Reviewerly/exHarmony huggingface dataset:
VideoDL: Video-Based Digital Learning Framework Using AI Question Generation and Answer Assessment

Assessing learners’ understanding and competency in video-based digital learning is time-consuming and very difficult for educators, as it requires the generation of accurate and valid questions from pre-recorded learning videos. This paper demonstrates VideoDL, a video-based learning framework powered by Artificial Intelligence (AI) that supports automatic question generation and answer assessment from videos. VideoDL comprises of various AI algorithms, and an interactive web-based user interface (UI) developed using the principles of human-centred design. Our empirical evaluation using real-world videos from multiple domains demonstrates the effectiveness of VideoDL.
Robust, hybrid algorithms in AI-aided automatic music production

Contemporary music market is vastly dominated by streaming services.Growing popularity of streamed music consumption enables each music genre to find its niche.Some genres are defined well enough in terms of musical form and structure to carry out attempts at making the process of their production fully automated.This work presents a selection of algorithms designed for automatic music production.The algorithms are implemented in a fully functional production system that uses a hybrid approach, combining robustness and controllability of classic solutions with ability to generate and evaluate complex structures inherent for AI-based methods.So far, the approach has been applied to produce relaxation, dance, and electronic musicgenres that are popular in streaming services, and well suited for automatic production.
Automated Identification of Disaster News for Crisis Management using Machine Learning

A lot of news sources picked up on Typhoon Rai (also known locally as Typhoon Odette), along with fake news outlets. The study honed in on the issue, to create a model that can identify between legitimate and illegitimate news articles. With this in mind, we chose the following machine learning algorithms in our development: Logistic Regression, Random Forest and Multinomial Naive Bayes. Bag of Words, TF-IDF and Lemmatization were implemented in the Model. Gathering 160 datasets from legitimate and illegitimate sources, the machine learning was trained and tested. By combining all the machine learning techniques, the Combined BOW model was able to reach an accuracy of 91.07%, precision of 88.33%, recall of 94.64%, and F1 score of 91.38% and Combined TF-IDF model was able to reach an accuracy of 91.18%, precision of 86.89%, recall of 94.64%, and F1 score of 90.60%.
Artificial intelligence in the stock market: present and future

The article shows the role of trading robots in the stock market and the degree of efficiency. A comparison of algorithmic robots and neurobots is given, a hypothesis about the possible future of their symbiosis is expressed. Assumptions are made about the impact of artificial intelligence on trading on the stock market, on the possibility of extracting profit from it
Educational Programs of Business Producers and System Creators for Future Strategy Design Based on Action Project Group Activities through Industry and University Cooperation

Our Japanese industry and university project group at Aoyama Gakuin University carried out two types of development and demonstration classes as part of new educational programs to create human resources focused on future strategy design over several years. In response to social issues related to SDGs and the circular economy (CE) that may arise in the future, new human resources who can formulate SDG/CE business scheme documents to solve these social issues are called “business producers.” New educational methods that combine both project-based learning (PBL) and active learning (AL) to create business producers were developed to accommodate hybrid group work exercises. Specifically, educational digital transformation (DX) technology was integrated to ensure a flexible response to the new normal following COVID-19. As prerequisites to develop the four types of human resources that make up the SDGs/CE business scheme, the learning of theories and mechanisms pertinent to the various advanced technologies is desirable. These new human resources equipped with specialized knowledge and practical skills are called “system creators.” A practical hands-on training program to enhance the skills of the system creators through future strategy design was created to cover the following subjects: IoT and platform services, as well as metaverse experiences.
Mini-batch stochastic subgradient for functional constrained optimization

