Reviewerly/exHarmony huggingface dataset:
Development of an Alcohol Refusal Training in Immersive Virtual Reality for Patients With Mild to Borderline Intellectual Disability and Alcohol Use Disorder: Cocreation With Experts in Addiction Care

People with mild to borderline intellectual disability (MBID; IQ=50-85) are at risk for developing an alcohol use disorder (AUD). One factor contributing to this risk is sensitivity to peer pressure. Hence, tailored trainings are needed to practice alcohol refusal in impacted patients. Immersive virtual reality (IVR) appears promising to engage patients in dialogs with virtual humans, allowing to practice alcohol refusal realistically. However, requirements for such an IVR have not been studied for MBID/AUD.This study aims to develop an IVR alcohol refusal training for patients with MBID and AUD. In this work, we cocreated our peer pressure simulation with experienced experts in addiction care.We followed the Persuasive System Design (PSD) model to develop our IVR alcohol refusal training. With 5 experts from a Dutch addiction clinic for patients with MBID, we held 3 focus groups to design the virtual environment, persuasive virtual human(s), and persuasive dialog. Subsequently, we developed our initial IVR prototype and conducted another focus group to evaluate IVR and procedures for clinical usage, resulting in our final peer pressure simulation.Our experts described visiting a friend at home with multiple friends as the most relevant peer pressure situation in the clinical setting. Based on the identified requirements, we developed a social-housing apartment with multiple virtual friends present. Moreover, we embedded a virtual man with generic appearance to exert peer pressure using a persuasive dialog. Patients can respond to persuasive attempts by selecting (refusal) responses with varying degrees of risk for relapse in alcohol use. Our evaluation showed that experts value a realistic and interactable IVR. However, experts identified lacking persuasive design elements, such as paralanguage, for our virtual human. For clinical usage, a user-centered customization is needed to prevent adverse effects. Further, interventions should be therapist delivered to avoid try-and-error in patients with MBID. Lastly, we identified factors for immersion, as well as facilitators and barriers for IVR accessibility.Our work establishes an initial PSD for IVR for alcohol refusal trainings in patients with MBID and AUD. With this, scholars can create comparable simulations by performing an analogous cocreation, replicate findings, and identify active PSD elements. For peer pressure, conveying emotional information in a virtual human's voice (eg, paralanguage) seems vital. However, previous rapport building may be needed to ensure that virtual humans are perceived as cognitively capable entities. Future work should validate our PSD with patients and start developing IVR treatment protocols using interdisciplinary teams.
[Risk Assessment and Source Analysis of Heavy Metal Pollution in Surface Sediments from Major River Systems in Maoming City, Guangdong Province].

In order to understand the spatial distribution and sources of heavy metals in surface sediments of MaoMing city and to reasonably evaluate the ecological risk of heavy metals in sediments of the study area, the contents of heavy metals (As, Hg, Cd, Co, Cr, Cu, Mn, Ni, Pb, and Zn) in surface sediments of eight rivers and three reservoirs were detected, and the risks of heavy metals were assessed using the geo-accumulation index (Igeo), potential ecological disk index (RI), and potential adverse biological impacts (ΣTUs). The sources of heavy metals were analyzed via correlation, principal component analysis (PCA), and positive matrix factorization (PMF). The results showed that the ω(Zn) (147.56 mg·kg-1) and ω(Hg) (0.20 mg·kg-1) were 3.72 and 2.25 times the background value, respectively, and the spatial distributions of Cd, Co, Cu, Mn, Ni, and Zn were in the order of northern>central>western>southeast. The geo-accumulation index results showed that Zn was at a moderate pollution level, 76.6% of the sampling sites of Hg were at a light-heavy pollution level, and other heavy metals were at a non-light pollution level. The results of potential ecological risk and potential adverse biological impacts indicated that the potential ecological risk index and toxicity effect of Gaozhou Reservoir were higher than those of other rivers, and Hg was the major contributor to heavy metal pollution. The three factors extracted from principal component analysis and positive matrix factorization represented natural sources, agricultural sources, and industrial sources, respectively. Therefore, in order to reduce the health hazards caused by heavy metals in sediments, a prevention and control system for the Hg element should be established.
Air-Writing Recognition System

