Reviewerly/exHarmony huggingface dataset:
Solar Tracking Technology to Harness the Green Energy

The world demand for green energy is increasing with a rapid increase in the price of fossil fuel and environmental challenges. Solar energy is an abundant, vast, and cost-free source of green energy. Solar energy is generally utilized in the form of electrical energy that can be generated by solar photovoltaic (SPV) system. The world is today researching and exploring the most feasibly optimized way of harnessing green energy. The amount of solar energy captured is a function of the SPV panel orientation. Maximum solar energy harvesting can be achieved by keeping SPV panels perpendicular to the solar irradiance. Hence, solar tracking system is essential to harness solar energy. This chapter is devoted to various solar tracking technologies including artificial intelligence (AI)-based solar trackers to track the optimal orientation of the panels during the day. Also, this chapter covers the overviews of the tracking techniques performance, construction, performance, advantages, and disadvantages of the existing solar tracking system. The limitations of solar tracking systems are also highlighted for future research and its improvement.
Human resource management system with human relations perspective in the industrial revolution 4.0 era in high schools

It is widely accepted that human existence has now changed dramatically as a result of the Fourth Industrial Revolution in terms of thinking, living, and interacting. The fast advancement of technology has had a significant impact on this transition. Equally significant is the impact of the Fourth Industrial Revolution on education. To be able to synergize with the world's rapid growth, education, the engine of cultural change and progress, must be responsive to the onset of this era. Human resource management is the most important factor in enhancing the quality of education so it can adapt to rapidly-changing circumstances in order to deal with this type of change. Human resource management can benefit from an understanding of human relations. This method is effective for humanizing employees in organizations, allowing them to work safely, cheerfully, and with a sense of fulfilment because they are respected. High school education is intended to prepare students to manage human resources effectively. Human connections should prepare high school students for the fourth industrial revolution.
Unification of Multiple Bank Cards and Smart Card with Formula Based Authentication in Big Data

Big data provides a greater space for various organizations to obtain knowledge-oriented decisions. Big data analytics would lead to an increased rate of success. Capturing, storing, searching, sharing, transferring, visualizing, querying, updating are the challenges in big data. In our proposal, the most recent developments in information management include the convergence of big data and RFID technology. We are proposing an advanced Banking, Hospital, and Passport &#x0026; Ration application for our implementation. For all these four applications, RFID is used as a user identification number. User behavior is monitored through Hidden Markov Model (HMM). Formula-based authentication is used for verifying the withdrawal of money above the limit. This card can also be used as a smart card in Ration shops. Users can use this multicard in hospitals to get their information. Multi-card can also be used in airports to register travel. All the information is kept in several Cloud Servers.
Deep learning approaches for analysing visual stimuli from human fMRI

Decoding brain activities corresponding to an external stimulus is an excellent challenge because of the complexity of brain activities data and the understood of the activity of the brain is not yet complete. This research paper focuses on the functional magnetic resonance imaging (fMRI) data of different people corresponding to external visual stimulus images. The images consist of three main types: letters, artificial shapes, and natural images. The proposed model provides an analysis and classification of the three main types of images using Support Vector Machine and Convolutional Neural Networks by proving that the brain is affected differently by each type. In addition, the identification of 200 natural image categories was analyzed by calculating the similarity between the features for each category by using the features of visual images using CNN and fMRI using the regression model. Also, we used deep convolution generative adversarial networks (DCGANs) for image reconstruction.
Empirical Study on Self-efficacy and Individual Innovation Behavior of Scientific Researchers

The optimal functioning of employees must be a constant concern of organizations wishing to present a competitive advantage. Indeed the goal of any company is to ensure its sustainability through the human factor which is one of the key elements of success. For this, companies must implement practices of recognition of the work performed by employees. Indeed, not taking into account this aspect of recognition leads to demotivation and a decline in performance by employees. In a company like LCB Bank, there is a real problem of recognition of others in the work done; which is the subject of our brief. This thesis shows the important place of the recognition of others and suggests to the managers of the LCB Bank to apply different forms of recognition and an appropriatestyle of management to mobilize more the employees in the tasks which are proposed to them.
Review on Occupancy Detection Techniques in Smart Buildings Using Machine Learning