In this paper we consider finite sum composite convex optimization problems with many functional constraints. The objective function is expressed as a finite sum of two terms, one of which admits easy computation of (sub)gradients while the other is amenable to proximal evaluations. We assume a generalized bounded gradient condition on the objective which allows us to simultaneously tackle both smooth and nonsmooth problems. We also consider the cases of both with and without a strong convexity property. Further, we assume that each constraint set is given as the level set of a convex but not necessarily differentiable function. We reformulate the constrained finite sum problem into a stochastic optimization problem for which the stochastic subgradient projection method from [17] specializes to a collection of mini-batch variants, with different mini-batch sizes for the objective function and functional constraints, respectively. More specifically, at each iteration, our algorithm takes a mini-batch stochastic proximal subgradient step aimed at minimizing the objective function and then a subsequent mini-batch subgradient projection step minimizing the feasibility violation. By specializing different mini-batching strategies, we derive exact expressions for the stepsizes as a function of the mini-batch size and in some cases we also derive insightful stepsize-switching rules which describe when one should switch from a constant to a decreasing stepsize regime. We also prove sublinear convergence rates for the mini-batch subgradient projection algorithm which depend explicitly on the mini-batch sizes and on the properties of the objective function. Numerical results also show a better performance of our mini-batch scheme over its single-batch counterpart.
Data-Driven Evaluation Evolution

Through more than three years of practice, Zhangzhou Academy High School provides each student with a 15-page “privately tailored” “report sheet”. These reports provide a big data analysis of each student's achievements, describe and analyze the degree of mastery of each knowledge point in each subject, and make a comprehensive evaluation of individual ability, like a detailed and comprehensive “medical diagnosis report”. According lying, students can find their own shortcomings and improve the relevance and effectiveness of learning, and teachers can find their own teaching problems and timely correct it.
“Data” Runs: in Smart Classrooms, Teachers and Teaching

More than 60 classrooms in Pingdung Middle School in Fuzhou are all equipped with “smart classroom” facilities. It is normal to use electronic whiteboard, generative courseware, virtual experiment and video situation broadcast in teaching.
Create a “Double New” Driven Fun Digital Campus

Chongqing No. 29 Middle School (“Chongqing 29”), as “the Ministry of Education's Education Information Pilot Unit” and “Chongqing Smart Campus Pilot Unit”, has accumulated rich experience in information technology. The school has determined the educational information concept of “building a fun digital campus driven by ‘new ideas and new technologies’ (Double News)” and made traditional teaching more interesting and active.
Adaptive Evaluation System APP Development: Achieve Project-Based Learning

Baohe District, Hefei City, Anhui Province, has 47 primary and secondary schools with 78,326 students.
Smart Classroom: Find the Teaching Methodology for Teaching Students According to Their Aptitude

In 2013, it is an important node for the development of education in Yangling Demonstration Area.
The Informatization Road of Educational Reform in Private Schools

Junxian Keda Middle School belongs to Henan Hebi Keda Education Group. It is a private boarding junior high school.
“QR Code” Application in Education and Teaching

After several years of efforts, Xingzhi Primary School in Chengxi District in Xining performs well in Teacher Information Technology Literacy, Creator Education, Wisdom Classroom, QR code Application, Electronic Whiteboard Application, Tablet Art Teaching, Teaching APP Application, etc., in Qinghai Province, creating a new situation in information application. Chen Baosheng, the minister of Education and other municipal leader come to the school to instruct.
“Cloud and Network and Terminal” Intelligent Classroom Teaching Mode

Huaxi Primary School in Dalian City, Liaoning Province, was founded in 1995.
“Micro-Course of Teaching Group”: Promote Balanced Development of Education in Different Regions

Taizhou City, Jiangsu Province, vigorously promotes education informatization and actively explores an effective way to promote the balance of educational resources.
Disciplines Are Fully Covered by Mobile Terminals

Ludi West Primary School in Liwan District, Guangzhou, utilizes characteristic technologies to provide rich curricula and various learning resources based on the individuality and needs of students, so that each student can gain from learning and his own strength, and potential can be fully developed.
“One-To-One” Digital Future Classroom