Air-Writing is the use of an object or finger movements to create linguistic characters or words in free space. Writing in the air with fingers/using an object is practically a metaphor of pen-based writing. Detecting intended writing among extraneous finger/object movements entirely irrelevant to letters or words poses a challenge which should be addressed in the common pattern recognition methods. We propose a system that writes the exact mean of the motion that is drawn in front of the sensor using Hidden Markov Algorithm and OpenCV. This system draws the exact motion and is also used for virtual key generation. The output is shown like 2D trajectory and we will recognize the word error of the exact drawing. We will also analyze the 6-DOF (Degree Of Freedom) motion of the recognition. The findings of the experiments indicate that the average rate of recognition of digits and numbers is 98.3% accurate.
Data glove-based sign language translation with convolutional neural networks

This research was carried out because of the communication barriers that currently exist between hearing impaired and hearing people. These barriers hinder their integration into society and affect their interpersonal relationships. The objective of the study was to propose the development of a stationary assistive robot capable of displaying sign language interpretation through the combination of data gloves and the D-CNN and LSTM algorithm to facilitate the communication of hearing-impaired children in Huancayo. The triple diamond research design was used, where the mind map and the lotus diagram were used for the delimitation and definition of the problem. In addition, the IDEF0 technique was used to obtain a structured design of the project system. A morphological matrix was also used to choose the best solution for the problem. The chosen design contemplates the use of an Arduino UNO, flex sensors, accelerometers and gyroscopes for sign detection. The main algorithm consists of the union of a deep convolutional neural network and a LSTM for a correct sign classification module. The proposed design proposes to visualize the conceptual development of the project mentioned above.
Analysis of Short Video Marketing Strategy Based on SICAS Model--Taking Kuaishou as an Example

In recent years, with the rapid development of Internet technology, we have entered the Web2.0 era which was famous as "interaction".Short video characterized by low information acquisition cost and wide coverage came into being.This article takes Kuaishou APP as an example and uses the SICAS model to study Kuaishou's current marketing situation.By collecting 113 data through the questionnaire platform and analyzing the basic situation of consumers in the short video shopping platform.The results show that consumers will be influenced by other people's comments and opinions when buying, and are willing to share a satisfactory shopping experience with others after buying.Combined with SICAS model, some suggestions for the future development of short video platform are put forward
Few-parameter learning for a hierarchical perceptual grouping system

Perceptual grouping along well-established Gestalt laws provides one set of traditional methods that provide a tiny set of meaningful parameters to be adjusted for each application field. More complex and challenging tasks require a hierarchical setting, where the results aggregated by a first grouping process are later subject to further processing on a larger scale and with more abstract objects. This can be several steps deep. An example from the domain of forestry provides insight into the search for suitable parameter settings providing sufficient performance for the machine-vision module to be of practical use within a larger robotic control setting in this application domain. This sets a stark contrast in comparison to the state-of-the-art deep-learning neural nets, where many millions of obscure parameters must be adjusted properly before the performance suffices. It is the opinion of the author that the huge freedom for possible settings in such a high-dimensional inscrutable parameter space poses an unnecessary risk. Moreover, few-parameter learning is getting along with less training material. Whereas the state-of-the-art networks require millions of images with expert labels, a single image can already provide good insight into the nature of the parameter domain of the Gestalt laws, and a domain expert labeling just a handful of salient contours in said image yields already a proper goal function, so that a well working sweet spot in the parameter domain can be found in a few steps. As compared to the state-of-the-art neural nets, a reduction of six orders of magnitude in the number of parameters results. Almost parameter-free statistical test methods can reduce the number of parameters to be trained further by one order of magnitude, but they are less flexible and currently lack the advantages of hierarchical feature processing.
Phishing Attack Victims and the Effect on Work Engagement

Most of the research carried out in cybersecurity considers the technical aspects of the security of an organisation’s systems. This work highlights the importance of considering the ‘softer’ social side of cybersecurity that looks at the lived experiences of phishing attack victims and the effect of such attacks on work engagement. In order to understand these effects, the study adopted the grounded theory (GT) approach to collecting and analysing data elicited from participants. The participants were theoretically sampled from the metropole area of Johannesburg and presented lived experiences of phishing attacks in their unique contexts. The data were transcribed and coded using GT techniques. From the codes, categories derived, and substantive theory that explains the effects of phishing attack victims on work engagement was generated. The implications of this theory to previous theories and scholars and practitioners are discussed.
How do we perceive Characters? An Analysis of Human Perception in Still Images, Animations and VR Scenarios

