Reviewerly/exHarmony huggingface dataset:
Multiresolution Registration Network (MRN) Hierarchy with Prior Knowledge Learning

Deep learning has been extensively used in unsupervised deformable image registration. U-Net structures are often used to infer deformation fields from concatenated input images, and training is achieved by minimizing losses derived from image similarity and field regularization terms. However, the mechanism of multiresolution encoding and decoding with skip connections tends to mix up the spatial relationship between corresponding voxels or features. This paper proposes a multiresolution registration network (MRN) based on simple convolution layers at each resolution level and forms a framework mimicking the ideas of well-accepted traditional image registration algorithms, wherein deformations are solved at the lowest resolution and further refined level-by-level. Multiresolution image features can be directly fed into the network, and wavelet decomposition is employed to maintain rich features at low resolution. In addition, prior knowledge of deformations at the lowest resolution is modeled by kernel-PCA when the template image is fixed, and such a prior loss is employed for training at that level to better tolerate shape variability. The proposed algorithm can be directly used for group analysis or image labeling and potentially applied for registering any image pairs. We compared the performance of MRN with different settings, i.e., w/wo wavelet features, w/wo kernel-PCA losses, using brain magnetic resonance (MR) images, and the results showed better performance for the multiresolution representation and prior knowledge learning.
CONDITIONS FOR FORMING TECHNOLOGICAL LITERACY OF SCHOOLBOYS

The article highlights the problem of the formation of technological literacy in the context of modern education. The interest on the part of society and the state in the formation of technologically competent personnel has been substantiated. The theoretical aspects of technological literacy are considered, as well as the concepts of technological literacy, technological culture and technological competence are differentiated. Technological literacy itself was viewed in three contexts:&#x0D; - as a property of the student's personality;&#x0D; -as an educational goal;&#x0D; - as a response of the education system to social demand.&#x0D; The request from the state is represented by a set of regulatory documents that determine the requirements for the quality and content of the educational process.&#x0D; The paper lists the main forms of thinking necessary for the formation of technological literacy, defines the pedagogical goals of technological education. The conditions for the formation of technological literacy in the form of a system of factors are described. Special attention is paid to the technological literacy of the teacher and the mechanism of the successive transfer of personal technological experience from teacher to student is described.
New Loss Function to Enhance the Training Stability of Face Recognition Model

With the rapid development of convolutional neural networks, deep learning has been widely used in the field of face recognition. In recent years, the accuracy of face recognition has increased rapidly, mainly due to the proposition of novel loss functions. On the current largest face test set MegaFace, the top model has achieved 97.91% 1∶N search performance, but the problem of convergence stability during training has not been properly solved. Thus a new type of loss function, Lineface, is proposed in this paper. Its logic curve is linear in the cosine space, which makes the gradient convergence better and more stable during training. A large number of experiments show that good model performance and convergence can be achieved.
AN ANALYSIS OF CLASSROOM INTERACTION PATTERNS IN ENGLISH TEACHING LEARNING PROCESS (A DESCRIPTIVE QUALITATIVE STUDY AT EIGHTH GRADE STUDENTS AL SMPN 19 BANDA ACEH)

Name : Nurul Hidayah Student Number : 0706102020033 Study Program Script Title Study Program : English Education Script Title : An Analysis ofClassroom Interaction Patterns in English Teaching Learning Process (A Descriptive Qualitative Study at Eighth Grade Students at SMPN 19 Banda Aceh) The purpose of this study is to find out the patterns of classroom interaction that occur in English teaching learning process at grade Ylll-3. The subjects of the study were 31 students and an English teacher of class Vlll-3 SMPN 19 Banda Aceh. The method used in this study is descriptive qualitative analysis. Moreover, the instruments that are used in this study were observation, field notes, and video-recording. The data of this study is taken from the interaction between the teacher and the learners in the classroom. In order to analyze the data, the writer used Flanders interaction Analysis System (FIAS) to obtain a clear view of the interaction patterns that happened in the class. The steps in analyzing the data using FIAS are coding the interaction that appeared in the teaching and learning process, and analyzing the matrix. The finding shows that in the classroom, the teacher and the students interact well. It means that they interact well in which they understand to each other's meaning. However, the teacher speech dominates more in the interaction. The most dominant interaction pattern in this class was teacher-student whole class. The students were active enough in the classroom interaction with proportion 45% from the total teaching-learning time was devoted to students' participation. The students participated mostly in talk-response and a little in talk-initiation. The interaction in this classroom was in five-way communication: there were interaction between teacher• students, teacher-student, student-teacher, student-student and student-students.
Super-Resolution MRI Using Fractional Order Kernel Regression and Total Variation