Chengdu No.7 Middle School Junior High School set up the first tablet-based “one-to-one” digital learning class in September 2012 and began to explore the future of classroom construction practice.
Digital Classrooms for Self-learning

Founded in 1999, Jingbian No. 4 Middle School, Shaanxi Province, was once a suburban middle school in the backward areas of the west, with small student activities and poor hardware facilities. Teachers were frequently mobilized, teacher shortage was serious, teachers were older overall, the level of information-based teaching was low, teaching tasks were heavy, and teachers had a clear sense of job burnout. Thirty percent of children were left behind, 50% were migrant children and 20% were students in service areas.
Making Use of Information Technology to Build “Independent Learning” Culture

How to better build a self-development learning culture and promote the growth of life? Modern information technology has entered their vision with its good interactivity, instantaneity and diversity. Since May 2013, Tianjin No. 2 High School has been focusing on the four keywords of “transforming learning mode”, “improving learning efficiency”, “innovating learning culture” and “reconstructing the new education ecology”, using information technology and adopting the “four-step” strategy, and striving to achieve the transformation of students’ learning style, the improvement of learning efficiency and the multiple inclusion of learning content.
China Mobile “+ Education”: “Cloud Platform” for Rural Education

In China, there are about 61 million children left behind in rural areas, accounting for 21.88 percent of the total number of children in China.
School-Based Curriculum Development: Cloud Farm Education Innovation

There is a “small farm” of less than ten square meters in Hongshan Middle School in Wuhan, Hubei Province.
3–3-6 Classroom Teaching Model Based on Smart Classroom: The Realization of Inquiry Learning

In June 2013, Fuzhou Pingdong middle school was determined as a provincial pilot school of educational informatization by the Department of education of Fujian Province.
Impact of Quality of Service on Customer Satisfaction in Clinical Laboratory Services

The goals and expectations of clinical laboratories and the "customer-oriented" principle—which emphasizes the importance of satisfying and keeping customers as well as recognizing, appreciating, and keeping them—are congruent. "Customer" One who buys a product or service is called a customer. Clientele might be either people or businesses. To better understand their customers' priorities, effective managers consistently solicit input from their clients as they develop service strategies. This has allowed them to track their customers' levels of satisfaction and hence change their focus to making sure their clients are happy. Success or failure for the firm hinges almost entirely on the quality of service provided by the laboratory.
An Improved Dense Crowd Detection Algorithm Based on YOLOv5

Due to the particularity with a large number of labels in dense crowd dataset, the dense crowd detection difficulty is mainly reflected in the missed detection and false detection of small objects. In order to better detect small objects, this paper proposes a more efficient feature fusion network based on YOLOv5. The experiment uses the crowd human public dataset, which improves the average accuracy of detection while ensuring the inference speed. Experimental results show that [email protected] of the improved YOLOv5 network reaches 92.07%, which is 6.21% higher than the original YOLOv5s. The detection frame rate is 49FPS, which has good real-time detection ability. Therefore, the improved algorithm proposed in this work can be a better alternative in dense crowd detection task.
Characterization of Earthquake Near-fault Ground Motion Parameters Using an Artificial Neural Network on Synthetic Big Data

