Reviewerly/exHarmony huggingface dataset:
Nowcasting Hourly-Averaged Tilt Angles of Acceptance for Solar Collector Applications Using Machine Learning Models

Challenges in utilising fossil fuels for generating energy call for the adoption of renewable energy sources. This study focuses on modelling and nowcasting optimal tilt angle(s) of solar energy harnessing using historical time series data collected from one of South Africa’s radiometric stations, USAid Venda station in Limpopo Province. In the study, we compared random forest (RF), K-nearest neighbours (KNN), and long short-term memory (LSTM) in nowcasting of optimum tilt angle. Gradient boosting (GB) is used as the benchmark model to compare the model’s predictive accuracy. The performance measures of mean absolute error (MAE), mean square error (MSE), root mean square error (RMSE) and R2 were used, and the results showed LSTM to have the best performance in nowcasting optimum tilt angle compared to other models, followed by the RF and GB, whereas KNN was the worst-performing model.
How Not To Design An Efficient FHE-Friendly Block Cipher: Seljuk

Abstract With the rapid increase in the practical applications of secure computation protocols, increasingly more research is focused on the efficiency of the symmetric-key primitives underlying them. Whereas traditional block ciphers have evolved to be efficient with respect to certain performance metrics, secure computation protocols call for a different efficiency metric: arithmetic complexity. Arithmetic complexity is viewed through the number and layout of nonlinear operations in the circuit implemented by the protocol. Symmetric-key algorithms that are optimized for this metric are said to be algebraic ciphers. It has been shown that recently proposed algebraic ciphers are greatly efficient in ZK and MPC protocols. However, there has not been many algebraic ciphers proposed targeting Fully Homomorphic Encryption (FHE). In this paper, we evaluate the behavior of Vision when implemented as a circuit in an FHE protocol. To this end, we present a state-of-the-art comparison of AES and Vision implemented using HElib. Counterintuitively, Vision does not deliver a better performance than AES in this setting. Then, by attempting to improve a bottleneck of the FHE implementation evaluating Vision we present a new cipher: Seljuk. Despite the improvement with respect to Vision, Seljuk does not deliver the expected performance.
Offline Calibration for Infant Gaze and Head Tracking across a Wide Horizontal Visual Field

Most well-established eye-tracking research paradigms adopt remote systems, which typically feature regular flat screens of limited width. Limitations of current eye-tracking methods over a wide area include calibration, the significant loss of data due to head movements, and the reduction of data quality over the course of an experimental session. Here, we introduced a novel method of tracking gaze and head movements that combines the possibility of investigating a wide field of view and an offline calibration procedure to enhance the accuracy of measurements. A 4-camera Smart Eye Pro system was adapted for infant research to detect gaze movements across 126° of the horizontal meridian. To accurately track this visual area, an online system calibration was combined with a new offline gaze calibration procedure. Results revealed that the proposed system successfully tracked infants' head and gaze beyond the average screen size. The implementation of an offline calibration procedure improved the validity and spatial accuracy of measures by correcting a systematic top-right error (1.38° mean horizontal error and 1.46° mean vertical error). This approach could be critical for deriving accurate physiological measures from the eye and represents a substantial methodological advance for tracking looking behaviour across both central and peripheral regions. The offline calibration is particularly useful for work with developing populations, such as infants, and for people who may have difficulties in following instructions.
Research on Edge Detection Model of Insulators and Defects Based on Improved YOLOv4-tiny

Edge computing can avoid the long-distance transmission of massive data and problems with large-scale centralized processing. Hence, defect identification for insulators with object detection models based on deep learning is gradually shifting from cloud servers to edge computing devices. Therefore, we propose a detection model for insulators and defects designed to deploy on edge computing devices. The proposed model is improved on the basis of YOLOv4-tiny, which is suitable for edge computing devices, and the detection accuracy of the model is improved on the premise of maintaining a high detection speed. First, in the neck network, the inverted residual module is introduced to perform feature fusion to improve the positioning ability of the insulators. Then, a high-resolution detection output head is added to the original model to enhance its ability to detect defects. Finally, the prediction boxes are post-processed to incorporate split object boxes for large-scale insulators. In an experimental evaluation, the proposed model achieved an mAP of 96.22% with a detection speed of 10.398 frames per second (FPS) on an edge computing device, which basically meets the requirements of insulator and defect detection scenarios in edge computing devices.
Educational content of modern web-developer training

