Reviewerly/exHarmony huggingface dataset:
A Novel Geo-Localization Method for UAV and Satellite Images Using Cross-View Consistent Attention

Geo-localization has been widely applied as an important technique to get the longitude and latitude for unmanned aerial vehicle (UAV) navigation in outdoor flight. Due to the possible interference and blocking of GPS signals, the method based on image retrieval, which is less likely to be interfered with, has received extensive attention in recent years. The geo-localization of UAVs and satellites can be achieved by querying pre-obtained satellite images with GPS-tagged and drone images from different perspectives. In this paper, an image transformation technique is used to extract cross-view geo-localization information from UAVs and satellites. A single-stage training method in UAV and satellite geo-localization is first proposed, which simultaneously realizes cross-view feature extraction and image retrieval, and achieves higher accuracy than existing multi-stage training techniques. A novel piecewise soft-margin triplet loss function is designed to avoid model parameters being trapped in suboptimal sets caused by the lack of constraint on positive and negative samples. The results illustrate that the proposed loss function enhances image retrieval accuracy and realizes a better convergence. Moreover, a data augmentation method for satellite images is proposed to overcome the disproportionate numbers of image samples. On the benchmark University-1652, the proposed method achieves the state-of-the-art result with a 6.67% improvement in recall rate (R@1) and 6.13% in average precision (AP). All codes will be publicized to promote reproducibility.
Investigation of the JPA-Bandwidth Improvement in the Performance of the QTMS Radar

Josephson parametric amplifier (JPA) engineering is a significant component in the quantum two-mode squeezed radar (QTMS) to enhance, for instance, radar performance and the detection range or bandwidth. We simulated a proposal of using engineered JPA (EJPA) to enhance the performance of a QTMS radar. We defined the signal-to-noise ratio (SNR) and detection range equations of the QTMS radar. The engineered JPA led to a remarkable improvement in the quantum radar performance, i.e., a large enhancement in SNR of about 6 dB more than the conventional QTMS radar (with respect to the latest version of the QTMS radar and not to the classical radar), a substantial improvement in the probability of detection through far fewer channels. The important point in this work was that we expressed the importance of choosing suitable detectors for the QTMS radars. Finally, we simulated the transmission of the signal to the target in the QTMS radar and obtained a huge increase in the QTMS radar range, up to 482 m in the current study.
Examination of the Accuracy of Movement Tracking Systems for Monitoring Exercise for Musculoskeletal Rehabilitation

When patients perform musculoskeletal rehabilitation exercises, it is of great importance to observe the correctness of their performance. The aim of this study is to increase the accuracy of recognizing human movements during exercise. The process of monitoring and evaluating musculoskeletal rehabilitation exercises was modeled using various tracking systems, and the necessary algorithms for processing information for each of the tracking systems were formalized. An approach to classifying exercises using machine learning methods is presented. Experimental studies were conducted to identify the most accurate tracking systems (virtual reality trackers, motion capture, and computer vision). A comparison of machine learning models is carried out to solve the problem of classifying musculoskeletal rehabilitation exercises, and 96% accuracy is obtained when using multilayer dense neural networks. With the use of computer vision technologies and the processing of a full set of body points, the accuracy of classification achieved is 100%. The hypotheses on the ranking of tracking systems based on the accuracy of positioning of human target points, the presence of restrictions on application in the field of musculoskeletal rehabilitation, and the potential to classify exercises are fully confirmed.
In-situ evaluation of zirconium-bearing minerals for geochronology using micro X-ray fluorescence

In this contribution we present a method for pre-screening geological materials for zircon prior to submitting samples for heavy mineral separation. The proposed workflow utilizes micro X-ray fluorescence to identify zirconium-bearing pixels in slabbed rock samples. The open-source image analysis software ImageJ™ is applied to the micro X-ray fluorescence elemental map to determine the abundance and spatial distribution of zirconium-bearing pixels in the scanned surface area. This method allows for the prediction of zircon abundance and estimation of grain size within a sample which can be used to prioritize samples for geochronology as well as inform crushing and grinding metrics for heavy mineral separation. This information can ultimately lead to improved recovery of zircon and other mineral geochronometers for geochronological studies. Advantages of the proposed workflow include:•Minimal sample preparation and rapid results;•Analytical method is non-destructive; and•In-situ grain size estimation and abundance predictions prior to initiating time-consuming and costly heavy mineral separation methods.
Interdisciplinary Approach to Research in Didactics: Possibilities, Assumptions, and Challenges of Realization