&amp;lt;p&amp;gt;The South Iceland Seismic Zone (SISZ) and Reykjanes Peninsula Oblique Rift (RPOR) in Southwest Iceland together form one of the two major transform zones in the country that have the greatest capacity for the occurrence of destructive earthquakes. Therefore, in these regions, the seismic hazard is highest and performing a probabilistic seismic hazard assessment (PSHA) is vital as the foundation of earthquake resistant building design and seismic risk mitigation. It is well known both from observations as well as physics-based (PB) modeling of earthquake rupture and near-fault ground motion simulations, that the most damaging part of near-fault seismic motion is the velocity pulse, the large-amplitude and long-period pulse-like ground motions found along the fault and away from the ends of strike-slip faults. Such motions cause intense earthquake action primarily on large buildings, such as hydroelectric power plants, dams, powerlines, bridges and pipelines. However, the data is still too limited to enable the reliable calibration of a physically realistic, yet parsimonious, near-fault model that incorporate such effects into empirical ground motions models (GMMs), thereby allowing their incorporation into a formal PSHA. However, in the recent European H2020 ChEESE project, we established a new 3D finite-fault system model for the SISZ-RPOR system that now has facilitated the simulation of finite-fault earthquake catalogues. Moreover, the catalogues have been implemented into the CyberShake platform, the PB earthquake simulator that was adapted to the characteristics of the SISZ-RPOR earthquakes in the ChEESE project. The seismic ground motions of each earthquake in the catalogue have thus been simulated on a dense grid of 594 near-fault stations in Southwest Iceland. The simulation has been carried out on high-performance computing systems of the Barcelona Supercomputing Centre in Spain. Moreover, the hypocentral locations and slip distributions on each synthetic fault have been varied, resulting in approximately 1 million earthquake-station-specific pairs of synthetic low-frequency and high-amplitude near-fault ground motion time histories. In this study, we analyse this dataset using an artificial neural network to reveal its characteristics in terms of amplitudes and the characteristics of near-fault velocity pulses, capturing all key features of such effects. The results will facilitate the incorporation of the near-fault effects into new near-fault and far-field GMMs, that are a key element of conventional PSHA. This will both enable the near-fault PB-PSHA along with the comparison of PSHA from the synthetic dataset vs. the GMMs. This will usher in a new era of PB-PSHA in Iceland.&amp;lt;/p&amp;gt;
GEOCHEMICAL FEATURES OF COPPER PORPHYRY МINERALIZATION IN THE GOSHGARCHAYORE MAGMATIC SYSTEM (MUROVDAG ORE REGION, AZERBAIJAN PART OF THE LESSER CAUCASUS)

The geochemical features of intrusive rocks and the surrounding rocks associated with porphyry copper mineralization in the Goshgarchay magmatic system were studied. Major factors of concentration of copper and copper-porphyritic mineralization in rocks of gabbro-diorite-granodiorite formation has been revealed. It has been established that the structure of this ore region was formed as a result of successive alteration of some deformation stages accompanied by development of fractures in intrusive massive, by dike intrusions, locks displacements along faults and the fractures composed of various mineral associations. Main ore components were defined and relations hips among elements were considered. Geochemical associations allowing the localization of the development area of mineralization have been analyzed in various formation stages of porphyry copper system according to the results of cluster analysis. In this study, Cu, Mo, Pb, Zn, Ag, Ni, Co, Mn, Ti, Cr, V, and Sr both in the surrounding rocks and in ore-bearing intrusive rocks were considered as stable elements. This group of elements can be regarded as indicator elements in porphyry copper. The results of the claster analysis show that the elements which are less characteristical for hydrothermal solutions (Mn, Ti, Cr, V, Sr) keep their freedom in all wallrocks and the existence of their grouping is probably associated with their transportation process from silicate rocks with surrounding basic-average content. The elements such as Cu, Mo, Ag, Pb and Zn which form free group are connected with the generation from the magmatic source in the course of crystallization differentiation process and exposure of rocks to the hydrothermal activity which is considered the source of these elements.The identification of reasons of the association of V with Cu and Zn and Pb with Fe group elements in the intrusive facies rocks is characterized with its uncertainty. The analysis of the schedule made according to the results of Cu and basic ore components (Mo, Ag, As, Bi, Gd, Co, Cr, Se, Ge, Li, Nb and etc.) in the ores of Goshgarchay deposit show their dependence on one another equally. The amount of Cu in the ores have Ag, As, Bi, Cd, Ce, Ge, Sr, Mo, Sb, Th and Ti positive correlation relationship, but it has negative correlation relationship with Co, Cr, Cs, La, Li, Pb, Rb, Ni, Nb and Zn. Direct dependence is observed for ore mass between concentrations of Cu, Mo, Pb, Zn, Ag, Se, Te and other elements in the Goshgarchay porphyry copper deposit. Three various mineral associations differing from one another participate in stock work type copper-porphyry mineralization: 1) primary sulfide minerals; 2) oxidized ores; 3) primary sulfide minerals significantly enriched with products of hydrothermal ore carrying solutions.
Consistent and Tractable Algorithm for Markov Network Learning

