Reviewerly/exHarmony huggingface dataset:
Professional Motivation of Secondary School Teachers

The problems of staff shortage in secondary school, mutual understanding between teacher and student, effective training of students are largely related to the teacher's high motivation to work and overcome objective difficulties. The subject of the study is the features of the professional motivation of secondary school teachers depending on the length of service. The purpose of the study: to study the content characteristics of the professional motivation of secondary school teachers, depending on the length of service. We studied the following groups of components of professional motivation: value-semantic; cognitive; emotional-personal component. To conduct the study, a sample was formed, the number of which was 45 teachers and divided into 3 age groups with different periods of teaching experience of 15 people in each group. The results of the study showed differences between groups of teachers with different professional experience. Teachers on the initial path of professional activity have a more pronounced focus on tasks and interactions, less on themselves. And teachers with more professional experience have a pronounced focus on themselves, and less on tasks and interactions in the motivational complex of secondary school teachers with different work experience, there are differences in the predominance of internal and external motives. External positive motives predominate, which are associated with the action of external incentives (the possibility of obtaining recognition, the availability of salary growth opportunities, the ability to use the provided measures of state support, etc. External negative motives in the sample of teachers are the least pronounced, which can also be regarded as a sign of a fairly prosperous environment associated with the working conditions of school teachers.
Groundwater Vulnerability Assessment Using Simple Vertical Vulnerability Method

Research on groundwater vulnerability using the simple vertical vulnerability (SVV) method in Wonosari district, Gunungkidul, Yogyakarta was conducted to identify groundwater vulnerability zones that require careful management in the research area.It is very important to know the extent of existing environmental and geological conditions in protecting groundwater from the potential pollution that may arise.In addition, this study also wants to prove the accuracy of the SVV method when carried out in limestone lithology conditions.The method used is the SVV method concerning three intrinsic parameters, namely the type of lithology based on the value of each specific retention of the soil or rock, the thickness of the unsaturated zone, the amount of groundwater recharge, and verified by land use.The nitrate content test in water samples at the research site was conducted to validate the research results.The study results found that two lithology types compose the research area, namely crystalline limestones, which are generally scattered in the southern part, and calcarenite limestones distribution in the central and northern parts.The depth of the unsaturated zone in the study area varies from 0 to more than 40 m, with the groundwater recharge being 438.68 mm/year.The land use of the research area varies from urban regions and rice fields to community plantation areas.The existing parameter overlay results are divided into three groundwater vulnerability zones: medium, high, and very high.The potential sources of pollutions zone are divided into four zones: low zone, medium zone, high zone, and very high zone.Based on the validation results carried out by comparing the nitrate content of groundwater samples taken in the research area, a correlation was found between the potential sources of pollutants and nitrate concentration.Therefore, the research results using the SVV method are considered accurate enough to represent nature's ability to protect groundwater quality in the research area.The result of the groundwater vulnerability zone by the SVV method is considered accurate enough to represent nature's ability to protect groundwater quality in the research area.
Mobile Learning Among University Students: Adoption and Application of M-Learning

The successful implementation of mobile learning is mainly impacted by learners’ attitudes to accepting and applying mobile learning systems. In the current study, an m-learning application was developed and implemented for university students, and their perspective toward the adoption and application of m-learning was investigated. This cross-sectional study was carried out in 2020. The participants were 114 university students at Abadan University of Medical Sciences. Data were collected by means of a valid questionnaire containing 42 questions in 13 subscales in addition to an open-ended question about the positive and negative aspects of the m-learning application. There was a significant relationship between acceptance and major (P=0.001), mobile usage (P=0.035), and familiarity with m-learning (P&lt;0.001). The total mean of m-learning application acceptance was 3.95±0.32, which shows a good level. Self-efficacy, perceived ease of use, and user interface were, respectively, the most influencing factors; mobile device limitation and governmental support were the least influencing factors. “Direct communication with the teacher/instructor” and “Internet disconnection during video teaching” were among the positive and negative aspects of applying the m-learning application, respectively. The m-learning application was well adopted among the students. Mobile device limitations are a reason for the student's concerns. “Usability features” can be a point for covering mobile device limitations.
MOTOR: A Time-To-Event Foundation Model For Structured Medical Records

