Reviewerly/exHarmony huggingface dataset:
A demonstration of contextuality using quantum computers

Abstract Open-access, online quantum computers have shown significant improvements in the past decade. Although they still suffer from noise and scalability limitations, they do offer the possibility of experimenting with quantum circuits which would otherwise have required laboratory resources and prowesses beyond the reach of most students (and even researchers). In view of this, we revisit from the ground up the notion of contextuality and show that it can now be easily demonstrated on one of the IBM quantum computers. We showcase this with an implementation of the Peres–Mermin square which, despite the high error rates, manages to violate noncontextuality by almost 28 standard deviations.
Learning Effect of Lay People in Gesture-Based Locomotion in Virtual Reality

Locomotion in Virtual Reality (VR) is an important part of VR applications. Many scientists are enriching the community with different variations that enable locomotion in VR. Some of the most promising methods are gesture-based and do not require additional handheld hardware. Recent work focused mostly on user preference and performance of the different locomotion techniques. This ignores the learning effect that users go through while new methods are being explored. In this work, it is investigated whether and how quickly users can adapt to a hand gesture-based locomotion system in VR. Four different locomotion techniques are implemented and tested by participants. The goal of this paper is twofold: First, it aims to encourage researchers to consider the learning effect in their studies. Second, this study aims to provide insight into the learning effect of users in gesture-based systems.
Automatic Prosody Annotation with Pre-Trained Text-Speech Model

Prosodic boundary plays an important role in text-to-speech synthesis (TTS) in terms of naturalness and readability. However, the acquisition of prosodic boundary labels relies on manual annotation, which is costly and time-consuming. In this paper, we propose to automatically extract prosodic boundary labels from text-audio data via a neural text-speech model with pre-trained audio encoders. This model is pre-trained on text and speech data separately and jointly fine-tuned on TTS data in a triplet format: {speech, text, prosody}. The experimental results on both automatic evaluation and human evaluation demonstrate that: 1) the proposed text-speech prosody annotation framework significantly outperforms text-only baselines; 2) the quality of automatic prosodic boundary annotations is comparable to human annotations; 3) TTS systems trained with model-annotated boundaries are slightly better than systems that use manual ones.
THE EFFECTIVENESS OF USING COMIC STRIPS TOWARD WRITING ABILITY IN MAKING DESCRIPTIVE TEXT

The aim of this research is to find out the effectiveness of using comic strip toward writing ability in making descriptive text. The research belongs to experimental research. The population of this research is the eighth grade of SMPN 7 Ambon consisting 210 students. The researchers took 60 students as the samples and the samples were divided into control group (VIII 3) consists of 30 students and experimental group (VIII 2) consists of 30 students. The researchers conducted testing to get the data (pre-test and post-test) in control group and experimental group. The researchers used descriptive and inferential analysis to analyze the data. The descriptive analysis shows that the result of experimental group shows that in pre-test, the mean is 37.20, the standard deviation is 22.69, and the highest category belongs to very poor category with 53.3% (16 students). While in the post-test the mean is 60.60, the standard deviation is 27.47, and the highest category belongs to very good category with 30.0% (9 students). Meanwhile, the result of control group shows that in pre-test, the mean is 43.26, the standard deviation is 28.20, and the highest category belongs to very poor category with 40.0% (12 students). While in the post-test, the mean is 48.16, the standard deviation is 19.12, and the highest category belongs to fair category with 50.0% (15 students). It means the hypothesis is accepted. There is a significance difference between the students taught using comic strip in making descriptive and those taught without using comic strip in making descriptive text in the eighth grade of SMPN 7 Ambon.
THE IMPLEMENTATION OF PICTURE SERIES IN TEACHING NARRATIVE READING TEXT

