Reviewerly/exHarmony huggingface dataset:
Nonlinear Error Correction for Color Phase-Shifting Profilometry with Histogram Equalization

Because color patterns with multiple channels can carry more information than gray patterns with only one channel, color phase-shifting profilometry (CPSP) has been widely used for high-speed, three-dimensional (3D) shape measurement. However, the accuracy of CPSP suffers from nonlinear errors caused by color crosstalk. This paper presents an effective nonlinear error correction method for CPSP based on histogram equalization. The two main steps of the proposed method are eliminating nonlinear errors with histogram equalization and optimizing the results using a spline fitting algorithm. Compared with other compensation methods, the proposed approach does not require any precalibration information or additional patterns, which are very time-consuming. The simulations and experiments indicate that the proposed method has a promising performance for nonlinear error elimination.
RETRACTED: Federation payment tree: An improved payment channel for scaling and efficient ZK-hash time lock commitment framework in blockchain technology

Federation Payment Tree, a new Off-chain with zero-knowledge hash time lock commitment setup is proposed in this paper. The security of blockchain is based on consensus protocols that delay when number of concurrent transactions processed in given throughput framework. The scalability of blockchain is the ability to perform support increasing workload transaction. The FP-Tree provides zero knowledge hash lock commitment connect with off-chain protocols by using the payment channel, which enables execution of off-chain protocol that allows interaction between the parties without involving the consensus protocol. It allows to make payment across an authorization path of payment channel. Such a payment tree requires two commitment scheme is Timelock and Fundlock, each party lock fund for a time period. The main challenges we faced in this paper is that the computational power, storage and cryptography. Furthermore, we discussed many attacks on off-chain payment channel that allows a malicious adversary to make fund lose. The FP-Tree supports multi-parti computation (MPC) merging transactions into single hash value in payment tree. We enable the parties to generate single hash value by consumes both less than 0 (log2 N ) and space less than 0 (log2 N ) time combine element over length of single hash. The results were discussed in this paper and efficiency of FP-Tree is well suited for the blockchain technology. We achieved the accuracy of 60.2% in federated payment tree when compared with the proof of work and proof of authority.
Role of Information Sharing on Supply Chain Performance – A Context of Developing Country

Purpose – This study aims at finding out how cost, quality, delivery and flexibility as supply chain performance (SCP) measures are affected by information sharing in the context of a developing country Nepal.&#x0D; Design/Methodology/Approach – The research was carried out in Nepal with data collected through a survey from 131 supply chain participants that includes suppliers, growers, manufacturers, distributors/dealers, wholesalers, retailers and logistics service providers. Exploratory factor analysis (EFA), confirmatory factor analysis (CFA) and path analysis were performed to assess the fitness of the proposed model and test the hypothesis developed for this study.&#x0D; Findings – The findings demonstrated that information sharing plays a key role in enhancing the performance of supply chains (SC). It shows that delivery and flexibility performance are significantly affected by operational as well as strategic information sharing while cost and quality performance are not affected by information sharing.&#x0D; Originality/Value – This study adds to the existing knowledge by providing empirical support towards the role of operational and strategic information sharing on cost, quality, delivery and flexibility, especially in the context of a landlocked developing country.&#x0D; Research Limitations/Implications – The main limitation is the moderate response rate than desired. While the composition of respondents represented the targeted companies, most of the participants were manufacturers (56%).&#x0D; Practical Implications – The results of this study will help supply chain participants in Nepal to have an enhanced insight and awareness towards the importance of information sharing in enhancing their performance.
Practicum Students&amp;#39; Perceptions In The Light Of COVID-19: Challenges &amp; Opportunities

This study investigates practicum students&amp;rsquo; challenges and opportunities of online teaching and learning in the time of COVID-19 at the University of Technology and Applied Sciences (UTAS), Al-rustaq, Oman. Utilizing a questionnaire containing quantitative and qualitative questions to 65 practicum students, the most prominent findings of the study were that online teaching helped practicum students to build confidence and equip them with the right skills and strategies to use online teaching platforms (Google Meet &amp;amp; Google Classroom). Also, the online teaching helped students to manage their pace, and use visual clues, affordable e-resources and teaching aids. However, the study found that internet connection and time management were the main challenges in the online teaching. Online teaching hinders them from getting students full attention, assisting them during the activities and promoting collaborative learning during the lesson. As a result, the study provided some recommendations such as providing practicum students with alternative and more interactive platforms and more training on how to utilize them as this strategy has a high potential of enhancing the impact of online teaching on practicum students&amp;rsquo; teaching performance.&amp;nbsp;
Automatized Bioinformatics Data Integration in a Hadoop-based Data Lake

