Reviewerly/exHarmony huggingface dataset:
Engineering design as a general area of study of informatics at the school of International Baccalaureate

Problem and goal. The features of the work of the direction of engineering design are revealed, taking into account the peculiarities of teaching under the International Baccalaureate program as part of the school curriculum to prepare students for the choice of a future profile of education in high school. Objectives: 1) to analyze the features of the work of this academic subject, taking into account the specifics of teaching the subject group “Design” within the framework of the International Baccalaureate program; 2) describe the features of this direction; 3) sum up the results of the work and development prospects of students studying according to the presented curriculum, taking into account the peculiarities of the implementation of this curriculum. Methodology. A set of research methods was used: analysis of regulatory documents, determination of priority tasks for teaching this area, work experience. Results . The experience of working with secondary school students within the framework of the presented direction is analyzed, features and opportunities for further work are identified. Conclusion. Education taking into account the implementation of the features of the International Baccalaureate program allows students to prepare for the choice of a future profile (future profession), get acquainted with information opportunities, and prove themselves when working with various information technologies at an early stage of education.
LANGUAGE POLITENESS USED BY LECTURERS AT BORDER AREA OF INDONESIA

This article aimed to describe the language politeness carried out by lecturers at border area of Indonesia at Timor University, especially at English Education Department. This article deals with the forms of observance of the maxims of modesty and the reasons of speech which contains of observance and non-observance maxims of language politeness. Language politeness enables lecturers to communicate better. This article is a qualitative research by using descriptive method. There were three lecturers involved as the participants in this study. The study was conducted at English Education Department of Timor University. The data collected through observation, and note taking method techniques. Data were analyzed in the following steps: (1) transcribing the recorded data into written form, (2) classifying the form of language politeness according to Leech, (3) analyzing the form of language politeness, (4) analyzing the factors of compliance and violations of language politeness, and (5) conclude the analysis results. The result shows that lecturers used both observance and non- observance maxim. Non-observance maxims were applied to give warning and motivation for the students. The lecturers’ compliance with the maxim of politeness helped the students to be more enthusiastic on learning. Based on the result, it could be concluded that it was necessary to used language politeness to make the communication could run well and effectively.
Need Analysis for English Reading Teaching Materials in Vocational School Based on Digital Applications

This study aims to determine the need for English reading teaching materials for Vocational High School students majoring in Fashion Design, and to determine the need for English reading skills in the world of work. Data were obtained from questionnaires and interviews. The subjects studied were students of SMK Rahmatutoyibah Gunung Kaler, grade X majoring in Fashion Design, and grade X English teaching materials for SMK. This research was conducted with a mixed-method design. The data were collected through questionnaires and structured interviews. This questionnaire is based on the SMK English learning curriculum. The results of this study indicate that Vocational High School students majoring in fashion need teaching materials that are by their majors, namely reading materials related to the fashion department as well as material that introduces a lot of the industrial world and can support the field they are engaged in. Furthermore, Grade X Vocational School students majoring in Fashion Design need English reading learning media to encourage easy understanding of English reading material, namely media in the form of interesting and contemporary digital applications. Furthermore, the need for the world of work for their English reading skills requires skilled workers who have good English reading skills, which include the ability to read manual books, the ability to read company regulations, the ability to read travel documents, the ability to read English messages, the ability to reading notes, the ability to read e-mails, the ability to read employment contracts, and the ability to read cooperation agreements.
Warp and blur model for imaging through turbulence

Point Spread Function (PSF) for imaging through inhomogeneous refractive medium, such as atmospheric turbulence is bounded by three constraints [Charnotskii, Opt. Eng., 52, 04600, (2013)]. PSF is non-negative, band-limited, and the third constraint, related to the energy conservation principle, warrants the absence of fluctuations in the image of a uniformly bright object. We develop a version of the common warp and blur model for the anisoplanatic image distortions by turbulence that satisfies these three constraints.
Crime scene classification from skeletal trajectory analysis in surveillance settings

