Reviewerly/exHarmony huggingface dataset:
‘Block-Change’: Exploring Change Management Principles to Overcome Challenges in Blockchain Adoption

Blockchain technology has attracted significant interest and investment over the past decade across multiple industries.While the research and development has been robust and there has been no shortage of attempts at implementation, successful implementations at scale have been somewhat limited.Evaluations of this limited success have often focused solely on the technology or isolated economic assessment of the business use cases.Individual users and the networks they create are another critical component of a successful blockchain implementation at scale.Change management is the approach of preparing, supporting, and guiding a group of people towards an organisational or network goal.This paper looks at change management as a critical component of successfully building a network for scaled adoption and implementation of blockchain use across industries.We explore what makes individuals resistant to change, offer solutions from the established fields of change strategy and change management, and consider how these can be applied to increase success in blockchain adoption and implementation.Crucial elements include identifying principal stakeholder groups and users, asking key questions and gathering input and feedback from these stakeholders, incorporating this information into the governance structure and consensus mechanisms of the blockchain use, demonstrating and describing value of use to the stakeholders, and aligning these components for successful adoption.We end with impactful recommendations for developers, business leaders, administrators, subject matter experts, advisors, and end users to consider to better incorporate successful change management principles into their blockchain projects.
Robust face recognition using convolutional neural networks combined with Krawtchouk moments

&lt;span lang="EN-US"&gt;Face recognition is a challenging task due to the complexity of pose variations, occlusion and the variety of face expressions performed by distinct subjects. Thus, many features have been proposed, however each feature has its own drawbacks. Therefore, in this paper, we propose a robust model called Krawtchouk moments convolutional neural networks (KMCNN) for face recognition. Our model is divided into two main steps. Firstly, we use 2D discrete orthogonal Krawtchouk moments to represent features. Then, we fed it into convolutional neural networks (CNN) for classification. The main goal of the proposed approach is to improve the classification accuracy of noisy grayscale face images. In fact, Krawtchouk moments are less sensitive to noisy effects. Moreover, they can extract pertinent features from an image using only low orders. To investigate the robustness of the proposed approach, two types of noise (salt and pepper and speckle) are added to three datasets (YaleB extended, our database of faces (ORL), and a subset of &lt;a name="_Hlk128818620"&gt;&lt;/a&gt;labeled faces in the wild (LFW)). Experimental results show that KMCNN is flexible and performs significantly better than using just CNN or when we combine it with other discrete moments such as Tchebichef, Hahn, Racah moments in most densities of noises.&lt;/span&gt;
Approximation-based homomorphic encryption for secure and efficient blockchain-driven watermarking service

&lt;p&gt;Homomorphic encryption has been widely used to preserve the privacy of watermarking process on blockchain-driven watermarking services. It offers transparent and traceable encrypted watermarking without revealing sensitive data such as original images or watermark data to the public. Nevertheless, the existing works suffer from enormous memory storage and extensive computing power. This study proposed an approximation-based homomorphic encryption for resource-efficient encrypted watermarking without sacrificing watermarking quality. We demonstrated the efficiency of the Cheon-Kim-Kim-Son (CKKS) encrypted watermarking process using discrete cosine transform-singular value decomposition (DCT-SVD) embedding. The evaluation results showed that it could preserve the watermarking quality similar to non-encrypted watermark embedding, even after geometrical and filtering attacks. Compared to existing homomorphic encryption, such as Brakerski-Gentry-Vaikuntanathan (BFV) encryption, it has superior performance regarding resource utilization and watermarking quality preservation.&lt;/p&gt;
Application of improved you only look once model in road traffic monitoring system

&lt;span lang="EN-US"&gt;The present research focuses on developing an intelligent traffic management solution for tracking the vehicles on roads. Our proposed work focuses on a much better you only look once (YOLOv4) traffic monitoring system that uses the CSPDarknet53 architecture as its foundation. Deep-sort learning methodology for vehicle multi-target detection from traffic video is also part of our research study. We have included features like the Kalman filter, which estimates unknown objects and can track moving targets. Hungarian techniques identify the correct frame for the object. We are using enhanced object detection network design and new data augmentation techniques with YOLOv4, which ultimately aids in traffic monitoring. Until recently, object identification models could either perform quickly or draw conclusions quickly. This was a big improvement, as YOLOv4 has an astoundingly good performance for a very high frames per second (FPS). The current study is focused on developing an intelligent video surveillance-based vehicle tracking system that tracks the vehicles using a neural network, image-based tracking, and YOLOv4. Real video sequences of road traffic are used to test the effectiveness of the method that has been suggested in the research. Through simulations, it is demonstrated that the suggested technique significantly increases graphics processing unit (GPU) speed and FSP as compared to baseline algorithms.&lt;/span&gt;
WAYS TO DETERMINE THE RANGE OF KEYWORDS IN A FREQUENCY DICTIONARY FOR TEXT CLASSIFICATION

