Reviewerly/exHarmony huggingface dataset:
Analisa Tingkat Kepuasan Mahasiswa Terhadap Perkuliahan Daring Pada Era Pandemi COVID-19

Online learning is learning that uses the internet network with accessibility, connectivity, flexibility, and the ability to bring up various types of learning interactions. Satisfaction is a person's feelings of pleasure or disappointment that arise after comparing his perceptions/impressions of the performance or results of a product and his expectations. Research on student perceptions of online learning is limited to aspects of teaching and learning, the ability of lecturers, facilities and infrastructure. To get results from the perception or opinion of a student from the level of satisfaction of online lectures, it can be done using the Fuzzy logic mamdani method and for calculations using the Slovin formula.
Empowering Mind Mapping Strategy To Improve Students’ Writing Skills In The EFL Classroom

Writing is one of the important language skills to communicate in written forms. Therefore, the improvement of writing skills is absolutely essential to be continually carried out. This study aims at developing writing skills by implementing a mind mapping strategy in the EFL classroom. There two cyclic learning sessions comprising planning, action, observation, and reflection were conducted in this study. The data were collected through administering pre-test, post-test, and questionnaires to the students who participated in this study. Based on the results of data analysis, this study revealed that students’ writing skills could be improved through implementing a mind mapping strategy. Therefore, this study implies that teachers should consider using mind mapping in teaching writing
Performance Analysis of 120 kWp Grid-Connected Rooftop Solar Photovoltaic System in Central Java

This study examines the performance of a solar power plant with a total capacity of 125 KWp, which operates for one year in Blora, Central Java. The ability of this power plant is a total of PV modules with 20 kWp, ten kWp, and five kWp capacities spread across eight locations. The annual performance of the rooftop solar power plant is measured automatically by the converter installed in each module. The resulting data from inverters are compared to the meteorological conditions from the meteorological agency. This research will investigate the influence of climate on the power generated, the efficiency of the equipment in a power plant, and the effect of pseudo motion of the sun. It was found that there were variations in energy output throughout the year, and it was concluded that the maximum annual energy was produced in July-August. In addition to weather, other factors need to be investigated further to determine the causes of variations in solar PV output.
Experiences of Adapting Multimodal Machine Translation Techniques for Hindi

Multimodal Neural Machine Translation (MNMT) is an interesting task in natural language processing (NLP) where we use visual modalities along with a source sentence to aid the source to target translation process.Recently, there has been a lot of works in MNMT frameworks to boost the performance of standalone Machine Translation tasks.Most of the prior works in MNMT tried to perform translation between two widely known languages (e.g.English-to-German, English-to-French ).In this paper, We explore the effectiveness of different state-of-the-art MNMT methods, which use various data oriented techniques including multimodal pre-training, for low resource languages.Although the existing methods works well on high resource languages, usability of those methods on low-resource languages is unknown.In this paper, we evaluate the existing methods on Hindi and report our findings.
Privacy-preserving Diverse Keyword Search and Online Pre-diagnosis in Cloud Computing

With the development of the Mobile Healthcare Monitoring Network (MHMN), patients’ data collected by body sensors not only allows patients to monitor their health or make online pre-diagnosis but also enables clinicians to make proper decisions by utilizing data mining techniques. In MHMN, patients’ personal data are collected by sensors per second and uploaded to the cloud server as multi-dimension vectors, cloud server stores the personal data as well as sends monitoring information to the hospital when the real-time data is abnormal. Hospital users (i.e., doctors, etc.) may query some samples which contain certain textual keywords or digital keywords in certain ranges for disease diagnosis or medical research. For example, a certain hospital user may query all samples with textual keywords ‘cancer; diabetes’ and digital vectors ‘age’ ∈ [30,50], ‘blood sugar’ ∈ [4,8], ‘heart rhythm’ ∈ [70,80]. Besides, the potential value of massive medical data has attracted considerable interests recently, for example, valuable results in diagnosis model can be yield with large-scale aggregation analysis of personal medical data. The cloud server can build a diagnosis model using data mining technology over massive data, so that hospital users or pre-diagnosis users upload medical data (i.e., age, blood pressure, blood sugar, etc.) to the cloud for diagnosis.
DESIGNING OF PERSONALIZED TRAINING FOR YOUNG TEACHERS