Video anomaly analysis is a core task actively pursued in the field of computer vision, with applications extending to real-world crime detection in surveillance footage. In this work, we address the task of human-related crime classification. In our proposed approach, the human body in video frames, represented as skeletal joints trajectories, is used as the main source of exploration. First, we introduce the significance of extending the ground truth labels for HR-Crime dataset and hence, propose a supervised and unsupervised methodology to generate trajectory-level ground truth labels. Next, given the availability of the trajectory-level ground truth, we introduce a trajectory-based crime classification framework. Ablation studies are conducted with various architectures and feature fusion strategies for the representation of the human trajectories. The conducted experiments demonstrate the feasibility of the task and pave the path for further research in the field.
tukey_hsd: An Accurate Implementation of the Tukey Honestly Significant Difference Test in Python

In a world awash with data and computers, it is tempting to automate the process of scientific discovery by performing comparisons between many pairs of variables in the hope of finding correlations.When frequentist hypothesis tests are performed at a fixed confidence level, increasing the number of tests increases the probability of observing a "statistically significant" result, even when the null hypothesis is actually true.Carefully-designed tests, such as Tukey's honestly significant difference (HSD) test (Tukey, 1949), protect against this practice of "p-hacking" by producing p-values and confidence intervals that account for the number of comparisons performed.Several such tests rely on the studentized range distribution (Lund & Lund, 1983), which models the range (i.e., the difference between maximum and minimum values) of the means of samples from a normally distributed population.Although there are already implementations of these tests available in the scientific Python ecosystem, all of them rely on approximations of the studentized range distribution, which are not accurate outside the range of inputs for which they are designed.Here we present a very accurate and sufficiently fast implementation of the studentized range distribution and a function for performing Tukey's HSD test.Both of these features are available in SciPy 1.8.0.
Development and Analysis of Biometric Ingress Surveillance

Face recognition is a classic problem in the field of computer vision and popular due to its wide applications in real-world problems such as access control, identity verification, physical security, surveillance, etc. Recent progress in deep learning techniques and the access to large-scale face databases has led to a significant improvement of face recognition accuracy under constrained and semi-constrained scenarios. Deep neural networks are shown to surpass human performance on Labelled Face in the Wild (LFW), which consists of celebrity photos captured in the wild. This technology can be used to create a surveillance for the ingress systems with broad scope of application in multiple scenarios. The major ingress problems that will be address will include, but are not limited to: lack of automata, robust face normalization, discrimination, representation learning and the ambiguity of facial features caused by information loss. This paper discusses biometric ingress surveillance. With a brief review of the subject the paper presents an application in this domain that highlights the true potential of a surveillance system that can have face recognition as a biometric authentication to ingress at homes, offices, universities and other potential ingress systems.
Assessment of Irrigation Performance by Using Remote Sensing Techniques in Naryanpur Command Area, India

Assessment of irrigation performance for any irrigation scheme becomes necessary to know about effectiveness in terms of its operational management and socio-economic impacts.This study will focus on the performance assessment parameters computed using meteorological, optical datasets, and ground measurements for the Narayanpur Command Area.Net crop area is calculated for both Kharif and Rabi seasons using Optical Datasets for 2018-19.Atmospherically calibrated Sentinel 2 MSI images were used to identify major crop types by using supervised algorithms.Actual and Potential Evapotranspiration was also computed from meteorological datasets for the same duration.The surface Energy Balance algorithm was used for calculating potential Evapotranspiration.Crop water stress index and crop coefficient were computed and multiplied with potential evapotranspiration for getting actual evapotranspiration.It was observed that the actual evapotranspiration for both Kharif and Rabi crops varied from 700 mm to 1550 mm.The temporal scale for each growth stage was evaluated to analyse operational performance based on the growth phase of major crops grown in the Narayanpur command area.For performance assessment, depleted fraction, relative evapotranspiration, and relative water supply index were calculated.Most of the growth stages' depleted fractions varied from 0.6 to 0.9 and relative evapotranspiration varied from 0.7 to 0.92.The relative water supply for Kharif was estimated as 1.05 and for Rabi, it was 0.69.
Feature Data Generation for Computer Adaptive Testing

