Reviewerly/exHarmony huggingface dataset:
Information Retrieval for Aviation Applications

&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;There is a recurring need for automatic Information Retrieval (IR) from quality documents, price tags, part markings, receipts, purchase orders and technical manuals - which are otherwise non-parsable. IR coupled with search functionalities has a wide range of applications from warehouses, marketplaces to even shop floors in the aviation sector. It helps in semi-automating workflows like document reviews, quality checks, collaborative Q&amp;amp;As and contextual extraction of information. These workflows make laborious tasks more intuitive and easier, thereby reducing the workload of the engineers using them. The paper describes an AI based IR platform which caters to the aforesaid scenarios in a scalable manner and integrates seamlessly with similar problems across different domains. It is the core to many different workflows that are currently used to detect paperwork mismatch for aviation parts, to auto-catalogue large amounts of documents, to detect the presence of sensitive information in documents, to digitize scanned documents, detecting presence of stamps in faceplates. Its capabilities can be extended beyond documents to other non-interactive and non-parsable contents as well. The intent of this paper is to describe different AI modules and services in this AI platform towards enabling Smart Factory and Industry 4.0.&lt;/div&gt;&lt;/div&gt;
Chronohacking: Between a thought experiment and deviations of digital solutions

The article deals with the phenomenon of chronohacking, hacking of time in different modes of digital temporality. The author considers chronohacking as a result of the expansion of biohacking practices of civil science into neuroscience. Methodological basis of the study is the STS paradigm, the working approach is the Laturnian actor-network theory, which allows to fix a variety of networks of actors formed due to various ways of measuring time. Digital temporality is considered as a set of digital chronopolitics, time management modes of various activities in environments formed by digital resources. The epistemic and praxeological possibility of chronohacking, according to the author, is set by two poles, theoretical and technological. The theoretical pole is a thought experiment as a simulation of impossible or unlikely situations. Within the framework of a thought experiment, ideas are accumulated about how social reality changes in the conditions of changes in the basic objective characteristics of time, to what social consequences the difference in the course and direction of time will lead. The technological pole is the development of specific digital resources of the brain training industry used to calibrate the perception of time, somatic training of immersion in a specific temporal context. As a case study of the brain training industry, which includes neurohacking developments, the computer game EndeavorRX is used – a medicinal agent for children with attention deficit hyperactivity disorder. The development of this industry itself increases the number of disagreements and new compromises between science, civil science and consumers, an important role in this process is played by “anecdotal evidence” about deviations in the use of neurotechnologies, the epistemic status of which is close to the thought experiment in terms of non-verifiability.
A PATH ANALYSIS ON ORAL COMMUNICATION STRATEGIES, SPEAKING ANXIETY AND STRATEGIC COMPETENCE OF STUDENTS

This study determined the significant influence of oral communication strategies and speaking anxiety on the strategic competence of students. The descriptive-correlational research design was utilized in this study. Using stratified random sampling, 300 college students in a State College in Mati City, Davao Oriental,were determined as respondents of the study and were given survey questionnaires. The experts validated the adapted instruments and were used to obtain data from the respondents during the survey. The data were analyzed using the Mean, Pearson r, and Path Analysis. The level of oral communication strategies of the respondents was very high, while the level of speaking anxiety was moderate. On the other hand, the students strategic competence level was high. Furthermore, results showed a significant relationship between oral communication strategies and strategic competence and between speaking anxiety and strategic competence. Moreover, it was found that both oral communication strategies and speaking anxiety significantly predict strategic competence thus, oral communication strategies and speaking anxiety significantly influenced strategic competence.
Virtual Reality Video CU Partition Fast System Based on Dynamic Selection Algorithm

Virtual reality technology is a new digital solution developed rapidly in recent years. It can realize real-time video playback and synchronous transmission through human-computer interaction interface according to user requirements. This paper introduces the concept of virtual reality video, and then studies the fast video Cu division system based on the dynamic selection virtual reality video generation algorithm. This method realizes the real-time image sequence synthesis and matching of multiple cameras by constructing a dynamic interactive single objective multi-level decision system. Then the performance of the algorithm is tested. The experimental results show that the algorithm is stable, safe and reliable. At the same time, the program has high portability and certain super large-scale computing ability. In addition, it also has the characteristics of friendly man-machine interface and simple operation, so it has low requirements for hardware.
Pragmatics between Formal Transformations and Technological Applications

