Reviewerly/exHarmony huggingface dataset:
Wireless Sensing Based Solar Tracking System Using Machine Learning

Solar energy is a clean source of energy that falls under the category of renewable and sustainable energy and is widely accessible around the globe. In solar power systems, solar tracking systems are critical for optimizing energy output from the sun. Single and dual-axis solar trackers have traditionally been used to move solar panels in different directions based on the sun’s beams in order to enhance energy. To optimize the energy gain, the deployed tracker must actively follow the sun’s rays and adjust its location appropriately. The key components needed for constructing tracking systems are sensors, microcontroller-controlled control circuits, and servomotors with supports and mountings. Two servo motors are used to adjust the position of the solar panel so that the sun’s beam remains aligned with the solar panel. The suggested solar tracking system, which is based on machine learning, allows the solar panel to spin in any direction. The proposed machine 140learning-based classification technique examines and categorizes sensor outputs as defective or not. If the sensor results are awarded the class label “Non-faulty,” the servo motor adjusts the position and direction of the solar panel depending on the input sensor data. If the sensor readings are classified as “Faulty,” the servo motor will modify the position and direction of the solar panel using a regression-based machine learning technique.
Emerging forensic genetic technologies

This chapter sees the partially realised nature of these technologies as an opportunity rather than a problem. It utilises this opportunity to explore interpretations of emerging forensic DNA technologies to illuminate how they render orderings of various domains fluid and malleable. Such domains include the natural and social sciences, ethics, law, commerce and society at large. The chapter draws on the conceptual framing of interpretive flexibility as developed via social construction of technology studies, which have highlighted the different perceptions of technology on the part of different stakeholders embedded in sociotechnical networks. Differing standpoints and interpretations of technology may lead to contested plans and imaginaries. Framing technolegal anticipation (namely, anticipations of law-science-technology-society relations) in terms of embedded interpretive flexibility enables the chapter to illuminate differing normative interpretations of technology and sociotechnical engagement. Here, discursive responses to three notable examples of emerging forensic DNA methods are explored: rapid DNA analysis, forensic DNA phenotyping (FDP) and forensic genealogical testing. These three examples are presented in order to examine how their perceived status embodies differing assumptions concerning how science and wider society should engage, which, in turn, order relations between domains in different ways.
Systemic (mis)trust in technolegal worlds

The deployment of science in support of criminal justice objectives is subject to particular trust relationships. On the example of forensic genetics, this chapter discusses some features of criminal justice that treat trust as a local and fragile achievement, subject to constant and rigorous testing. This restlessness about the fragility of the achievement of trust is a constitutive and distinctive feature of criminal justice uses of science. This chapter considers the ways in which trust in forensic genetics is negotiated. It explores some of the multiple uses of the idea of trust in context, together with the types of people who are invoked as part of three trust relationships – epistemic, operational and courtroom credibility – to explore the role of trust in organising technolegal worlds of using of genetics in the criminal justice system. The chapter develops the concepts 1) systemic trust for forensic genetics in the criminal justice system and 2) technology of situated trustworthiness to characterise trust relationships here.
A data transmission approach with energy reduction based on virtual machine migration technique in cloud computing

To provide quicker data access, database centres use virtual machines (VMs) migration to maintain regular content pages in the necessary unit. Memory sharing without downtime is ideal for offline VM migration. However, it has several problems while migrating active VMs. To improve bandwidth availability and hardware stability, it is utilised in workload balancing, low energy retains, and dynamic VM resizing. Thus, needless memory (dirty pages) moving leads in lengthy migration time and downtime. To minimise energy usage and the number of VM migration stages, we offer the NPA-FLI-EC. It combines neural prior prediction algorithm and fuzzy logic insertion of energy reduction on VMM method. Using NPA-FLI-EC, it may optimise VM placement and minimise connection loss on physical servers, while anticipating resource identification from each host reduces needless VM migrations. Thus, it allows for task diversification over multiple servers while saving 2/3 of total energy usage. It also saves bandwidth and improves energy efficiency by consolidating the number of VMs.
Research on the application of artificial intelligence in traditional Chinese medicine online education

