Reviewerly/exHarmony huggingface dataset:
VIDI: A Video Dataset of Incidents

Automatic detection of natural disasters and incidents has become more important as a tool for fast response. There have been many studies to detect incidents using still images and text. However, the number of approaches that exploit temporal information is rather limited. One of the main reasons for this is that a diverse video dataset with various incident types does not exist. To address this need, in this paper we present a video dataset, Video Dataset of Incidents, VIDI, that contains 4,534 video clips corresponding to 43 incident categories. Each incident class has around 100 videos with a duration of ten seconds on average. To increase diversity, the videos have been searched in several languages. To assess the performance of the recent state-of-the-art approaches, Vision Transformer and TimeSformer, as well as to explore the contribution of video-based information for incident classification, we performed benchmark experiments on the VIDI and Incidents Dataset. We have shown that the recent methods improve the incident classification accuracy. We have found that employing video data is very beneficial for the task. By using the video data, the top-1 accuracy is increased to 76.56% from 67.37%, which was obtained using a single frame. VIDI will be made publicly available. Additional materials can be found at the following link: https://github.com/vididataset/VIDI.
Perceptual Quality Assessment for Fine-Grained Compressed Images

Recent years have witnessed the rapid development of image storage and transmission systems, in which image compression plays an important role. Generally speaking, image compression algorithms are developed to ensure good visual quality at limited bit rates. However, due to the different compression optimization methods, the compressed images may have different levels of quality, which needs to be evaluated quantificationally. Nowadays, the mainstream full-reference (FR) metrics are effective to predict the quality of compressed images at coarse-grained levels (the bit rates differences of compressed images are obvious), however, they may perform poorly for fine-grained compressed images whose bit rates differences are quite subtle. Therefore, to better improve the Quality of Experience (QoE) and provide useful guidance for compression algorithms, we propose a full-reference image quality assessment (FR-IQA) method for compressed images of fine-grained levels. Specifically, the reference images and compressed images are first converted to $YCbCr$ color space. The gradient features are extracted from regions that are sensitive to compression artifacts. Then we employ the Log-Gabor transformation to further analyze the texture difference. Finally, the obtained features are fused into a quality score. The proposed method is validated on the fine-grained compression image quality assessment (FGIQA) database, which is especially constructed for assessing the quality of compressed images with close bit rates. The experimental results show that our metric outperforms mainstream FR-IQA metrics on the FGIQA database. We also test our method on other commonly used compression IQA databases and the results show that our method obtains competitive performance on the coarse-grained compression IQA databases as well.
Perturbation Theory and the Sum of Squares

The sum-of-squares (SoS) hierarchy is a powerful technique based on semi-definite programming that can be used for both classical and quantum optimization problems. This hierarchy goes under several names; in particular, in quantum chemistry it is called the reduced density matrix (RDM) method. We consider the ability of this hierarchy to reproduce weak coupling perturbation theory for three different kinds of systems: spin (or qubit) systems, bosonic systems (the anharmonic oscillator), and fermionic systems with quartic interactions. For such fermionic systems, we show that degree-$4$ SoS (called $2$-RDM in quantum chemsitry) does not reproduce second order perturbation theory but degree-$6$ SoS ($3$-RDM) does (and we conjecture that it reproduces third order perturbation theory). Indeed, we identify a fragment of degree-$6$ SoS which can do this, which may be useful for practical quantum chemical calculations as it may be possible to implement this fragment with less cost than the full degree-$6$ SoS. Remarkably, this fragment is very similar to one studied by Hastings and O'Donnell for the Sachdev-Ye-Kitaev (SYK) model.
Anomaly Detection with Test Time Augmentation and Consistency Evaluation

Deep neural networks are known to be vulnerable to unseen data: they may wrongly assign high confidence stcores to out-distribuion samples. Recent works try to solve the problem using representation learning methods and specific metrics. In this paper, we propose a simple, yet effective post-hoc anomaly detection algorithm named Test Time Augmentation Anomaly Detection (TTA-AD), inspired by a novel observation. Specifically, we observe that in-distribution data enjoy more consistent predictions for its original and augmented versions on a trained network than out-distribution data, which separates in-distribution and out-distribution samples. Experiments on various high-resolution image benchmark datasets demonstrate that TTA-AD achieves comparable or better detection performance under dataset-vs-dataset anomaly detection settings with a 60%~90\% running time reduction of existing classifier-based algorithms. We provide empirical verification that the key to TTA-AD lies in the remaining classes between augmented features, which has long been partially ignored by previous works. Additionally, we use RUNS as a surrogate to analyze our algorithm theoretically.
Exploiting Consumption Diversity and neighbour Similarity Trade-offs in Recommender Systems: a User-Centric Offline Evaluation of Diversity Objectives

