Reviewerly/exHarmony huggingface dataset:
Reviews

Mining Geophysics: A Canadian Story, by Norman Reed Paterson, ISBN 978-1-926-87242-1, 2019, Canadian Institute of Mining, Metallurgy, and Petroleum, 188 p. Exploration and Research for Atomic Minerals: Special Volume on Geophysics, edited by S. C. Verma and D. K. Sinha, ISSN 0970-9231, 2020, Atomic Minerals Directorate for Exploration and Research, 265 p.
Rhythm, Syntax, Punctuation: A Distant Analysis of the European Sonnet

Elaborating on an analysis of a corpus of more than 1200 sonnets by Italian, French, Spanish, English and Russian authors, this article describes the general rhythmic-syntactic arrangement of thirteenth- and fourteenth-century Italian sonnets, European Petrarchist sonnets, and several experiments with this form in the nineteenth and twentieth centuries. It presents results obtained with the help of a computer program developed for the automated analysis of strophic syntax. The program was created using Boris Tomashevsky’s method based on analyzing the punctuation at the end of poetic lines (the strength of the syntactic pause is evaluated depending on the absence or presence of a punctuation sign: i.e., a comma, a dash, a semicolon, or a full stop / question mark / exclamation mark). We supplemented this with two more indices also based on punctuation. The first characterizes the length of sentences (the percentage of sentences in one line, two lines, three lines, etc.), and the second characterizes the number of sentences that end with a full stop, which comes in the middle of a line followed by the beginning of the next sentence in the same line (or, which is the same, the number of such lines). This study demonstrates that both the number of lines with a strong pause in the middle and the number of short sentences have increased over time.
Developing Machine Learning Algorithms on Routinely Collected Administrative Health Data - Lessons from Ontario, Canada.

There has been considerable growth in the development of machine learning models for clinical applications; however, less attention has been paid to applications at the health systems level. Here, we survey recent models developed using provincial administrative health data holdings in Ontario, Canada to synthesize key learnings across use cases.&#x0D; We have developed four models in the areas of diabetes incidence and complications, hospitalization due to ambulatory care sensitive conditions, and hospitalization due to SARS-CoV-2 infection. Our team was highly multidisciplinary with expertise across clinical medicine, administrative health data, epidemiology, and computer science. We used a “sliding window” approach to aggregate healthcare events across multiple health administrative data sets chronologically and map them dynamically onto a patient timeline. Tree-based algorithms, specifically gradient boosted decision trees, are well suited for the underlying tabular structure of administrative data and were used for each prediction task.&#x0D; Our models achieved excellent discrimination, measured by the area under the receiver operating characteristic curve, between 0.77-0.85 at prediction windows between 30 days and 3 years in advance. They were also well-calibrated, both in-the-large and in population subgroups such as older adults, those living in rural areas, and the materially deprived. Measures of feature importance revealed that our models were leveraging predictors across administrative datasets (e.g. demographics, interactions with the healthcare system, medications) in intuitive and defensible ways. Finally, we demonstrated the utility of our models with “recall at top k” metrics - for example, the top 1% of patients predicted at risk of diabetes complications represented a cost of over $400 million to the healthcare system.&#x0D; We identify three key learnings needed for the successful application of machine learning methods to health administrative data: synergy between nature of training data and intended algorithm use, adherence to methodological best practices for rigour and transparency, and multidisciplinary teams with expertise across data provenance, methodological approach, and impact assessment.
The Best of Life is a Dinner Conversation

Theodore Zeldin started inviting people with very different backgrounds and interests to conversation dinners in Oxford, UK, in 2000 to bring strangers together to let them have a conversation that went beyond small talk. The author considers the effect his idea had on her, on conversations with colleagues in the European AI Network, and proposes that we add the conversation dinner to our AI toolbox.
STUDENTS’ PERCEPTIONS TOWARDS THE ADOPTION OF ODT AND PBL IN SPEAKING CLASS

There are many researchers who have been discussing EFL learners’ perceptions on the implementation of online digital technology (ODT), but there are few of them who specifically investigate their familiarity in using technology when applying project-based approach. This research analysis students’ attitudes in using ODT to improve their speaking skills and how familiar students use ODT to accomplish a project in a Speaking Class. Because the approach of learning English in this research is PBL with ODT, the students must be familiar with the technology in order to create some projects assigned. Therefore, they had to own smartphones or laptops, and familiar with very basic ODT before beginning the program. 24 students of Speaking class were selected and trained to pedagogically show their awareness towards the learning approach and the use of ODT. The researcher divided them into some smaller groups to work together to improve their projects by looking at their learning approach with technology. The result of the posttest indicated their positive attitudes towards the implementation of PBL in the Speaking class with digital technology and the increasing familiarity of using ODT. They realized that they needed to create, and evaluate the results of their project by themselves during online learning to improve their speaking skills.&#x0D; &#x0D; Keywords: Speaking, Project-based, ODT, Students’ Perceptions
Analysis of the Albanian Economy through the IS-LM Model