The Pragamatics represents a critical theory that deals with the analysis of discourse and is related in different fields such as philosophy, law, economics and the arts. It appears in multiple analyzes that study the special phenomena in these fields in the linguistic analyzes, which require studying all the rationales and problems according to the surrounding of many questions. Functional purpose, contextual and communicative aspects, and are therefore subject to evidential and developmental processes leading to interpretation. On this basis, it has evolved into several paths resulting from the different specialties of researchers in the interests of deliberative theory. The deliberative process is also concerned with the study of the technical work according to the objective communication between the artist, the message, the artistic work, and research on how to deal with the technical elements in the visual achievement, And the mechanisms of the process of evidence in the processing of the outputs of the plastic analysis of the discourse in the work, which necessitates a Pragmatics reading aware of the significance and Beyond the above to discuss the intent of the message and the context, resulting from the interactive installations between the sender and the work and the future, which are implicit in conjunction with the appropriate context. Based on this, the study is entitled “Pragmatics between formal transformations and technological applications”. This paper contains the problem of what are the formal and technical transformations in the contemporary plastic pattern? The study discusses the concept of Pragmatics and approach in reading the transformations of the contemporary art, including the new media art and its technical and formal representations. Under the last title “results and discussion”, the findings of the study are Summarized.
Youth-led Participatory Sensing (YPS) Model to enhance drinking water security: a case study of Pokhara Metropolitan City, Nepal

&amp;lt;p&amp;gt;Water supply for drinking purpose with adequate quality is a global challenge. Majority of the developing countries face serious problems in proper technology and management strategy to regulate drinking water quality, though there are numerous cases of adverse health impacts. Population growth, unsystematic urbanization and improper management of the resources are some of the pressing factors. In Nepal, about 80% of prevalent communicable diseases are due to poor sanitation and lack of access to quality water. The coverage and functionality of the water supply system is still crucial owing to the degraded quality of water. In fact, there is no data available on water quality. Despite huge investment in implementing Water Safety Plan (WSP) approach in developing regions, many countries still lack the baseline water quality data (information flow) in the water supply system. Nepal is one of the countries where WSP is implemented for a long time (more than a decade) but the regular drinking water monitoring mechanism is still a matter of question. Studies have mentioned Water, Sanitation and Hygiene (WASH) practices in schools and possibilities of involving schools in WSP programs as well but the systematic method and model to integrate Youth/ Students and Information and Communication Technologies (ICTs) in Drinking Water Quality Monitoring is yet unexplored. In addition, the data accuracy of Citizen Based Monitoring needs to be checked. Therefore, the first phase of this research has developed a suitable design of Youth-led Participatory Sensing (YPS) to improve water supply management facility, including the strategy to support Climate Resilient Water Safety Plan (CR-WSP) framework of the local water utilities and, this paper highlights on performance evaluation and accuracy of data acquired from YPS Model with paired experimental approach, and gamified techniques in designing the participation from training to field implementation, including the community awareness targets for the selected water supply schemes of Pokhara Metropolitan City (PMC), Nepal, which can be validated and replicated in similar urban or peri-urban settings of national, regional and the global context.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;lt;strong&amp;gt;Keywords: &amp;lt;/strong&amp;gt;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Youth-led Participatory Sensing (YPS), Drinking Water Security, Water Quality, ICTs, Water Supply Schemes, CR-WSPs&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;https://www.youtube.com/watch?v=kS71uqFnjF0&amp;amp;t=66s&amp;lt;/p&amp;gt;&amp;lt;ul&amp;gt;&amp;lt;li&amp;gt;A video link about a part of the on-going doctoral research work in Nepal&amp;lt;/li&amp;gt; &amp;lt;/ul&amp;gt;
Constructing totally disjoint spectra plateaued functions and searching five-value spectrum functions in odd variables

In this paper we introduce a concept of nearly totally disjoint spectra (NTDS) functions that slightly extends the notion of basic totally disjoint spectra functions. Novel construction methods of totally disjoint spectra (TDS) plateaued functions are proposed. We investigate the design of five-value spectrum functions with Walsh supports, the cardinalities of which are not a power of two. We also study the construction of TDS functions using NTDS functions. To acquire five-value spectrum functions in odd variables in practice, a succinct searching procedure using TDS functions designed in this paper is introduced finally. Experimental results show that such approach could yield plenty of desirable functions in odd-variable with few Walsh spectral values.
Multi-Relational Stacking Ensemble Recommender System Using Cinematic Experience