Abstract Recommender systems (RS) have seen widespread adoption across the Internet. However, by emphasising personalisation through the optimisation of accuracy-focused metrics, \textit{over}-\textit{personalisation} may emerge, with negative effects on the user experience. A countermeasure to the problem is to diversify recommendations. In this paper, we present a solution that addresses the problem for three application domains: movies, books, and music. Our solution, which we call \textit{VarSeek}, models the consumption diversity vs. neighbour similarity trade-off to control diversity and observe its impact on four related dimensions, namely item diversity, local coverage, novelty, and redundancy. The proposed solution is designed to diversify user profiles built on categorical preferences in a collaborative filtering scenario. We perform offline evaluations against state-of-the-art methods on three widely used datasets and show that the proposed algorithm is able to control recommendation novelty and redundancy.
Rancang Bangun Sistem informasi Akuntansi Penerimaan dan Pengeluaran Kas Pada BUMDes Agung Mandiri

Information systems are the most important part in a company or institution, one of which is an accounting information system for cash receipts and disbursements, which are usually used as support for decision making by management. BUMDes Agung Mandiri, which is engaged in services and trade, where the accounting information system for cash receipts and disbursements is still manual, therefore a computerized information system is needed to make work easier. The method used for reference in this research includes data collection techniques and system development techniques. Data collection techniques were observations, interviews, and literature research. Meanwhile, the system development technique uses a waterfall development model which consists of analysis, design, coding, testing, and maintenance. This research resulted in the design of cash receipts and disbursements accounting information systems that would facilitate the finance department in processing reports and also be used as a support for management in making decisions.
A parametrisation for symmetric designs admitting a flag-transitive, point-primitive automorphism group with a product action

We study (v,k,λ)-symmetric designs having a flag-transitive, point-primitive automorphism group, with v = m2 and (k,λ) = t &gt; 1, and prove that if D is such a design with m even admitting a flag-transitive, point-primitive automorphism group G, then either:D is a design with parameters ((2t+s−1)2, (2t2 − (2−s)t)/s, (t2 − t)/s2)) with s ≥ 1 odd, orG does not have a non-trivial product action.We observe that the parameters in (1), when s = 1, correspond to Menon designs.We also prove that if D is a (v,k,λ)-symmetric design with a flag-transitive, point-primitive automorphism group of product action type with v = ml and l ≥ 2 then the complement of D does not admit a flag-transitive automorphism group.
‘Face-to-Face vs. Distance Learning’: analysis of the training of musicians during Covid-19

The Covid-19 pandemic has significantly accelerated the introduction and expansion of forms of distance learning around the world. However, there are still some areas of learning that require direct interaction between the teacher and the student – like «face to face». Teaching of music (solo and choral singing, playing musical instruments) requires constant personal control of the teacher during the lesson. The main purpose of this article is to analyze the quality of distance and mixed learning for students of musical specialties at three humanitarian universities of Russia, Kazakhstan and Kyrgyzstan. Students answered to 32 questions of an online questionnaire on the using of various digital technologies in the process of distance learning during the pandemic. The authors come to the conclusion that the most promising is the mixed model of music education, in which digital technologies serve as an additional means for the development of professional skills.
The ways to develop students’ self-organization and self-education competences in the process of studying further mathematics

The paper describes the way of pedagogical conditions implementation that ensures the development of self-organization and self-education competences among technical university students. The theoretical substantiation of the need to create an integral complex of such conditions at a technical university is presented, the definition of organizational, pedagogical, psychological and didactic conditions for the development of self-organization and self-education competences among students is given, and the means of their implementation developed by the authors are listed. The possibilities of the traditional subject content are shown on the example of the course Further Mathematics for the purposeful development of cognitive, personal and activity components of self-organization and self-education competences. Examples from the developed set of tasks for the course Further Mathematics are given, as well as tasks of a project and research nature. All these tasks are aimed at the development of such regulatory actions that are part of self-organization and self-education competences, as forecasting, goal setting, planning, control, reflection, as well as such qualities of thinking as flexibility (variability), rationality, speed. Some results of experimental verification of the developed tasks effectiveness (for the activity and personal components of self-organization and self-education competences) are presented, proving the expediency of using them in the educational process at the university. The methods described in the paper for the pedagogical conditions implementation that ensure the development of self-organization and self-education competences among students of a technical university are invariant with respect to the subject content and can be extended to teaching other disciplines.
A Photovoice Study Exploring Deaf Students Experiences during The COVID-19 Pandemic