With the rapid development and progress of modern information technology computer networking technology, many colleges and universities have paid attention to the necessity of opening and using computer network courses. The main form of teaching, computer network classroom teaching actually refers to the process in which teachers use computer networks to allow learners to complete basic knowledge exercises. It has become a new way for learners to master basic knowledge, and it has also greatly improved. The disadvantages of traditional teaching methods. For this kind of innovative education, in order to achieve the improvement of teaching efficiency and quality level, it is necessary to effectively base on the background of the development of science and technology, and continuously apply various advanced science and technology to realize the innovative development of Chinese medicine online education. The research focus is based on the concept and characteristics of artificial intelligence to deeply explore its application in traditional Chinese medicine online education.
The Effect of Artificial Intelligence Education Program on Self-efficacy and Systems Thinking of Elementary Gifted Students

This study analyzes the effect of presenting artificial intelligence education as an overall process to gifted students who will be the main players in the future industry. In this study, artificial intelligence education focused on one overall process of physically expressing image learning, modeling, web services, and physical computing. As a result of applying this to selected information-gifted students of S Office of Education, there was a significant improvement in social efficacy overall, and in systems thinking, there was a significant improvement in mental model, personal mastery, systems thinking, shared vision, and overall. It was found that applying artificial intelligence education to information-gifted students can have advantages. It is hoped that the paper will contribute to the expansion of artificial intelligence education for information-gifted students who will be the main players in the future.
UJI BLACK BOX TES APLIKASI SOFTWARE DEVELOPMENT SYSTEM INFORMATION (SODEVI) PT. DIMATA SORA JAYATE MENGGUNAKAN KATALON STUDIO

Software Development System Information (SoDevi) is a web-based application used by programmers and testers to work on projects at PT. In the eyes of Sora Jayate. This application is used to perform enhancements to the UI/UX web display to improve web performance and layout. It is necessary to test the SoDevi application, in order to improve the quality of the application developed by PT. In the eyes of Sora Jayate to minimize bugs or errors in the application. In previous applications that were developed there were problems, namely, when testing manually, human errors often occurred which resulted in the test results not being carried out optimally. By doing automated testing in search of bugs or errors in the system, it is very necessary to do, where one of the tests that can be done is to do a black box test. Performing a black box test will be very influential in testing a system, where this test will look for deficiencies and errors from the system that has been built. Testing is carried out in order to get an assessment, so that the system that has been built is in accordance with expectations and later there is no need to do repeated testing. A system can be said to be valid if the testing process has been carried out, because by testing it will be known with certainty the error function of the process in the system or not. In the black box test, the focus of the test is only on the functional test of the system, not on testing the model or program code. In the system test carried out on the SoDevi application, an automation tool called Katalon Studio will be used which will record the testing and scripting steps to run the test with the test focus only on the create, read, update and delete (CRUD) processes. The results of the black box test carried out on the SoDevi application have been running according to function and no bugs or errors were found from the system. From the black box test which is done automatically using Katalon Studio, it can be concluded that the system is running well where errors that occur in the application are a factor of human error.
Identity Checks &amp; Correctness of Bank Account Using Penny Drop Procedure

Accuracy in identity of the person, his contact details, bank account are most essential data in any establishment to conduct any operations. These data must be collected and validated before on-boarding stage with requisite support evidence and must be maintained in the accounting system. In this fintech world there are many advancement in process to verify the correctness of the identity of the person and his bank account without major effort and time. Since the verification is done through the system there is no paper work and subsequent workflow can be smooth and reliable. Verification of identity of the persons bank account in penny drop mechanism is discussed in this write-up.
Information security protection for eHealth records using temporal hash signature

Patient health record information management becomes an important and challenging task through the different practices followed by hospitals. Also, the risks associated with securing the data from cyber-attacks and data breaches become inevitable. Ransomware is the biggest cyber-attack in the history of National Health Service (NHS) which has affected nearly 100 countries worldwide in 2017. In the healthcare system, loss of sensitive data leads to embarrassment whereas loss of integrity leads to loss of the patient's life. Though many technical solutions exist to store the electronic health record (EHR) information in a secure way, it is not sufficient to satisfy the security requirements such as clear attributes for role-based access, common regulations that protect patient's privacy and specific guidelines to control the data. This paper provides a brief discussion on the existing security mechanisms with a proposal based on the temporal shadow in the cloud. The integrity of the patient's document is modelled with linked records and verified by temporal signature.
Experiences and Perceptions of Pre-service Special Education Teachers on Flipped Learning