The article analyzes the main qualitative characteristics that determine the development process of additional education at the pedagogical university. The potential of the postgraduate education system as a resource for the development of the regional education system is revealed. The diagnostic potential of projects of postgraduate support of young teachers has been determined. The mechanism of designing personalized educational routes for advanced training of young teachers is disclosed.
Actividades de resolución de problemas matemáticos con apoyo de la serie animada Renata y los problemas en el contexto de la emergencia sanitaria SARS-Cov-2

In the health emergency context generated by the SARS-Cov-2 , an investigation has been developed focusing on implementing a training program for primary students, using the ARPA methodology, adapted to remote training (arpa-d), using multimedia material from the animated series Renata y Los Problemas. The aim has been to explore the experience of implementing this methodology. The research methodology followed was the case study of remote implementation in a 2nd-grade course in a state subsidized school with a high level of vulnerability. Among the main findings are the role of parents, the fundamental value of affectivity and relational aspects between students and teachers, and the contribution of the digital narrative incorporated to the methodology. The findings are a relevant contribution both for future implementations of this methodology and for understanding the barriers and facilitators for the use of digital resources in emergency distance training.
Electromagnetic field induced strong two photon blockade with hyperradiant behavior

We theoretically study the electromagnetic field controlled photon correlation and radiation properties in a two-atom-cavity quantum electrodynamic (QED) system with different atom-cavity coupling strengths. When two three-level atoms are coherently driven by a probe field and a strong control field, forming a ladder type electromagnetically induced transparency configuration, there exist four different excitation pathways via the two photon processes, yielding four different frequencies for realizing two photon blockades. Carefully choosing the intensity of the control field, resonant single-photon and two-photon excitation can be achieved at the same probe field frequency. Thus, two photon blockade phenomenon can be significantly improved and the collective radiation behavior becomes superradiance or even hyperradiance. Our system presented here can be considered to be a converter of a weak coherent light to two correlated photons.
E - Capacity - Equivocation Region of Wiretap Channel

One of the problems of information - theoretic security concerns secure communication over a wiretap channel. The aim in the general wiretap channel model is to maximize the rate of the reliable communication from the source to the legitimate receiver, while keeping the confidential information as secret as possible from the wiretapper (eavesdropper). We introduce and investigate the E - capacity - equivocation region and the E - secrecy capacity function for the wiretap channel, which are, correspondingly, the generalizations of the capacity - equivocation region and secrecy - capacity studied by Csisz&amp;aacute;r and K&amp;ouml;rner (1978). The E - capacity equivocation region is the closure of the set of all achievable rate - reliability and equivocation pairs, where the rate - reliability function represents the optimal dependence of rate on the error probability exponent (reliability). By analogy with the notion of E - capacity, we consider the E - secrecy capacity function that for the given E is the maximum rate at which the message can be transmitted being kept perfectly secret from the wiretapper.
Bigarren hizkuntzen klaseetako plangintza: hiru aldiko narratiba

Gizartean, narratibak beti izan dira presente; batez ere, irakaskuntza-eremuan. Hauxe da gure proposamena: ikasleak narratiba horiek eraikitzeko lanetan inplikatzea, gehiago motiba daitezen ikasprozesuan. Horretarako, eskola-plangintzak diseinatzea izango da irakaslearen rola, narrazio-egitura argiak segi ditzaten, ezusteko norabide-aldaketa eta guzti, ikasleek erabakiak hartu eta hipotesiak prestatu behar izan ditzaten, emaitza posibleak aurkitzeko ikasgelan guztien artean lantzen ari diren istorioari. Eskola-plangintzak diseinatzeko ideiez aparte, joko batzuk ere aurkeztuko ditugu, ikasgelan erabili ohi direnak, nahiz eta ez diren sortu bigarren hizkuntzak irakasteko.
Processes aimed at students to improve their learning

Nowadays educators are using less frequent activities that motivate students, usually, some teachers often repeat techniques similar to the previous one, and that causes distraction in children. Motivational activities are factors that influence the teaching-learning process, being the fundamental engine to attract attention and have participative children capable of expressing the knowledge acquired in their environment because they like to know, learn. The objective of the work is to investigate the motivation that the teacher has in the teaching-learning process, which opens the student's reflective observation. The study of playful activities was used that offer the ability to internalize knowledge with technological tools where the modality is applied playing I learn, but it does not necessarily have to do with a game itself, but with a phrase. It was obtained as a result that students learn better with recreational activities than with traditional methodology.
Room Borrowing Information System Website Based using PHP and MySQL with Waterfall Model