Virtual characters can elicit an uncomfortable sensation usually known as Uncanny Valley (UV). Evidence suggests that animation exacerbates the UV effect. This paper revisits the UV hypothesis to assess its effects on people’s perception of virtual characters, to try to answer the questions “What happens to the perceptual comfort if, in addition to images and videos of characters, we include those characters in an interactive Virtual Reality (VR) environment?”, and “Considering the VR environment, do people feel equally comfortable if we increase the number of characters?”. The results indicate that there are differences in the perception of scenarios with low and high densities.
THE EFFECT OF USING EDUCATIONAL WEBSITES ON ACADEMIC ACHIEVEMENT OF PRIMARY SCHOOL STUDENTS IN THE UAE

This study was conducted to investigate the effect of educational websites on the academic achievement of primary students in the UAE.As E-learning is gaining momentum in educational fields all across the world, there are several conflicts and discussions going around regarding the effect of using educational websites on students' learning outcomes.To find a solution to these conflicts, the researchers conducted research to examine how the academic achievement of primary students in the UAE is better with the implementation of technology.Moreover, this study investigated the perspective of grade three students in an Abu Dhabi school following the Cambridge curriculum.To conduct this study, an educational website Purple Mash was introduced as an intervention to an experimental group for a time period of three months (fall semester).A control group (n = 15) was exposed to a traditional way of teaching, whereas an experimental group (n = 14) was exposed to an intervention.The results of this study suggested that there is a positive influence of educational websites on student achievement.Also, students found it easy and fun to learn creatively using interactive educational websites.The researchers also recommended creating a website for each lesson taught to ensure that it is available for both teachers and students.
Transfer Learning with Pre-trained CNNs for Breast Cancer Stage Identification

Breast cancer stage identification is an important prerequisite for early treatment to increase the chance of survival, and predict the recurrence of cancer. Research works done so far were mainly focused on the classification of breast cancer types while many of them are neglecting to stage of breast cancer. Obtaining an adequate labeled breast cancer image dataset for training machine learning algorithms is challenging. In this paper, we propose a pre-trained Convolutional Neural Network (Pretrained-CNN) model for Breast Cancer Stage Identification. The proposed method is designed by leveraging transfer learning techniques. Further, the performance of the pre-trained model is compared with CNN-based models that are trained from scratch. The performance of the proposed model is tested using a publicly available breast cancer-image dataset taken and achieved a promising result with an overall classification accuracy of 90%
Artificial Intelligence in College English Teaching under the Background of Big Data

With the deepening and development of world education reform, the theory of multiple intelligences has been increasingly accepted and recognized by international and domestic educators with its outstanding advantages and positive effects.Quality education has been implemented in our country for many years, and domestic education reforms have also made some achievements.This article mainly introduces BP neural network(BPNN) and hill climbing algorithm(HCA).Based on the big data, this paper uses artificial intelligence(AI) to detect college English(CE) teaching and establishes a mathematical model of potential pre-and post-test.The mountain climbing algorithm is used to solve the problem, and it also identifies the status quo of AI in CE teaching, and corrects model parameters through past data to improve teaching quality.The results found that the BPNN and the HCA have increased the effect of college English teaching by 33%, and increased students' interest in learning English.However, our country's artificial intelligence has not been established in CE teaching, so that the use of AI cannot be fully carried out.
On the Evaluation of (Meta-)solver Approaches

Meta-solver approaches exploits a number of individual solvers to potentially build a better solver. To assess the performance of meta-solvers, one can simply adopt the metrics typically used for individual solvers (e.g., runtime or solution quality), or employ more specific evaluation metrics (e.g., by measuring how close the meta-solver gets to its virtual best performance). In this paper, based on some recently published works, we provide an overview of different performance metrics for evaluating (meta-)solvers, by underlying their strengths and weaknesses.
On the question of the ontogeny of the model specialist in line with the evolution of educational standards

The specialist model is an important concept of Higher Education didactics, a system-forming element in the design of educational process to train specialists, the basis for evaluating its effectiveness, forming the subject field of the educational process, and choosing educational technologies and teaching methods. The specialist model, as a system of professional qualities requirements for a specialist, is reflected in the regulatory and legal documentation on professional training, such as State Educational Standards of Higher Education. The last decade has been a period of significant changes in the educational standards of the third generation for higher education, the development and implementation of educational standards of the fourth generation is on the threshold. The topic of transformation of the specialist model presented in educational standards has become especially relevant. The article aims to consider the changes (ontogenesis) of the specialist model in compliance with the evolution of educational standards of higher education and how it affected the design and development of educational programs for training specialists. Changes in the specialist model are considered, the case of engineering training programs (bachelor’s) throughout the entire period of implementation of educational standards of three generations. It is shown that many changes are both of negative and positive systemic nature. The solution to the problems is not so much in the field of didactics, but in the field of lawmaking when developing fourth-generation standards. For this purpose, some recommendations regarding the properties of the specialist model, being the vital link of educational standards, are given.
Track and Field Teaching Management System Based on B/S Architecture