There is no gain-saying that machines can learn from data to derive patterns and insights to aid various applications, also known as artificial intelligence, which is gaining relevance today. This study implemented feature data generation (FDG) as a novel technique for psychometrics improvements using the Post-hoc Simulation approach. The descriptive design of the correlation type was adopted for this study and deployed quantitatively. The instrument for the study was a test aligned to the behavioural objectives of the Postgraduate Certificate Curriculum with the programme enrollees as the study participants. The test underwent a thorough validation procedure which yielded a reliability coefficient of 0.98. The item parameters of the test were analysed using XCalibre 4.2 to analyse the real data from 38 respondents, while the WINGEN application through the post-hoc approach was used to generate the simulated data with 500 respondents. The findings of the study revealed that the 3 Parameter Logistic Model fit the generated data determined using chi-square goodness of fit statistics, and the FDG is a viable approach with a strong and positive correlation between real data and simulated data, which enables the generalisation of findings on the basis on which conclusions were made. The developed FDG method for psychometric improvement has wide applicability, a plus for the novel technique while strengthening transdisciplinary research.
Exploring Undergraduate Students’ Perceptions and Practices on How to Use Netiquette Rules in Creating Professional Emails

In this current study, we explored Saudi undergraduate students’ perceptions toward netiquette rules in professional and formal emails through their communication with their professor in spring semester 2020. We investigated how learners formulated their formal emails in an academic domain or for their future careers whether they needed clarification, asked question, or shared issues. To apply this research, we chose critical discourse analysis as a theoretical framework to understand students’ perceptions and practices. This qualitative study applied open-ended questions survey, semi-structured interviews, and document analysis (students’ emails) with a thick description of their perceptions and practices. We had seven Saudi students from TESOL course. The data was analyzed through vivo coding that went through three different phases and wrote separate memos for every participant to reflect the intended meaning of the data. The results of the study revealed students’ understanding of netiquette rules in professional emails. However, students’ actual practices under stressful situations showed that they did not always follow the netiquette rules in emails with their professor.&#x0D; &#x0D; Received: 21 April 2022 / Accepted: 29 June 2022 / Published: 5 July 2022
Innovation through Web 2.0 to support English language learning

This investigation had the purpose of understanding how the use of a website created by the teacher-researcher contributed to an improvement in the educational experience in English language teaching with Mexican high schoolers. The inquiry undertook a qualitative methodology following an action research design tied to the critical educational science paradigm. Results revealed that the online site encouraged a positive educational experience by attending to the learners’ interests and needs, offering support, an easy navigational interface, and a good experience in the study of English. Furthermore, the internet site was perceived as highly supportive as the subject’s contents were organized by levels and topics, where videos were available to explain each linguistic item clearly. In conclusion, it can be said that the intervention benefited the teenagers’ formation since the website favored their learning of the foreign language with the support that it provided, the simple navigation, the pedagogical approach, and the personal touch employed by the teacher.
Features, experience and benefits of implementing STEAM technology in the main school

Problem statement. The educational life of the modern school is a huge field for observation and analysis. A variety of technologies used in the world to enhance cognitive activity and increase the role of independence in the activities of students create new forms and methods within the educational process. STEAM technologies are actively used in the system of additional education. However, the use of such technology in the main educational process has not been practically studied. This is due to the difficulty of combining innovative approaches with the implementation of the school curriculum. Methodology. The study uses methods for designing a learning model, pedagogical experiment, observation, conversation, and experience generalization. Content analysis and thematic monitoring of existing publications were carried out for the keywords, such as STEAM-technologies, increase of cognitive activity, and creation of educational laboratories. Results. The three-year experience of experimental application of educational STEAM-technology in the primary school is considered in order to analyze and highlight the most significant examples of the application of this technology for practice. The essence and features of the educational STEAM technology are described, as well as the ways of creating educational laboratories based on the proposed approaches implemented within the framework of the study. Significant aspects of the use of such technology in the modern school are revealed. Examples from the practice of school work are given, types of laboratories, goals and content of training, and obtained educational results are considered. Conclusion. In the process of performing research work using STEAM technology in the educational process of the secondary school, the most effective ways to create educational laboratories and the most significant aspects of the use of such technology in school were identified.
"Even if ..." -- Diverse Semifactual Explanations of Reject

Machine learning based decision making systems applied in safety critical areas require reliable high certainty predictions. For this purpose, the system can be extended by an reject option which allows the system to reject inputs where only a prediction with an unacceptably low certainty would be possible. While being able to reject uncertain samples is important, it is also of importance to be able to explain why a particular sample was rejected. With the ongoing rise of eXplainable AI (XAI), a lot of explanation methodologies for machine learning based systems have been developed -- explaining reject options, however, is still a novel field where only very little prior work exists. In this work, we propose to explain rejects by semifactual explanations, an instance of example-based explanation methods, which them self have not been widely considered in the XAI community yet. We propose a conceptual modeling of semifactual explanations for arbitrary reject options and empirically evaluate a specific implementation on a conformal prediction based reject option.
A new image encryption method based on a 6D hyperchaotic map and genetic operators

