Reviewerly/exHarmony huggingface dataset:
An Improved k-Nearest Centroid Neighbor Classification Method for Incomplete Data

Missing values often exist in scientific datasets. Therefore, practical methods for missing data imputation and classification are necessary for machine learning, data analysis. The k-Nearest Neighbor (KNN) algorithm is a simple and effective algorithm in missing data imputation and classification. This paper focuses on the missing data classification problem and proposes a new classification method based on the local mean k-nearest centroid neighbour. When making classification judgments, the proposed method examines the closeness and symmetrical arrangement of the k neighbours and adopts the local mean-based vector of the k centroid neighbours for each class. We run classification error experiments on six UCI datasets to see how well the proposed method performs when there is missing data. Experimental results show that the performance of our proposed method obtains a significant improvement compared to the most advanced KNN-based algorithms.
Performing information: exploring conceptualisations of embodied information

Embodied information researchers have described bodies as performative. The body forms an important information source for leisure pursuits such as running but bodies remain under- theorised as sources of information. This paper explores how performance theories can contribute new conceptualisations of embodied information practices. A review of information science literature was conducted to identity use of Goffman’s dramaturgical model or descriptions of bodies as performing. Embodied information is conceptualised through analysis of performance theory literature, focusing Goffman’s dramaturgical model. The strengths and limitations of Goffman’s dramaturgy are discussed using examples from embodied information literature. Dramaturgical metaphors, such frontstage and backstage, can explain how individuals perform identity in everyday interactions. Dramaturgical principles can deepen understanding of how bodies create and share embodied information. Goffman’s dramaturgical model can be used to address gaps in understanding about how embodied information is created and shared. The complex theoretical underpinnings of performance should be further examined to develop new conceptualisations of embodied information practices.
A plastic virtual self

This chapter discusses how virtual reality (VR) has been used to elicit body ownership illusions and their consequences for transformation of cognitive processes, attitudes, behaviours, and physiological responses, including pain. We review how VR can be used to engender body ownership over a virtual body that is seen from first-person perspective. The virtual body is programmed to move synchronously with participant movements or be seen to receive tactile stimulation while the participant feels this synchronously on their body. We show that body ownership occurs over a wide range of body forms, even those that go beyond the appearance of humans. We then consider the consequences of ownership over a virtual body with characteristics that are different from the person’s actual body. For example, a different race will typically lead to a reduction of implicit bias against that race, or a certain physical aspect may influence motor behaviours of the participant, and even physiological responses. We also show that ownership over a virtual body can lead to illusory agency, that is the sense that the participant might have of carrying out an action that only their virtual body did. Overall, we demonstrate that VR is an excellent tool for the study of body representation, and that it can be used to induce rapid changes across a number of dimensions from attitudes through to pain perception. We finish with the question – if our body representation is so highly plastic, then who are we?
Blockchain Mechanism, DLTs, CBDC, Smart Contracts and NFTs

We examine the connection between fundamental blockchain component of cryptographic forms of money and its distributional attributes. Notwithstanding cost, we stress on utilizing real block size and block time as the functional elements of cryptos. We utilize distributional attributes like Fourier power range, minutes, and quantiles, worldwide we desired states, as well as the actions for long haul conditions, chance and commotion to sum up the data from crypto time series. With the speculation that the blockchain structure makes sense of the distributional attributes of cryptos, we utilize trademark based ghastly bunching to bunch the chose cryptos into five gatherings. We investigate these groups and find very that the bunches of cryptos share comparative system like beginning of fork, trouble change recurrence, and the idea of block size. This paper furnishes crypto makers and clients with a superior comprehension toward the association between the blockchain convention plan and distributional qualities of cryptos. A blockchain is a decentralized, dispersed, and frequently open, computerized record comprising of records called blocks that are utilized to record exchanges across numerous PCs so that any elaborate block can't be changed retroactively, without the modification of every resulting block.
SENTIMENT ANALYSIS OF ROMAN URDU REVIEWS