Today’s fast-moving world has forced time-deprived humans to depend on machines not just for their routine tasks, but also for specialized decision-making. Technology has offered so many gadgets to cater to the need of human comfort-seeking that we are moving fast towards the development of smart environments. The development of Smart Commercial buildings is a big step in this direction to facilitate human comfort. Apart from comfort-seeking, these Smart buildings have help in Energy conservation and efficient utilization of resources. Automation of HVAC devices in these smart buildings based on human occupancy has contributed to reduce the Energy consumption, leading to green environment. Automation is primarily assisted by the use of machine learning algorithms that tend to offer predictions based on historical data and previous learning.
Data Augmentation based on Deep Learning for Object Detection of Infrared Cameras in Extreme Environments

Recently, in-depth studies on sensors of autonomous vehicles have been conducted. In particular, the trend to pursue only camera-based autonomous driving is progressing. Studies on object detection using IR (Infrared) cameras is essential in overcoming the limitations of the VIS (Visible) camera environment. Deep learning-based object detection technology requires sufficient data, and data augmentation can make the object detection network more robust and improve performance. In this paper, a method to increase the performance of object detection by generating and learning a high-resolution image of an infrared dataset, based on a data augmentation method based on a Generative Adversarial Network (GAN) was studied. We collected data from VIS and IR cameras under severe conditions such as snowfall, fog, and heavy rain. The infrared data images from KAIST were used for data learning and verification. We confirmed that the proposed data augmentation method improved the object detection performance, by applying generated dataset to various object detection networks. Based on the study results, we plan on developing object detection technology using only cameras, by creating IR datasets from numerous VIS camera data to be secured in the future and fusion with VIS cameras.
Online Learning App

Nowadays, many students are using online learning apps due to the surge of people having Internet connectivity as well as due to ongoing pandemic where getting an education in a traditional way is not possible. The students can learn and practice at their own pace as well as educators can monitor student’s progress and teach them easily through online learning platforms. Online learning app is developed using the Java language which can be used by students to learn different coding concepts, data structures, and algorithms. Students can test their knowledge by attempting quiz regarding the same. The platform being used is Android Studio. The backend used is Firebase Realtime Database where the assets required by the app are stored and email authentication is performed using the authentication service provided by Firebase.
Live Patching Database Management Systems

Share on Live Patching Database Management Systems Author: Michael Fruth University of Passau, Passau, Germany University of Passau, Passau, GermanyView Profile Authors Info & Claims SIGMOD '22: Proceedings of the 2022 International Conference on Management of DataJune 2022 Pages 2524–2526https://doi.org/10.1145/3514221.3520253Online:11 June 2022Publication History 0citation46DownloadsMetricsTotal Citations0Total Downloads46Last 12 Months46Last 6 weeks6 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my Alerts New Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
#multilingualself: Hashtagging as a Resource for Performing a Multilingual Identity

Vandergriff’s discourse-analytic study of a Reddit discussion shows how L2 errors are construed as obstacles to full participation. In reproducing language ideologies and affirming the hegemony of the native speaker, Reddit community norms are shown to promote linguistic gatekeeping but the data also provide compelling evidence of inclusion of L2 users.
Using TDM data to study treatment failure

Introduction Psychotropic drug treatments are associated with frequent ‘trial-and-error’ events reflecting insufficient clinical responses or serious side effects. The term treatment failure is in this context defined as an unsuccessful outcome of the medical intervention. Accordingly, indirect endpoints of treatment failure comprise drug discontinuation (1), drug switch (2), hospitalization or nonadherence during drug treatment (3), serum concentrations outside the target range (4), and treatment-resistance (5). Use of therapeutic drug monitoring (TDM) data in research projects offers unique possibilities of providing rates of such endpoints and also relate their occurrence to patient factors, including pharmacogenetics.
Implementation of Project Activities in Engineering Education on the Example of the Educational Program "Space Technologies"