In this paper, we adopt a kernel regression approach with steering kernel estimation using fractional order gradients and a Taylor series representation involving integer and fractional order. TV regularization using Fractional-order gradients is known to enhance textural details in smooth regions along with suppression of staircase artifacts. Thus, introducing the fractional-order gradient will make the adaptation of steering kernel more effective. With this motivation, we model a kernel regression framework using TV functional with local fractional-order Taylor series signal representation termed Fractional-order Adaptive Kernel Total Variation (FO-AKTV). Noise suppression in the texture region is achieved by Weighted Non-Local Nuclear Norm (WNLNN) based spectral low rank prior. To achieve the desired super-resolution solution, the cost function with aforementioned priors is minimized using the Alternating Direction Method of Multipliers (ADMM). The proposed method outperforms the state-of-the-art methods such as low rank total variation (LRTV), dictionary learning (DL) and adaptive kernel total variaton (AKTV) in terms of the output signal-to-noise ratio (SNR) at different input noise levels.
Hierarchical Bilevel Learning with Architecture and Loss Search for Hadamard-based Image Restoration

In the past few decades, Hadamard-based image restoration problems (e.g., low-light image enhancement) attract wide concerns in multiple areas related to artificial intelligence. However, existing works mostly focus on heuristically defining architecture and loss by the engineering experiences that came from extensive practices. This way brings about expensive verification costs for seeking out the optimal solution. To this end, we develop a novel hierarchical bilevel learning scheme to discover the architecture and loss simultaneously for different Hadamard-based image restoration tasks. More concretely, we first establish a new Hadamard-inspired neural unit to aggregate domain knowledge into the network design. Then we model a triple-level optimization that consists of the architecture, loss and parameters optimizations to deliver a macro perspective for network learning. Then we introduce a new hierarchical bilevel learning scheme for solving the built triple-level model to progressively generate the desired architecture and loss. We also define an architecture search space consisting of a series of simple operations and an image quality-oriented loss search space. Extensive experiments on three Hadamard-based image restoration tasks (including low-light image enhancement, single image haze removal and underwater image enhancement) fully verify our superiority against state-of-the-art methods.
Facial Micro-Expression Recognition for Recommended Music

Deep learning has gained more and more traction in the industry because the usage of big data. Convolutional Neural Network (CNN) play a crucial role in facial image identification since they are deep learning neural networks. As a result of this research, a combination of CNN micro-expression detection technology and an automatic music recommendation system has been developed. For the recognition of face micro expressions, the dataset of facial expressions obtained from the kaggle website is used in this study. To extract the song's feature vector, a content-based music recommendation algorithm is utilised. To increase the practicality of music recommendation system, this method is proposed.
Statistical Inference: The Missing Piece of RecSys Experiment Reliability Discourse.

This paper calls attention to the missing component of the recommender system evaluation process: Statistical Inference. There is active research in several components of the recommender system evaluation process: selecting baselines, standardizing benchmarks, and target item sampling. However, there has not yet been significant work on the role and use of statistical inference for analyzing recommender system evaluation results. In this paper, we argue that the use of statistical inference is a key component of the evaluation process that has not been given sufficient attention. We support this argument with systematic review of recent RecSys papers to understand how statistical inference is currently being used, along with a brief survey of studies that have been done on the use of statistical inference in the information retrieval community. We present several challenges that exist for inference in recommendation experiment which buttresses the need for empirical studies to aid with appropriately selecting and applying statistical inference techniques.
BlockChain (BC), Technology Notary in Data Driven Marketing (DDM) Contracts

Today, Data Driven Marketing is challenged by the supply of vague data, inconsistencies between them and fraud through advertising in the digital marketing ecosystem. Through three basic concepts like open ledger, distributed ledger, and miners, BlockChain (BC) is a perfectly positioned technology, restoring not only trust and transparency, but ensuring a greater uniformity of transactions within a largely fragmented sector. BC makes DDM more directly and reliable, validating and analyzing each customer's movement in advertising campaigns. In BlockChain the traditional principle that creates the positive correlation between fee and delivery time through the Third Trust Party becomes null because transparency is one of the basic properties of this technology, which on the other hand for DDM is the Achilles heel.
Eroded Sovereignty or Algorithmic Nation: Transnational Diffusion of Blockchain in Governance