The objective of the study is the analysis of IS-LM curves. The aim is to prove that the current theoretical models of IS-LM are not applicable in the Albanian economy. In this paper, the theoretical IS-LM model is analyzed according to the balance of I = S (investment - savings), and AE = Y (aggregate expenditure - gross domestic product). The models I + G = S + T and NX = NFI are not analyzed in this study. Two representative models were obtained, by the authors Hicks - Hansen and Dornbusch - Fischer - Startz. The theoretical and practical aspects of the application of the models are analyzed. The defect of the Dornbusch-Fischer-Startz model and the impossibility of applying it to the data of the Albanian economy is evident. The authors have proposed an improvement of the Hicks-Hansen model for the IS curve because the theoretical model is not applicable. They have replaced the half where Investment equals Savings with a reflection curve of the opportunity cost. This has made the model effective. In the analysis, two of the features of the Albanian economy were taken into consideration: the structure of the currency market where half of it is covered by foreign currency (euro and dollar), and the informal economy that affects the exchange rates and the effectiveness of the policies of the Bank of Albania. In the material, it is found that the transmission effect of the monetary policies implemented by the Bank of Albania is missing. There are weak connections between the rate of REPOs, monetary aggregates and some of the macroeconomic indicators. The rate of inflation and the rate of REPOs are strongly related to the first direction. Recommended; to apply the IS model according to the proposal made by the authors, to realize the de-euroization of the market, to change the objective of the Central Bank, putting as the main objective the preservation of the exchange rate of All in function of economic growth and financial stability. In the analysis, the method of comparison, description, analytical methods and statistical methods are used. Used Data is from INSTAT and the Central Bank of Albania.&#x0D; &#x0D; Received: 18 July 2022 / Accepted: 25 August 2022 / Published: 2 September 2022
Opportunities for integrated education in STEM

Teachers in STEM (Science + Technology + Engineering + Mathematics = Science + Technology + Engineering + Mathematics) have a unique role in motivating and attracting their students' professions for which science, technology, engineering or mathematics degrees are required. However, STEM teachers do not acquire such interdisciplinary, interrelated in-depth knowledge sufficient for education during their training. Interdisciplinary STEM education requires teachers to have a good understanding and understanding of the concept of integrated STEM education (C. C. Johnson et al., 2020). In primary and secondary education, teachers in science and mathematics should be trained interdisciplinary in parallel with discipline-specific pedagogical studies. (Holik - Sanda, 2021).
Features of the value sphere of personality in crisis situations

International scientific conference «The role of psychology and pedagogy in the spiritual development of modern society» : conference proceedings, July 30–31, 2022. Riga, Latvia : «Baltija Publishing», 2022. 363 pages.
Histogram-based comparison of metric spaces using HMMs

Comparison is a powerful tool for decision support. Many measures have been proposed for comparing two metric spaces, but they do not consider the data dispersion in each metric space. Furthermore, no dedicated measure has yet been proposed for comparing two metric spaces containing elements belonging to various subtypes of a global datatype. In order to attenuate the aforementioned limitations, this paper proposes a new technique for comparing two metric spaces. More formally, given a metric space X, histograms are used for performing a gradual analysis of the data dispersion inside the neighborhood of each element of X. This is a refinement of the neighborhoods' analysis realized in an existing work. Then, another existing technique is used for associating one hidden Markov model $${\lambda }_X$$ with X such that $${\lambda }_X$$ learns the bin values and the visual shapes of the histograms derived from the instances in X. Meta-data derived from $${\lambda }_X$$ are then saved as the components of a descriptor vector $$\overrightarrow{X}$$ associated with X. Finally, the comparison between two metric spaces is performed through the comparison of their respective associated descriptor vectors using existing distance or similarity measures between two vectors. The proposed approach inherits the accuracy and the efficiency of the existing techniques on which it relies. Therefore, the experiments realized in this paper are only intended to show how it can be used for comparing particular metric spaces containing geolocations or stars in the celestial sphere.
Metaheuristics Applied to Pattern-Based Portuguese Relation Extraction