The results of the analyses show that in addition to the differences that exist between different disciplines, there is generally a trend of an increase in the number of researches conducted as a team and a decrease in the number of individually conducted research. Therefore, the paper aimed to look at the possibilities, assumptions, and challenges of achieving an interdisciplinary approach to basic, developmental, and applied research in didactics using the method of theoretical analysis and synthesis. Basic research is applied not only in didactics, but also in disciplines closely related to didactics (psychology, sociology, philosophy, cybernetics...) and forms the basis for establishing didactic regularities, and has the task of determining didactic knowledge of capital value and significantly influences the development of didactic theories, educational and teaching practices in all types and levels of schools and other educational institutions and forms of organized learning and teaching. An interdisciplinary approach to developmental research, which refers to the investigation of the regularities of the application of research results obtained through basic research, can directly contribute to the improvement of didactic theory and practice. Through applied didactic research of an interdisciplinary character, researchers find solutions for specific practical questions and problems of educational and teaching practice in certain conditions based on known didactic knowledge. Certain assumptions and challenges in the realization of interdisciplinary research in didactics aim to ensure methodological competence, scientific objectivity, and the integration of several disciplines. In the concluding remarks, it was emphasized that research methodology in didactics that has an interdisciplinary approach is not realized in isolation, but in dynamic and creative cooperation with other disciplines. With integrated basic, developmental, and applied didactic research of an interdisciplinary character, we contribute to the development of scientific theory and progressive changes in teaching practice and the educational process in general.
Horizontal Learning: Challenges for Changes in the Professional Development of School Teachers and Preschool Teachers

The authors of this paper start from the position that horizontal learning implies a reflective dialogue among participants in the learning process within the professional development of teachers and preschool teachers, critical examination, observation, and understanding of theory and practice from different perspectives, building common knowledge, skills, and values based on which the necessary changes in practice can be planned and implemented. The findings of several types of research indicate that horizontal learning, despite the recognized benefit by the participants of the process, is still poorly represented in practice. The research aims to examine the factors that, according to school teachers and educators, negatively affect their motivation to participate in horizontal learning and at the analysis of their proposals on how to overcome the existing problems and difficulties in the current practice of horizontal learning in the Republic of Serbia. The combined method was applied in the research. The research sample included preschool teachers, subject and classroom teachers employed in institutions from several cities in the Republic of Serbia. For the quantitative part of the research, a questionnaire was constructed (N=330), while the qualitative part of the research was carried out through a semi-structured interview (N=30). Based on the obtained research findings, we can conclude that an unfavorable social environment for learning is the dominant factor that determines the motivation of teachers and educators to participate in horizontal learning activities. In this regard, the research findings indicate that with a higher level of support for horizontal learning in the institutions where the respondents are employed, their motivation to participate in horizontal learning activities also increases. Teachers and preschool teachers recognize the director of the institution as a leader of changes and development of the institution, but also as a manager who provides conditions for the realization of horizontal learning. Research findings and concluding considerations contribute to mapping current practice and a more complete understanding of the process of horizontal learning, providing a basis for creating future policies for the professional development of employees in education.
Blockchain-based integrity auditing for shared data in cloud storage with file prediction

With the increasing publicity of information, more and more users are willing to share their data with others. Therefore, in cloud storage services, the security of shared data has begun to attract attention. Most of the current integrity auditing schemes cannot balance data sharing and audit security well. In view of this, we propose an audit scheme based on blockchain and file prediction in the shared environment. On the one hand, a lightweight signature algorithm is designed to realize the revocation of group members without source data transmission, which greatly avoids the communication overhead between the user and the cloud. On the other hand, we introduce blockchain technology into auditing and use smart contracts to verify the integrity of cloud data, making the system more secure, tamper-resistant, and traceable. Finally, in order to ensure that a file is audited only when necessary, we propose the concept of valid auditing and predict the frequently accessed or likely accessed files in the sharing group, which greatly improves the valid auditing rate and saves system computing resources. The security analysis proves that our method is safe and reliable. The performance evaluation and experimental comparison prove that our scheme has high efficiency.
Metaphor as Invective in the Genre of Internet Commentary: A Focus on German Political Discourse