This paper explores the relationship between transnational non-state actors and sovereignty through the adoption of blockchain technology in governance. Governments have introduced a growing number of blockchain applications to reform state functions and authority mechanisms. Initial expectations for blockchain were to act as a disruptive and transformative force to decentralise state authority; however, this is only part of the real picture. The decentralising tendencies of blockchain technology appear in political spaces where state sovereignty is weakened or absent, particularly among displaced and stateless communities. Conversely, strong states use blockchain technology to upgrade their existing digital infrastructure to empower and reinforce state power. Thus, the diffusion of blockchain in governance leads to the birth of two opposite phenomena: 'eroded sovereignty' and 'algorithmic nation'. This paper presents the data-based illustration of the two-directional diffusion and analyse the motives, pathways and impacts of emerging technologies on the sovereignty-dominated and territory-based international order.
Educación Matemática y Pandemia: experiencias en los Estados Unidos de América

This overview of experiences in Mathematics Education in the United States of America (USA) begins with a brief explanation of the educational system in the USA. The Introduction is followed by what happened during the beginning of the Pandemia, how Mathematics Education has continued to confront the Pandemia, what have been the activities of some professional associations, what are some of the online resources available, how student achievement has been impacted, and a look to the future.
Assessment of spontaneous emotional facial expressions using optical flow analysis- Lina Sidavong- University of Technology Sydney, Australia

Statement of the Problem: Investigations on emotion manifested through facial expressions has valuable applications in predictive behavioral studies. This has piqued interest towards developing intelligent visual surveillance for facial expression analysis. The idea is perpetuated by its immediate utility in closed circuit television (CCTV) surveillance and the growing belief that the subjective experience and emotion reflect one’s facial expression changes. A facial recognition program tailored to evaluating facial expression for forensic and surveillance purposes can be met if patterns of facial emotions can be detected. The purpose of this study was to induce emotions in individuals to determine if specific facial movements during different expressions could be detected by optical flow analysis. Methodology: Individuals were videotaped while watching three emotion inducing short films. The films were shown with the intention of inducing one of three emotions: amusement, sadness and fear. Skin conductance (SC) was measured along with a ninepoint Likert scale (self-reported emotional assessment) questionnaire to establish the type and extent of emotion felt. This allowed for still facial images representative of neutral and peak of emotional expressions to be extracted from recorded footage. Optical flow analysis was performed on the image sets using the MATLAB software to quantify the magnitude and direction of facial activity between neutral and peak emotional states. Results: Optical flow analysis produced vector maps depicting global velocity vectors of facial movement. When summarizing this information derived from the vector maps of amusement, sadness and fear, we observed similar trends and patterns of activity with a greater magnitude for the expression of amusement compared to sadness and fear. Conclusion and significance: Optical flow analysis shows potential in the discrimination of emotional facial expressions. However, further data analysis is necessary to confirm if different types of emotion can be identified clearly using optical flow or other such techniques.
Fired for Facebook…terminated for Tinder: dismissal for social media misconduct in New Zealand

This article reports the findings of a qualitative study of first instance New Zealand employment tribunal decisions concerned with employee dismissal for social media misconduct. There are two main findings. The first relates to the legal approach to employee dismissal for social media misconduct developing in New Zealand. The decisions show New Zealand decision-makers are following the approach in other jurisdictions of treating social media misconduct dismissals as involving a balance between public and private considerations of employment conduct and calculating harm in the employment relationship. However, the decisions do not only track the emerging legal approach to social media misconduct in employment. The decisions are also a record of how social media is affecting employment relations within New Zealand. They are not only legal but also social records. The second finding relates to what the decisions reveal about employment and social media in New Zealand. The sample showed something different from other similar studies. In New Zealand, there was a large cluster of decisions where social media facilitated gender-based harassment. This finding resonates with wider research into New Zealand workplaces that suggests an enduring toxic culture where gender-based harassment is normalized.
The Organization of Monitoring of Future Teachers’ Psychological and Pedagogical Training in Establishments of Professional and Technical Education