The Indonesia government through Large-Scale Social Restrictions (PSBB) policy urges distance learning with no exception distance learning for all citizens including for deaf students. Students with disabilities may have been harder to adapt to the distance learning. To explore these potential challenges, this study intended to reveal the exeperince deaf student during study from home using photovoice. The participants of this study were 8 deaf students (4 males and 4 females) from 10,11, and 12nd grades Special School in Surakarta. The study revealed three primary findings. Firstly, deaf students felt more convenient to study with the teacher than the parents. Secondly, they expressed their sadness and tedium during distance learning because of no meeting with friends and their teachers. Thirdly, the interviewed students are dread with the Covid-19 in the other hand they have difficulties to enhanced their communication skills and their competences. As the preliminary study, this study's result would be beneficial for future research. The stakeholder or the researcher can be developing meaningful and joyful learning for helping deaf students adapt the distance learning.
Improving Students’ Intensive Reading Ability by Using Survey-Question-Read-Review-Recite-Reflect Method

The current study is a classroom action research with the objective of analyzing the improvement of students’ intensive reading ability using Survey-Question-Read-Review-Recite-Reflect (SQ4R) method. This research was conducted at Ryulgok Secondary School, Pyongyang, by involving 32 the 3rd grade students as the research participants. Data collection techniques were interviews, observation, documentation, and tests. The data analysis method used in this study was divided into qualitative data analysis and quantitative data analysis. The results of the first cycle of the research showed that 58.4% of students were active, it meant that it was still less than the target 75% of the results of intensive reading, because only 53% of students achieved a score of 70 and above for reading ability. In the second cycle, it shows that 85% of students actively participated in learning and the percentage of students was 87% of the target 75% of students got a score of 70 and above for reading ability. This indicated that there was an increase in learning outcomes (reading ability) as a result of an increase in the learning process after using the SQ4R method.
Towards a Toolbox for Privacy-Preserving Computation on Health Data

Substantial advances in methods of collecting and aggregating large amounts of biomedical data have been met with insufficient measures of protecting it from unwarranted access and use. Most of the current layers of protection are merely aimed at ensuring compliance with regulations (e.g., the EU's General Data Protection Regulation) but do not represent a vision of privacy-by-design as an efficient and ethical advantage in biomedical research and clinical applications. This not only slows down the pace of such efforts but also leaves the data exposed to a wide spectrum of cyberattacks. This work presents an overview of recent advancements in data and compuation security, along with a discussion of their limitations and potential for deployement in both health care and research settings.
Some Compound Fractional Poisson Processes

In this paper, we introduce and study fractional versions of three compound Poisson processes, namely, the Bell-Touchard process, the Poisson-logarithmic process and the generalized P\'olya-Aeppli process. It is shown that these processes are limiting cases of a recently introduced process by Di Crescenzo et al. (2016), namely, the generalized counting process. We obtain the mean, variance, covariance, long-range dependence property etc. for these processes. Also, we obtain several equivalent forms of the one-dimensional distribution of fractional versions of these processes.
An Application of InterCriteria Analysis Approach to Assess the AMMOS Software Platform Outcomes

The experimental procedures of drug design, proven to be time-consuming and costly, are successfully complemented with computer-aided (in silico) approaches nowadays. Virtual ligand screening (VLS) is one of the most promising approaches when searching for new hit compounds. The efficiency of VLS procedures might be improved via post-docking optimization. In the focus of this investigation is AMMOS (Automatic Molecular Mechanics Optimization for in silico Screening) developed as multi-step structure-based procedure for efficient computational refinement of protein-ligand complexes at different levels of protein flexibility. Their performance has been assessed by the recently developed InterCriteria Analysis (ICrA), elaborated as multi-criterion decision-making approach to reveal possible relations in the behavior of pairs of criteria when multiple objects are considered. The capacity of ICrA as a supporting tool to assess the effect of applying different levels of protein flexibility in the post-docking optimization via AMMOS has been investigated and analyzed.
A Verbal and Non-Verbal Signs of Walt Disney Posters

This study aims to find out the verbal and non-verbal signs found in Walt Disney posters and analyze the meaning of verbal and non-verbal signs found in Walt Disney posters. Verbal sign is about text or words that appear in the Walt Disney poster. For the non-verbal signs appears as characters and colors used. The data of the research were downloaded from the pinterest. This study used a descriptive qualitative method. This study used a theory by Saussure in Chandler (2007) to analyze verbal and non-verbal signs. While the theory from Barthes (1977) to analyze the meaning of signs, and the supporting theory from Cerrato (2012) to analyze color terms. This research reveals that 6 verbal signs and 6 non-verbal signs were found in Walt Disney posters. These signs also contained 5 denotative and 9 connotative meanings from the story line in the poster. These meanings were found in the words and picture of Walt Disney posters.
WRITING A NEW POETRY WITH TANDUR STEPS: LEARNING USING QUANTUM LEARNING METHOD ASSISTED IN ICT