Easy access and economic availability of Computers, Tabs, Smartphones and high—speed internet people are now using web for Social interaction and Business correspondence. People are becoming habitual to post their reviews about any specific entity/product, they used. These reviews are very helpful for both—user and seller. Initially these reviews not too much they can easily be analyzed by reading them. The continuous increase in the amount of these reviews creates a need that reviews can be analyzed and useful pattern be found and explored through automated channel. This need leads to a new filed in the domain of research known as “Sentiment Analysis”. Sentiment Analysis is the study of people’s opinions, sentiments, attitude and emotions expressed in written language or also said that, it is a process of categorizing people’s opinions expressed in the piece of text especially in order to determine whether the writer’s attitude towards a particular topic or product is positive, negative, or neutral. This research is targeting the mining of the sentiments from these reviews of PSL anthums. In this thesis, five different classification model are used for text classification of reviews by using Rapid Miner Tool. Thesis presents a Sentiment Analysis of Roman Urdu reviews on PSL Anthums available on YouTube. These reviews are scraped, pre—process and analysed using Naïve Bayes, Gradient Boost Tree, Support Vector Machine, K-Nearist Neighbours and Artificail Neural Netwrok. The Roman Urdu Sentiment Analysis is perform at 7000 bi-lingual reviews. The Naïve Bayes and and Logistic Regression correctly predicted 68.86% reviews. ANN achived 68.86% on testing dataset and 69.71% on the validation of the results.
Learning English Grammar by Means of M-Learning: A Case Study

Purpose. The paper deals with the effective implementation of mobile applications for learning grammar in the EFL course for students of non-linguistic higher educational institutions. The tasks for the research are the following: to discover the didactic properties of mobile applications that enable students’ progress in learning English grammar and to apply them; observe students’ attitudes towards mobile learning applications for training English grammar skills and their grounds. Methodology. Quantitative outcomes of the experiment were calculated by means of the knowledge ratio technique. Scaling method was applied to organize the data into numerical form for comparative analysis of the experimental groups and control groups’ achievements. A case study was conducted on the basis of Sumy National Agrarian University, Ukraine. A sample consisted of two experimental groups (35 students), and two control groups (36 students), aged 18-19, who studied second year at different faculties during 2021-2022 in the University and participated voluntarily in the study. In experimental groups the studying process was organized with the implementation of tablets and cellphones with the ability to access the Internet via Wi-Fi as mobile learning tools and mobile learning applications. A series of the interviews were held to learn students’ attitudes towards mobile apps. Results. English grammar command levels in experimental groups are predominantly sufficient and high in contrast to the predominantly low and initial levels in control groups. The attitudes of students towards mobile apps for learning EFL are mostly positive. Conclusions. It was concluded that the implementation of mobile learning tools provided the efficient mastering of English grammar by students of non-linguistic higher educational institutions. Improving of EFL teachers’ methodological preparation for the introduction of mobile learning requires further researches in this sphere.
Degitalization of Medical Record Administration Services at Dian Rapha Medika Toraja Clinic

In the world of health, the management of administrative documents, especially medical records, is a very important thing to do. Management of medical records in collaboration with information technology can improve services effectively and efficiently in managing information data quickly and avoiding delays in service. Until now, the Dian Rapha Medika Toraja Clinic still uses manual medical record administration management with several existing obstacles. This causes health services that should be handled quickly cannot be carried out. Therefore, the researcher is interested and aims to design a website-based medical record administration management system at the Dian Rapha Medika Clinic Toraja. This study uses the waterfall model design method, which consists of 1) Needs Analysis, 2) System Design, 3) Implementation, and 4) Testing. The data collection techniques in this design are 1) Interview and 2) Observation. The results of this study indicate several advantages when using digitization of administrative services for medical colleagues at Dian Rapha Medika Toraja clinic, namely: 1) assisting in digitally documenting patient medical record data; 2) input of patient medical record data is easier and faster; 3) facilitate doctors in analyzing the patient's medical records; 4) searching for patient medical record data is easier and faster; 5) storage of medical record data is more concise and well-structured due to the integration of patient data and medical records so that it can accelerate administrative management at the clinic.
POTENTIAL OF A DEEP CONVOLUTIONAL NEURAL NETWORK IN THE SELECTION OF HUMAN BLASTOCYSTS TO PREDICT CLINCIAL PREGNANCY AND LIVE BIRTH

The present study aimed to evaluate the potential of deep models in the process of machine learning-based prediction of clinical pregnancy and live birth based on clinical data and single static-morphology blastocyst images.
Producing planned hedonism among opiate users in an online drug market

This chapter examines the relationship between drug distribution modes and users’ presentation of self. It argues that the design and operation of illicit drug marketplaces produce specific subjectivities among dealers and buyers. It uses the case of opiate buyers in a darknet cryptomarket to examine the relationship between market processes and drug culture. Taking a material culture perspective, it discusses what aspects of potency are sought after and how the drugs themselves are calibrated to reflect market conditions and users’ experiences and expectations. It examines how the substance’s potency becomes stable, both as a physical substance and as a consistent commodity, and the introduction of harm through the supply chain. It discusses users’ presentation as hyper-modern, risk-reflexive consumers. Increasingly, we are seeing self-efficacy being used as the measure of a substance’s potency, a new development which points towards a novel understanding of the relationship between self and intoxication. Features of the marketplace design plug into this subjectivity, promoting a rational consumer ethic through its feedback features. The chapter ends with some critical thoughts on how the ‘rational market’ design makes some features of the commodity chain transparent while obscuring others.
Cultural Studies’ Approach as a Methodological Basis of Modern Pedagogical Education