In the article there have been theoretically grounded the process of organization of the monitoring of future teachers’ psychological and pedagogical training in establishments of professional and technical education which consists of five stages: 1 stage – goals and planning of the research; 2 stage – tool development; 3 stage – conducting the research; 4 stage – processing of results; 5 stage – analysis and interpretation of the research results.On the basis of the given components of psychological and pedagogical competence there have been defined three criteria: personal, content and procedural, evaluative and regulatory. Every criterion is a complex of some indexes which characterize the most important and necessary manifestations of components of the psychological and pedagogical competence of future teachers in establishments of professional and technical education. There have been taken the diagnostic tools which give an opportunity to evaluate the levels of formation of components of future teachers’ psychological and pedagogical competence in establishments of professional and technical education according to definite criteria. Diagnostic tools of the cognitive component consist of testing methods: J. Raven test, R. Amthauer test (personal criterion: accordance of psychophysiological peculiarities to professional requirements (mental process: fillings, perception, memory, thinking, imagination and attention)); method of test control, analysis of written and oral answers (content and procedural criterion: theoretical knowledge of academic field (flexibility, strength, understanding); questionnaire of meta-cognitive involvement in the activity (evaluative and regulatory criterion: meta-cognitive knowledge (subject’s knowledge about personal learning strategies), meta-cognitive evaluation (judgments about mental abilities and limitations, their need in a particular situations), meta-cognitive regulation (subject’s modification of thinking).There have been revealed the content of experimental implementation of the method of organizing the psychological and pedagogical training of professional and technical educational establishments’ future teachers (on the example of checking the level of formation of cognitive and meta-cognitive skills, abilities, knowledge and understanding, which have a place in mastering the peculiarities of the psychological and pedagogical activity) and there have been proved the validity and adequacy of the research tools and reliability of the results.The study addresses the problem of labor migration at the level of quality vocational education and training, in particular in the context of the acquisition of higher education qualifiers for personal and professional self-realization, career development throughout life.
Eficacia del cuaderno viajero en la animación a la lectura en niños de cinco años

This research responded to the problem of the effectiveness of the traveler's notebook in reading animation in 5-year-olds of the Bilingual Initial Educational Institutions of Yarinacocha 2021, in dimensions: Playful activities, book world, simulated situations, visual imagination, family coexistence. Effectiveness of the traveler's notebook as a didactic strategy in animation to reading in 5-year-olds of the Educational Institutions of Yarinacocha 2021. It was obtained as a result, that traveler's notebook as a strategy contributes effectively in animation to reading in children 5 years of the initial educational institutions of Yarinacocha in 2021, with an improvement of 66.4% in the postest, with an average difference of 46,136 and 0.05 level of significance.
Consolidation via Tacit Culpability Measures: Between Explicit and Implicit Degrees of Culpability

Restoring consistency of a knowledge base, known as consolidation, should preserve as much information as possible of the original knowledge base. On the one hand, the field of belief change captures this principle of minimal change via rationality postulates. On the other hand, within the field of inconsistency measurement, culpability measures have been developed to assess how much a formula participates in making a knowledge base inconsistent. We look at culpability measures as a tool to disclose epistemic preference relations and build rational consolidation functions. We introduce tacit culpability measures that consider semantic counterparts between conflicting formulae, and we define a special class of these culpability measures based on a fixed-point characterisation: the stable tacit culpability measures. We show that the stable tacit culpability measures yield rational consolidation functions and that these are also the only culpability measures that yield rational consolidation functions.
Research on Eyesight Protection-Oriented Teaching Aids Using Machine Vision Technology

Eye machine ranging technology plays an important role in safety monitoring, assistant driving and prevention of myopia. However, there are some problems of accuracy and real-time in eye machine ranging. To solve this problem, this paper adopts the technical idea of “face detection-eye recognition-spatial positioning”, from coarse to fine, and constructs an adaptive vision protection desk system based on machine vision. Firstly, the improved census transform edge matching algorithm is used to obtain the edge depth map, intercept the human contour, and separate the head and shoulder to get the face area; Then, the designed eye detector is used to detect the human eyes, and the disparity is obtained by matching the corresponding human eyes on the right side; Finally, the vertical distance between the human eyes and the desktop is obtained through the optimized disparity calculation formula combined with the height calculation equation. Through many experiments, the remarkable effect of this method to improve the accuracy and real-time of man-machine ranging is verified.
The Need for Report Writing Training for Law Enforcement Professionals

Report writing is a crucial and necessary duty in the law enforcement profession. Police officers respond to calls of service on a continuous basis and take actions according to established laws and departmental policies. Those enforcement actions must be recorded clearly and accurately. However, police officers and their agencies often fall short of this requirement. Licensed Texas Peace Officers graduating from law enforcement academy are only required to have 16 hours of report writing training according to the Texas Commission on Law Enforcement (TCOLE). More law enforcement training related to report writing is needed. Law enforcement officers and the agencies they work for have seen an increase in civil litigations due to improper documentation in a police report. Also, poorly written police reports could be used by defense attorneys to make a case that the arresting officer had insufficient probable cause to arrest and charge the client, leading to an acquittal. Some of the benefits of additional report writing training is less civil lawsuit against the officers and their agencies, increase conviction rates, and providing statistical information used to combat crime issues to name a few. Therefore, law enforcement agencies should implement more report writing training.