Relation extraction is an important part of the natural language processing field that has been receiving increasing attention due to the massive growth of the information available on the web, which makes its tasks impossible through manual means. Although for domain-specific relation extraction tasks, pattern-based methods have a long and established history as a successful approach, and they can suffer from precision and recall problems and may require a lot of manual effort. To work around these issues, this paper proposes the application of well-known metaheuristics to select patterns that maximize performance metric. This approach was applied to a binary sentence-level relation extraction problem in Portuguese language, and the results were compared using statistical tests and F1 score, reaching a significant value of 0.67 with the harmony search algorithm. The other algorithms evaluated are genetic algorithm and simulated annealing.
Comparative Analysis of Various Software Development Life Cycle

Software development life cycle is the process used by the software industry to design, build, and test high-quality software. SDLC's primary objective is to provide high-quality software that exceeds customer expectations. SDLC may also be referred to as Application Development Life Cycle. SDLC is not a technique; rather, it is a description of several phases. Participate in software development from project design to deployment. Sustainment. These SDLC phases serve as a roadmap for project activities. In our in this study, we describe many SDLC models (Waterfall, Spiral, V-Model, Iterative,). Rapid Application Development Model).
Multimedia Applications in Forensics, Security and Intelligence

A multimedia explosion of digital image, video, and audio material has occurred in recent years. End users can now easily create large volumes of multimedia content, store it, and distribute it through the Internet thanks to the rapid spread of mobile devices, which is followed by high-bandwidth Internet and cheaper storage. Meanwhile, our public spaces are being monitored by an increasing number of surveillance cameras. As a result, interactive multimedia has become embedded in our daily routines. With the proliferation of multimedia data, it has become important to protect it from unauthorized usage, identify and reconstruct illicit activities from it, and use it as a source of intelligence. However, the sheer volume of data poses serious challenges – tasks that were traditionally subjected to manual analysis are now well beyond the capabilities of forensic experts. There would be a need for tools. Over the last few years, the multimedia research community has established a number of innovative solutions for dealing with video, photographs, audio, and other types of multimedia content, including information extraction, automated categorization, and indexing. Despite the fact that this work lays a solid framework for preserving and evaluating multimedia content, difficulties remain due to the material’s scope, a lack of structure and metadata, and other application-specific constraints. It’s finally time to customize, adapt, and broaden multimedia analysis for forensics, defense, and intelligence.
Online Recommendation Using Machine Learning (ML) and NLP

Recommendation Systems (RSs) are not just about suggesting products to the customers, sometimes they can be for suggesting uses for the products. Many times RSs are not about products. When Google maps suggest the shortest path and when Gmail suggests possible quick replies, that’s also done by the RSs. In addition to content-based, collaborative filtering and knowledge-based approaches, deep learning models can also be used when building a recommendation system. Knowledge-based RSs are based on obvious information about the user’s likings, things, and or recommendation measures. They’re especially useful when the alternative approaches such as collaborative filtering or content-based methods cannot be applied. RSs have advanced into a principal apparatus for helping clients settle on educated choices and decisions, particularly in the period of enormous information wherein clients need to settle on the decisions from the countless items and administrations.
Natural Language Processing and Translation Using Machine Learning

Natural language processing is a field of computer science that deals with the development of computer systems that can be used to interpret text and speeches. If NLP is used to analyze words and to deal with text then certain aspects of language analysis and understand the use of machine learning. When machine learning is used for natural language processing and text analytics, it involves the machine-learning algorithm and artificial intelligence to understand the meaning of the documents and the text written. As per the current needs, it seems that machine learning is an essential tool for natural language processing associated with the text classification and word sense analysis.
Tata Kelola Air Dalam Prespektif Islam

Water is one of the most important natural resources in human life. You can imagine what life would be like if there was no water. The rate of population growth which is inversely proportional to the availability of water has caused a water crisis. The water crisis has made people aware of the need for efforts to raise awareness about the importance of water and its maintenance. Water as one of the fulfillment of needs, as well as a means of worship requirements. To what extent Islam views water as a very urgent resource, it can be seen from the explanation of the rules for managing these resources.&#x0D; The research method this time is a qualitative research that emphasizes research that uses library materials as the main source (data). From this presentation, it can be seen that both Islam and the rule of law in Indonesia place water as a very important resource.
Technology Effecting on Education

Development is a gift of God. After the progress of life, it is maybe perfect of God's gifts. It is the mother of updates, of explanations and of sciences. Development has unequivocally changed how we live. It has impacted various pieces of life and rethought living. Indication of this present reality, improvement anticipates a central part in each circle of life. A couple of manual undertakings can be robotized, by honorability of progress. Also, exceptional wavering and principal cycles ought to be conceivable really and more obvious capacity with the assistance of current new turn of events. By commendable nature of the utilization of progress life has evolved, and it has evolved for the better. Development has changed the field of getting ready. It is impossible to overestimate the importance of development in schools.. Really, with the beginning of PCs in planning, it is now clearer for educators to acquaint themselves with information and for understudies to acquire it. The use of technology has made the most all-encompassing saw method for overseeing schooling and seeing comprehensively truly remarkable.
A Contrastive Analysis of Ideational, Interpersonal and Textual Themes in English and Urdu