Research by developing an information system is a research that aims to produce and develop an information service system design in the form of website-based rooms lending using PHP as a programming language and MySQL as a database that will be used at the Faculty of Teacher Training and Education, Sultan Ageng Tirtayasa University in-room management as room loan, room loan schedule, room loan data, and room information. This study uses the waterfall development model, with 5 (five) stages of development including the stages of communication, planning, modelling, construction and deployment. This research used Alpha and Beta testing to 3 (three) media experts and 31 (thirty-one) users including 1 (one) admin and 30 (thirty) students. Data collection techniques using interview techniques, observation and dissemination of research instruments. With data analysis in the form of a feasibility test using a Likert scale instrument of 4 (four) assessment scores to media experts and respondents. The final product produced is a website for rooms loaning information system, by average score by media experts (Alpha Testing) of 71.6 with the "very feasible" category. The results of the feasibility test by users (Beta Testing) were 34.32 with the "very feasible" category. Therefore, it can be concluded that the website-based room loan information system is very feasible to use.
AxP: A HW-SW Co-Design Pipeline for Energy-Efficient Approximated ConvNets via Associative Matching

The reduction in energy consumption is key for deep neural networks (DNNs) to ensure usability and reliability, whether they are deployed on low-power end-nodes with limited resources or high-performance platforms that serve large pools of users. Leveraging the over-parametrization shown by many DNN models, convolutional neural networks (ConvNets) in particular, energy efficiency can be improved substantially preserving the model accuracy. The solution proposed in this work exploits the intrinsic redundancy of ConvNets to maximize the reuse of partial arithmetic results during the inference stages. Specifically, the weight-set of a given ConvNet is discretized through a clustering procedure such that the largest possible number of inner multiplications fall into predefined bins; this allows an off-line computation of the most frequent results, which in turn can be stored locally and retrieved when needed during the forward pass. Such a reuse mechanism leads to remarkable energy savings with the aid of a custom processing element (PE) that integrates an associative memory with a standard floating-point unit (FPU). Moreover, the adoption of an approximate associative rule based on a partial bit-match increases the hit rate over the pre-computed results, maximizing the energy reduction even further. Results collected on a set of ConvNets trained for computer vision and speech processing tasks reveal that the proposed associative-based hw-sw co-design achieves up to 77% in energy savings with less than 1% in accuracy loss.
Analisis proses bisnis kurasi data penelitian di Pusat Data dan Dokumentasi Ilmiah

Introduction. This study aims to identify research data curation activities and business processes at PDDI LIPI&#x0D; Data Collection Methods. This research used a case study approach with interviews and observations of five informants from June to July 2021.&#x0D; Data Analysis Three stages of coding are used to sort, identify, and associate categories with existing theories. Presentation of data was conducted through the description of entities from business processes based on the business process model and notation (BPMN).&#x0D; Results and Discussion. Four main activities of the curation process were carried out. The data owners and curators become actors in the process, and between the two requires trust, communication, and collaboration in their implementation. In addition, validation of the business processes was conducted to show that the process has been running scientifically.&#x0D; Conclusion. The flow of knowledge in these activities is documented in a structured manner based on mapped business procedures and processes. It is necessary to conduct periodic reviews and analyzes of time and resources. Further research should focus on human resources, policy documents, and facilities related to research data curation activities.
Research on Fault Diagnosis Model of Generative Adss Based on Improved Semisupervised Diagnosis Algorithm

With the advent of the era of big data and the rapid development of deep learning and other technologies, people can use complex neural network models to mine and extract key information in massive data with the support of powerful computing power. However, it also increases the complexity of heterogeneous network and greatly increases the difficulty of network maintenance and management. In order to solve the problem of network fault diagnosis, this paper first proposes an improved semisupervised inverse network fault diagnosis algorithm; the proposed algorithm effectively guarantees the convergence of generated against network model, makes full use of a large amount of trouble-free tag data, and obtains a good accuracy of fault diagnosis. Then, the diagnosis model is further optimized and the fault classification task is completed by the convolutional neural network, the discriminant function of the network is simplified, and the generation pair network is only responsible for generating fault samples. The simulation results also show that the fault diagnosis algorithm based on network generation and convolutional neural network achieves good fault diagnosis accuracy and saves the overhead of manually labeling a large number of data samples.
STEAM Education in the View of the Bulgarian Teacher

The reality we live in is constantly changing, modern technologies comprise all spheres of life, changing it irreversibly. These transformations require completely different knowledge, skills, and especially competencies with the modern human. To meet these needs adequately, the educational system is also changing - new approaches, methods, and technologies of teaching are being introduced. The purpose of the study, which found a place in this report, is to examine the teacher's position and opinion on the very popular STEAM training in the Republic of Bulgaria during the last two years.
The Role Of ‘Think-Pair-Share’ In Enhancing the Moroccan University Students’ Speaking Skills in Online Classes