Markov network (MN) structured output classifiers provide a transparent and powerful way to model dependencies between output labels. The MN classifiers can be learned using the M3N algorithm, which, however, is not statistically consistent and requires expensive fully annotated examples. We propose an algorithm to learn MN classifiers that is based on Fisher-consistent adversarial loss minimization. Learning is transformed into a tractable convex optimization that is amenable to standard gradient methods. We also extend the algorithm to learn from examples with missing labels. We show that the extended algorithm remains convex, tractable, and statistically consistent.
A Survey on the Effective Machine Learning Approaches for Medical Images Forgery Detection

In today’s scenario medical image forgery has turned out to be unsophisticated because of capable PCs, propelled image editing softwares and high resolution capturing gadgets. Insurance fraud is a deliberate deception perpetrated against or by an insurance company or agent for financial gain. The only downside that the health insurance industry has faced is the rise in the number of health insurance frauds. An endeavor is prepared to review the current improvements in the research area of advanced medical image fraud detection and comprehensive reference index has been exhibited on different methods for medical forgery identification. Key Words: CNN, Forgery detection, medical images
Prolegomena a una nuova edizione critica delle opere volgari di Bonvesin da la Riva

Abstract Our perception of the vernacular works of Bonvesin da la Riva is still largely shaped by the editions of Gianfranco Contini (1941 and 1960). A reassessment of Bonvesin in terms of language and literary history can only start from a reflection on the textual basis of his works. The high quality of the Berlin manuscript (ca. 1300), which contains about half of Bonvesin’s oeuvre, is undisputed. However, the “retranslation” of the texts contained exclusively in later manuscripts which converts them into the form of the codex optimus , as still practised by Gökçen (2001), seems unacceptable today. Rather, the aim should be to identify different linguistic, stylistic and textual tendencies of the individual works by making recourse to the entire textual tradition. In this context, the assumption of an absolutely regular metrical form of the alexandrine, which has been advocated since Salvioni and Contini, is becoming increasingly questionable. It is suggested that Bonvesin’s poetry should be considered in the light of the tradition of anisosyllabism, which was well attested in the 13th century. The hypothesis of a “dialectal authenticity” of Bonvesin’s language is also problematic. Rather, an edition must preserve the constitutive polymorphism of the medieval scripta . Overall, the aim must be to recognise the distinctive personality of the medieval poet in the heterogeneity and variability of the surviving texts, beyond anachronistic expectations of a “classic”.
Investigation of Acoustic and Vibrational Properties Using Laser Doppler Vibrometry (LDV) and Electronic Speckle Pattern Interferometry (ESPI) of the Kulintangan Instruments

This study visualises the mode of the vibration of kulintangan using Electronic Speckle Pattern Interferometry (ESPI) to reveal the modes. It was found that the production of sound by the kulintangan was dominated by a particular mode which may be the (0,1), (1,1), (2,2), (3,2), and (4,2) of free edge circular gong. The spectrum distribution from the strike on the kulintangan showed it. The small gong A-H has an approximately harmonic spectrum with a fundamental frequency of 1240, 1055, 934, 792, 705, 624, 474, and 422 Hz. The gong does not display a similar occurrence of harmonics due to the ruggedness of the surface texture of the gong. This finding can be of great importance to facilitate a better understanding of the mechanisms involved in the sound production of musical instruments. Our research is visualising the sound sonically through PicoScope oscilloscopes and ESPI.