When we work in a data lake, data integration is not easy, mainly because the data is usually stored in raw format. Manually performing data integration is a time-consuming task that requires the supervision of a specialist, which can make mistakes or not be able to see the optimal point for data integration among two or more datasets. This paper presents a model to perform heterogeneous in-memory data integration in a Hadoop-based data lake based on a top-k set similarity approach. Our main contribution is the process of ingesting, storing, processing, integrating, and visualizing the data integration points. The algorithm for data integration is based on the Overlap coefficient since it presented better results when compared with the set similarity metrics Jaccard, Sørensen-Dice, and the Tversky index. We tested our model applying it on eight bioinformatics-domain datasets. Our model presents better results when compared to an analysis of a specialist, and we expect our model can be reused for other domains of datasets.
INVESTIGATING AN INDIVIDUAL’S OPINION ON SOCIAL MEDIA ABOUT THE CRYPTOCURRENCY MARKET

Cryptocurrencies are growing rapidly, with various altcoin being introduced recently, despite the fact that the market is very volatile, cryptocurrency now holds trillions of dollars in the market and has plenty of platforms for trading and owning cryptocurrencies, like Binance, Coinbase, and others. In particular, Bitcoin has caught the atten-tion of many people over the year with a current market cap. of 731.56 billion dollars circulating in the market. One of the major problems in cryptocurrencies is volatility, and often the prices can vary due to the external events that trigger the market. That is, Twitter sentiment. The objective of the article is to investigate people’s opinion about the cryptocurrency market on social media using collected tweets for 2 popular hashtags of Bitcoin and investigating the tweets using sentiment analysis. The study found that sentiment scores could be related to observed price fluctuations.
Dynamic Attribute Tree for the Data Encryption and Third Party Auditing for Cloud Storage

Background: To reduce the burden of the users to perform cloud audits.The tree based key handling method provides the structure format of data and increases performance in the search process.Methods: The Dynamic Attribute Tree method is proposed for Third-Party auditing to encrypt the data based on its attribute.The attributes are stored in tree structure along with data and key that helps to effectively improve the dynamic update of the data in the cloud.Findings: The proposed Dynamic Attribute Tree method has 6.7milliseconds computation time for 100 blocks of data and the existing Merkel Tree method has 7.5milliseconds computation time.Novelty: The Novelty of the project is the Dynamic Attribute Tree method uses bilinear mapping to verify the integrity of the data without retrieving the actual data from the cloud.
Analysis Of The Possibility Of Creating A Research Environment For Pedagogical Education

The implementation of the model of research education, the basic condition of which is the research educational environment of the university will form the willingness of the future teachers to perform their professional tasks successfully in schools that are in different socio-economic contexts.The article shows the results of two studies.The first to build the competence profile of the teacher-researcher considers the opinions of the heads of educational organizations of the Primorsky Territory.To build a competence profile, the focus group method was used, in which headteachers of the Primorsky Territory -curators of the "500+" project were involved.During the focus groups, the participants identified the key competencies that are formed within the framework of the research model of pedagogical education.The second one is related to the assessment of the potential for creating the necessary educational environment for the implementation of the research educational model.In the context of the second study, a cluster analysis of universities that were under the direction of the Ministry of Education of the Russian Federation was conducted.The data obtained during the first study show that there is a differentiation of universities that are under the direction of the Ministry of Education of the Russian Federation on such an indicator as to the potential to create the necessary educational environment for the implementation of the model of research education.
Intrinsic and extrinsic quality of data for open data repositories

This work assesses the quality of Internet of Things data not only as an intrinsic quality on how well it represents the related phenomenon but also, on how much information it contains to educate an artificial entity. The quality metrics here proposed are tested with real datasets. Also, they are implemented on OpenCPU, so the open data repositories can use them off-the-shelf to rate their datasets without computational cost and minimum human intervention, making them more attractive to potential users and gaining visibility and impact.
IoT-Based Hydroponic Plant Monitoring and Control System to Maintain Plant Fertility

Hydroponics is a method of cultivating plants by utilizing a small amount of land without using soil media. Hydroponic cultivation is still done conventionally in monitoring and controlling nutrients and pH of the air. Hydroponics is already with Internet of Things (IoT) technology in the cultivation process. The research aims to use IoT technology by developing control devices and monitoring hydroponic plants remotely, to make it easier for cultivators to control and monitor plant color, temperature, nutrients and the pH value of hydroponic plant water. Control and monitoring can be done through a smartphone application. The data from testing the condition of hydroponic plants obtained an average error of 1.8% for air temperature, 4.8% for water pH, 6.6% for plant color and 7% for water nutrients. Hydroponic plants with the TCS3200 sensor get a monitoring opportunity of 53.3%. Testing of tool control related to nutritional improvement has been carried out using the fuzzy Mamdani method with an increase in the probability of 88.75% for adding nutritional value and 0% for decreasing nutritional value. Tool control for improving the pH value of hydroponic plant water has been successfully carried out.
The detection of distributional discrepancy for language GANs