This research aimed at finding out the implementation of picture series in teaching narrative reading text to the eight grade students of MTs al-Khairaat Uemalingku Ampana. This research was qualitative research, the subjects of this research were teachers and students. The data collection methods employed in this study were observation, interviews, and documentation. The data sources used in this study were primary data and secondary data. Data analysis techniques used were data reduction, data presentation, and data verification. The result of this research showed that the implementation of Picture Series in Teaching Narrative Reading Text to the Eight grade Students of MTs al-Khairaat Uemalingku Ampana consists of the following steps: firstly, the teacher trained the students to think and directed them to find answer to problems by playing drawing games. Secondly, the teacher explained the material deeply, such as the step to write narrative text. Thirdly, the teacher distributed some random pictures to the students to short the pictures into a logical sequence and to find out the difference in the learning outcomes that had been achieved by students in learning narrative text. The learning evaluation was carried out at the end of the lesson.
Food Nutrition and Healthy diet During Covid-19 Using AI/ ML

Abstract: The COVID-19 outbreak has negatively affected the day-to-day life of people. Food nutrition and a healthy diet are even more essential since a well-balanced diet rich in nutrients supports a healthy immune system. In our approach, we take the symptoms of covid-19 and classify them using a DNN classifier, resulting in the conclusion that dietary nutrition and a balanced diet are important during covid-19. Following the categorization, a Decision Tree is utilized to decide on the patient’s replies and provide the decision and answers. A Decision Tree is simple to learn since it can think like a human while making a decision. Keywords: DNN Classifier, Decision Tree, Food Nutrition and Diet.
Vehicle Detection from Aerial Images with Object and Motion Detection

Moving vehicle detection is one of important issues in surveillance and traffic monitoring applications for aerial images. In this study, a vehicle detection method is proposed by combining motion and object detection. A method based on background modeling and subtraction is applied for motion detection, while Faster-RCNN architecture is used for object detection. Motion detection result is enhanced with the proposed superpixel based refinement method. Experimental study shows that performance of motion detection increases about 8\% for $F_1$ metric with the proposed post processing method. Object detection, motion detection and superpixel segmentation methods interact with each other in parallel processes with the proposed software architecture, which significantly increases the working speed of the method. In last step of the proposed method, each vehicle is tracked with the kalman filter. The performance of proposed method is evaluated on the VIVID dataset. The performance evaluation shows that proposed method increases $F_1$ and recall values significantly compared to the motion and object detection methods alone. It also outperforms SCBU and MCD methods which are widely used for performance comparison in motion detection studies in the literature
Cluster Analysis for Grouping Districts in Sidoarjo Regency Based on Education Indicators

The purpose of education is to develop self-ability, knowledge, skills, and habits that are passed down from one generation to the next and from educators to students through a teaching process to shape a personality physically and spiritually. It also serves as a benchmark of success for a region. Education indicators can be used as a measuring tool to analyze the quality of education in an area. The current study aimed to determine the level of education in the districts of the Sidoarjo Regency, Indonesia. In this study, the sub-districts of the Sidoarjo Regency were grouped based on the education indicators using cluster analysis. Cluster analysis is a multivariate analysis that groups objects into different categories. Based on the results, two clusters were formed. Of the 18 districts in Sidoarjo Regency, the first cluster comprised of 14 districts (Prambon, Tulangan, Krembung, Tarik, Wonoayu, Gedangan, Porong, Buduran, Candi, Sukodono, Tanggulangin, Sedati, Jabon, Balongbendo), while the second included 4 (Sidoarjo, Waru, Taman, Krian). The results showed higher education indicators in the second cluster. Therefore, the researchers recommend using the results of this study as a reference for developing an equal distribution of education in the Sidoarjo Regency.&#x0D; Keywords: education indicators, cluster analysis, Sidoarjo districts
Analyzing the Teaching Strategies for Physical Education in Middle Schools Under the Background of the New Curriculum

