Reviewerly/exHarmony huggingface dataset:
Optimizing Wisdom-of-the-Crowd by Measuring Idiosyncratic Perceptual Biases

Combining multiple observers can improve performance. This wisdom-of-the-crowd technique harnesses the independency of different observers by averaging out randomly-distributed noise. However, recent studies have shown that individuals have idiosyncratic perceptual biases, and some observers have biases that are more similar to each other. This presents the possibility that the choice of pairs when employing two observers in the same task could be optimized by measuring the perceptual biases for each observer and coupling the most independent pairs. Here we tested this hypothesis through a series of studies ranging from low-level visual localization to high-level emotion recognition tasks. In Experiment 1, observers adjusted a cursor to indicate the locations of briefly-presented noise patches. In Experiment 2, observers adjusted morphed shapes to match previously-seen shapes. In Experiment 3, observers used a cursor to dynamically track and report the emotion of a target actor in Hollywood movies. Stimulus-specific perceptual errors (the difference between perceptual report and corresponding ground truth) were measured for each observer. Emotional ground truth was defined as the consensus of an independent group of observers. We calculated the correlation between the perceptual errors for every pair of participants, within each task. To test our hypothesis, we combined the responses between each least-correlated pair of observers, using an independent set of data. This yielded significantly higher accuracies in all three studies compared to the performance of single observers or random pairs. Our results demonstrate that pairing observers according to their perceptual biases rather than sensitivity can also optimize the paired-observer performance, and this technique can be widely applied even to situations where ground truth is subjective rather than objective, such as emotion recognition. Our findings highlight the importance of measuring individual differences in perceptual biases, and they have implications for critical applications such as TSA and radiological screening.
Criminal Prosecutions and Civil Litigation Concerning Blockchain Technologies

Although we have already cited a number of civil and criminal cases as they relate to specific subject-matter in prior chapters, we will focus on the broader enforcement both criminally and civilly. Criminal cases in US federal courts are prosecuted by the US Attorney’s Office in the District where the alleged federal crime has taken place and the admissible evidence will probably be sufficient to obtain and sustain a conviction.
Federal Regulation of Virtual Currencies

Legal issues arising from blockchain technology and other advancements in the digital arena are reminiscent and comparable to the rise of the internet some two decades ago. Among the difficulties presented in the civil and criminal arenas are the adjustments required of legislators, regulators, and judges to address new challenges posed by innovative technologies. National and local governments, both in the US and abroad, are attempting to understand and regulate virtual currencies which raise issues affecting investors and consumers using them.
GraphQL-based Backend Service Development Tool for CRUD Operations, Authentication, and Authorization

The development of GraphQL-based backend services needs: (1) data model, (2) create, read, update, and delete (CRUD) operations, (3) authentication, and (4) authorization system implementations. There are often repetitions of those implementations in the development process so that a large number of code writings are required. A GraphQL-based backend service development tool for CRUD operations, authentication, and authorization is proposed. This tool was created with the aim of reducing the code writings required for developers to implement CRUD operations, authentication, and authorization systems. GraphQL is used as the query language to access and manipulate data because GraphQL has a schema that can be utilized to define model data and the metadata needed. JSON Web Token (JWT) is chosen as the authentication method because JWT is one of the authentication methods that has a subject context used by the authorization method. Attribute-based access control (ABAC) is used as the authorization method because ABAC can validate up to the attribute level so it can handle many system requirements. The result is a GraphQL-based backend service development tool for CRUD operations, authentication, and authorization called Homura. The following results were obtained: (1) The GraphQL API server was successfully created using Homura based on the definition of CRUD operations, data model, authentication, and authorization, and (2) Homura succeeded in reducing the number of code writings required by 82%.
Sistem Pakar Deteksi Hemangioma pada Batita menggunakan Metode Hybrid

Hemangioma is a type of disease caused by active glands in the body. Hemangiomas occur in newborns up to the age of five (BATITA). This disease is indicated when a toddler has a fever or body temperature of more than 38°C. This condition affects the nerves and motor organs of the body that are attacked. This condition is sometimes undetected but develops quickly so it is necessary to consult an expert. This study aims to provide building a system in providing early education to parents in identifying toddlers with hemangiomas. This research makes it easy for parents to carry out further consultations with experts regarding the condition of toddlers. The processing of data and facts in this study was carried out by combining several methods (hybrid) in tracing each symptom according to the conditions experienced by system users. This method is continued by giving a weight value in the form of a percentage for each symptom experienced. The results of this study provide new knowledge in the form of information about Hemangioma with a confidence value in the form of a percentage of the patient's condition. This research provides the latest breakthrough in the form of presenting a system using an application that provides an accuracy value to ensure that patients have Hemangioma. This system can provide maximum value for users in gaining new knowledge for patients before further consultation with experts to get action.
RESULTS OF THE SCIENTIFIC SEMINAR "THEORY AND PRACTICE OF APPLIED CULTURAL RESEARCH" ON 26TH OCTOBER 2022 (MUSEUM CENTRE “PLOSCHAD MIRA”, KRASNOYARSK)