This article presents the results of a linguo-stylistic analysis of a Germanlanguage commentary within the context of public political internet discourse. The analysis aims to identify distinctive features specific to this genre. Empirical material consists of over 200 comments on internet posts made by the German political party “Alternative for Germany,” selected through random sampling. The study applies both general scientific and linguistic methods, such as discourse analysis and contextual analysis. The relevance of this chosen topic is justified by the need for research in the field of internet linguistics, particularly in addressing genre-related issues. The goal is to determine, identify, and describe the characteristic features of commentary as an internet text. The article thoroughly examines the approaches taken by German linguists to define the concept of “invective,” encompassing lexical-semantic perspectives, speech act theory, and post-structural discourse analysis. Additionally, the analysis of the material reveals that invective is a hallmark of German political internet discourse, with manifestations in both explicit and implicit forms. The article discusses implicatures, arising through irony and metaphorization. The author concludes that metaphor can serve as a tool of persuasion. Metaphor, as a persuasive device, involves the intentional alteration of the mental representation of a given object based on the metaphorical image imposed by the manipulator. This typically includes exaggeration in some aspects of the metaphorically represented phenomenon while diminishing others.
On multi-path bandwidth scheduling for multiple fixed-slot reservations in high-performance networks

Large-scale applications in various fields generate big data at a high speed, which needs to be transferred through High-Performance Networks (HPNs). Bandwidth scheduling in HPNs plays a pivotal role in providing Quality of Service (QoS) to such applications. In this paper, we formulate two bandwidth scheduling problems: (i) maximize the amount of bandwidths to be allocated for multiple fixed-slot bandwidth reservation requests (FBRRs), referred to as maxAB-MultF, and (ii) maximize the number of requests to be satisfied as well as the degree of user’s satisfaction for multiple prioritized fixed-slot bandwidth reservation requests (PFBRRs), referred to as maxNR-MultPF. We prove both of these problems to be NP-complete, and design two heuristic algorithms, namely, Maximal Reserved Bandwidth Resources (MaxRBR) and Dynamic Resource Occupation (DynRO), for them, respectively. For each problem, we also design two algorithms based on greedy strategy for performance comparison. Extensive simulation results illustrate that MaxRBR for maxAB-MultF improves Reserved Bandwidth Resource Ratio over two other algorithms in comparison by 18% and 15%, respectively, and DynRO for maxNR-MultPF improves over another two algorithms in comparison scheduling success ratio by 10% and 5%, respectively, and user satisfaction by 6.5% and 5.5%, respectively. Considering the rapid expansion of HPNs in both speed and scale, the proposed scheduling algorithms have great potentials to improve the network performance of big data applications that require these two types of services.
Approach for Enneagram personality detection for Twitter text: a case study

Understanding people’s emotions and orientations attracts researchers nowadays. Current personality detection research concentrates on models such as the big five model, the three-factor model. The Enneagram is deeper than these models for providing a comprehensive view. This theory is a unique personality model because it illustrates what drives human behavior. This recognition helps in building smarter recommendation systems and intelligent educational systems. Enneagram personalities are realized through a long questionnaire-based test. People are not concerned about doing a test because it is time-consuming. A proposed case study employs Twitter’s text to detect Enneagram personality because it requires no time or effort. The proposed case study is based on an approach that uses a combination of ontology, lexicon, and statistical technique. This proposed case study uses the biography description text and 40 tweets of a Twitter profile text. The highest probability percentage is peacemaker personality which is 15.58%. This result means that the identified personality is the peacemaker. The outcome is equivalent to the determination of the Enneagram’s specialized people. This result promises more positive outcomes. This is the first automated approach to determine the Enneagram from text.
Detection of lung pathology using the fractal method

&lt;span lang="EN-US"&gt;Currently, the detection of pathology of lung cavities and their digitalization is one of the urgent problems of the healthcare industry in Kazakhstan. In this paper, the method of fractal analysis was considered to solve the task set. Diagnosis of lung pathology based on fractal analysis is an actively developing area of medical research. Conducted experiments on a set of clinical data confirm the effectiveness of the proposed methodology. The results obtained show that fractal analysis can be a useful tool for early detection of lung pathologies. It allows you to detect even minor changes in the structure and texture of lung tissues, which may not be obvious during visual analysis. The article deals with images of pathology of the pulmonary cavity, taken from an open data source. Based on the analysis of fractal objects, they were pre-assembled. Software algorithms for the operation of the information system for screening diagnostics have been developed. Based on the information contained in the fractal image of the lungs, mathematical models have been developed to create a diagnostic rule. A reference set of information features has been created that allows you to create algorithms for diagnosing the lungs: healthy and with pathologies of tuberculosis. &lt;/span&gt;
Milestones on the Quantum Utility Highway: Quantum Annealing Case Study