The paper is devoted to the actual problem of classifying textual documents of the collection by characteristic features, which is used for classifying news, reviews, determining the emotional tone of the text, as well as for forming catalogs of scientific, academic and research works. The paper proposes an approach for determining the significant words of a document for their further use as a feature vector in the classification process. In the course of the work, the author's keywords were identified, a partial dictionary was built, and the correlation between the author's keywords and the list of ordered words of the frequency dictionary based on the TF method, which also includes the author’s keywords, was analyzed. The determination of the range and percentage of significant words allows for further classification of scientific and research papers when forming thematic catalogs even in the absence of a list of author's keywords that can be used for classification. The results show that the use of the entire input range of frequency dictionary words is redundant and leads to a longer classification time.
Correlation of Visual and Verbal Components in a Poem by Nikolai Morshen and Some Works by Vilen Barsky

this article analyses the formal organisation of one poetic text by the poet Nikolai Morshen. The focus is on the relationship and nature of interaction between the visual and the verbal in the Morshen’s poem and two works by the artist, the poet Vilen Barsky. The poetic text can use various graphical devices and means of expression, from punctuation and orthographic irregularities to unusual positioning of signs on the page or absence of signs altogether. Morschen’s text and, as will be seen, Barsky’s work follow a paradigmatic model which allows for maximum engagement of the reader in the process of text creation and decoding. At the same time, it helps us to clarify the unobvious, hidden from a superficial glance meanings of words. The method of the two authors work with the text is similar in many respects, but it is not correct to identify their tasks: with Barsky the semantic weight is attached to the visual component, rather than the verbal one; with Morshen, on the contrary, the word is interesting above all – the graphic component is designed to support and enrich the content.
Blackfoot Words: a database of Blackfoot lexical forms

Abstract This paper describes the structure and creation of Blackfoot Words, a new relational database of lexical forms (inflected words, stems, and morphemes) in Blackfoot (Algonquian; ISO 639-3: bla). To date, we have digitized 63,493 individual lexical forms from 30 sources, representing all four major dialects, and spanning the years 1743–2017. Version 1.1 of the database includes lexical forms from nine of these sources. This project has two aims. The first is to digitize and provide access to the lexical data in these sources, many of which are difficult to access and discover. The second is to organize the data so that connections can be made between instances of the “same” lexical form across all sources, despite variation across sources in the dialect recorded, orthographic conventions, and the depth of morpheme analysis. The database structure was developed in response to these aims. The database comprises five tables: Sources, Words, Stems, Morphemes, and Lemmas. The Sources table contains bibliographic information and commentary on the sources. The Words table contains inflected words in the source orthography. Each word is broken down into stems and morphemes which are entered into the Stems and Morphemes tables in the source orthography. The Lemmas table contains abstract versions of each stem or morpheme in a standardized orthography. Instances of the same stem or morpheme are linked to a common lemma. We expect that the database will support projects by the language community and other researchers.
TECHNOLOGY THE FIRE DETECTION SYSTEM ON THE RAILWAY LINE IS BASED ON IMAGE PROCESSING WITH THE COMPUTER VISION METHOD

The rail transportation system plays a role important as a medium of transportation for the movement of goods and people in large quantities and is one of the modes of cheap transportation, this transportation model evolved from a steam train until it evolves to become more sophisticated using electric and magnetic technology, trains system works well with support from several the first factor is human resources, supporting technology and facilities. The problem with the rail system is that damage to the rails can cause result in the transportation route being blocked and can cause a very fatal accident, Based on these problems, besides the feasibility of the rail system, rail maintenance is a very important key, the railroad track maintenance system is usually carried out periodically. The solution to handle this problem is to use a computer vision method by utilizing surveillance cameras or CCTV installed on railroad crossings able to detect damage, the detection of damage is categorized into a few types first is track damage, due to shifts, fires on rail lines and finally structural damage due to earthquakes or landslides in the railway line area, this technology has been applied to several developed countries. and can monitor a large area and can provide a quick response if a malfunction occurs, the system will be a smart monitoring system but doesn't replace the role of a railway officer but as a tool that will provide complete information where the location of the damage is so that prompt and more effective repair action can be taken.
CREATIVE LANDING PAGE DESIGN TO SHOW PROGRESS OF “ PETANI SEJAHTERA “ APPLICATION