The study investigated the experiences and perceptions of pre-service special education teachers who had adopted flipped classrooms. The participants in this study were fourteen second- and third- year students majoring in special education at K University. They took a course entitled “Theory of Early Childhood Special Education,” which adopted the flipped learning format for one semester. The researcher conducted individual interviews to identify participants’ experiences and perceptions with respect to the flipped classroom. The results of the interviews were transcribed, and the transcriptions were analyzed by constant comparative methods. Three themes and six subcategories were derived: (a) opinion about operation of flipped learning, (b) experience with flipped learning, and (c) proposals to improve flipped learning in universities. Based on the results of this study, various teaching support methods in teacher training institutions were discussed to improve the training of special education teachers.
Live broadcasting of sporting events: a trigger to the revolutionary reform of Chinese copyright law by transforming the condition of originality

In Chinese law, the seemingly transparent condition of originality has been used to classify audiovisual productions into two categories: videograms protectable by neighboring rights and cinematographic works protectable by copyright, the latter of which benefit from a higher level of protection.However, the reality is that audiovisual productions often involve the intellectual efforts of their production teams, as shown through the live broadcasting of sporting events, such that one cannot completely deny the absence of originality therein.In addition, considering that the legitimate interests of TV and broadcasting organizations are justified by their significant investments and the need to prohibit rampant retransmission of their broadcasts on the Internet, it is no longer possible to maintain the distinction between cinematographic works and non-copyrightable audiovisual productions.In these circumstances, a series of famous cases and doctrinal debates regarding live broadcasting of sporting events have triggered the revolutionary reform of the Copyright Law of China in 2020, in which the statutory category of cinematographic works has been replaced by audiovisual works.This reform has not only granted copyright protection to all audiovisual productions but has also adopted the minimum threshold requirement for which copyrightable works may qualify for originality.This minimum threshold will likely further open the door of copyrights to encompass all productions vital to industries.
A Study on the Improvement of the Accreditation System for Learning Experience Recognition System in the Open School

본 연구의 목적은 방송중·고 학습경험인정제 이수인정평가체제를 진단하고 해당 결과를 바탕으로 기존 학습경험인정제 이수인정평가체제 개선 방안을 마련하는 데 있다. 이를 위해 본 연구에서는 1)문헌연구, 2)설문조사, 3)전문가 협의회, 4)표적집단면접(FGI: Focus Group Interview)의 네 가지 연구방법을 활용하여 실증적 데이터에 기반한 현 체제의 체계적인 진단과 함께 제도 관계자 및 분야별 전문가들의 여러 가지 요구와 의견을 바탕으로 개선 방안을 도출하였다. 연구결과, 4개 부문, 14개 쟁점 가운데 4개는 학습경험인정제 인정대상 영역 확대 방안을 모색할 필요가 있는 것으로 나타났다. 특히 학생들의 수혜 확대를 위해 ‘학력미인정 학교형태 평생교육시설’을 인정대상 영역으로 확대하는 방안과 사후평가를 통해 인정 범위를 확대하는 방안이 도출되었다. 방송중·고에서 운영되고 있는 학습경험인정제 이수인정평가체제를 다룬 본 연구는 고교학점제와 2022 개정 교육과정에서 논의 중인 ‘학교 밖 학습경험’에 대해 시사점을 제시해 줄 수 있을 것으로 기대된다.The purpose of this study is to diagnose the accreditation system of the learning experience recognition system which is recognition of prior learning system of the open schools and prepare the improvement plan for the accreditation system based on the results. In this study, four research methods were used: 1) literature studies, 2) surveys, 3) expert councils, 4) focus group interview to systematically diagnose the current system based on empirical data, and to derive improvements based on various demands and opinions from institutional officials and experts. As a result, 14 issues in four areas have been identified. In particular, 4 out of 14 explained the need to expand the area of the subject of learning experience recognition in order to expand the benefits of students. As a specific plan, the scope of recognition was expanded through recognition of learning experiences in lifetime education facilities in the form of unrecognized schools and post-evaluation. This study, which deals with learning experience recognition system of the open schools, is expected to provide implications for the “out-of-school learning experience” being discussed in the high school credit system and the 2022 revised curriculum.
Supervised Learning Using PyTorch

Supervised machine learning is the most sophisticated branch of machine learning. It is in use in almost all fields, including artificial intelligence, cognitive computing, and language processing. Machine learning literature broadly talks about three types of learning: supervised, unsupervised, and reinforcement learning. In supervised learning, the machine learns to recognize the output; hence, it is task driven and the task can be classification or regression. In unsupervised learning, the machine learns patterns from data; thus, it generalizes a new dataset and the learning happens by taking a set of input features. In reinforcement learning, the learning happens in response to a system that reacts to situations.
Data Augmentation, Feature Engineering, and Extractions for Image and Audio