Formulae display:?Mathematical formulae have been encoded as MathML and are displayed in this HTML version using MathJax in order to improve their display. Uncheck the box to turn MathJax off. This feature requires Javascript. Click on a formula to zoom.
Artificial intelligence based virtual voice assistance

Artificial intelligence (AI) is a versatile technology that allows us to combine data, analyse it, and make decisions based upon the results. It is already transforming our lives in many ways. To respond to commands and carry out tasks, a virtual voice assistant software agent can be used. The major purpose of this paper is to create a local voice assistant that can perform human-like tasks and tasks that a human must perform on a daily basis. Users may ask their assistant’s questions, listen to music, control home automation devices and manage other basic tasks like calendars using voice commands, e-mail, and to-do lists. The proposed system is constructed with open-source software components that can accept any future modifications. Because this system is modular, it is more adaptable and easier to add new features without disrupting existing system functionality. The entire system is based on verbal rather than textual input. The integrated voice assistant system can open YouTube, Gmail, and Google Docs and other websites like geeks for geeks, Google meet, Google classroom, can also open Notepad, Command Prompt, and switch the window of laptop. Predict current date and time, open camera, search Wikipedia to abstract required data, get top headline news, fetch jokes, play music on browser and from the system and get the IP address of the machine.
Dual Projection Fusion for Reference-Based Image Super-Resolution

Reference-based image super-resolution (RefSR) methods have achieved performance superior to that of single image super-resolution (SISR) methods by transferring texture details from an additional high-resolution (HR) reference image to the low-resolution (LR) image. However, existing RefSR methods simply add or concatenate the transferred texture feature with the LR features, which cannot effectively fuse the information of these two independently extracted features. Therefore, this paper proposes a dual projection fusion for reference-based image super-resolution (DPFSR), which enables the network to focus more on the different information between feature sources through inter-residual projection operations, ensuring effective filling of detailed information in the LR feature. Moreover, this paper also proposes a novel backbone called the deep channel attention connection network (DCACN), which is capable of extracting valuable high-frequency components from the LR space to further facilitate the effectiveness of image reconstruction. Experimental results show that we achieve the best peak signal-to-noise ratio (PSNR) and structure similarity (SSIM) performance compared with the state-of-the-art (SOTA) SISR and RefSR methods. Visual results demonstrate that the proposed method in this paper recovers more natural and realistic texture details.
Measurement of the Magnetic Monopole Charge, the Missing Link in Quantum Mechanics, Aether and the Dark Energy

Charge conservation in the theory of elementary particle physics is one of the best-established principles ‎in physics. As such, if ‎there are magnetic monopoles in the universe, the magnetic charge will most likely be a ‎conserved quantity like electric ‎charges. If neutrinos are magnetic monopoles, as physicists have reported ‎the possibility, the Earth should show signs of ‎having a magnetic monopole charge on a macroscopic scale ‎since neutrons must also have a magnetic monopole charge if ‎the general charge conservation principle is valid. ‎To test this hypothesis, experiments were performed to detect the collective ‎effect of the magnetic monopole ‎charge of neutrons on the earth's equator using two balanced high-strength neodymium rod ‎magnets. We ‎were able to identify the non-zero magnetic monopole charge of the individual neutrons from the experiments. ‎‎The presence of individual magnetic monopole charges in the universe prompted the proposition of the new ‎symmetric form ‎of Maxwell's equations. Based on the theoretical investigation of the new Maxwell's ‎equations, we conclude that magnetic ‎monopole neutrinos are the cause of the origin of quantum ‎mechanical uncertainty, dark energy, and the medium for ‎electromagnetic wave propagation in space.‎‎
The Fourth Space as Reality

In 2021, Daniel Hardegger reinterpreted the notion of The 4th Space as meaning the virtual space. It dwells within the three dimensions: Physical space where it is instantiated, technological medium used to access it, and the time frame. The ontology of Hardegger&rsquo;s 4th space relies on traditionalist real-space physicalism. Luciano Floridi, in his 2014 The 4th Revolution, has placed the informational revolution within his prior framework of information-based ontology, where human beings as well as virtual and physical objects, are all inforgs&mdash;informational entities. In this brief article, we compare and contrast these ontologies.
Text sentiment analysis in banking