We introduce quantum utility , a new approach to evaluating quantum performance that aims to capture the user experience by considering the overhead costs associated with a quantum computation. A demonstration of quantum utility by the quantum processing unit (QPU) shows that the QPU can outperform classical solvers at some tasks of interest to practitioners, when considering the costs of computational overheads. A milestone is a test of quantum utility that is restricted to a specific subset of overhead costs and input types. We illustrate this approach with a benchmark study of a D-Wave annealing-based QPU versus seven classical solvers for a variety of problems in heuristic optimization. We consider overhead costs that arise in standalone use of the D-Wave QPU (as opposed to a hybrid computation). We define three early milestones on the path to broad-scale quantum utility. Milestone 0 is the purely quantum computation with no overhead costs and is demonstrated implicitly by positive results on other milestones. We evaluate the performance of a D-Wave Advantage QPU with respect to milestones 1 and 2: For milestone 1, the QPU outperformed all classical solvers in 99% of our tests. For milestone 2, the QPU outperformed all classical solvers in 19% of our tests, and the scenarios in which the QPU found success correspond to cases where classical solvers most frequently failed. This approach of isolating subsets of overheads for separate analysis reveals distinct mechanisms in quantum versus classical performance, which explain the observed differences in patterns of success and failure. We present evidence-based arguments that these distinctions bode well for annealing quantum processors to support demonstrations of quantum utility on ever-expanding classes of inputs and with more challenging milestones in the very near future.
Flood Disaster Risk Reduction Strategies in Urban Area, Bulukumba Regency

Flood is a disaster that often occurs in big cities in Indonesia, caused by the high density of buildings and the unpreparedness of infrastructure to adapt. Urban Areas of Bulukumba Regency (UABR) is one of the centers of urban areas that has experienced flooding in recent years. The urban area ofBulukumba Regency is a downstream area of the Bialo Watershed whose upstream area is also in the Bantaeng Regency area. Rapid urban development has resulted in a change in land cover to become built-up land so that catchment areas are narrower in the middle and downstream zones, as well as changes in vegetation in the upstream zone which has received land conversion from forest areas to plantation areas. In addition to the potential for flooding due to river flow, the urban area of Bulukumba also has the potential for flooding due to sea tides or tidal floods. The high level of hazard flood potential has not been followed up with sustainable flood management based on disaster risk reduction in the UABR. Based on this, it is necessary to study the level of risk of flooding in the Urban Area of Bulukumba Regency and an appropriate strategy to reduce the risk of flooding in the Urban Area ofBulukumba. The aim of this research is; (1) identify the level of risk of flooding in the UABR; and (2) formulate an appropriate strategy as an effort to reduce the risk of flood disaster in the UABR. The research approach used is the mixed method, with the analytical method used for data processing in the form of risk analysis, spatial analysis namely overlay analysis using GIS software and qualitative descriptive in formulating strategies. The results of this study are a map of the level of flood disaster risk and recommendations for flood risk reduction strategies in the UABR.
Aggravated impoliteness in Chinese online negative restaurant reviews

Abstract This paper examines aggravated impoliteness in online restaurant reviews, with a dataset consisting of 92 negative reviews from the Chinese-based website Dazhongdianping . It first analyzes the usage and frequency of different types of aggravated impoliteness strategies. The topic categories of the review samples are then investigated, and the connection between these two aspects is further discussed. The variety of aggravated impoliteness strategies includes: preceding intensifiers, indignant exclamations, unpalatable questions, emoji, postpositional intensifiers, unfavorable comparisons, emphatic structure and taboo words, in decreasing order of frequency. These strategies are employed in connection with the ratings of: food, service, general experience, interpersonal judgments, price and environment. This study contributes to the impoliteness research by investigating the aggravated impoliteness in Chinese online data, and also enriches and provides insights into research on the genre of online consumer reviews.
Simplified Initial Setting of a Nurse Call System Driven by Eye Movement Using Image Processing

In this research, a nurse call system with simplified initial setting is developed. The system is constructed by improving an existing nurse call system driven by eye movement, where the movement is detected by image processing. In the initial setting of previous research, template images for the detection of face and eye were created manually. However, it was not easy for system operator to generate suitable template images. To solve this problem, in the research, automatic generation of template images is attempted to simplify the initial setting. The system with simplified initial setting is realized by introducing gamma correction, cascade classifier and false positive rejection. The usefulness of the proposed system was verified through operation of not only initial setting but also nurse call.