Reviewerly/exHarmony huggingface dataset:
Informative Prompt Learning for Low-Shot Commonsense Question Answering via Fine-Grained Redundancy Reduction

Low-shot commonsense question answering (CQA) poses a big challenge due to the absence of sufficient labeled data and commonsense knowledge. Recent work focuses on utilizing the potential of commonsense reasoning of pre-trained language models (PLMs) for low-shot CQA. In addition, various prompt learning methods have been studied to elicit implicit knowledge from PLMs for performance promotion. Whereas, it has been shown that PLMs suffer from the redundancy problem that many neurons encode similar information, especially under a small sample regime, leading prompt learning to be less informative in low-shot scenarios. In this paper, we propose an informative prompt learning approach, which aims to elicit more diverse and useful knowledge from PLMs for low-shot CQA via fine-grained redundancy reduction. Specifically, our redundancy-reduction method imposes restrictions upon the fine-grained neuron-level to encourage each dimension to model different knowledge or clues. Experiments on three benchmark datasets show the great advantages of our proposed approach in low-shot settings. Moreover, we conduct both quantitative and qualitative analyses, which shed light on why our approach can lead to great improvements.
Image Inpainting with Semantic U-Transformer

With the driving force of powerful convolutional neural networks, image inpainting has made tremendous progress. Recently, transformer has demonstrated its effectiveness in various vision tasks, mainly due to its capacity to model long-term relationships. However, when it comes to image inpainting tasks, the transformer tends to fall short in terms of modeling local information, and interference from damaged regions can pose challenges. To tackle these issues, we introduce a novel Semantic U-shaped Transformer (SUT) in this work. The SUT is designed with spectral transformer blocks in its shallow layers, effectively capturing local information. Conversely, deeper layers utilize BRA transformer blocks to model global information. A key feature of the SUT is its attention mechanism, which employs bi-level routing attention. This approach significantly reduces the interference of damaged regions on overall information, making the SUT more suitable for image inpainting tasks. Experiments on several datasets indicate that the performance of the proposed method outperforms the current state-of-the-art (SOTA) inpainting approaches. In general, the PSNR of our method is on average 0.93 dB higher than SOTA, and the SSIM is higher by 0.026.
Lower Bounds on Assumptions Behind Registration-Based Encryption

Registration-based encryption (RBE) [11] is a primitive that aims to offer what identity-based encryption (IBE) [2] offers without the so-called key-escrow problem. In RBE parties who wish to join the system will generate their own secret and public keys and register their public keys to a transparent party called key curator (KC) who does not have any secret state. The initial constructions of RBE made non-black-box use of building block primitives, due to their use of either indistinguishability obfuscation [11] or some garbling scheme [12]. More recently, it was shown [14, 17] how to achieve black-box constructions of (variants of) RBE and even stronger primitives based on bilinear maps in which the RBE is relaxed to have a CRS whose length can grow with the number of registered identities. Making cryptographic constructions in general, and RBE in particular, black-box is an important step as it can play a significant role in its efficiency and potential deployment. Hence, in this work we ask: what are the minimal assumptions for black-box constructions of RBE? Particularly, can we black-box construct RBE schemes from the same assumptions used for public-key encryption or simpler algebraic assumptions that hold in the generic group model? In this work, we prove the first black-box separation results for RBE beyond the separations that follow from the observation that RBE black-box implies public-key encryption. In particular, we answer both of the questions above negatively and prove that neither trapdoor permutations nor (even Shoup’s) generic group model can be used as the sole source of hardness for building RBE schemes. More generally, we prove that a relaxation of RBE in which all the keys are registered and compressed at the same time is already too complex to be built from either of the above-mentioned primitives in a black-box way. At a technical level, using compression techniques, we prove lemmas in the TDP and GGM oracle settings that prove the following intuitive yet useful fact: that compact strings cannot signal too many trapdoors, even if their generation algorithm takes exponential time. Due to their generality, our lemmas could be of independent interest and find more applications.
DILEMMA OF WORLD BANK ACTION IN BIRR DEVALUATION AND ITS EFFECTS ON ETHIOPIA