This text presents a summary of the work of the educational, scientific and methodological seminar "Theories and Practices of Applied Cultural Research" (October 26, 2022, Krasnoyarsk, Museum Center "Ploschad Mira"). The seminar was devoted to the presentation of topical art studies in accordance with memorable dates for the world of culture and art: 1) Compositional formulas in works of visual and audiovisual art; 2) Creation of archives as an actual form of audiovisual culture research; 3) Actual studies of cinematography: 65 years since the release of the film "The Cranes Are Flying" by M. Kalatozov, 85 years since the birth of Soviet screenwriter Gennady Shpalikov, 75 years since the birth of writer Stephen King; 4) History of publishing: 160 years since the birth of the Russian publisher Petr Petrovich Soykin.
Psychometric Properties of the Georgian Version of Motivated Strategies for Learning Questionnaire (MSLQ)

The article concerns the psychometric properties of the Georgian version of the Motivated Strategies for Learning Questionnaire (MSLQ) such as factorial properties, internal consistency of the sub-scales and gender differences by factors of the motivation and learning strategies scales. 560 Bachelor program students from 17 higher education institutions participated in the study. The instrument assessing motivation and self–regulated learning combine two main scales: 1) motivational orientation scale, and 2) learning strategies scale. There are 81-items in the instrument measured on a 7-point Likert type scale where point 1 means ‘Does not at all correspond’ and point 7 ‘Fully corresponds’.&nbsp; The administration of the questionnaire requires about 20-30 minutes. Study results show that the Georgian version of the Motivated Strategies for Learning Questionnaire is similar by factorial properties to the original version of the instrument. Internal consistency value is .70 for the motivation scale and .80 for learning strategies scale which meets the instrument validation standard.&nbsp; Reliability values for the factors in the scales ​​range from .51 to .89. As for gender differences, male and female respondents showed statistically significant difference on both motivation factors (task value, control beliefs and self-efficacy for learning) and learning strategies factors (elaboration, organization, metacognitive self-regulation, time and study environment management and effort regulation). The above findings lead to the conclusion that the Georgian version of Motivated Strategies for Learning Questionnaire can be used for future research purposes.
La littérature haïtienne en Italie : diffusion, réception et enjeux (2004-20)

Centered on the dissemination and legitimisation of Haitian literature in Italy, this article will provide a provisional state of the art of Haitian literature in the peninsula. The Italian case deserves particular attention as Italian universities took an early interest in Francophone literatures by promoting the creation of specific PhD programs, academic positions, and specialised journals. For our analysis, we will take as a starting point studies that have already addressed the issue – like Alessandro Costantini’s “Per un’introduzione alla letteratura haitiana: le opere tradotte in italiano” (2004) – and will try to understand the reasons why critics, in recent years, have been neglecting the subject, given that a systematic investigation has not been conducted since 2004. The legitimisation of Haitian literature in Italy occurs in various ways. We will take into account the different entities that contribute to its dissemination, like publishing houses, cultural and academic centers, journals, websites, etc. We will then focus on criticism in its broadest sense and will finally examine the critical productions published in Italian journals in order to detect the aesthetic orientations specific to the Haitian literary field.
Solving the Shortest Path Problem with QAOA

Graph computation is a core technique for solving realistic problems of graph representations. In solving the shortest path problem (SPP), the current classical methods are encountering a huge performance bottleneck. Attempting to solve this dilemma, we try to solve the SPP with a Quantum Approximate Optimal Algorithm (QAOA)-based quantum method. In this paper, we propose a QAOA-based shortest path algorithm (SPA) by constructing a suitable Hamiltonian quantity and using the idea of variational quantum computing, and verify the algorithm using a quantum simulator and an International Business Machines cloud quantum computer. The proposed algorithm is able to achieve a near-optimal solution with a correct rate that significantly exceeds the invalid solutions, reaching a good preliminary result. Furthermore, the proposed algorithm is expected to achieve a huge advantage over the classical algorithm and the SPA based on Grover’s algorithm with a suitable selection of parameters and number of steps. In addition, the proposed algorithm requires fewer quantum bits than other quantum algorithms, thus promising quantum computing superiority on current noisy intermediate-scale quantum (NISQ) quantum computing devices.
THE PROJECT "THE BEST HOSTESS OF THE HEARTH" IN ETHNO-CULTURAL EDUCATION