The farmers in Sukapura village have problems in distributing their harvests due to the large amount of costs in the planting process and the distribution process of their harvests. “Petani Sejahtera” is the name of an application created to assist farmers in distributing their harvests to those who are willing to accommodate, so that the farmers' crops do not accumulate. In the “Petani Sejahtera” application, farmers will be asked to input data from their harvests. To introduce the “Petani Sejahtera” application, a landing page was created as the initial page for the introduction of the “Petani Sejahtera” application as well as to show data and information that have been grouped and arranged, the data and information are the progress of the number of farmers, the number of products, the number of transactions, the number of partner, and a price list of products that have been registered to farmers who use the “Petani Sejahtera” application. The data and information will be automatically updated on the landing page based on the database from the “Petani Sejahtera” application. To make it easier for farmers and potential partner to access the landing page, a website-based landing page was created so that farmers and potential partner can access it using a smartphone or computer via a browser. By creating a landing page, farmers and potential partner know the data and information in the “Petani Sejahtera” application.
E-BUSINESS TO SUPPORT SALES OF FARMER CROPS BASED ON MOBILE APPLICATIONS

The agricultural sector is essential because it is the leading sector and supports the Indonesian economy. Sukapura Village is one of the producers of plant products in the Kertasari District. But on the other hand, most of the farmers experienced problems, and several obstacles emerged, such as the accumulation of harvests that were sold at low prices, which resulted in losses, and the difficulty of distribution because it was pretty complicated. Of course, this situation must be improved so that people can enjoy Indonesian agricultural products. One of them is by building an android-based application "Petani Sejahtera" which is specifically made as an alternative to make it easier for farmers. It can break the distribution chain of agricultural products. You can directly contact the courier who has collaborated with the manager by displaying information on product price lists, farmers' products, and harvested products, which will later be distributed during the main harvest period. So that later, farmers will find it easier to see the products planted and do not have to think about how to distribute the products. The purpose of making this "Petani Sejahtera" Application is to help farmers more easily distribute their products to various suppliers, so there is no accumulation of harvest yields. The benefits generated have a positive influence, especially regarding the price of products produced by farmers following the "current" market price so that farmers do not experience losses and continue to increase their agricultural output.
Instruments development for measuring student worksheet media based on scientific approaches

Student Worksheets a media in the form of sheets containing tasks and activities that students must carry out, which are useful in supporting the learning process, one of which is in the material on the Structure and Function of Plant Tissues so that students can be active in the learning process. An assessment instrument is needed for the Student Worksheets. For this reason, this study aimed to measure the instrument's validity and reliability for using Student Worksheets as a learning media. This study used Research and Development (RND) methodology with an instrument in the form of a Student Worksheets measurement questionnaire consisting of three constructs: product design, material feasibility, and language feasibility. This research was carried out by involving seven teachers from several schools. Data were obtained by distributing the questionnaire via a Google form from September to October 2022 by obtaining prior consent from the respondents. The data obtained were quantitative, then analyzed using SPSS version 29 in the form of Alpha Cronbach analysis. The results of the test show that the validity of the instrument data meets the valid and reliable criteria with each Cronbach Alpha value per construct, namely Product Design (0.795), Material Feasibility (0.712), and Language Feasibility (0.712). Therefore, this study shows that the developed instrument meets the use requirements in developing Student Worksheets media students. Thus, stakeholders and teachers can use this instrument to develop media, particularly Student Worksheets, whereas further researchers can use this instrument to measure media before the study.
A Study on the Construction of Five-In-One Teaching Model for Sports Clubs in Hubei Enshi College

In the 20 years since Shenzhen University took the lead in implementing the teaching reform of the university public sports club system in 1994, well-known and local universities throughout China have implemented the teaching mode of public sports extracurricular club systems one after another. This paper uses research methods such as literature review, expert interviews, and mathematical and statistical analysis to investigate the current situation of sports clubs at Hubei Enshi College and analyze the teaching mode of sports clubs there. Based on this analysis, it was concluded that the sports club at Enshi College in Hubei should adopt a five-in-one teaching mode of "ladder teaching, online learning and practice, multiple assessments, public competitions, and brand sports." The paper suggests that in local ethnic colleges and universities, the university sports club should first establish a unique teaching content and teaching mode of the sports club system. Additionally, the club should form an independent teaching assessment system, and the management system of the university sports club should be continuously optimized, thus promoting the continuous improvement of the comprehensive education system of Hubei Enshi College. This research provides practical guidance to promote the benign development of university sports clubs at Hubei Enshi College and enhance the campus cultural atmosphere of comprehensive sports for university students.
The evaluation of e-learning readiness as a distance learning media of the first-semester biology students

