Reviewerly/exHarmony huggingface dataset:
THE USE OF PERSONAL-RESPONSE APPROACH (PRA) IN POETRY ANALYSIS AMONG JUNIOR HIGH SCHOOL STUDENTS

This study aimed to examine the personal response approach in the context of poetry analysis and sought to identify the phases the responses of the students fall and the possible influencing factors in their responses.Thirty-five (35) grade 10 students of Mary Help of Christians College took part in this study.The qualitative research design was used for this study.The data were gathered by conducting three synchronous sessions of poetry lessons applying the personal response approach.The sessions were recorded, and the students' responses to poetry analysis, both verbal and written, were transcribed as primary data.The researcher applied the personal response approach in discussing the following poems: "I remember, I remember" by Thomas Hood; "The Road Not Taken by Robert Frost", and "Sonnet 116" by William Shakespeare, and obtained the responses of the students to the analysis questions during the poetry lessons.The responses were qualitatively analyzed using the phases of the developmental model by Thomson (1987) presented in Spirovska (2019).The responses were categorized in the phases reached: literal, empathy, analogy, reflection, evaluation, and recognition.One hundred forty-six responses were gathered from the analysis of three poetries used.The data revealed that students were able to provide responses the analysis question of the text until the sixth phase of the developmental model of the personal response approach.using PRA creates an opportunity for the student to further understand the text by connecting their experiences, emotions, reflections, realization, and role in the reading process.With this, students improve their literary skills and reading comprehension for they understand better the given poetry.PRA in this regard, improves the pedagogy of poetry teaching by letting the students have a more personal connection to the text to understand the essence of literature, as well as to improve understanding of others.In addition, influencing factors were identified namely linguistic knowledge, emotion and subject matter, experience, reflective ability, values and beliefs, and role awareness.These factors can be considered in order to assist students to have deeper understanding of the text.The study recommends that the conclusions generative be investigated.To improve poetry analysis using the approach teachers are encouraged to use prompt responses that would guide students to a clearer understanding of the text.They may also consider the influencing factors identified in the current study in selecting appropriate literature for the students.For future researchers that would dwell in a similar study, it is recommended to gather both qualitative and quantitative data to compare and statistically validate the students' understanding of poetry analysis.As well as to conduct the study measuring the students' perception, attitudes, and metric scores in the implementation of the personal response approach to poetry analysis.
Education Behind Bars: Problems and Strategies for Teaching English to Protégés of Central Lombok Juvenile Detention Center

This research investigates the encountered problems and strategies for teaching English to an inclusive classroom contains of law-conflicted students. This research is based on an educational ethnography study conducted in Tojong-Ojong in Central Lombok District, Indonesia. This research highlights on the issues regarding the problems faced and strategies applied by the English teacher, challenging teachers’ capability to assist the troubled students on the subject, their utilization of teaching approach with limited learning resources while adjusting the needs’ of these students, and managing the impact of internal and external on students’ engagement and disengagement in the learning process. This penitentiary applies to equivalency program of A,B,C packages. However, this study focuses on protégés with C-Package equivalency, involving 12 students in total. There is only 1 certified English teacher assisted with a tutor without significant teaching qualification. Qualitative method was applied in this study by combining teacher interview, students’ questionnaire, observation with video and audio recording, and field notes. The results of the collected data shows several problems occurred during the teaching and learning process and what strategies used by teacher to overcome them. The problems and strategies were categorized into three parts. The problems were concerning (1) teacher-related, (2) student-related and (3) teaching related problems, while the strategies including (1) course materials, (2) teaching approach, and (3) teacher strategies.
On the Training Mechanism of College Students' Learning Ability at Going Down to the Grass-roots Unit Based on the Investigation

College graduates are the country's valuable human resources. The Party Central Committee and the State Council attach great importance to the employment of college graduates, regard the grassroots as an important platform for college graduates to grow into talents, and put forward clear requirements for guiding and encouraging college graduates to work at the grassroots level. By understanding the current situation of college students going to the grass-roots level, and through the investigation and analysis of the college students' going to the grass-roots level, this paper points out that there are environmental conditions, lack of subject knowledge system, lack of education guidance, lack of communication platform for grass-roots staff, lack of experience, etc. difficulty. Finally, this paper puts forward corresponding policy recommendations in a targeted manner.
Analisis SWOT pada Pelaksanaan Kegiatan Pemilihan Pustakawan Berprestasi Terbaik Tingkat Nasional di Masa Pandemi COVID-19