The traditional culture of the indigenous peoples of the North is gradually losing its functions in the modern development of innovative creative industries. In preserving cultural landmarks, the professional activity of future teachers of the North, bearing the foundations of the formation of an ethno-cultural worldview, is of great importance. Students are trained not only in the classroom, but also in extracurricular activities of the Institute of the Peoples of the North. Project activities under the program of ethno-cultural education are carried out in the educational work of the institute in the process of formation of professional competencies of the culturologist. The aim of the project is to introduce students to the cultural heritage in the process of preserving and popularizing the traditions of indigenous peoples of the North, Siberia and the Far East in ethno-cultural education. Design is one of the main forms of implementation of cultural policy for the training of professional personnel in the field of education. The educational activity of the Institute at the A. I. Herzen State Pedagogical University involves constant work to develop interest in events aimed at forming knowledge about the multiethnic diversity of the peoples of Russia, introducing students to the cultural heritage of the peoples of the North, Siberia and the Far East.
Multimedia as the Effective Tool for Teaching Local Wisdom to the Literature Students

This study examines the values ​​of local wisdom in multimedia-based learning of Cross Culture Understanding courses. Cross culture understanding is a course taught in the English Literature study program, where in the Cross Culture Understanding course students learn an understanding, namely an understanding of cultural differences and how to appreciate the differences that occur in their lives. This course is related to the mastery of knowledge of local wisdom, especially the values ​​contained in it, including social, economic, and educational values ​​of a culture. During the industrial revolution 4.0 and also the new normal period of the current covid-19 pandemic, all learning is still recommended not to meet face to face as an effort to prevent the transmission of covid-19. Various learning media are needed in the delivery of material, especially in this case material about culture and local wisdom which will be more interesting if you use several media in its presentation. Multimedia and technology play a very important role in changing the way of teaching and learning so that it becomes more innovative and multimedia itself is a combination of several media such as: text, graphics, audio or sound, and video that are in one software model to explain or describe a learning material. . Multimedia in the teaching and learning process aims to assist lecturers in explaining material that is difficult for students to understand. The use of multimedia technology can generate student learning motivation and make learning more interesting even though it is carried out online. The output of this research is in the form of scientific articles published in international journals and national proceedings. Keywords: Local Wisdom, Cross Culture Understanding, Multimedia
A Novel Approach for Credit Card Fraud Detection Using LR Method - Comparative Studies

Creditcard fraud detection mechanism is the most needed one in the present world. This is due to the development of e-commerce and online transaction. The main aim of this paper is to predict fraudulent transactions in a credit card transaction data set using statistical methods. Statistical methods based on Logistic Regression and Random Forest are developed and applied to credit card fraud detection problems. This work mainly focuses on machine learning algorithms as a classification model. The classification model is used for categorizing the dataset into fraud and non-fraudulent transactions. This project comprises methods for analyzing the fraud data to extract meaningful statistics and other characteristics of the data. The use of a model is to predict fraud with different statistical methods. This paper is one of the first to compare the performance of Logistic Regression and Random Forest methods in credit card fraud detection with a transaction data set using R. The results of the two algorithms are based on accuracy, precision, recall, and F1-score. The ROC curve is plotted based on the confusion matrix. The Random Forest and the Logistic Regression algorithms are compared and the algorithm that has the greatest accuracy, precision, recall, and F1 score is considered the best algorithm that is used to detect fraud.
Analysis of Intercultural Communication Models Among UINSU FIS Students

This study aims to determine the intercultural communication in question is the process of communication between groups of different cultures between foreign students and UINSU FIS students. This research uses descriptive research, which means a systematic, factual, and accurate description of the facts, characteristics and relationships between the phenomena being investigated. Research that uses descriptive type is research that is intended to describe, describe, or explain the state of the object being studied as it is about the analysis of intercultural communication in students of FIS UINSU. This research results that there is a KAB model for Aceh and Javanese students involving a mediator. This model illustrates that differences in communication behavior cause Papuan students to have difficulty adapting to Javanese students so that effective KAB is difficult to achieve. Therefore, the presence of a mediator from Javanese students is needed to bridge communication with Javanese student groups as well as to be a companion in class.
On the Challenge of Developing Key Competencies Through Natural Science Education of Primary School Students