The Ethiopian financial crisis has been ongoing for several years, with various economic challenges such as high inflation, foreign exchange shortages, and a growing public debt burden. However, one of the major events that triggered the crisis was the devaluation of the Ethiopian birr (the country's currency) in October 2017, which led to a rapid increase in inflation and caused significant economic hardship for many Ethiopians. The World Bank has been providing financial and technical assistance to the Ethiopian government to help address the crisis and promote sustainable economic growth. This research paper analyzes the World Bank's role in addressing Ethiopia's financial crisis using a combination of qualitative and quantitative research methods. The study includes in-depth interviews with key stakeholders, secondary data analysis of World Bank reports and other relevant documents, and exploratory data research methods to analyze economic trends in Ethiopia. Writer also highlights the value of using a combination of research methods to examine complex economic issues such as Ethiopia's financial crisis. By drawing on multiple data sources and research methods, the study provides a comprehensive understanding of the World Bank's role in addressing the crisis and the broader economic context in which it operates.
The COVID-19 Pandemic and Its Influence on Slovak Media Professionals

The research focuses on the status of media coverage of the COVID-19 pandemic by media professionals in Slovakia. Out of a representative research sample calculated to be 242 reporters out of a total of 2,130 reporters in Slovakia, only 50 reporters responded to the questionnaire, which is also a limitation of this research. From the responses, the authors generated the current status of media coverage of the COVID-19 pandemic. Positive results of the questionnaire survey include that most of the media reporters tried to rely on the opinions of experts such as epidemiologists, virologists, etc. Also, 64% of the respondents did not feel any restriction of freedom in their work. The high percentage of self-study by reporters should also be added to the positive phenomena. On the negative side, as many as 56% of the respondents stated that it was not important for them to influence public opinion, and a smaller percentage also mentioned various influences that interfered with the impartiality and objectivity of reporting. Also, a high percentage of respondents were critical of the government’s management of the pandemic. Based on these findings, it can be concluded that the state of media coverage in Slovakia during the COVID-19 pandemic was not entirely optimal. Further research should complement and refine the picture of the Slovak media at the time of the COVID-19 pandemic.
Effect of Adobe Flash CS6 Learning Media on Social Studies Learning Outcomes in Fifth Grade Student

&#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; This study aimed to investigate the impact of using Adobe Flash CS6 learning media on social studies learning outcomes related to national events surrounding the proclamation of independence in fifth-grade students at SDN Keboananom. The research utilized a quantitative experiment with a Quasi Experimental research design in the form of a non-equivalent control group design. Data analysis involved the Independent Sample T-test to test the hypothesis and address the research problem. The results revealed a significant improvement in students' understanding of social studies concepts after using Adobe Flash interactive learning media, as indicated by the average posttest data exceeding the pretest data. The findings imply that the integration of Adobe Flash learning media in the material related to the proclamation of Indonesian independence positively impacted social studies learning outcomes in fifth-grade students, offering a potential solution for enhancing social studies education in elementary schools.&#x0D; Highlight:&#x0D; &#x0D; The study examines the impact of using Adobe Flash CS6 learning media on social studies learning outcomes in fifth-grade students.&#x0D; The research employs a quantitative experiment with a Quasi Experimental research design, utilizing a non-equivalent control group design.&#x0D; Data analysis involves the Independent Sample T-test to test the hypothesis and determine the effect of using Adobe Flash interactive learning media on understanding social studies concepts in SDN Keboananom.&#x0D; &#x0D; Keyword: Adobe Flash CS6, Learning Media, Social Studies, Learning Outcomes, Fifth-Grade Students.&#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D;
Time Loop Lapbook Media on Unit Time Material for Third-Grade Elementary School Students