We present a self-supervised, time-to-event (TTE) foundation model called MOTOR (Many Outcome Time Oriented Representations) which is pretrained on timestamped sequences of events in electronic health records (EHR) and health insurance claims. TTE models are used for estimating the probability distribution of the time until a specific event occurs, which is an important task in medical settings. TTE models provide many advantages over classification using fixed time horizons, including naturally handling censored observations, but are challenging to train with limited labeled data. MOTOR addresses this challenge by pretraining on up to 55M patient records (9B clinical events). We evaluate MOTOR's transfer learning performance on 19 tasks, across 3 patient databases (a private EHR system, MIMIC-IV, and Merative claims data). Task-specific models adapted from MOTOR improve time-dependent C statistics by 4.6% over state-of-the-art, improve label efficiency by up to 95% ,and are more robust to temporal distributional shifts. We further evaluate cross-site portability by adapting our MOTOR foundation model for six prediction tasks on the MIMIC-IV dataset, where it outperforms all baselines. MOTOR is the first foundation model for medical TTE predictions and we release a 143M parameter pretrained model for research use at [redacted URL].
Research on Online English Speech Interactive Recognition System Based on Nose Algorithm

Speech database evaluation algorithm and recognition function are the key factors affecting speech recognition rate and recognition time. In this paper, an online English speech interactive recognition system is designed by using nose algorithm and Mel frequency cepstrum coefficient windowing function. The system can recognize English speech information accurately and quickly, and use the reference database for evaluation and expert knowledge database for speech error correction, which greatly improves the recognition efficiency. Compared with similar mainstream English speech recognition systems, this system has certain advantages in recognition rate and recognition time. This design provides a reference for the development of English speech recognition technology.
Institutions, Robots, Algorithms and Law

Inclusive realities, where decision making in all spheres of life becomes more and more shared with algorithmic technologies or presence of robots, either in traditional or new social phenomena, requires reconceptualisation of design approaches and improvement of general understanding of the role and responsibility of the algorithm. Legal scholarship should be the appropriate perspective for building the definitions, and the current state of research in Law is polemic.
Realization of the Avatar Symbiotic Society: The Concept and Technologies

The author has long been engaged in the research and development of robots that act as human surrogates. Moreover, the author has addressed the issues of how to give robots a sense of presence, how to make them look and feel alive, how to enrich human–robot interactions, and how to design a society where humans and robots coexist. Recently, based on this research and development, the author has led a project to realize the “Avatar-Symbiotic Society,” in which one can easily manipulate multiple avatars as one wishes and participate in various social activities through them. This study introduces some of the technologies developed in this research and introduces the concept of an avatar-symbiotic society. After describing the outline of the project, this study discusses ethical issues concerning the research and development of avatars.
A Three-Mode Erasure Code for Continuous Variable Quantum Communications

Quantum states of light being transmitted via realistic free-space channels often suffer erasure errors due to several factors such as coupling inefficiencies between transmitter and receiver. In this work, an error correction code capable of protecting a single-mode quantum state against erasures is presented. Our three-mode code protects a single-mode Continuous Variable (CV) state via a bipartite CV entangled state. In realistic deployments, it can almost completely reverse a single erasure on the encoded state, and for two erasures can it improve the fidelities of received states relative to direct transmission. The bipartite entangled state used in the encoding can be Gaussian or non-Gaussian, with the latter further enhancing the performance of the code. Our new code is the simplest code known that protects a single mode against erasures and should prove useful in the construction of practical CV quantum networks that rely on free-space optics.
A New Approach for an End-to-end Communication System Using Variational Auto-encoder (VAE)

In this paper, a new approach has been proposed and investigated with the help of variational auto-encoder (VAE) as a probabilistic model to reconstruct the transmitted symbol without sending the data bits out of the transmitter. The novelty of the proposed End-to-end (E2E) wireless system is in representing the symbol as a image hot vector (IHV) that contains the features of the shape such as spikes, closed squared frame, pixels index location and pixels grey-scale colours. The previously mentioned features are inferred by latent random variables (LRVs). The LRVs are used for fronthaul and backhaul data representation. The LRVs parameters have only been transmitted through the physical wireless channel instead of the original bits as in the classical modulations or the hot vectors in the Auto-encoders (AE) E2E systems. The new proposed VAE architecture achieved the reconstruction of the symbol from the received LRV. The results show that the VAE with a simple classifier can provide a better symbol error rate (SER) than both AE baseline and classical Hamming code with hard decision decoding, especially at high <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$E_{b}/N_{o}$</tex> .
EU: Best Efforts Exception of ISP’s Liability for Unauthorised Sharing of Copyrighted Material