Specificities of the project activities teaching within frames of the authorial educational program "Space Technologies" are considered in the paper. Nowadays project activities are being implemented widespread, but among all programs, special attention is paid to engineering education. This is related to the necessity to train young specialists who will be capable to solve complex and non-standard tasks. It should be noted that the implementation of project activities takes place both at the level of higher and secondary education. To solve this task, teachers with practical experience are involved, who have mastered all the nuances and complexities of project activities. The implementation process takes place in various ways: from setting individual or group tasks in the subject or discipline program to allocating certain time and premises for working on projects. But the purpose of this implementation remains unchanged, regardless of the form or level of education: to educate the young generation, ready not only to perform standard work, but also to invent and produce really working products and services in demand. This paper discusses methods of organization and examples of project activities based on the engineering educational program "Space Technologies", main results of developed projects are presented. A detailed description of space objects and models designed on the space simulator "Kerbal Space Program" basis can be found by linking to articles from the list of references, where the feasibility of created space objects is based on modern achievements of science and technologies is proved.
Recent advances in multi-modal data fusion: status, challenges and perspectives

Advancements in computer science, especially artificial intelligence (AI) and machine learning(ML) have brought about a scientific revolution in a plethora of military and commercial applications. One of such area has been data science, where the sheer astronomical amount of available data has spurred sub-fields of research involving its storage, analysis, and use. One such area of focus in recent years has been the fusion of data coming from multiple modalities, called multi-modal data fusion, and their use and analysis for practical and employable applications. Because of the differences within the data types, ranging from infrared/radio-frequency to audio/visual, it is extremely difficult, if not flat-out impossible, to analyze them via one singular method. The need to fuse multiple data types and sources properly and adequately for analysis, therefore arises an extra degree of freedom for data-science. This paper provides a survey for multi-modal data fusion. We provide an in-depth review of multi-modal data fusion themes, and describe the methods for designing and developing such data fusion techniques. We include an overview for the different methods and levels of data fusion techniques. An overview of security of data-fusion techniques, is also provided which highlights the present gaps within the field that need to be addressed.
Revisiting Universals and Typology of Vowel Systems

This work aims to revisit universals and typology of vowel systems in natural language. In general, the universals of a vowel system are evaluated by four criteria: the size of the vowel inventory of the language, the nature of constitutional entities of the vowel system, the phonetic features of the vowels, and the distribution of vowels in the vowel space. However, there are languages that are evaluated more correctly when other standards are applied. In this paper, we considered some examples of such languages. Furthermore, in terms of vowel typology, there are vowel systems that cannot be properly approached with a standard view. How to analyze such vowel systems is also discussed. In addition, we discussed the vowel space from a new perspective.
Artificial neural network modeling for predicting the quality of water in the Sabak Bernam River

Water &lt;span&gt;quality prediction is aided by environmental monitoring, ecological sustainability, and aquaculture. Traditional prediction approaches capture the nonlinearity and non-stationarity of water quality well. Due to their rapid progress, artificial neural networks (ANNs) have become a hotspot in water quality prediction in recent years. ANNs are utilised in this study to predict water quality using soft computing techniques. The feedforward network and the standard back-propagation method of Levenberg-Marquardt and scaled conjugate gradient learning algorithm were employed in this research. One hidden layer has been recommended for the modelling, with the number of hidden neurons set at 3, 24, and 49. For this analysis, six different testing percentages were used, and the output data can be categorised as '0' for clean water and '1' for polluted water. From the results, it can be shown that the most optimised model was from the model of trainlm with a testing percentage of 18% and with 3 number of neurons. This most optimised model obtains an accuracy of 91.7%, the best validation performance of 0.073346 with 24 epochs, and having a receiver operating characteristic (ROC) curve that is closer to the true positive rate compared to other samples.&lt;/span&gt;
Index/Impressum: Vakuum in Forschung und Praxis 3/2022

Vakuum in Forschung und PraxisVolume 34, Issue 3 p. 51-51 Magazin Index/Impressum: Vakuum in Forschung und Praxis 3/2022 First published: 05 June 2022 https://doi.org/10.1002/vipr.202270309AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume34, Issue3June/July 2022Pages 51-51 RelatedInformation
Location Verification and 2-way privacy preserving in Location-based Services