The article provides an answer to the frequently asked question about what to teach students so that they can easily enter the area of web development and become sought-after specialists in the modern IT industry upon graduation. We completed a review of publications and scientific discussions on this subject, performed an analysis of the relevant professional standards as well as the transformation dynamics of the requirements set out by employers for web developers. In addition, the paper examines the demand for designing educational programs. We interviewed representatives of professional communities and university graduates to understand the challenges which former students face while seeking employment in the field of web development and design. Six main skill groups of a modern successful specialist have been identified. They include basic web development skills, web programming skills, web design skills, development skills and development management skills, web resource promotion skills, universal skills. For each group, we identified the main skills and tools which are advisable to be studied as part of the educational program. It has been discovered that training should be based on using skill-oriented educational technologies since solving specific practical problems will enable each student to form their own future workspace. We also created a model of a graduate who aspires to work in the field of web development.
Adaptive technologies for rapid web interface design of corporate educational systems within the framework of the 1C:Enterprise 8.3 platform

The article discusses technologies for fast web application deployment design based on continuous information exchange with a corporate system developed using the 1C:Enterprise 8.3 platform. We identify data exchange formats between a web application and a software product based on the 1C:Enterprise 8.3 platform to handle the tasks of dynamically generated and adaptable interfaces. The study proposes the concept of a modifiable component-based architecture for the interaction of a web application with commercial data storage and processing systems. This concept makes it possible to implement a dynamic web application interface design and to automate the data management functionality directly from the enterprise solution based on the 1C:Enterprise 8.3 platform. The article formulates the criteria and operating principles for such an application. We have also developed system technologies to design a web application that can be integrated into replicated software solutions permitting control of the mechanisms for dynamic interface design and data transfer from the solution to a web application. The launched application for web application interfaces designing makes it possible to dynamically change the components of web forms as well as determine the details displayed to the user in the output interface. In addition, we describe the principles of dynamic interaction between a web application and the data interface management component. The research enabled us to identify the components of the module for interaction of interfaces with the web application. A conceptual universal control scheme for generating dynamic interfaces has been formulated. It can be implemented to create almost any kind of web forms, including processing incoming data from a web application using the REST interchange in JSON format. The article provides a comparison of interchange formats. We describe implemented IT-projects for organizing a prospective student’s personal account and the applicant’s dynamic rating. These projects are the result of the ideas proposed in the article.
Élaboration d’une liste de vocabulaire dans un contexte FLE

In this article, we discuss the elaboration and use of vocabulary lists aimed for learners of French as a for-eign language. These lists are commonly based on corpora, which, in the ideal case, are representative, relevant and large. As for the English language, this kind of corpora has been available for a long time (e.g. the COCA and the BNC). Vocabulary lists, which are often used in learning contexts, have been based on these corpora. The situation is, however, less favorable when it comes to the French language, with fewer corpora meeting the mentioned criteria, and, thus, fewer possibilities to create vocabulary lists that are useful for learners. In this contribution, we present work that has been done in order to create a vocabulary list, Riksprovsordlistan, containing about 4,000 words and used at all Swedish universities. The discussion focuses on methodological challenges such as choice of counting unit – lemma vs. word family –, the role of frequency, thematic vocabulary, as well as characteristics of written vs. spoken corpora.
A brute force tuning of training length for concept drift

We present a brute-force approach to analyze the concept drift behind time sequence data. This approach, named SELECT, searches for the optimal length of training data to minimize error metrics. In other words, SELECT searches for the start point of a new concept from the input sequence. Unlike many related methods, SELECT does not require a pre-specified error threshold to detect drift. In addition, the visual analysis obtained from SELECT enables us to understand how significant a drift has occurred. We test SELECT on two real-world datasets, stock price and COVID-19 infection data. The experimental results show that SELECT can improve the model performance of both datasets. In addition, the visual analysis shows the points of significant drifts, e.g., Lehman’s collapse in stock price data and the spread of variants in COVID-19 data. These results show the effectiveness of the brute-force approach in analyzing concept drift.
Launching a meteorological rocket as an instructive object of computer simulation in the school informatics course