Learning based on the background of studentÂ ability to write new poetry is low. Based on the evaluation results, writing poetry does not reach the indicators of success in writing poetry. The research aims to determine the scenario and implementation, teacher and student responses, as well as to determine the difficulties experienced by grade X Vocational High School students in completing tasks of writing new poetry using the Quantum Learning method assisted by ICT media. This study uses a qualitative description method. The results of the study: (1) The learning scenario consisted of five meetings, namely four treatments using the Quantum Learning method with TANDUR (Grow, Experience, Name, Demonstrate, Repeat, and Celebrate) steps assisted by ICT media (powtoon and kahoot) and one test, the results of the implementation of learning get the percentage of teacher and student observations of 97.5% and 97.8% and can improve the ability to write new poetry by getting an average score of 82.
DEVELOPMENT OF CREATIVE ABILITIES OF PUPILS OF PRE-SCHOOL GROUPS WITH THE HELP OF ART THERAPY

Effective use of unusual methods in the activities of older children of preschool age. The importance of sand therapy in the activities of preschool adults, ways to use sand therapy in the creative activities of preschool adults and in the mental development of the child
USE OF ACTIVE TEACHING METHODS SYSTEMS TRAINING SYSTEMS FOR ECONOMICS

Methodology of a framing game is consiolered. This article deals with the question of formation of student creative abilities. The author shows the specific conditions to form student’s creative abilities at schools of higher learning.
Pemanfaatan Media Interaktif dalam Pembelajaran Geografi pada Masa Pandemi

In the 21st century, technological developments are increasingly advanced and very rapid. The role of interactive multimedia is increasingly playing a role in the field of education in line with the growth of computer users and the growth of the internet in society which increasingly facilitates the flow of multimedia products, both in the form of videos, animations, Google applications for assessment and for learning both online and offline. Along with the Covid-19 pandemic, it is increasingly visible the importance of the role of technology to be able to harmonize learning that runs remotely (online). The ability to make learning interactive, pro-student designing appropriate media adapted to the conditions of different students. Integrating multimedia and then pouring it into a storyboard is a key to the success of an interactive multimedia product development project. Learning geography during the Covid-19 pandemic requires new methods and media so that geography learning remains fun, interactive and able to increase student interest in learning geography, through interactive multimedia learning geography is expected to improve the quality of learning.
Research on the Application of Computer Network Technology in Electronic Information Engineering

Computer network technology has a very important role in electronic information engineering. The application of this technology not only enriches the traditional information engineering functions, but also effectively guarantees the efficiency and quality. At present, due to the wide variety of external information that Chinese citizens are exposed to, in addition to the variegated and mixed content, it is easy for information to be leaked or stolen. In order to avoid similar situations, it is necessary for people to pay more attention to network system security, so as to ensure that the quality of life of citizens can be guaranteed. In view of that, this paper discusses and analyzes the application of computer network technology in electronic information engineering.
Medical Workflow Design and Planning Using Node-RED Data Fusion

The space of clinical planning requires a complex arrangement of information, often not capable of being captured in a singular dataset. As a result, data fusion techniques can be used to combine multiple data sources as a method of enriching data to mimic and compliment the nature of clinical planning. These techniques are capable of aiding healthcare providers to produce higher quality clinical plans and better progression monitoring techniques. Clinical planning and monitoring are important facets of healthcare which are essential to improving the prognosis and quality of life of patients with chronic and debilitating conditions such as COPD. To exemplify this concept, we utilize a Node-Red-based clinical planning and monitoring tool that combines data fusion techniques using the JDL Model for data fusion and a domain specific language which features a self-organizing abstract syntax tree.
Risk Measures and Upper Probabilities: Coherence and Stratification

Machine learning typically presupposes classical probability theory which implies that aggregation is built upon expectation. There are now multiple reasons to motivate looking at richer alternatives to classical probability theory as a mathematical foundation for machine learning. We systematically examine a powerful and rich class of alternative aggregation functionals, known variously as spectral risk measures, Choquet integrals or Lorentz norms. We present a range of characterization results, and demonstrate what makes this spectral family so special. In doing so we arrive at a natural stratification of all coherent risk measures in terms of the upper probabilities that they induce by exploiting results from the theory of rearrangement invariant Banach spaces. We empirically demonstrate how this new approach to uncertainty helps tackling practical machine learning problems.