The subject of this article is the methodological features of the cultural studies’ approach as the foundation, the basis of modern teacher education. The article deals with various types of culture; the need for understanding at a new historical stage characterized by global environmental and social challenges, the role of the teacher as a carrier of Culture in the modern school, the application of various aspects of the cultural studies’ approach to building individual cultural trajectories of students in the process of modern teacher education is noted. Based on the consideration of the views of scientists from various scientific schools regarding possible solutions to the above very complex and urgent tasks, the significance of art and creative activity in the professional and pedagogical development of a modern teacher is revealed. The result of the theoretical and empirical study of this issue by the authors of the article was the development and implementation on the basis of pedagogical universities of the Russian Federation of a parametric model of professional and pedagogical training of future teachers for the organization of culturally appropriate pedagogical interaction with schoolchildren. The goals, objectives and fundamental principles of introducing this model into the educational process are briefly disclosed in this article.
Innovators: Advantages and Disadvantages of the Future Profession from the Perspective of Students

Development and implementation of innovations in different fields of human life becomes a driving force of economic development of any country in the modern world. Russian higher educational institutions are enrolling students for the Innovatics course to train future innovators. This raises a logical question - who is an innovator and what is he/she dealing with?&#x0D; The purpose of the survey discussed by the article was to identify students’ opinions - the future innovators – on advantages and disadvantages of their future professional activity. Using a longitudinal method, two groups of students who took the Innovatics course (bachelor's degree) have been monitored for four years, which allowed identifying the students' opinions on both how they imagined their future profession, and how this opinion had changed throughout the period of study.&#x0D; Key methods of the research were general scientific cognition methods, such as theoretical analysis of different positions on such area of knowledge as Innovatics and the profession of innovator, as well as empirical methods, such as observation, interviews and questionnaires.&#x0D; The surveys of students obtained data on not only the advantages and disadvantages, which, according to future innovators, are associated with their professional activities, but also on what would be interesting for them to learn in the course of their professional activity.&#x0D; Key competencies to be formed in the process of Innovatics training were listed to make the innovators-graduates demanded in the labor market.
The AI‐powered Patient Experience

Healthcare is one domain where AI progress is phenomenal and is saving lives every day. AI is here to stay, and its advantages are many in healthcare. Design can tame its awkwardness to create experiences that empower patients to be more active in their journeys.
Virtual and Augmented Reality: A Glance into the Future

Over the past two decades, we have seen an unimaginable amount of change in the technology we use and how we use that technology. Get ready for the future (and some ways you may already be experiencing it) with this primer on augmented and virtual realities.
Life sharing or crimes sharing: an investigation on crime learning from China short-form video platforms

The worldwide proliferation of TikTok revealed the shifting interests of users from text-and-image-based content to short-form videos (SVs). Short-form Video Platforms (SVPs) have been further acknowledged as mainstream life-sharing platforms and novel learning resources for informational and practical needs. Surprisingly, increasing evidence from China’s judicial practices unfolded that, offenders were motivated and learned criminal skills by interacting with and imitating from the SVPs’ uploaders. Previous literature has focused on harmful contents and its negative impact on traditional social media platforms, limited has drawn attention on SVPs nor its shared SVs which may potentially spread criminal intentions or even skills to the audience. To fill these gaps, this article for the first time focused on SVP, intended to investigate the criminal motivations and skills identified in China’s major SVPs, explored the rationales behind crime learning behaviors, and proposed feasible regulatory solutions for the SVPs to facilitate the prevention of crimes.
Information and Management Culture of the Head as a Factor of Improving the Management Process of a General Education Organisation in the Context of Digital Transformation of Education

The study aims to formulate an idea about the essence of the information and management culture of the head and its place regarding the improvement of the management process of a general education organisation in the context of digital transformation of education. The paper examines the impact of the information and management culture of the head on the development of a general education organisation in terms of identifying alternatives, choosing a variant of development strategies, analysing achievements in the innovation field. Scientific novelty of the study lies in defining the notion of the information and management culture of the head of a general education organisation and providing the basic recommendations for its successful improvement within the activities of a general education organisation. As a result, it has been proved that the formation and then improvement of the information and management culture of the head contributes to the development of a unified information space and the introduction of digitalisation elements in the activities of a general education organisation.
Estimating the degree of non-Markovianity using variational quantum circuits