In recent years, with the reform of the educational system and the introduction of new curriculum standards, the teaching quality of physical education in middle schools has greatly improved. The education industry in China is now in a phase of high-quality development. In order to further enhance the effect of middle school physical education, it is necessary to strengthen the discussion on teaching strategies. Taking this as the starting point, this paper summarizes the importance of middle school physical education under the background of the new curriculum, analyzes the current teaching situation, and on this basis, proposes several strategies to enhance the teaching effect from three aspects: core literacy, student subject, and information technology.
MOTIVASI BELAJAR SELAMA MASA PANDEMI COVID-19 PADA SISWA KELAS V SDN 03 KETAPANG RAYA KECAMATAN KERUAK TAHUN PELAJARAN 2020/2021

The purpose of this study was to determine the motivation to learn during the Covid-19 pandemic in fifth grade students at SDN 03 Ketapang Raya, Keruak District, for the 2020/2021 academic year. The results of this study are that the learning motivation of grade V students at SDN 03 Ketapang Raya, Keruak District, East Lombok Regency during the covid-19 pandemic is classified as good, indicated by: 1) Students have shown an attitude of desire and desire to succeed in learning even during the covid-19 pandemic. 19; 2) Students have shown an attitude of encouragement and need in learning; 3) Students have shown an attitude of hope and ideals in the future; 4) Students have shown an attitude of appreciation in learning; 5) Students have shown an attitude of interesting activities in learning during the covid-19 pandemic; 6) Students demonstrate a conducive learning environment during the covid-19 pandemic&#x0D; Keywords: Student Learning Motivation, Covid-19 Pandemic Period
Adversarial Scrutiny of Evidentiary Statistical Software

The U.S. criminal legal system increasingly relies on software output to convict and incarcerate people. In a large number of cases each year, the government makes these consequential decisions based on evidence from statistical software—such as probabilistic genotyping, environmental audio detection and toolmark analysis tools—that the defense counsel cannot fully cross-examine or scrutinize. This undermines the commitments of the adversarial criminal legal system, which relies on the defense’s ability to probe and test the prosecution’s case to safeguard individual rights.
LONG-TERM IMPACTS OF SARS-COV-2 ON HEALTH-RELATED QUALITY OF LIFE AND SYMPTOMS OF ANXIETY AND DEPRESSION ON PATIENTS REQUIRING HOSPITALIZATION IN NORTHEASTERN BRAZIL

TYPE: Abstract TOPIC: Signs and Symptoms of Chest Diseases PURPOSE: To assess the possible long-term impairments in health-related quality of life (HRQoL) and symptoms of anxiety and depression in patients after discharge from hospital in a city in northeastern Brazil. METHODS: This is a cross-sectional study involving adults of both genders with a diagnosis of COVID-19 confirmed by RT-PCR who were discharged from the hospital. All subjects underwent interviews and completed surveys to assess their and the presence of symptoms of anxiety and depression represented respectively by 36-item Short-Form Health Survey (SF-36) and HADS (Hospital anxiety and depression scale). RESULTS: Characteristics: 31 patients included, 58% female, 52±10 years. BMI 30.7 ± 6.3 kg/m2 , length of hospital stay with median 17 days (IQ 10-40). There was a difference statistically significant for all domains of SF-36 (p <0,001). Worst scores were in role physical (mean difference: 67; CI:95% 46.6-87.4), role emotional (mean difference: 52; CI:95%; 34.3-69) and physical functioning (mean difference: 51; CI: 95%; 30.3-56.5) domains (table 1). 70% of the subjects reported symptoms of anxiety and depression defined as HADS > 8. 50% of these were moderate or severe. CONCLUSIONS: Three months after hospital discharge following recovery from COVID-19-associated pneumonia quality of life impairments and the presence of symptoms of anxiety and depression are still highly prevalent in this population. CLINICAL IMPLICATIONS: The persistence of symptoms after hospital discharge implies the need for follow-up and multidisciplinary care to return to health conditions prior the disease. This work has been supported by the research agencies: UFPE, CAPES, CNPq (403341/2020-5) and FACEPE (APQ-0249-4.08/20). DISCLOSURE: Nothing to declare. KEYWORD: COVID-19
Student Affairs Management System