Speaking English as a foreign language presents one of the most common challenges for learners of English due to many factors related to their perception of the teacher as “a sage on the stage,” their own shyness, a lack of appropriate vocabulary and accurate grammar, and a lack of cooperative learning skills. To help students remedy this problem, the Think-Pair-Share’ strategy was used in this study of online classes during the COVID 19 pandemic. Research has demonstrated that learners can improve their speaking skills and learn more effectively through meaningful collaboration and sharing. This study aims to investigate the role of the Think-Pair-Share’ approach in promoting students’ speaking skills. The study adopts a qualitative approach and addresses the following two research questions: (i) To what extent does the Think-Pair- Share help in improving students’ speaking skills? (ii) How can this improvement be justified? Twenty-eight first-year Moroccan university students took part in this study. The research instruments used combined pre- and post-speaking tests, students’ self-evaluation, and classroom observations. Data were video recorded, analysed qualitatively using the FCE speaking-assessment criteria, and compared to the students’ self- evaluation of their own performance. The results show that the Think-Pair-Share strategy enabled predominantly average and weak students to exchange their views on a range of familiar topics with more ease, confidence, and fluency using more appropriate vocabulary and a clearer organisation of ideas. Although the learners still had problems with their pronunciation and accurate grammar, they demonstrated better interactive communication.
Octave Deep Compression: In-Parallel Pruning-Quantization on Different Frequencies

Though deep neural networks achieve great accuracy in visual recognition tasks, they contain millions of weights and thus require a large space to be stored. This presents a challenge in developing deeper neural networks as well as installing those models on mobile devices. In this paper, we propose Octave Deep Compression (ODC), a deep compression algorithm targeted toward the Octave Convolutional Networks (OCNs). ODC compresses OCNs with in-parallel pruning-quantization on different frequencies. We performed extensive experiments on Cifar10 and ImageNet, and our compression results on popular deep learning models such as VGG, ResNet50, and MobileNetV2 demonstrate that ODC can simultaneously achieve a smaller model size and a higher classification accuracy when compared to the state-of-the-art network compression methods.
Retraction Note: Evaluation of solar energy potential based on target detection and design of English vocabulary teaching platform

Target detection is now a hot research direction in the field of computer vision, where we can find applications for national defense, security, and medical security. Currently, there are many target detection algorithms, such as Fast R-CNN, Faster R-CNN, YOLOv3, and SSD. Among them, the YOLOv3 algorithm treats target detection as a regression problem and recognizes the entire image, which effectively improves the detection speed. The backbone network uses a residual structure to significantly increase network depth and balance accuracy. Currently, the international community has agreed to use new energy technologies to solve energy and environmental problems. At the same time, the energy consumption of urban buildings is one of the main reasons for energy consumption. The solar energy on the roof of the building has no pollution and noise and is easy to collect. Now, it has become one of the new energy technologies that are very suitable for applications in people’s residential areas. The combination of advanced educational theories and modern information technology is the direction of the development of English vocabulary education. It combines POA and modern technology and integrates advanced concepts such as output drive and input to promote learning and other advanced concepts into English vocabulary teaching. It plays a role in promoting. At the same time, it can also find problems in learning English vocabulary and develop related software theory and technology. According to the specific needs of learners, combined with the development of modern technology, it involves an English vocabulary learning software, which is based on the Android mobile teaching platform and innovates a variety of memory methods to help learners.
Linked open data and aggregation infrastructure in the cultural heritage sector

Aggregation services are, for now, a necessary reality in the world of linked open data. This chapter looks at some of the benefits and tradeoffs that come with the aggregation of linked open data, before looking at the specific case of the Swedish Open Cultural Heritage (SOCH) national aggregator. By gathering disparate but thematically related data sets and republishing them in a common format, aggregators not only make data more accessible and discoverable, but also place it within a wider context. However, there are concomitant design compromises which must be made. SOCH is a national aggregator for heritage data in Sweden. Since 2010 it has harvested data from museums, archives and historic environment registers, and published them as linked open data mapped to a common data model and made them questionable via a web application programming interface (API). SOCH now aggregates more than 9 million records from more than 75 Swedish heritage institutions. Over its ten-year lifespan, SOCH has had significant success in opening up Swedish heritage data. However, as an early adopter of linked open data in Swedish heritage, there are nonetheless challenges to be addressed in future development.