Abstract This paper presents a novel and secure image encryption method. The plain image’s pixels are confused using the N-point crossover operation of genetic algorithms. Randomly paired rows and columns are determined by the two state variables of a six-dimensional hyperchaotic map. The number of crossover points, which are calculated by the two other state variables of the hyperchaotic map, differ from each other for each row or column pair. The crossover positions are specified according to the number of crossover points with the help of the last two state variables. The proposed algorithm generates the diffusion stage’s encryption key using the SHA-256 hash value of the plain image. Mutation and crossover operators are implemented into the 16-bit subblocks of the 256-bit hash value. Thus, a total of 16 subblocks with the size of 16 bits are employed as the encryption key after the implementation of the genetic operations. The scrambled image’s pixels are altered with the generated encryption key and previously encrypted pixels. Key space and sensitivity, histogram, correlation, information entropy, differential, data loss, noise attack, and computational time analyzes are performed to test the safety and effectiveness of the encryption method. The experiments and simulation results show that the proposed encryption technique is highly secure and efficient since it can resist various attacks. The comparisons with recent works show that this method outperforms many state-of-the-art algorithms in several performance metrics.
New model for intelligent breast cancer monitoring Summary

Abstract Monitoring the patient's condition and diagnosing the type of disease are very important goals. Therefore, its analysis and evaluation is also very important, creating the necessary ability in specialists to evaluate the patient's condition in different treatment conditions has been important. Designing a robust network requires robust agents and topology. Here we show a model of monitoring the patient's condition and diagnosing the type of disease with robust agents and topology, which is here based on the type of relationship between agents. Agencies and capabilities have been able to design a robust network for diagnosing, analyzing and evaluating the patient's condition. By changing the possible parameters of the tumor status, we were able to evaluate the ability of the network in the identification process. This is a general criterion in the analysis of the patient's condition by specialists. The simulation results show that this network has the necessary strength to diagnose and treat the disease with good accuracy.
Market Basket Analysis using Apriori Algorithm

A Technique that check for dependency for one Data item to another is Association Rule which is an old Data mining approach. Which is used to identify the next product that might interest a customer. The Apriori Algorithm is applied in this for mining frequent products sets and relevant Association rule. With this algorithm we can use this for up-sell and also in cross-sell to show the Association rule with the help of the algorithm. These methods are widely used in global companies, so for the good understanding the companies used the methods to remain up to date that what customers demands with which products. The results helps the big retailers to identify a trend for customers buying patterns, which is very helpful information for the retailers to plan their big business operations.
Third-generation stress reduction interventions for people with chronic diseases: a theoretical review

In this article, a theoretical review was carried out from 2014 to 2021 on interventions based on third generation therapies for stress reduction, aimed at people with chronic diseases, the objective was to find the efficacy of interventions such as mindfulness and acceptance and commitment therapy, a search was made for articles related to contextual therapy interventions to reduce stress in people with chronic degenerative diseases. The research was found that demonstrates its effectiveness with programs to reduce stress, taking the premise of not disappearing the pain or avoid it, but accept it and generate stretegies for coping.
Drone Detection and Tracking in Real-Time by Fusion of Different Sensing Modalities

Automatic detection of flying drones is a key issue where its presence, especially if unauthorized, can create risky situations or compromise security. Here, we design and evaluate a multi-sensor drone detection system. In conjunction with standard video cameras and microphone sensors, we explore the use of thermal infrared cameras, pointed out as a feasible and promising solution that is scarcely addressed in the related literature. Our solution integrates a fish-eye camera as well to monitor a wider part of the sky and steer the other cameras towards objects of interest. The sensing solutions are complemented with an ADS-B receiver, a GPS receiver, and a radar module. However, our final deployment has not included the latter due to its limited detection range. The thermal camera is shown to be a feasible solution as good as the video camera, even if the camera employed here has a lower resolution. Two other novelties of our work are the creation of a new public dataset of multi-sensor annotated data that expands the number of classes compared to existing ones, as well as the study of the detector performance as a function of the sensor-to-target distance. Sensor fusion is also explored, showing that the system can be made more robust in this way, mitigating false detections of the individual sensors.