Article EU: Best Efforts Exception of ISP’s Liability for Unauthorised Sharing of Copyrighted Material was published on December 1, 2022 in the journal Computer Law Review International (volume 23, issue 6).
Search Redirection Attacks of Web-Server Use Case of Drug Perception

Search Redirection Attacks of Web-Server Use Case of Drug Perception
Research on Interactive English Grammar Learning System Based on Android Platform

In recent years, with more and more Chinese learning English, there are more and more English learning software, but most of the software are lack of good pronunciation evaluation and feedback correction. However, in English pronunciation learning, especially for non-native English learners, effective feedback motivation is very important. This has become a bottleneck restricting intelligent English learning software. According to the characteristics of Android mobile learning platform, this paper designs an interactive English grammar learning software based on Android platform, which is based on online learning algorithm and interactive system Combined with C-SVC and v-svc data analysis, this paper expounds the main algorithm ideas in the development process based on Android, which is used to improve and promote the learning of English grammar. Finally, the implementation of the interactive system proposed by the algorithm, the results show that the system search accurate, comprehensive content, conducive to English grammar learning, has strong practicability.
AN ANALYSIS OF THE PRODUCING MECHANISM OF HOMOPHONIC WITTICISM FROM THE PERSPECTIVE OF VERBAL COMMUNICATION：TAKING ROAST AND TALK SHOW CONGRESS AS AN EXAMPLE

With the make complaints about comedy show in the two stage of Tucao con-ference and talk show Congress, the frequent "homophonic witticism" has also been wide-ly watched and imitated by the public. As the dissemination of information,"homophonic witticism" is a kind of innovation in language form, which has a unique expression func-tion. In addition to the classification and analysis of "homophonic witticism" in form, its internal mechanism is also worth exploring. The "homophonic witticism" in talk show is more used by talk show actors to express their attitude towards post-modern social life with this special language form, which reflects the relationship between language and thinking. In addition, "homophonic witticism" is different from other network catchwords in that it teaches the public a new way of expression and thinking.
THE USE OF SMARTPHONES AS EXTRAMURAL ENGLISH LEARNING TO ENRICH EFL LEARNERS’ VOCABULARY

Smartphone has long been considered as a double-edged sword which has both positive and negative effects. Instead of banning the use of smartphones, a smart teacher has to be able to encourage EFL learners to use smartphones wisely to facilitate their learning. Smartphones enable the learners to use the language in a real situation outside the classroom, which is called Extramural English Learning. This kind of situation is believed to contribute to learners vocabularies. Learners’ ability to use various kinds of vocabulary, especially English academic words, will make a positive contribution to their writing. Employing a correlation design, the aim of the research was to investigate the correlation between the use of smartphones as extramural English learning and learners’ vocabularies focusing on English academic words. Questionnaire and writing test were used as instruments to collect the data from 35 undergraduate students of English department in East Java, Indonesia. The results of the data analysis by using Pearson Correlation confirmed the significant positive correlation between the use of smartphones as extramural English learning and learners’ vocabularies that indicated the benefit of extramural activities with smartphones on enriching learners’ vocabulary. Further, the pedagogical implication was also discussed.
발달장애 전공과의 평생교육기관으로의 재구조화를 위한 직업재활(재활상담) 분야의 평생교육 전문인력 자격 융합 요구 분석

The purpose of this study is to qualitatively analyze the needs for the convergence of qualifications of lifelong education professionals in the field of vocational rehabilitation (rehabilitation counseling), which is one of the measures to be considered in order to restructure the majoring courses for students with developmental disabilities as lifelong education institutions in an organizational level. FGI was used for the research method, targeting experts in the field of vocational rehabilitation (rehabilitation counseling). The study contents and results were presented in three main aspects. First, based on the consistency of the curriculum composed by the current majoring courses for developmental disabilities with the field of vocational rehabilitation (rehabilitation counseling), the consistency between the field of vocational rehabilitation (rehabilitation counseling) and the lifelong education curriculum for IDD, the study examined whether it is reasonable for the current majoring courses for developmental disabilities to be restructured as a lifelong education institution through convergence with the qualification of lifelong education professionals in the field of vocational rehabilitation (rehabilitation counseling). Second, the plan required to train lifelong education professionals in the field of vocational rehabilitation (rehabilitation counseling) was suggested for the restructure of majoring courses for developmental disabilities into lifelong education institutions. Third, the plan required for the placement of lifelong education professionals in the field of vocational rehabilitation (rehabilitation counseling) was suggested for the restructure of majoring courses for developmental disabilities into lifelong education institutions. As a result of the study, if the majoring courses for the current developmental disability are converged with the training and placement of lifelong education professionals in the field of vocational rehabilitation (rehabilitation counseling) in order to be restructured into lifelong education institutions, the linkage and advancement of the current majoring courses curriculum into lifelong education curriculum, the qualification of coordinator type professionals through counseling-based curriculum planning, the qualification of professionals centered on curriculum operation, and the realization of standards for training lifelong education professionals through cooperation between university and major courses possible could be analyzed. In addition, it was analyzed that the lifelong education professionals manpower exchange project through linkage between majoring courses-led regional institutions can be promoted.
Öğretim Görevlilerinin Öğrencilerin Dil Öğreniminde Google Çeviri Kullanımına İlişkin Algıları

