a Multi-Level Modeling Framework for Just-in-Time Adaptive Interventions (JITAIs) in Mobile Health

The JITAI is an intervention design to support health behavior change. We designed a multi-level modeling framework for JITAIs and developed a proof-of-concept prototype (POC). This study aimed at investigating the usability of the POC by conducting two usability tests with students. We assessed the usability and the students' workload and success in completing tasks. In the second usability test, however, they faced difficulties in completing the tasks. We will work on hiding the complexity of the framework as well as improving the frontend and the instructions.
Mitigating the negative views of customers while the adoption of Artificial-Intelligence chatbots in online banking services: Relevant gaps and future research agenda

Mitigating the negative views of customers while the adoption of Mitigating the negative views of customers while the adoption of
PudgyTurtle Mode Resists Bit-Flipping Attacks

Cryptosystems employing a synchronous binary-additive stream cipher are susceptible to a generic attack called ’bit-flipping’, in which the ciphertext is modified to decrypt into a fraudulent message. While authenticated encryption and message authentication codes can effectively negate this attack, encryption modes can also provide partial protection against bit-flipping. PudgyTurtle is a stream-cipher mode which uses keystream to encode (via an error-correcting code) and to encipher (via modulo-2 addition). Here, we describe the behavior of this mode during bit-flipping attacks and demonstrate how it creates uncertainty about the number, positions, and identities of decrypted bits that will be affected.
Immersive Spatial Planning in Healthcare: Developing a Pipeline to Automatically Convert Computer Aided DesignData to Virtual Reality

Equipping rooms used for medical purposes, like e.g., intensive care units, is an expensive and time-consuming task. In order to avoid extensive subsequent adjustments due to inappropriate layout visualization or geometric conditions difficult to identify in 2D plans, it is of utmost importance to provide an optimal planning environment to future users such as physicians and nurses. In this paper we present the concept of a fully automatized pipeline, which is designed to visualize computer aided design (CAD) data using virtual reality (VR). The immersive VR experience results in improvement of efficiency in the decision-making process during the planning phase due to better spatial imagination. The pipeline was successfully tested with CAD data from existing Intensive Care Units. The results indicate that the pipeline can be a valuable tool in the field of spatial planning in healthcare, due to simple usage and fast conversion of CAD data. The next step will be the development of a plugin for CAD tools to allow for interactions with the CAD models in Virtual Reality, which is not yet possible without manual intervention.
Impact of Social Media Marketing on Brand Equity of Small &amp; Medium-sized Enterprises (SMEs) in UAE

Purpose: To investigate the impacts of SMM on brands equity of SMEs in UAE.&#x0D; Methodology: We administered a survey using SurveyMonkey.com to select 50 participants, with a developed questionnaire emphasizing the effects of SMM on brand awareness, brand loyalty, brand image, customer engagement, and brand equity.&#x0D; Findings: Findings indicated that social media marketing (SMM) of SME brands in the UAE affect their brand equity, brand image and brand awareness. However, there was no sufficient evidence supporting the effect of SMM of SMEs in the UAE on brand loyalty and customer engagement. This implies that social media marketing activities of firms alone may not be enough to influence loyalty among customers towards the brand.&#x0D; Unique Contribution to Theory, Practice and Policy: The study assists business owners of SMEs in the UAE in evaluating the worthiness of investing in SMM to grow their customer base and maintain strong brand equity.
WEB-BASED FOOD AND BEVERAGES ORDERING INFORMATION SYSTEM AT CAFE IN BEKASI

A cafe is a place that serves food and drink orders in a relaxed or informal atmosphere, a cafe is also a center for social interaction where people can gather to read, write, have business meetings, or just fill their spare time. Recording of food and beverage orders at the Freezing Point Cafe is still done manually and the sales system is still offline where if a buyer wants to order food from the cafe they have to come to the location so it is time consuming and inefficient and many people don't know about the cafe, so a This web-based Food &amp; Beverage Ordering Information System aims to introduce the Cafe to the wider community and make it easier for buyers to place orders for food and drinks offered by the Café without coming directly to the location. This study uses the SDLC method which consists of Planning, Analysis, Design, Implementation and Testing. The results of the tests that have been carried out can be concluded that this website has been successfully created, which in terms of appearance is quite attractive, all the menus on the website function properly and are in accordance with the designs and algorithms that have been made before.
INTERJECTION HE SOAYA LE...! IN NIASNESE: A NATURAL SEMANTIC METAFUNCTION APPROACH

This study explores the interjection of He Soaya le…! in Nias language using a descriptive qualitative method. Words that denote reactions or spontaneous expressions are interjections. The Nias language has an interjection that is similar to the exclamation of oh my God, namely He Soaya le...! Where this interjection is one of the quite iconic interjections in the daily conversation of the Nias people. This research aims to know the meaning of the Interjection He Soaya le...! . In this paper, researchers identify Nias interjections in the Nias language using the Natural Semantic Metafunction approach. The method used in this study is a qualitative research method, namely research that uses written and oral data sources. The data is taken from a dialogue in the comedy-drama series entitled Abunawa. Distribution and contextual methods are the methods used in this study to obtain data. From the results obtained in this study, there is one meaning of the interjection He Soaya le...! Namely shock, fear and panic, and emotional expressions that can be formed through physiological changes in humans. In Nias language, it is also expressed in two semantic aspects of its metafunction, namely emotive and cognitive aspects. From the results of this research, it is hoped that it can become a source of knowledge and understanding for other people of different ethnicities from the people of Nias and can avoid misunderstandings about a language.
THE EFFECT OF USING REDW STRATEGY ON STUDENTS’ READING COMPREHENSION OF NARRATIVE TEXT AT THE X GRADE OF SMA NEGERI 1 AIR JOMAN IN 2022/2023 ACADEMIC YEAR

This research was meant to find out the empirical evidence of the students' accomplishment in reading comprehension of narrative text by utilizing Read Examine Decide Write (REDW) Strategy at the X Grade of SMA Negeri 1 Air Joman. This research was quantitative research. The entire class of students at SMA Negeri 1 Air Joman's grade X made up the population of this study. 30 students from the experimental group (class X IPA 4) and 30 students from the control group served as the research's sample subjects (class X IPA 1). A test with multiple choices was used to obtain the data. (1) The students' achievement in reading comprehension narrative text by utilizing the Read Examine Decide Write (REDW) Strategy got the post-test with an average result after the data was analyzed. (1) The students' accomplishment in reading comprehension narrative text by utilizing the Read Examine Decide Write (REDW) Strategy got the post- test with an average result of 83 after the data was analyzed (2) The post-test showed that the students had successfully read narrative texts with comprehension using the conventional way, with an average score of 67. The value of t-observed was 8,43 and t- table was 2,009. The fact that the value of t-observed was higher than t-table indicates that the Read Examine Decide Write (REDW) Strategy had a significant impact on students' reading comprehension success.