Selection of the Best Outstanding Librarian at the National Level is one way to appreciate librarians who are highly dedicated to their duties. This event is carried out by the National Library of Indonesia through the Center for Librarian Development in a systematic and tiered manner, starting from the election at the provincial level to the national level. The COVID-19 pandemic brought a different color to the Selection of National Best Outstanding Librarian year 2020, which was held online for the first time. Through this study, it provides an overview of the differences in the offline and online selection process for Outstanding Librarians, as well as a SWOT strategy analysis for each mechanism. The studywas conducted with a descriptive qualitative approach. Data collection is done by document review and observation, analysis is done by SWOT analysis. The results obtained the portrait of the change in the mechanism for the Selection ofOutstanding Librarians, where the online selection process is fully carried out via the virtual meeting application and eliminating of visit activities. Meanwhile, in the SWOT analysis, the results obtained are the ST strategy on the offline mechanism and the WO strategy on the online mechanism.
Psychology and Cybernetics

Cyberpsychology is an emerged field in Social Sciences concerned with control and communication of humans and machines focusing on Psychology and Communication Studies. In its generalized form operates as a thematic “umbrella” for all branches of Psychology and Communication employing different methodologies, methods and techniques related to interactive, cognitive and behavioral phenomena that are observed on the internet and social media. As a special science, in the form of Cybernetic Psychology, is focusing on the mechanisms of cognitive control of perception, information and behavior. It targets the programmable simulation of these phenomena; their algorithmic representation and the feedback learning processes that allow adaptation in cyberspace. Issues as integration of everyday life in digital context, management in governance, problem-solving in human-machine interaction, consulting and therapy assistance to practitioners, establish Cyberpsychology and Cybernetic Psychology as areas that contribute and furthering the scientific knowledge of successful or failed human evolutionary processes and strategies. Homo Virtualis as cybernetic organism seeks to maintain and strengthen control over itself, the others and machines, in digital environments, through cognitive, behavioral and affective processes. The paper attempts an introduction to questions regarding the dimensions of the ontological basis of Cybernetic Psychology as foundation of general Cyberpsychology. The special issue “Initiation to Cyber-Psychology: A Students’ Research Anthology” is dedicated to the work of undergraduate students of the Psychology Department of Panteion University of Social and Political Sciences. Students’ papers were prepared within the “Cyberpsychology” course, taught, for the first time as a compulsory, during the spring semester of the academic year 2020-2021.
Collision Warning System Using Naïve Bayes Classifier

Motor vehicle crashes can lead to traumatic experiences. High-impact collisions usually cause severe injuries or fatalities. A collision warning system that analyzes driving behaviors and warns drivers of impending crashes can prevent road collisions and save lives, so increasing traffic safety. An application of the Naïve Bayes classifier model to determine the potential for rear-end collisions between highway vehicles is presented. The Naïve Bayes classifier is a supervised machine-learning model based on Bayes’s theorem. Two vehicles are utilized, with one vehicle following the other. The parameters studied are speed, distance, acceleration, and deceleration. Training examples involving over 100 potential collision scenarios have been evaluated. Simulation results show that the model successfully responds to and correctly predicts potential collisions.
End-to-End Security for Distributed Event-Driven Enclave Applications on Heterogeneous TEEs

This paper presents an approach to provide strong assurance of the secure execution of distributed event-driven applications on shared infrastructures, while relying on a small Trusted Computing Base. We build upon and extend security primitives provided by Trusted Execution Environments (TEEs) to guarantee authenticity and integrity properties of applications, and to secure control of input and output devices. More specifically, we guarantee that if an output is produced by the application, it was allowed to be produced by the application's source code based on an authentic trace of inputs. We present an integrated open-source framework to develop, deploy, and use such applications across heterogeneous TEEs. Beyond authenticity and integrity, our framework optionally provides confidentiality and a notion of availability, and facilitates software development at a high level of abstraction over the platform-specific TEE layer. We support event-driven programming to develop distributed enclave applications in Rust and C for heterogeneous TEE, including Intel SGX, ARM TrustZone and Sancus. In this article we discuss the workings of our approach, the extensions we made to the Sancus processor, and the integration of our development model with commercial TEEs. Our evaluation of security and performance aspects show that TEEs, together with our programming model, form a basis for powerful security architectures for dependable systems in domains such as Industrial Control Systems and the Internet of Things, illustrating our framework's unique suitability for a broad range of use cases which combine cloud processing, mobile and edge devices, and lightweight sensing and actuation.
Privacy-Preserving Cross-Zone Ride-Matching for Online Ride-Hailing Service

Although online ride-hailing supplies the nearest taxi matching for riders, the potential leakage of riders’ hobbies and physical condition raises privacy concerns. Since most of the privacy-preserving schemes do limited matching of riders and drivers in the same zone, in this paper, we propose a novel privacy-preserving cross-zone ride-matching scheme, namely, Cride, which extends one zone into multiple neighboring zones. Based on the zone division of a city, CRide allows distance computation between rider and driver across adjacent zones in the encrypted domain. Furthermore, towards efficiency improvement, a ciphertext packing technique is introduced. Theoretical analysis and experimental results suggest that CRide achieves a high ride-matching accuracy and acceptable efficiency without leaking privacy.
Classification Algorithm for Link Prediction Based on Generated Features of Local Similarity-Based Method