The formation of key competencies as a contributing factor to the development of human personality is among the many challenges of our time. Based on the results of the participation of fourth graders in national and international assessments, the article presents the author’s conceptual model for developing key competencies through natural science education of elementary school students, structured and operating at a synergistic level. The synergistic approach is applied in the complex and unbalanced process of developing key competencies, which emphasizes the paradoxical property of ‘emergence’ as a consequence of the overactive effect of forming competencies in the development of the student’s personality. Adaptive solutions for sustainability of the processes are proposed through progression and multiplication of the effects of developing competencies in the field of natural science education.
Challenges to the Social Learning Process

The content of the article is focused on the process of social learning, overviewed in the context of the contemporary educational reality and influence of the distance learning in an electronic environment, which pose variety of challenges in the learning process. The research determines creating an educational concept emphasizing the optimization of the activities of specialists in the socio-pedagogical field.
Prof. Marin Petrov Lyulyushev, Dr. Habil, on the Popularization of the Latest Research of Scientists from the Faculty of Education

The article is dedicated to the 90th anniversary of the birth of Prof. Marin Lyulyushev, the first dean of the Faculty of Education and the first editor-in-chief of Pedagogical Almanac. It presents his contribution to: uniting the academic community aiming to integrate teaching and research work; international cooperation – necessity and responsibility; academic writing in the creative work of teachers; the first editorial board of the journal.
The Tunnel Fire Emergency Response Ontology Construction

Tunnel fire emergency response is one of the most complex fire of all kinds of fire emergency response. Although the frequency of occurrence is small, once it occurs, it will seriously threaten the life and property safety of the surrounding people and road traffic. T-FERO ontology model for tunnel fire emergency response is constructed based on typical tunnel fire emergency response texts in China and abroad. We choose Protege as the realization tool of tunnel fire emergency ontology. Through the construction of upper ontology based on the guidance of domain experts, we built a quintuple including highway tunnel, tunnel auxiliary equipment, passing vehicles, safety passage and other elements, and then the constructed emergency ontology of tunnel fire emergency response stage is evaluated through a group of examples.
Atrous Space Bender U-Net (ASBU-Net/LogiNet)

$ $With recent advances in CNNs, exceptional improvements have been made in semantic segmentation of high resolution images in terms of accuracy and latency. However, challenges still remain in detecting objects in crowded scenes, large scale variations, partial occlusion, and distortions, while still maintaining mobility and latency. We introduce a fast and efficient convolutional neural network, ASBU-Net, for semantic segmentation of high resolution images that addresses these problems and uses no novelty layers for ease of quantization and embedded hardware support. ASBU-Net is based on a new feature extraction module, atrous space bender layer (ASBL), which is efficient in terms of computation and memory. The ASB layers form a building block that is used to make ASBNet. Since this network does not use any special layers it can be easily implemented, quantized and deployed on FPGAs and other hardware with limited memory. We present experiments on resource and accuracy trade-offs and show strong performance compared to other popular models.
A reinforcement learning approach to improve the performance of the Avellaneda-Stoikov market-making algorithm

Market making is a high-frequency trading problem for which solutions based on reinforcement learning (RL) are being explored increasingly. This paper presents an approach to market making using deep reinforcement learning, with the novelty that, rather than to set the bid and ask prices directly, the neural network output is used to tweak the risk aversion parameter and the output of the Avellaneda-Stoikov procedure to obtain bid and ask prices that minimise inventory risk. Two further contributions are, first, that the initial parameters for the Avellaneda-Stoikov equations are optimised with a genetic algorithm, which parameters are also used to create a baseline Avellaneda-Stoikov agent (Gen-AS); and second, that state-defining features forming the RL agent's neural network input are selected based on their relative importance by means of a random forest. Two variants of the deep RL model (Alpha-AS-1 and Alpha-AS-2) were backtested on real data (L2 tick data from 30 days of bitcoin-dollar pair trading) alongside the Gen-AS model and two other baselines. The performance of the five models was recorded through four indicators (the Sharpe, Sortino and P&L-to-MAP ratios, and the maximum drawdown). Gen-AS outperformed the two other baseline models on all indicators, and in turn the two Alpha-AS models substantially outperformed Gen-AS on Sharpe, Sortino and P&L-to-MAP. Localised excessive risk-taking by the Alpha-AS models, as reflected in a few heavy dropdowns, is a source of concern for which possible solutions are discussed.