Since the first Russian school textbook on computer science edited by A. P. Ershov and V. M. Monakhov came out in 1985, the subject of “Computer simulation and computer experiment” has been explored through the simulation of physical processes unfolding in time and accessible to direct observation in many textbooks on Informatics. For such processes, the idea of temporal discretization can be introduced visually with the help of the videotaping metaphor. Russian Informatics textbooks examined a small oscillation of a load on a spring, water flowing out of a cubic tank, a fall of a person without a parachute (“delayed jump”) in the atmosphere considering air resistance as well as the flight of a small object thrown by a person disregarding air resistance as physical processes simulated by computer programs. These examples are informative, but they do not contain any unobvious conclusions that cannot be reached without computer simulation. The article suggests a more attractive simulation object for the school Informatics course, namely the process of vertical takeoff of a one-stage rocket delivering scientific equipment to the upper air of the Earth and the adjacent near-Earth space. Such rockets are called meteorological. The proposed computer simulation object is good because computer experiments with a developed model make it possible to obtain new results. These include designing a rocket whose maximum lift height paradoxically grows with an increase in the payload as well as showing that the lift height of one-stage meteorological rockets could be significantly increased if we only learned to stop the rocket engine for a few seconds during acceleration.
The Sentiment Analysis of EndSARS Protest in Nigeria

The extraction of public opinions from online communication platforms can serve several purposes in corporate institutions, state politics, and governance. The analysis of these opinions may be useful for both immediate business decision making and professional planning. This analysis is becoming relevant in managing social movements and digital activism by applying computational technology. There is a need to deploy this opinion mining technology to the recent largest digital activism in Nigeria known as the #EndSARS movement. In this work, we proposed the EndSARS live analytics framework which holds a promising solution to social unrest and may serve as a panacea to curbing the menace of vandalism resulting from unresolved protest issues. Using a dataset of 12,357 tweets, we demonstrated that computational technology can be relevant to addressing online protests. The result of the analysis shows the eight basic emotions expressed during the protest and approaches the government may adopt to address future activisms.
Exploring factors influencing acceptability of online capacity building platform for HIV and AIDS monitoring and evaluation in Ghana

Introduction: Ghana's multi-sectoral approach towards the management of HIV and AIDS has resulted in many community-level activities and programs aimed at stopping HIV infections and reducing the impact of HIV and AIDS. This study seeks to investigate whether Monitoring & Evaluation (M&E) officers in Ghana will be willing to join in an electronic learning platform which is web-based as a means of building M&E capacity. Methods: 123 out of 130 participants were involved in the study. Continuous and categorical variables were analysed using means and proportions. Structural equation Modelling technique was used to determine the factors associated with acceptability/intention to use. Results: The results showed that Attitude toward usage had a positive significant influence on acceptability/intention to use (AITU). In addition, experience with online learning and Internet discussion also had a positive influence on perceived usefulness and perceived ease of use respectively. The overall model shows 71% of variation of M&E officers' attitude toward usage on acceptability/intention to use online M&E platform as observed by the covariates in the model. Conclusions: Attitude toward usage was observed to be the strongest determinant of the AITU online HIV/AIDS M&E platform for monitoring and evaluation activities.
Consistency preserving database watermarking algorithm for decision trees

Database watermarking technologies provide an effective solution to data security problems by embedding the watermark in the database to prove copyright or trace the source of data leakage. However, when the watermarked database is used for data mining model building, such as decision trees, it may cause a different mining result in comparison with the result from the original database caused by the distortion of watermark embedding. Traditional watermarking algorithms mainly consider the statistical distortion of data, such as the mean square error, but very few consider the effect of the watermark on database mining. Therefore, in this paper, a consistency preserving database watermarking algorithm is proposed for decision trees. First, label classification statistics and label state transfer methods are proposed to adjust the watermarked data so that the model structure of the watermarked decision tree is the same as that of the original decision tree. Then, the splitting values of the decision tree are adjusted according to the defined constraint equations. Finally, the adjusted database can obtain a decision tree consistent with the original decision tree. The experimental results demonstrated that the proposed algorithm does not corrupt the watermarks, and makes the watermarked decision tree consistent with the original decision tree with a small distortion.
Weighted alignment‐based multi‐source domain adaptation for object detection