The paper presents the author's approach to solving the problem of sentiment analysis of online Russian-language messages about the activities of banks. The study data are customer reviews about banks in general and their products, services and quality of service posted on the Banki.ru portal. In this paper, the problem of text sentiment analysis is considered as a binary classification task based on a set of positive and negative reviews. A vector model with a tf-idf weighting scheme was used to represent the collected and preprocessed texts. The following algorithms with the selection of optimal parameters on the grid were used for binary classification task: naive Bayesian classifier, support vector machine, logistic regression, random forest and gradient boosting. Standard statistical metrics, such as accuracy, completeness, and F-measure, were used to evaluate the quality of solving the classification problem. For the indicated metrics, the best results were obtained on the classification model developed with the use of Support Vector Machine. Thematic text modeling was also carried out using the Dirichlet latent placement method to define the most typical topics of customer messages. As a result, it was concluded that the most popular message topics are "cards" and "quality of service". The obtained results can be used in the activities of banks to automate its reputation monitoring in the media and when routing client requests to solve various problems. When solving problems, the features of the Python programming language were actively used, namely, libraries for web scraping, machine learning, and natural language processing.
OntoStrength: An Ontology for Psychomotor Strength Development

An ontology is a formal, explicit description of concepts and relations from a domain while considering underlying properties, restrictions, and instances.With the advancement of the Semantic Web, the rise of the Educational Semantic Web, and the lack of uniformity between approaches for knowledge representation, ontologies are becoming more and more popular, including adaptive learning environments such as the Intelligent Tutoring Systems (ITSs). OntoStrength is an ontology developed to support the Selfit ITS, a platform that aims to improve the fundamental human psychomotor skills and, more specifically, bio-motor strength abilities. The goal of Selfit is to prevent the negative consequences of a sedentary lifestyle and accidents involving inadequate strength skills. Most ontologies in the sports domain support the development of digital solutions for sports performance and data collected during competitions. In contrast, OntoStrength’s goal is to contribute to the development of digital solutions dedicated to bio-motor strength ability analysis. OntoStrength considers other bio-motor skills like speed, endurance, or flexibility, as well as other activities like muscle analysis, movement patterns, or training load management, to support sport, professional and daily-life activities. OntoStrength enables the personalization of strength development programs in the Selfit ITS by providing a comprehensive data layer for its student, domain, and tutoring models.
Negativity and quantum phase transition in a mixed spin-(<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="d1e593" altimg="si4.svg"><mml:mfrac><mml:mrow><mml:mn>1</mml:mn></mml:mrow><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:mfrac></mml:math>, <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="d1e603" altimg="si5.svg"><mml:mfrac><mml:mrow><mml:mn>5</mml:mn></mml:mrow><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:mfrac></mml:math>, <mml:…

The thermal entanglement in a mixed spin-( 1 / 2 , 5 / 2 , 1 / 2 ) Ising–Heisenberg branched chain is investigated by employing negativity as entanglement measurement. Using transfer-matrix approach, the negativity is calculated numerically both near and at a quantum phase transition point. We establish the relationship between negativity and quantum phase transition. It is found that whether negativity can be used to detect quantum phase transition point depends on the typical thermal energy, and we show the range of temperature at which negativity can be used to signal each ground-state transition. In addition, the thermal stability of negativity is closely related to energy gap in the system. It is worth noting that the negativity exhibits distinct behavior between quantum and classical phases. Negativity decreases with the increase of temperature in the quantum phase, while it exhibits a ”regrowth” behavior in the classical phases. • We study the thermal entanglement in a mixed spin Ising–Heisenberg branched chain. • The relationship between energy gap and quantum phase transition is discussed. • Quantum phase transition can be detected and signaled by thermal negativity.
Bandoneon 2.0: an interdisciplinary project for research and development of electronic bandoneons in Argentina

In this article we present Bandoneón 2.0, an interdisciplinary project whose main objective is to produce electronic bandoneons in Argentina.The current prices of bandoneons and the scarcity of manufacturers are endangering the possibility of access for the new generations to one of the most emblematic instruments of the culture of this country.Therefore, we aim to create an expressive and accessible electronic bandoneon that can be used in recreational, academic and professional contexts, providing an inclusive response to the current sociocultural demand.The project also involves research on instrument acoustics and the development of specialized software and hardware tools.This paper summarizes our project and its evolution, as well as a brief history of the bandoneon and the problems faced by today's local musicians.We also describe our first prototype, "Alfa", and its outcomes, the scientific research we carry out using an Integral Measurement System we developed, and some preliminary results.Finally, we comment on the next steps for the future of the project, and we discuss some points that we have collected from our perspective as NIME developers in our country.