In an audio classification model, you want the deep learning algorithm to learn the sounds and predict a category. Similarly, in image classification, you want the deep learning model to remember the images, learn the patterns from the images, and classify new images into various categories that the learning algorithm has been trained on. In sound classification, you typically start by taking the audio files as inputs and convert them into something called a spectogram. A spectrogram produces a high-dimensional space of data that can be further reduced by applying the convolutional neural network model. As you know, the final layer of a CNN is a neural network, which is also called a fully connected layer and is typically used as a classifier.
Introduction to PyTorch, Tensors, and Tensor Operations

PyTorch has been evolving as a larger framework for writing dynamic models. Because of this, it is very popular among data scientists and data engineers for deploying large-scale deep learning frameworks. This book provides a structure for experts in terms of handling activities while working on a practical data science problem. As evident from applications that we use in our day-to-day lives, there are layers of intelligence embedded with the product features. These features are enabled to provide a better experience and better services to the user.
Checklist for assessing and designing data governance policies

This chapter presents a checklist for policy makers in any domain to review data governance policies and assess whether they address key policy tensions and achieve related objectives effectively. The policy tensions considered are the need to balance data openness and control while maximising trust; to manage overlapping and potentially conflicting interests and regulations related to data governance; and to incentivise investments in data and their effective re-use. Although these three tensions and objectives are common across most policies for data governance, not all questions and policy solutions will be relevant to all contexts.
Simulation of downward solar radiation and profiles of meteorological parameters using model complex WRF-Solar under summer conditions in Tomsk

In this work, we present estimates of the predictions of global horizontal irradiance, as well as of the profiles of air temperature and relative humidity in the interval of 10-40 m under the clear-sky summer conditions near Tomsk. The numerical experiments are carried out for three different configurations of the WRF-Solar model. Data of measurements are obtained using the measurement complex, located on the territory of “Fonovaya” observatory (IAO SB RAS). The statistical analysis of the calculation errors showed that the mean absolute errors and the root-mean-square errors are: 30 W/m2 and 40 W/m2 for GHI, 1.2&deg;C and 1.5&deg;C for air temperature, as well as 10% and 15% for the relative air humidity, averaged over the altitude interval of 10-40 m. Preliminary results showed that the chosen sets of parameterizations make it possible to simulate these characteristics with the accuracy no worse than that of similar calculations by other authors under the analogous conditions.
Trusts of Cryptoassets

The birth of bitcoin in the Great Recession of 2008 appealed to cypherpunks and libertarians distrustful of government. Together with copycat altcoins, the volatility of cryptoassets has drawn interest from investors and speculators who did not share in these ideals, including trustees, raising four questions. First, can cryptoassets be the subject-matter of trusts? Second, if so, how may the rules relating to validity be applied to cryptoassets? Third, is such an investment permitted under the terms and/or governing law of a particular trust? Finally, what must trustees be aware of in deciding whether to invest in this new asset class?
‘…e poi le parole’

Any attempt to write a history of the libretto is fraught with paradox. Almost without exception, a text is the starting point for any opera. Indeed, before Mozart, and often after, the libretto was normally complete before the composer put pen to paper, for all that it might then be revised according to the musical and other demands made upon it. As we shall see, its poetry usually had quite precise musical implications. Moreover, in early opera the poet was normally the prime mover in the operatic enterprise, not just by devising the subject and fleshing it out with appropriate words, but also given his often standard role as director of the production. The libretto was itself the public face of opera in terms of the artefacts that survive to record a given performance: libretti were usually printed for general consumption inside or outside the theatre, whereas musical scores were, on the whole, regarded as more ephemeral performance materials, to be adopted, adapted, and disposed of at will. Poets also acted as the chief ideologues of opera, promoting and defending the genre against its detractors and inserting it into broader literary and cultural debates. In a very real sense, the history of the libretto is the history of opera tout court.1
Blockchain Technology Application in Manufacturing

As the name implies, a blockchain is a series of data blocks. It is a distributed database that allows for the tracking of data that has been encrypted using a particular technique called hash. Although blockchain was initially developed for bitcoin trading, its promise extends well beyond cryptocurrencies.