Online machine translation has become one of the most commonly used applications among university students, and google translate (GT) is the most popular among them due to the availability of mobile devices with the internet. This mixed-method study investigated university prep school instructors' attitudes and perceptions of GT use regarding its effectiveness, ethicality, frequency, and students' purposes of using it. An online questionnaire was administered to 46 instructors, and semi-structured interview sessions were held with 11 instructors. Results indicated that nearly all of the participant instructors' students frequently use GT. Another important finding was that many students use GT in reading and writing classes. Results also revealed that students tend to use GT far more beyond a dictionary function, and this overuse dramatically decreases instructors' perception of the effectiveness and ethicality of GT. Although instructors are worried about its usage for longer segments and adverse effects on student learning, they do not prefer banning or limiting its usage in language classes due to its simplicity and practicality. Therefore, there is a need to have a working policy to avoid the harmful effects of GT and use them effectively in language classes.
DSGRAE: Deep Sparse Graph Regularized Autoencoder for Anomaly Detection

Anomaly detection aims to distinguish significant deviation data from an observed dataset, which has wide applications in various fields. Autoencoder (AE) is an effective approach, which maps the original data into latent feature space, and then identifies the anomalies with higher reconstruction errors. However, the performance of autoencoder-based approach heavily relies on feature representations in the latent space, which requires the feature representations be captured as much essential as possible. Therefore, a graph regularization constraint term is first introduced into Deep Autoencoder (DAE) to explore the geometric structure information. Moreover, to avoid the problem of overfitting and enhance the ability of feature representations, a constraint term is imposed and then a Deep Sparse Graph Regularized Autoencoder (DSGRAE) approach is proposed. Finally, we carry out extensive experiments on 14 widely used datasets and compare them with other state-of-the-art methods, which demonstrate the effectiveness of the proposed method.
An Empirical Study Towards SAR Adversarial Examples

Adversarial attack and adversarial detection have become a hot issue in the field of deep learning based image forensics. However, current researches mainly focus on optical images. Synthetic aperture radar (SAR) images are quite different from the optical images in both imaging mechanism and data structure. This paper aims to study adversarial attack and adversarial detection for SAR images. Firstly, we analyze the distribution characteristics of SAR adversarial examples (AEs) in both output space and feature space by transferring optical attacks. In order to match the digital perturbation with the scattering energy of target, we then propose a generation method of SAR AEs with regional constraint. Experiments show that the proposed method generates SAR AEs that can evade current adversarial detection at the cost of attack success rate. Finally, we point out an open issue that decreasing the perturbation scale leads to the degradation of adversarial detection against both optical AEs and SAR AEs.
A new hearth? Defining social units during the Covid-19 pandemic

Slogans like ‘stay safe, stay apart’ stare at us at train stations, shopping malls, community centres and the like. The link between safety and separation has become a theme over the course of the Covid-19 pandemic. The social units to be separated are the household and the bubble, the former an established social unit, the latter a pandemic creation. During the pandemic, strict rules govern (i) household mixing, including variously the rule of 1 other person, the rule of 6 and the rule of one other household, (ii) shielding, which is a prohibition on mixing, and (iii) bubbles, including childcare, care and support bubbles. These rules were perceived in various ways by the population subjected to them, with one prominent theme being the restriction of personal freedom (Duffy 2020). Three research questions emerge from this situation: (i) (How) does the household as a social unit fit into modern-day society?(ii) What is the process of defining successfully a basic social unit?(iii) (How) can one persuade people to trade their liberty for safety?