With the advent of many movie content platforms, users face a flood of contents and consequent difficulties in selecting appropriate movie titles. Although much research has been done in developing effective recommender systems to provide personalized recommendations based on customers' past preferences and behaviors, not much attention has been paid to leveraging users' sentiments and emotions together. In this study, we built graph-based movie recommender system that utilized sentiment and emotion information along with user ratings, and evaluated its performance in comparison to well known conventional models. The sentiment and emotion information was extracted using fine-tuned BERT. We used a Kaggle dataset created by crawling movies' meta-data and review data from the Rotten Tomatoes website. The study results show that the proposed models coupled with emotion and sentiment are superior over the conventional models. The results of this study support the possibility of using sentiment and emotion information together in relation to movie recommender system.
Tuneable spin-glass optical simulator based on multiple light scattering

The race to heuristically solve non-deterministic polynomial-time (NP) problems through efficient methods is ongoing. Recently, optics was demonstrated as a promising tool to find the ground state of a spin-glass Ising Hamiltonian, which represents an archetypal NP problem. However, achieving completely programmable spin couplings in these large-scale optical Ising simulators remains an open challenge. Here, by exploiting the knowledge of the transmission matrix of a random medium, we experimentally demonstrate the possibility of controlling the couplings of a fully connected Ising spin system. By further tailoring the input wavefront we showcase the possibility of modifying the Ising Hamiltonian both by accounting for an external magnetic field and by controlling the number of degenerate ground states and their properties and probabilities. Our results represent a relevant step toward the realisation of fully-programmable Ising machines on thin optical platforms, capable of solving complex spin-glass Hamiltonians on a large scale.
Demonstrating Ethical Leadership in a Virtual World: Accessibility, Community, and Identity in advance

During the COVID-19 pandemic, ethics centers were forced to reimagine program delivery. In a tumultuous time with rampant social isolation, the need for ethics education and dialogue was also critical. The authors, members of the directorship team of the Kegley Institute of Ethics (KIE), discuss how KIE met these challenges through organizing over fifty online events during the pandemic, including webinars, pedagogy workshops, ethics bowls, intercollegiate student conversations, colloquia, film viewings, and podcasts. The article describes both the opportunities and challenges that different types of virtual events present and argues that innovation in online programming can help ethics centers show ethical leadership in their communities. As one example, we discuss how online events can both enhance and hinder accessibility for participants. We also describe how online programming presents both barriers and opportunities for community building and can prompt ethics centers to reflect on their identities and missions.
The Relation Between the Difficulty of Italian Texts and Language Level in the Reading Skill

This study aims to show the readability limits of the B and C language level Italian texts, which can be used for the reading assessment and the characteristics they depend on. For this purpose, 184 Italian texts used in the certification exams of the KPG system were analysed in an attempt to reveal the main traits (quantitative, lexical and syntactic) of the texts defining their readability and their correlation with the language level for which they are intended. The correlation analysis indicated that cognitive characteristics are more important than quantitative characteristics, while a high correlation of lexical variables with B1 and B2 levels and syntactic variables with C1 and C2 levels emerged.
Evidence for biomass burning-forced dimming in southern Africa

&amp;lt;p&amp;gt;&amp;lt;span&amp;gt;D&amp;lt;/span&amp;gt;&amp;lt;span&amp;gt;ecadal trends in Surface solar radiation (SSR) have gained attention in the last few decades after several studies identified the non stable behaviour of such measurements. Also referred to as Global Dimming and Global Brightening, these decadal trends are known to be spatially heterogeneous, meaning that different regions might experience different trends, associated with different causes. While measurements have allowed the identification of trends around the world, the understanding of the causes of those trends is limited to a few regional studies mostly focusing on developed countries. The lack of data in developing countries leads to an underrepresentation of those regions in what regards to global dimming and brightening research. In this work, we use around 39 years&amp;lt;span&amp;gt;&amp;amp;#160; &amp;lt;/span&amp;gt;(1967-2005) of daily SSR measurements of two stations in Zimbabwe, and apply a new method for clear-sky derivation, using satellite cloud fraction to identify optimal daily transmittance thresholds for clear-sky identification. The all-sky and clear-sky time series of SSR are then compared to cloud fraction and water vapor data from ERA5 reanalysis and to aerosol emissions from the EDGAR database. The SSR time series show a persistent dimming of similar magnitude both in all-sky and clear-sky. The cloud fraction does not show any significant trends, reinforcing the hypothesis that the dimming was caused by cloud-free radiative processes in the atmosphere. The water vapour time series also does not show any significant trend which could justify the negative trends in SSR. However, the monthly interannual variability show that the dimming is stronger between July and September, months with higher emission of biomass burning aerosols in that region. This might also indicate an anthropogenic related cause of the dimming observed in southern Africa. This study intends to contribute to the understanding of the global dimming and brightening phenomena in southern Africa, but also to highlight the importance of studies focusing in underrepresented regions of the world.&amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt;
History of ‘Physics and High Technology’ Based on Keyword Analysis