The ability to send data online when computers are networked allows immediate sharing of data and avoids duplication of work, thus making physical education a standardised management that can positively improve the efficiency of administration.The aim of this paper is to investigate the design and implementation of an athletics teaching management system based on a B/S architecture.Firstly, it introduces the development history of the B/S architecture-based athletics teaching system, summarises the relevant research on the management information system for athletics teaching, and explains the development value and development significance of the system.Secondly, the reasons for the difficulties in teaching track and field special classes are analysed, the general design principles of the track and field teaching management system are introduced, and the detailed structure of the system data flow analysis and database design are described.Finally, the system design and implementation work is shown to implement the key algorithms for document management and key codes for grade management of the system.The results show that the system can help physical education teachers to manage athletics teaching more effectively.
Athletics Teaching Based on Multimedia Network Resource System Integration Based on Computer Technology

With the emergence of computer technology (CT), traditional educational technology has been challenged, and the theories and methods of modern educational technology that have been replaced have gradually penetrated into various educational levels and campus education and teaching.Modern educational technology has constructed a modern teaching mode through the integration and combination of most disciplines.The modern teaching mode has formed a digital, networked and computerized system.Therefore, this paper uses CT to design a multimedia network resource system, and applies the system to the actual track and field teaching, so that students can learn through the multimedia teaching resources included in the system.To more track and field competition skills, use scientific training methods for daily training.After comparing the teaching results of the physical quality of the students in the two classes, it is found that the use of the multimedia network resource system in this paper can also achieve a good teaching effect compared with the traditional teaching mode.
Innovative Education Promotes the Teaching of Computer Basic Courses

Efficiently cultivating students' innovative ability is an important historical mission facing higher education workers.Combining with the practice of basic computer teaching in colleges, this paper expounds how to teach students in teaching from five aspects: updating educational concepts, creating problem situations, implementing problem-based teaching models, giving full play to students' subjectivity and innovation, and combining theory with practice.The cultivation of innovative ability and innovative spirit provides new ideas for the implementation of innovative education in education and teaching.
"1+X" Course Certificate Fusion and Environmental Design Professional Training Quality Evaluation Model Based on Big Data

With the rapid development of modern science and technology, the "1+x" characteristic curriculum reform based on big data has received widespread attention from all walks of life in recent years as a phased and landmark achievement of my country's basic education reform.Oriented by cultivating talents that meet the needs of today's society, with the goal of environmental design related vocational qualification certificates, the main course teaching of the main teacher is the leading, environmental design guidance skills as the core competence, vocational skills training as the main line, and qualification verification.It is closely integrated with course teaching to realize the improvement of teaching quality and the construction of an evaluation model for the training of professional talents.The purpose of this article is to study the "1+X" course certificate fusion based on big data and the construction of the quality evaluation model of environmental design professionals.This article mainly uses literature data method, questionnaire survey method, mathematical statistics method, comparative analysis method, logical analysis method and other research methods to study the environmental design students and graduates of a university in this province, and first defines the quality of talent training Monitoring system, sustainable development, quality standard research and stakeholder theory and other related concepts, analyze the composition of monitoring indicators for the quality of personnel training in secondary vocational schools, and build the "1+X" course certificate integration based on big data and the training of environmental design professionals Quality evaluation model.The results show that after the construction of the "1+X" course certificate integration based on big data and the construction of the environmental design professional talent training quality evaluation model, the employment rate has increased significantly.This is the best proof of the strong competitiveness of the students, indicating that the students are still It is more recognized and welcomed by enterprises, and the higher employment rate shows that the quality of talent training is also higher.
The Influence of Blended Learning on English Learning Motivation and Achievement of English Majors

Blended learning is the combination of network learning and classroom learning, which is a supplement of the conventional teaching mode.As the continuous advancement of the Internet, blended learning is becoming increasingly prevalent.This paper mainly discusses the influence of blended learning on English learning motivation and achievement of English majors.Quantitative research is adopted through questionnaire survey on students majoring in English Education in the college of Arts and Sciences of Hubei Normal University.The questionnaire includes basic personal information, the motivation of students' learning under blended learning and the experience of blended learning.The results show that blended learning mode can improve students' English learning motivation.