A social network is a social structure that consists consisting of nodes, edges, or links and describes activity on a social media platform. Later, link prediction is a technique to predict new relationships for future networks based on information explored from the current network topology. Several local similarity-based methods use topological information to predict the link. However, these methods have different performances and depend on the network topology. This study proposes using classification algorithms of machine learning to predict future links. The classification algorithms compared are k-Nearest Neighbors (KNN), Naive Bayes, Decision Tree, and Random Forest by comparing six social network datasets with features generated from local similarity-based methods. This research was conducted in three stages: preprocessing, classification comparison, and performance evaluation. The findings of this study are that the Random Forest algorithm outperforms for testing accuracy, precision, and F1-Score. However, in the recall test results, Random Forest only outperformed other benchmark algorithms in the four datasets: soc-karate, soc-dolphin, soc-highschool M, and Soc-sparrowlyon-flock-season 03. Meanwhile, in the datasets soc-tribes and soc-aves-weaver-social-05, the Decision Tree algorithm outperformed other benchmark algorithms.
Perbandingan Haversine Formula dan Euclidean Distance dalam Pencarian Jarak Terdekat Rumah Penampungan Hewan (Shelter)

Animal cages (shelters) and animal hospitals still receive less attention from some people, and also lack of information and education about the number of animals (shelters) and animal hospitals, animal shelters have a noble mission for abandoned or abandoned animals by their owners. as well as hospitals where people can bring their pets for treatment while keeping their pets so that we as owners know what our animals are suffering from at that time and also to avoid diseases that can harm us as owners. Geographic Information System (GIS) has the ability to present information in graphic form using a map as an interface, so that it can be used as a presentation of information related to animal shelters. where the public can obtain data and information about animal shelters for personal and organizational or agency needs. The development researcher uses the haversine algorithm to be used as a search for the closest distance between the user and the location of the animal's house, as well as the Euclidian distance as a comparison to find the appropriate distance accuracy. From the results of these calculation it can be concluded that haversine and google maps this method has an accuracy level that is almost close to accurate with a percentage value of 99.88% with manual calculationsKeywords: website, haversine, euclidian, animal shelter
Rancang Bangun Sistem Informasi Portal Berita Berbasis Web pada Dinas Pemuda dan Olahraga Kabupaten Cirebon

The Cirebon Regency Youth and Sports Office (Dispora Cirebon) is a regional work unit that is given the mandate and duties and responsibilities in handling development in the Youth and Sports Sector in the Cirebon Regency environment. In this day and age, a touch of Information System technology such as a website must have become a necessity for government agencies, as a support for more centralized, accurate, and fast information. However, there was no website-based information system at the Cirebon Dispora as a medium for disseminating information at that time. The writer uses primary data sources (Observation and Interview) and secondary data sources (Documentation Study). For system design, the author uses the SDLC (System Development Life Cycle) method. The final result obtained is a website-based Information System, which can provide information about profiles, activities or articles about Dispora Cirebon to the wider community. With several advantages of website technology, the Website-Based News Portal Information System is expected to expand the reach of information dissemination to all aspects of society.
Leveraging Heterogeneous Capabilities in Multi-Agent Systems for Environmental Conflict Resolution

In this paper, we introduce a high-level controller synthesis framework that enables teams of heterogeneous agents to assist each other in resolving environmental conflicts that appear at runtime. This conflict resolution method is built upon temporal-logic-based reactive synthesis to guarantee safety and task completion under specific environment assumptions. In heterogeneous multi-agent systems, every agent is expected to complete its own tasks in service of a global team objective. However, at runtime, an agent may encounter un-modeled obstacles (e.g., doors or walls) that prevent it from achieving its own task. To address this problem, we employ the capabilities of other heterogeneous agents to resolve the obstacle. A controller framework is proposed to redirect agents with the capability of resolving the appropriate obstacles to the required target when such a situation is detected. Three case studies involving a bipedal robot Digit and a quadcopter are used to evaluate the controller performance in action. Additionally, we implement the proposed framework on a physical multi-agent robotic system to demonstrate its viability for real world applications.
Sistem Pakar Delirium Pasien COVID-19 Pada Lansia Menggunakan Metode Certainty Factor dan Forward Chaining