Beyond single-source domain adaption (DA) for object detection, multi-source domain adaptation for object detection is another challenge because the authors should solve the multiple domain shifts between the source and target domains as well as between multiple source domains. In this letter, the authors propose a novel multi-source domain adaptation via weighted alignment for object detection where the authors adopt a teacher–student framework. The authors first propose the weighted multiple binary discriminator (MBD) to align the multiple domains considering individual domain shifts. The authors also design the weighted class balance loss (CBL) that aligns the different weights to efficiently learn the detection model even if the number of objects is not balanced in an image under the teacher–student learning scheme. The authors empirically prove the superiority of our method on widely used benchmarks such as Cityscapes, KITTI, and BDD100k datasets.
Partial nonseparability of spin-orbit modes

Abstract Structured light plays an essential role in several quantum information protocols by using the degrees of freedom of light to encode qubits. For exploring different correlations, especially in mixed states, such as discord, it is necessary to prepare partially entangled states. In this work, we present a theoretical and experimental study of a partial nonseparable spin-orbit modes. By exploring classical-quantum analogy, we perform the measurement of the concurrence of partially separable modes directly from projective measurement of polarization. The results show a clear agreement with predictions of quantum theory for partially entangled states. We also perform a study of Clauser, Horn, Shimony, and Holt (CHSH) inequality and show that partial violation is observed in entire agreement with the expected by quantum theory. For the maximally nonseparable mode, we achieve a violation of <?CDATA $S = 2.73 \pm 0.03 $?> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mi>S</mml:mi> <mml:mo>=</mml:mo> <mml:mn>2.73</mml:mn> <mml:mo>±</mml:mo> <mml:mn>0.03</mml:mn> </mml:math> , one of the higher ones observed for spin-orbit modes based on our best knowledge.
Modeling GPDA and Its Application in Deep Mineral Prediction in the Jiguanzui Cu-Au Mining Area in Hubei, China

Geochemical anomalies are the basis of mineral deposit prediction. Through the study of the characteristics of geochemical anomalies, we found that their distribution was consistent with a generalized Pareto distribution (GPD). In the present study, we designed a model for geochemical anomaly extraction via a GPD. In the designed GPD model, we used the kurtosis method to estimate the threshold value of the GPD. Furthermore, a principal component analysis (PCA) was used to extract comprehensive information of different geochemical elements in which minerals are enriched. On this basis, a new algorithm named the GPDA model was designed for deep mineral prediction by using the GPD and PCA, and the methods of the GPDA for selecting parameters were studied. The study data for Ba, Pb, As, Cu, Au, Mo, Co, and Zn originated from 26 exploration lines of the Jiguanzui Cu-Au mining area in Hubei, China. The proposed GPDA model was applied to deep mineral prediction in the study area. We estimated the parameters of the GPDA model, and the thresholds of Ba, Pb, As, Cu, Au, Mo, Co, and Zn were 457.8612, 56.1823, 28.8454, 910.1272, 89.4283, 34.5267, 84.9445, and 121.4863, respectively. The comprehensive information threshold value was 0.4551. The comprehensive abnormal distribution area of geochemical element contents was obtained from thresholds. The results showed that the method used to identify abnormal areas was consistent with the range of ore bodies identified by actual engineering exploration, demonstrating that the GPDA model was effective. Finally, we predicted that there was a new blind ore body located at a depth of about 1100 m below ground between drill holes KZK10 and KZK11. The results have important theoretical and practical significance for deep ore prospecting.
Business Future With the Metaverse

This research is about the metaverse as the next evolutionary step in doing business. In addition, the purpose of this research is to get to know more about the metaverse, ranging from positive and negative impacts to business opportunities and business strategies in the metaverse. This metaverse is a proof of the technological development that occurs and does not only refer to one type of technology. However, it leads to ways to utilise the technology. The metaverse is important because it has stylistic ideas that might help us organise society to be more productive, shared standards, and protocols that bring different virtual worlds (the metaverse) and augmented reality into one open metaverse that can help people work together. The study revealed that the metaverse is very important to expand business reachability so that users can explore this virtual world in real life. The metaverse will be co-created and responsibly built so that any type of business can be realised in the future.