The present study deals with metafunctional diversity of thematic relations i.e. ideational, interpersonal and textual in English and Urdu. The objectives are: (1) to describe the functional significance particular to thematic progression (McCabe, 1999) of thematic structures in the English and the Urdu texts, and (2) to discuss how effectively the English thematic structures have been translated into Urdu. The English text Things Fall Apart by Achebe(1994) and its Urdu translation, Bikharti Duniya byUllah (1991) have been annotated through the annotation scheme of the UAM Corpus Tool(O`Donnell, 2008). The annotated English and Urdu clauses are analyzed to discuss their the maticstructures. The results show that the functional significance and thematic progression patterns are identical, but because of the unmotivated displacement of themes, the translation choices become ambiguous.To resolve ambiguities, possible translation choices have been suggested.
A Comprehensive Stability Study of Glucose Concentrations Measured in Sodium Fluoride, Heparin and Serum Separator Tubes: A Cross-sectional Study

Introduction: Sodium fluoride mixed vacutainers were once viewed as the gold standard tubes for glucose analysis. However, their ineffectiveness in inhibiting glycolysis, especially in the first one to four hours has been reported in several studies. The accurate blood glucose estimation is crucial for the diagnosis and management of diabetes mellitus. Aim: To find out a cost effective and feasible alternative blood collection vacutainer for the estimation of accurate blood glucose. Materials and Methods: A cross-sectional study was conducted at the Blood Collection Centre of HAH Centenary Hospital, New Delhi, India, from December 2019 to July 2020. A blood sample was collected from 155 subjects in each-sodium fluoride [Na2EDTA], heparin [sodium heparin] and Serum Separator Tube (SST). To find out the glucose reduction during blood coagulation in SST tubes, the glucose levels (n=25) of sodium fluoride (plasma) at 0 hr and 30 mins after coagulation in SST tubes were compared. The remaining study subjects (n=130) were categorised into two groups (65 subjects in each group) and assessed for the reduction of glucose at 4°C and 25°C. Further, the reduction of glucose was also studied in both the groups as per glucose concentrations &lt;100 mg/dL (n=25), 100-200 mg/dL (n=25) and &gt;200 mg/dL (n=15) in each group. Results: The inter assay coefficient of variation of quality control samples of glucose (n=61) was 3.0%. The highest percentage of glucose reduction was found in the green vacutainers (p&lt;0.05) at 4°C and 25°C storage temperatures. There was no significant reduction of glucose level in SST vacutainers at 4°C up to 96 hrs of analysis (p&gt;0.05) and the result was comparable to grey vacutainers. Further, there was no haemolysis in the SST vacutainers up to 96 hrs of analysis, however, green and grey vacutainers showed enormous haemolysis. Conclusion: The glucose analysis in SST vacutainers can reduce the loss of sample, cost of analysis, and interferences in the analysis due to haemolysis. The study strongly suggests that all the analytical laboratories should do glucose analysis in SST vacutainers.
Kannada Text Recognition

Abstract: The task of automatic handwriting recognition is critical. This can be a difficult subject, and it has gotten a lot of attention in recent years. In the realm of picture grouping, handwritten character recognition is a problem. Handwritten characters are difficult to decipher since various people have distinct handwriting styles. For decades, researchers have been focusing on character identification in Latin handwriting. Kannada has had fewer studies conducted on it. Our "Kannada Text Recognition" research and effort attempts to classify and recognize characters written in Kannada, a south Indian language. The characters are taken from written documents, preprocessed with numpy and OpenCV, and then run through a CNN.
Paying Attention to the Insider Threat

The misuse of information systems by internal actors -the insider threat -is an ever-growing concern in organizations of all types.The timely detection of an insider threat is as important as it is difficult.Analyzing user behaviors recorded in electronic logs require significant computing resources and the capability to find and interpret complex patterns in temporal sequences that may contain irrelevant, temporary or novel elements.In this paper we use an attentionbased architecture derived from BERT (Bidirectional Encoder Representations from Transformers) for the creation, storage and updating of an always-current, holistic user behavior model that enables real-time insider threat detection through anomaly detection and user behavior prediction techniques.A case study with a very large transaction system is provided.