In this study, it is related to an expert system for detecting delirium in COVID-19 patients which has never been done in Indonesia in previous studies, related to the method used by researchers to compare 2 hybrid methods, namely the Certanty Factor method with the Forward Chaining method compared to the Bayes method and Forward Chaining . From the results of the comparison, a higher confidence value is obtained, namely the certainty factor and forward chaining as a method in making an expert system application for detecting delirium in elderly COVOD-19 patients. From the results of the application test, which is compared with the calculation results, it is known that from the 20 patient samples, 70% of the samples stated Possibility and 30% stated Most Likely from the diagnosed disease. The certainty factor technique is applied to calculate the certainty value of a fact or rule and the forward chain method is used to draw conclusions that will help diagnose a disease.
APPReddit: a Corpus of Reddit Posts Annotated for Appraisal

Despite the large number of computational resources for emotion recognition, there is a lack of data sets relying on appraisal models. According to Appraisal theories, emotions are the outcome of a multi-dimensional evaluation of events. In this paper, we present APPReddit, the first corpus of non-experimental data annotated according to this theory. After describing its development, we compare our resource with enISEAR, a corpus of events created in an experimental setting and annotated for appraisal. Results show that the two corpora can be mapped notwithstanding different typologies of data and annotations schemes. A SVM model trained on APPReddit predicts four appraisal dimensions without significant loss. Merging both corpora in a single training set increases the prediction of 3 out of 4 dimensions. Such findings pave the way to a better performing classification model for appraisal prediction.
EVALUATION OF SELF-SUPERVISED LEARNING APPROACHES FOR SEMANTIC SEGMENTATION OF INDUSTRIAL BURNER FLAMES

Abstract. In recent years, self-supervised learning has made tremendous progress in closing the gap to supervised learning due to the rapid development of more sophisticated approaches like SimCLR, MoCo, and SwAV. However, these achievements are primarily evaluated on common benchmark datasets. In this paper, we focus on evaluating self-supervised learning for semantic segmentation of industrial burner flames. Our goal is to build an intuition on how self-supervision performs in a scenario relevant for industrial application where training labels and the opportunities for hyperparameter tuning are limited. We demonstrate that self-supervised pre-training can constitute an alternative to the state-of-the-art approach of pre-training on ImageNet. Across all scenarios, the self-supervised approaches are less susceptible to sub-optimal learning rates and achieve higher mean accuracies than ImageNet pre-training, especially when training labels are scarce.
Generalization Error Bounds for Deep Neural Networks Trained by SGD

Generalization error bounds for deep neural networks trained by stochastic gradient descent (SGD) are derived by combining a dynamical control of an appropriate parameter norm and the Rademacher complexity estimate based on parameter norms. The bounds explicitly depend on the loss along the training trajectory, and work for a wide range of network architectures including multilayer perceptron (MLP) and convolutional neural networks (CNN). Compared with other algorithm-depending generalization estimates such as uniform stability-based bounds, our bounds do not require $L$-smoothness of the nonconvex loss function, and apply directly to SGD instead of Stochastic Langevin gradient descent (SGLD). Numerical results show that our bounds are non-vacuous and robust with the change of optimizer and network hyperparameters.
STUDY OF THE PROBLEM OF FORMATION PROFESSIONAL AND PEDAGOGICAL CULTURE FUTURE PRIMARY SCHOOL TEACHERS

In clause it is shown growth of professional - pedagogical cultural of students and the future teachers of initial classes.
ASSESSMENT OF STUDENTS’ ENVIRONMENTAL COMPETENCIES WITHIN THE FRAMEWORK OF PEDAGOGICAL ACTIVITY

Environmental competencies of students are a necessary link in the pedagogical activity of future specialists. The process of formation of environmental competencies depends on the content component of the disciplines taught and the methodological approach to the organization of the educational process. The greatest effectiveness of the formation of environmental competencies is achieved through the use of active forms of learning.
NeuPSL: Neural Probabilistic Soft Logic

In this paper, we introduce Neural Probabilistic Soft Logic (NeuPSL), a novel neuro-symbolic (NeSy) framework that unites state-of-the-art symbolic reasoning with the low-level perception of deep neural networks. To model the boundary between neural and symbolic representations, we propose a family of energy-based models, NeSy Energy-Based Models, and show that they are general enough to include NeuPSL and many other NeSy approaches. Using this framework, we show how to seamlessly integrate neural and symbolic parameter learning and inference in NeuPSL. Through an extensive empirical evaluation, we demonstrate the benefits of using NeSy methods, achieving upwards of 30% improvement over independent neural network models. On a well-established NeSy task, MNIST-Addition, NeuPSL demonstrates its joint reasoning capabilities by outperforming existing NeSy approaches by up to 10% in low-data settings. Furthermore, NeuPSL achieves a 5% boost in performance over state-of-the-art NeSy methods in a canonical citation network task with up to a 40 times speed up.