As we are developing, the location-based services are increasing, and along with them, the security issues are also growing. The security of the user’s query i.e. whatever request he asked for is no longer secure, and also the response that he is getting is not secure as well. So it becomes essential to provide privacy to the user’s query from the ends, the user and the server. Many people are doing their work and have some progress as well, but the problem is they are either able to provide efficiency in this or the security. The solution proposed till now cannot offer both are things simultaneously. They have to compromise with either of these two. And if they can do that, then the cost of estimating that is way high. Too many computations and because of this method becomes too complex so that the light working gadgets which are using these location-based services will not be able to use this, and their system may get crashed with these complex approaches. So to overcome this, we are proposing this approach of camenisch-shoup based oblivious function that provides security and efficiency, and the cost is not that high. This method allows privacy to the user. He can send the request to the server without exposing too much information. Also, the server responds to the request without telling the other information. Both the user and server can interact with each other without sharing little information.
Problems and suggestions on the teaching quality of Chinese vocational education

The purpose of the study is to identify factors affecting the quality of teaching through the actualization of problems related to the quality of teaching in vocational education. The scientific novelty lies in the fact that theory and practice are combined to solve the tasks assigned to the study. As a result, a practical list of proposals was put forward to promote the improvement of the quality of teacher training in the field of vocational education and to increase the attractiveness of vocational education in general.
Rapid Calibration of the Projector in Structured Light Systems Based on Brox Optical Flow Estimation

In this work, we propose a rapid calibration technique for locating the projector in the structured light measurement system. Using Brox optical flow, the calibration of the three-dimensional (3-D) coordinates of the projector only requires two images captured before and after the motion of the calibration plate. The calibration principle presented in geometry depicts the relation between the position of the projector, the camera, and the optical flow caused by the movement of the calibration plate. Some important influences on accuracy are discussed, such as the environmental noises and the localization error of the camera and the calibration plate, illustrated by numerical simulations. The simulation results show that the relative errors of the projector calibration results are less than 0.8% and 1% in the case of the calibration images polluted by Gaussian noise of SNR of 40 dB and 20 dB, respectively. An actual experiment measured a square standard block, and a circular thin plate verifies the proposed method’s feasibility and practicality. The results show that the height distributions of the two specimens are in good agreement with their true values, and the maximum absolute errors are 0.1 mm and 0.08 mm, respectively.
Online Shaming on Social Media: Analyze and Mitigation

In this paper we would be discussing about online shaming and analyse different type of shaming and how to deal with it. The task of public shaming detection in social media is automated from the perspective of victims. It explores primarily about two aspects, namely, events and shamers. Based on classification of shaming tweets, a web application has been designed and deployed especially for one type of shaming tweet that of sarcasm, and the website also provide information about shamer who has used abusive comments under the user profile more than three time and sent alert message to user about the informing about the shamer
An Analysis of The Perceived Factors Impacting Employee Satisfaction and Retention in Saudi Arabia’s Higher Education Sector

The purpose of the study is to examine the factors that are perceived to have an impact on employee satisfaction and retention. This study employed a survey approach in order to gain the respondents' perceptions of the study. The target respondents of this study are academicians in the educational sector in Saudi Arabia. The source of the sampling based on the Saudi Ministry of Higher Education. A total of 384 respondents participated in this study, and the collection of the data was based on a stratified probability sampling technique. To address the research objectives, the study employed PLS-SEM to test the hypotheses of the study. The study has found that work engagement, co-worker relationships, and a supportive work environment are key to employee satisfaction in the educational sector in Saudi Arabia. Meanwhile, the working environment, perceived organizational support, and a supportive work environment are key to employee retention.
Machine Learning and Data Analysis

Data-driven discovery is revolutionizing how we model, predict, and control complex systems. Now with Python and MATLAB®, this textbook trains mathematical scientists and engineers for the next generation of scientific discovery by offering a broad overview of the growing intersection of data-driven methods, machine learning, applied optimization, and classical fields of engineering mathematics and mathematical physics. With a focus on integrating dynamical systems modeling and control with modern methods in applied machine learning, this text includes methods that were chosen for their relevance, simplicity, and generality. Topics range from introductory to research-level material, making it accessible to advanced undergraduate and beginning graduate students from the engineering and physical sciences. The second edition features new chapters on reinforcement learning and physics-informed machine learning, significant new sections throughout, and chapter exercises. Online supplementary material – including lecture videos per section, homeworks, data, and code in MATLAB®, Python, Julia, and R – available on databookuw.com.