Abstract: Main aim in developing Student Affairs Management System is to provide an easy way not only to automate all functionalities of college, but also to provide full functional reports to top management of college with the finest of details about any aspect of the college. The platform is built by multiple modules, each module has a certain independence. Student Affairs Management System is a software for keeping their information secure and make their management easier. We can write a message in this platform. Admin can send Message to the recipient who is the parents or guardian of the student .This platform contains Library management in which details of the books, books issued and books returned are taken into account
Internet Plus University and College Foreign Language Teaching Reform

The “Internet Plus” on-line plateforms provide many innovative approach to learning; but providing convenient college education on-line also poses many new challenges that have not been explored. Some of these educational challenges are explored in the development of an innovative foreign language teaching program in China Universities. Foreign language education networks can be designed on “Internet Plus” platforms to enhance teachers' teaching capabilities. Using "Internet Plus" plateforms is key to foreign language teaching reform in colleges and universities.
A Modal Criterion for Epistemic Argumentation

In this paper, I spell out and argue for a new epistemic theory of argumentation. Contrary to extant views, this theory is compatible with a pluralistic framework on argumentation, where the norms governing argumentation depend on the aim with which we engage in the practice. A domain of specifically epistemic argumentation is singled out, and I argue based on recent findings in modal epistemology that this domain is governed by the modal norm of safety; where a belief is safe just in case it is produced by a method that would not easily produce a false belief. While this criterion is well-known and uncontroversial in epistemology, it has hitherto not been applied to epistemic theories of argumentation. I show that the norm allows for a novel and superior perspective of the relevance of the persistent interlocutor in argumentation theory, and on the relation between dialectical and epistemic norms more generally.
Real-Time Trajectory Planning and Control for Constrained UAV Based on Differential Flatness

The trajectory planning of UAV with nonholonomic constraints is usually taken as differential algebraic equation to solve the optimal control problem of functional extremum under the condition of inequality constraints. However, it can be challenging to meet the requirements of real-time for the high complexity. A differential flat theory based on B-spline trajectory planning can replace the optimal control problem with nonlinear programming and be a good means to achieve the efficient trajectory planning of an UAV under multiple dynamic constraints. This research verifies the feasibility of this theory with actual flight experiments.
DADDE:deep anomaly detection with density estimation

Abstract The problem of abnormal nodes detection in attributed network is widely used in daily life, such as social networks, cyberspace security, financial fields and so on. Most existing detection methods ignore the relationship between structure information and attribute information in attributed network. Although some methods consider the relationship between them, but it can’t distinguish the types of abnormal nodes well, that is, attribute exceptions or structural exceptions. Aiming at the shortcomings of existing methods, this paper proposes a deep anomaly detection model combining density estimation. The idea of detecting abnormal nodes by reconstruction error is used, the structure information and attribute information of attributed network are reconstructed respectively, and abnormal nodes are detected by density estimation based on reconstruction error and embedding vector of nodes. In this paper, the validity of DADDE model is proved by experiments on three commonly used data sets in this field.
A Spatial Fuzzy Co-Location Pattern Mining Method Based on Interval Type-2 Fuzzy Sets