The low learning outcomes of students' mathematics are due to teachers' less optimal use of learning media. So to overcome these problems, students need media that can support the process of learning mathematics. This study aimed to determine the feasibility of time loop lapbook media on time unit material for 3rd-grade elementary school students. This research belongs to the type of development research that was developed using the Bord and Gall model. The subjects involved in this study were six experts, two material experts, two media experts, two language experts, and 20 grade 3 elementary school students. Data collection in the study was carried out using test methods, interviews, validation questionnaires, and practicality questionnaires, with research instruments in the form of media product validity questionnaire sheets by experts. The data obtained in the study were then analyzed using qualitative descriptive analysis techniques and combining quantitative data to revise the development of lapbook learning media products. The results of the research analysis showed that the validity of the lapbook media, which included media experts, material experts, and linguists stated that the time lap lapbook learning media obtained a score of 89.5%, which means that this lapbook learning media is very feasible to use in supporting the learning process, especially on material unit time class III elementary school. Then the results of practicality, which include aspects of ease of use, the time required, and ease of interpretation, obtain a score of 94%, which means that the learning media for the lapbook is very practical. Based on the results of the data analysis, the lapbook media is in the valid category and is very feasible to develop.
Design and Construction of a Didactic Prototype for Dermatological Laser Procedures

With the correct application, laser units are capable of performing complex procedures in the dermatological field, ranging from hair removal to the treatment of vascular lesions. The risk that patients face is inversely proportional to the knowledge, skills and preparation of the clinical staff. This article describes the development of a didactic tool for training students and professionals in the use of dermatological laser units. To this end, the module that was constructed allows simulating the operation of such medical technology and recreating the clinical situation that test decision-making. Considering the results, it is concluded that the use of this tool can result in benefits for the healthcare system, not only for the training of future professionals but also for its own development and the reduction of incidents or complications due to medical errors.
100W Solar Tracker with Arduino MKR1000 (Preliminary Results)

Solar tracking systems have proven to be an effective technique for improving the performance of solar panels by keeping them aligned with the incident light source for most of the day. The main objective of this project is to carry out a quantitative analysis to evaluate the performance improvement of a 100 W polycrystalline solar panel equipped with a 1-axis horizontal solar tracking system (which we call ”100 W solar tracker”), compared to a panel with the same characteristics that remains fixed. An Arduino MKR1000 is used to control the movement of the solar tracker and collect data from both solar panels, which is stored on a microSD card and uploaded to a MySQL database via WiFi connection. The solar tracker was developed at the ”Centro de Investigación con Técnicas Nucleares (CITEN)” and is in operation at the ”Estación Meteorológica Colina” of the University of Panama. The results of this study reveal a clear increase in the maximum instantaneous power of the solar tracker compared to the fixed panel. Demonstrating that the implementation of a tracking system significantly improves the performance of a solar panel.
Design and Development of Task-oriented Robots with Hybrid Energy

This research focuses on the 2023 SPDC competition project, which provides the necessary power for robots based on energy types such as wind and light. Under the guidance of many special restrictions, a competitive task-oriented robot was designed, and it must complete the task of carrying items in the planned field. In order to make it more intelligent, this study conducts experiments and analyzes the charging schedule, so as to formulate a feasible and better solution. From the experimental results, it can be seen that the proposed method can improve the scheme used in past competitions. Saves 32 % in charging time costs and provides 43 % additional scoring time. This also adds 1 kg to the total cumulative weight. In future research work, we will still consider more elements to improve the performance of the robot, making it more competitive and practical.
Securing Digital Ecosystems

Industries are evolving towards an integral digitisation of their processes. In the face of ever-faster market demands and ever-increasing quality, information technology (IT) progress represents the only solution to these needs. Industry 4.0 was born with this focus, where cybernetic systems interact with each other to achieve, efficiently, a predetermined goal. The whole process takes place with minimal, or in some cases total, absence of human intervention, leaving the systems to interact in full autonomy. This approach commonly falls under the internet of things (IoT) paradigm, in which all objects, regardless of size and functionality, are connected in a standard network exchanging information. In this sense, objects acquire intelligence because they can modify their behaviours based on the data they receive and transmit.
SWOT Analysis of Artificial Intelligence Enabling Rural Teacher Team Building in Context of Rural Revitalization