Universitas Sulawesi Barat (Unsulbar) launched its primary Learning Management System (LMS) named E-learning of Universitas Sulawesi Barat or often called “E-learning Unsulbar” in 2020 (https://elearning.unsulbar.ac.id/). Implementing E-learning at Unsulbar is one of the university’s efforts to maximize distance learning, especially during the COVID-19 pandemic. A study was conducted to evaluate E-learning readiness to measure the readiness of new students of the Biology Education Study Program towards the E-learning implementation. It is a quantitative descriptive study using a survey method adapted from a questionnaire developed by Akaslan and Law. The respondents were 77 new students from the biology education class of 2020 in the odd semester of 2020-2021. The measurement adapts three main stages, i.e., readiness (technology, people, institutions, content), acceptance, and training. The result showed that the readiness of new students for E-learning Unsulbar for technology and training factors were 3.1 and 3.3, respectively. It was categorized as not ready, which means that there needed to be more readiness of students’ internet infrastructures and academics who need training in using E-learning Unsulbar. Meanwhile, the scores for the factor of people, institutions, content, and acceptance were 3.8, 4.2, 3.85, and 3.9, respectively, and categorized as ready to be implemented. This result is an evaluation material for the university in determining the right policy for implementing E-learning Unsulbar.
Development of image super-resolution framework

There are some scenarios where the images taken are of low resolution and it is hard to judge the features from them, resulting in the need for enhancement. Super-resolution is a technique to produce a high-resolution image from a lower-resolution image. The intention here is to develop a system that enhances images of faces and satellite images by integrating these models and providing an interface to access this model. There have been various ways of achieving super-resolution using different techniques. Throughout the years, techniques involving deep learning methods, interpolation techniques, and recursive networks have been explored. We find it promising to use generative adversarial networks (GANs). The system has been deployed through Google Collaborate, Python libraries, and the TensorFlow framework. To assess the developed system, which consists of images, three metrics have been calculated. namely, peak signal-to-noise ratio, mean squared error, and structural similarity index. The model successfully demonstrated the capability of GANs by efficiently generating a high-resolution image from a low-resolution image for the given cases. The model would then be run on a standalone server for free Internet access for users to use super-resolution facial images and satellite images.
Correction to: A Notion of Equivalence for Refactorings with Abstract Execution

Correction to: Chapter “A Notion of Equivalence for Refactorings with Abstract Execution” in: T. Margaria and B. Steffen (Eds.): Leveraging Applications of Formal Methods, Verification and Validation. Software Engineering, LNCS 13702, https://doi.org/10.1007/978-3-031-19756-7_15In the originally published version of this chapter a sentence in the 4th paragraph of section 5 “Discussion” was incomplete. This has been corrected and the sentence has been updated as follows “Conversely, due to the challenges in checking instantiation of schemata against concrete programs already pointed out by Steinhöfel [28, 119,137], one has to take care not to write too restrictive programs that rule out useful working instances.”
Development of Earthquake Detection and Warning System Based on Sensors

Earthquakes often cause severe disasters.Taiwan is located in an earthquake zone, where earthquakes occur frequently.For example, the Meinong earthquake in Kaohsiung in 2016 and the Hualien earthquake in 2018 caused the collapse of buildings in Tainan and Hualien, resulting in a total of 232 deaths and more than 100 injuries.Due to the strong vibration, earthquakes are often accompanied by fire and the leakage of toxic gases, causing loss of life and property.In this study, we integrate Arduino, sensors, and transmission technology to design an earthquake detection and warning system.When an earthquake is detected, the system immediately notifies everyone to evacuate.When the harmful gas concentration exceeds a critical value, the warning light is switched on, and the exhaust fan is turned on to extract the indoor toxic gas.When the flame sensor detects a flame, the system activates an alarm to warn people to escape quickly.In the designed system, capacitive three-axis accelerators are used as vibration measurement sensors to issue warnings in the early stage of an earthquake.In addition, the system includes an IR flame sensor to detect fires and an MQ series air quality sensor to detect harmful gases.The newly designed sensing system not only has the advantage of notifying people immediately during an earthquake but is also cheap and easy to use.
Social Media as a Means for Everyday Advocacy

Over the past several years, the power of social media to create connections through the pandemic has had both positive and negative impacts. Libraries make use of social media as a marketing tool, a public forum, and as a digital third place for programming and community connection.Most libraries use social media to communicate the needs of the library and patrons, and as a means to connect with community partners and stakeholders. I’ve spent the last eight years working in rural and remote libraries in Wyoming, New Mexico, and Nebraska, and each has used social media to their advantage in community engagement.