We study the keyword network of ‘Physics and High Technology’ for its entire history. It covers physics as well as its related issues, such as industrial technology, education, and policy. We try to find the research trends and the social changes from the articles. The complex network analysis is employed for the study.
Using DSCB: A Depthwise Separable Convolution Block Rebuild MTCNN for Face Detection

Nowadays, there are huge demands of face detection in images and videos for surveillance, education, autonomous driving and health care. These application scenarios need high accuracy and efficiency of face detection. However, in some scene, unconstrained pose variation, occlusion, large number of faces and illumination bring great challenges to existing face detection methods. In view of above problems, we propose a depthwise separable convolution block (DSCB) which can maintain the speed of training and improve the accuracy at the same time. Then, using the proposed DSCB, we design a face detection model based on MTCNN (Multi-task Convolution Neural Network) to improve performance of occlusion, unconstrained pose variation, large numbers of small targets. In order to better evaluate the proposed method, we built a new dataset which is derived from the classroom teaching scene for training and evaluating. Our dataset consists of 7168 images and 294924 face bounding boxes with occlusion, unconstrained pose variation, and large numbers of small targets. The comparative experiments on our dataset show that the proposed method is superior to other state-of-the-art methods in accuracy and speed of face detection. Compared with the original MTCNN, the face detection method we proposed can bring about 3.9%, 8.66% and 1.39 times overall performance improvement on precision, recall and detection speed respectively.
EDUCATIONAL PROGRAMS IN THE NETWORK FORM: INDICATORS OF STUDENTS’ TRAINING QUALITY

Y. Denisova 1, T. Bukina 2 1Kazan National Research Technological University (RUSSIAN FEDERATION) 2Kazan Federal University (RUSSIAN FEDERATION)
Mobile Application Design for Ornamental Fish Virtual Contest with User Center Design Approach

The rapid development of technology provides changes in human life in carrying out activities. One of them is SMEs that can have an impact on ornamental fish SMEs. This development is very rapid with the Covid-19 pandemic changing the economy, especially income for SMEs has decreased. Another problem with the pandemic is the existence of social restrictions in all activities, thus limiting the activities that can be done specifically for contest events. Innovation in contests requires technology to expand the range of participants to participate in contests. The combination of contests with technology creates virtual contests. Design development with a user center design approach with FGDs with related parties. The result of this research is a virtual contest application design. Usercustomized contest application features that play an important role include: Event Organizer can create events, create event categories, enter judges, create evaluation categories, accept participant registrations, provide information on contest results. Jury users can judge according to the event category. Participants register for the contest event and get the contest results. Administrators manage events that occur. Developing a virtual contest design in this mobile application can help ornamental fish lovers to participate regardless of the distance, place, and time of the contest. The innovation contest provides more information to help new/deserved customers get quality ornamental fish for the contest. Contest innovation requires technology to generate virtual contests. Virtual contest contests can help broaden the range of participants who can participate in contest events. Keywords— User Interface, Mobile, Virtual Contest, Ornamental Fish, User Center Design.
Social Recommendation Algorithm Based on Trust and Distrust

Recommendation system can alleviate the problem of information overload effectively and enable users to obtain target information quickly. However, data sparsity is one of the important factors affecting the accuracy of recommendation system. The matrix decomposition algorithm based on trust makes use of the rating information and trust relationship between users to make recommendations. However, most matrix decomposition algorithms based on trust only consider the explicit trust relationship between users, and rarely consider the distrust relationship and implicit social relationship between users. Therefore, this paper proposes a new recommendation algorithm, which makes use of the rating information between users, explicit social relations and implicit social relations obtained through the rating information to recommend, which can alleviate the problem of data sparsity to a large extent. Finally, experiments with real data set Epinions show that the proposed algorithm can further improve the accuracy of the recommendation system.
Prediction of Heart Disease Using Machine Learning Algorithms

Abstract: In living organisms, the heart plays an important function. Diagnosis and prediction of heart diseases necessitates greater precision, perfection, and accuracy because even a minor error will result in fatigue or death. There are multiple death cases related to the heart, and the number is growing rapidly day by day. The scope of this study is restricted to discovering associations in CHD data using three super- vised learning techniques: Logistic Regression, K-Nearest Neighbour, and Random Forest, in order to improve the prediction rate. As a result, this paper conducts a comparative analysis of the results of various machine learning algorithms. The trial results verify that Logistic Regression algorithm has achieved the highest accuracy of 89% com- pared to other ML algorithmsimplemented. Keywords: Machine Learning, Logistic Regression, K-Nearest Neighbour, Random Forest, Python, Heart Disease, Prediction model, Healthcare