The goal of spatial co-location pattern mining is to find subsets of spatial features whose instances are often neighbors in a geographical space. In many practical cases, instances of spatial features contain not only spatial location information but also attribute information. Although there have been several studies that use type-1 fuzzy membership functions to mine spatial fuzzy co-location patterns, there is great uncertainty associated with such membership functions. To address this problem, we propose a spatial fuzzy co-location pattern mining method based on interval type-2 fuzzy sets. First, we collect the interval evaluation values of the interval data of attribute information from experts to form granular data. Next, the original type-1 fuzzy membership function is extended to a granular type-2 fuzzy membership function based on elliptic curves. We use a gradual method to adjust the parameters of the fuzzy membership function so that its footprint of uncertainty satisfies both the connectivity and the given confidence. Based on this granular type-2 fuzzy membership function, we fuzzify the attribute information of instances and define the concepts of fuzzy features and fuzzy co-location patterns. A fuzzy co-location pattern mining algorithm based on spatial cliques is then proposed, termed the FCPM-Clique algorithm. In order to improve the efficiency of the algorithm, we propose two pruning strategies. In addition, we extend two classical spatial pattern mining algorithms, the Join-based algorithm and the Joinless algorithm, to mine fuzzy co-location patterns based on interval type-2 fuzzy sets. Many experiments on synthetic and real-world datasets are conducted, the performance of the three algorithms is compared, and the effectiveness and efficiency of our proposed FCPM-Clique algorithm is demonstrated.
When learning becomes impossible

We formally analyze an epistemic bias we call interpretive blindness (IB), in which under certain conditions a learner will be incapable of learning. IB is now common in our society, but it is a natural consequence of Bayesian inference and what we argue are mild assumptions about the relation between belief and evidence. IB a special problem for learning from testimony, in which one acquires information only from text or conversation. We show that IB follows from a codependence between background beliefs and interpretation in a Bayesian setting and the nature of contemporary testimony. We argue that a particular characteristic of contemporary testimony, argumentative completeness, can preclude learning in hierarchical Bayesian settings, even in the presence of constraints that are designed to promote good epistemic practices.
Violence in Cyberspace and Possible Prevention

This paper describes some of the forms of violence in cyberspace and possible prevention. The second part of this paper provides an analysis of students’ views on possible online abuse and prevention. The research aims to highlight statistically significant opportunities for raising awareness of possible online abuse and the prevention of cyberbullying. The survey consists of a total of 20 testimonials, which are divided into 4 parts, and each part assesses different aspects. The conclusion of this research is that the Internet environment does not provide enough feedback on the reactions of the person to whom the harassing messages were sent, which in the abuser reduces the feeling of causing true emotional and psychological harm to another person, reducing the degree of self-control and insight into the level of bullying.
CITRA VISUAL FOTOGRAFI POTRET PADA KEMASAN HERBANA

Visualization of packaging is one of the main attractions in persuading consumers of the product. In addition to conveying the message can also lead to a sense of emotional attachment. The portrait photography displayed can represent the superiority of the product as a visual narrative. Balance Madia Menstrual Comfort has natural ingredients that are processed in a modern way to make herbal products PT. Deltomed Laboratories is a solution for menstrual relieving drugs. In this study, the field of visual communication design becomes the main step in the analysis process that leads to a discussion about understanding the correlation between signs in portrait photography contained in Herbana packaging. This study can explain in detail the influence of portrait photography in creating value and function. This study uses a qualitative method with Barthes' semiotic approach. So it can be found the results of this study that portrait photography as a medium that is able to persuade consumers to the product
Teacher's Strategy In Improving Reading And Writing Skills Of Second-Grade Students At SDN 100020 Simardoa Padang Lawas Utara Regency

&lt;p&gt;&lt;em&gt;This research aims at describing the teacher's strategy for improving second-grade students' reading and writing skills at SD Negeri 100020 Simardona, Padang Lawas Utara Regency. It is descriptive qualitative research, with data collected through interviews, observations, and documentation. The followings are the findings of this research; a). the teacher's strategy to improve the second graders' reading and writing skills at SD Negeri Simardona is to read alternately at the beginning of the lesson, read together (joint reading), read in front of the class, read word for word in sequence, and read their own and their classmates' writings in notebooks and on the blackboard, b). strategies for improving writing skills are by copying writing into a notebook, writing on the blackboard, writing dictation, copying writing from textbooks, and giving writing assignments at home.&lt;/em&gt;&lt;/p&gt;