Several applications of quantum machine learning (QML) rely on a quantum measurement followed by training algorithms using the measurement outcomes. However, recently developed QML models, such as variational quantum circuits (VQCs), can be implemented directly on the state of the quantum system (quantum data). Here, we propose to use a qubit as a probe to estimate the degree of non-Markovianity of the environment. Using VQCs, we find an optimal sequence of qubit-environment interactions that yield accurate estimations of the degree of non-Markovianity for the amplitude damping, phase damping, and the combination of both models. We introduce a problem-based ansatz that optimizes upon the probe qubit and the interaction time with the environment. This work contributes to practical quantum applications of VQCs and delivers a feasible experimental procedure to estimate the degree of non-Markovianity.
Energy Treasure Hunts

This discussion will highlight the steps necessary to find energy savings opportunities within any type of processing facility. An Energy Treasure Hunt or €œKaisen€ is a three day, plant-wide activity (but can take up to 5 days for large facilities) that focuses on:&lt; ![if !supportLists] &gt;1 &lt; ![endif] &gt;Low cost and no cost actions to reduce energy consumption&lt; ![if !supportLists] &gt;2 &lt; ![endif] &gt;Learning ways to continuously improve and reduce energy consumption&lt; ![if !supportLists] &gt;3 &lt; ![endif] &gt;Brainstorming ways to reduce energy use throughout the facility 4 &lt; ![endif] &gt;Identifying, analyzing and evaluating energy savings opportunities by observing daily operations 5 &lt; Quantifying those opportunities for energy reduction using a standard methodology and calculationFacility employees implement the Energy Treasure Hunt process with the aid of outside energy experts.The purpose of an Energy Treasure Hunt is to:&lt; ![if !supportLists] &gt;1 &lt; ![endif] &gt;Combine knowledge from other plants, suppliers, consultants&lt; ![if !supportLists] &gt;2 &lt; ![endif] &gt;Go and see, listen and smell&lt; ![if !supportLists] &gt;3 &lt; ![endif] &gt;Identify energy use in the facility&lt; ![if !supportLists] &gt;4 &lt; ![endif] &gt;Conceive new ideas and share exiting ones&lt; ![if !supportLists] &gt;5 &lt; ![endif] &gt;Find new ways to save&lt; ![if !supportLists] &gt;6 &lt; Increase energy awarenessOnce the Energy Treasure Hunt has been completed, the facility is responsible to implement the projects that meet the necessary return on investment.
Anywhere Hoop: Virtual Free Throw Training System

To complete successfully a high percentage of free throws in basketball, the shooter must achieve a stable trajectory with the ball. A player must practice shooting repeatedly to shoot a ball with a stable trajectory. However, traditional practice methods require the preparation of a real basketball hoop, which has made it difficult for some players to prepare a practice environment. We propose a training method for free throws using a virtual basketball hoop. In this paper, we present an implementation of the proposed method and experimental results showing its effectiveness.
Semi-Supervised Learning Based on Reference Model for Low-resource TTS

Most previous neural text-to-speech (TTS) methods are mainly based on supervised learning methods, which means they depend on a large training dataset and hard to achieve comparable performance under low-resource conditions. To address this issue, we propose a semi-supervised learning method for neural TTS in which labeled target data is limited, which can also resolve the problem of exposure bias in the previous auto-regressive models. Specifically, we pre-train the reference model based on Fastspeech2 with much source data, fine-tuned on a limited target dataset. Meanwhile, pseudo labels generated by the original reference model are used to guide the fine-tuned model's training further, achieve a regularization effect, and reduce the overfitting of the fine-tuned model during training on the limited target data. Experimental results show that our proposed semi-supervised learning scheme with limited target data significantly improves the voice quality for test data to achieve naturalness and robustness in speech synthesis.
Anti leakage method of power information communication data based on chaotic mapping

Power information communication contains sensitive and private data, which may be illegally stolen and tampered after being leaked, posing a threat to the data security of power enterprises and users. Aiming at the problem of limited key space, a data leakage prevention method for power information communication based on chaotic mapping is proposed. The physical layer of power communication includes power data produced and distributed by power equipment, and the information layer includes operation, monitoring and dispatching data. There is an association between the two data. The dispatch and control center uses the association relationship to establish access rights for users and generate access private keys for trusted users. According to the user authority, the communication data is encrypted and decrypted by chaotic mapping, so that the two adjacent components of the reconstructed key space are relatively independent, and the properties of the chaotic sequence are maintained. The test results show that the proposed method can effectively reduce the computing and communication overhead of the power data encryption process and improve the encryption efficiency.