Rural revitalization lies in the revitalization of rural education, and the revitalization of rural education lies in the construction of rural teachers. Artificial intelligence empowers the construction of rural teachers, which is an inevitable initiative to comply with Chinas rural revitalization strategy. Through SWOT analysis, the advantages, disadvantages, opportunities and threats of AI-enabled rural teacher team building are comprehensively analyzed, in order to achieve the strengths to avoid weaknesses, grasp the opportunities, meet the threats, and put forward the following countermeasures to promote the construction of AI-enabled rural teacher team. It also proposes countermeasures to promote the sustainable and healthy development of rural teachers team construction.
Percepción de la ciencia pre y post-pandemia: un estudio de caso sobre la comunicación científica en la didáctica de la Educación Secundaria

Social perception of science is a multi-faceted concept that helps to understand the evolving relations between the knowledge ecosystem and the public opinions and views on it. Science communication is a key aspect of science perception as a flow of information from science, research and innovation professionals to civil society that helps to shape its conceptions/opinions. This work is framed into a science outreach activity, in which scientists directly interacted with secondary educational centres, to analyse the effect of scientific communication as a didactic methodology. Since the COVID-19 pandemic hit, we hypothesised that this could have affected these students’ perception of science. We used grouped-longitudinal quantitative methodology to address this hypothesis and evaluated the changes in perception of science through a survey scored twice; firstly, after a scientific communication (pre-pandemic) and secondly, after students returned to classes (post-pandemic). Results showed COVID-19 pandemic has positively influenced the interest in science in society. Interestingly, students declared a loss of confidence in scientific integrity due to a lack of transparency of the scientific news in post-pandemic surveys. These results suggest the need to have access to clear and scientifically validated information to increase the positive social perception of this stratum of society.
Strategi Guru Dalam Mengatasi Kendala Penggunaan Media Pembelajaran PAI Pada Masa Pandemi Covid-19

This study aims to disclose information and discuss teacher strategies in overcoming obstacles to the use of PAI learning media during the Covid-19 pandemic at SMA N 1 Harau. This type of research is descriptive research with a phenomenological approach. Data collection comes from interviews and observations, as well as documentation. Interviews were conducted with five informants, consisting of two pie subject teachers and two class IX students and another informant from class XII. The research was conducted from June to July. This research consists of two cycles, namely the planning and implementation stages. To obtain research data, four data collection tools were used, namely field notes, tests, observation and documentation. In the planning stage, the PAI teacher prepares a list of questions according to the research for the resource persons. Furthermore, at the implementation stage, the researcher processes data related to the research. In order to obtain information on the strategies and efforts of teachers in overcoming obstacles to the use of learning media.
Exploring the Impact of Slang Usage Among Students on WhatsApp: A Dig-ital Linguistic Analysis

This research delves into the dynamic world of informal language usage among students on the popular messaging platform, WhatsApp. As digital communication becomes an integral part of daily life, the study examines the frequency, variability, motivations, and social dynamics of slang usage among students. Through surveys, interviews, and, where possible, data analysis of WhatsApp conversations, the research uncovers the complex interplay between language, technology, and human connection in the digital realm. The findings reveal that slang is not merely a linguistic phenomenon but a reflection of the adaptability of language in the digital age. It serves as a linguistic bridge that enables informal communication in digital interactions. The lexicon of slang is diverse and ever-evolving, reflecting the cultural and social context in which it thrives. Motivations for slang usage go beyond humor and informality, extending to self-expression, emotional connection, and the formation of digital identities. Slang enhances social bonds and fosters a sense of belonging among peers, shaping the quality of digital interactions. Demographic variations in slang usage demonstrate its context-dependent nature, influenced by factors such as age, gender, and geographical location. Slang's impact on digital communication is significant, enhancing informal exchanges while presenting challenges, particularly in cross-cultural interactions. This research underscores the importance of digital literacy and cross-cultural understanding in online interactions and has implications for education, linguistic research, and cross-cultural communication. As the digital landscape continues to evolve, this research offers a deeper understanding of the role of language in shaping human connections in the digital age. It calls for ongoing exploration into the ever-changing linguistic dynamics of digital communication and its profound impact on contemporary society.
The Influence of Digital Influencers on Linguistic Evolution in the Javanese Language

Language is a dynamic entity that evolves in response to cultural and societal shifts. In the digital age, the emergence of influencers as prominent figures on social media platforms has introduced a new dimension to linguistic evolution. This research delves into the interplay between influencers and the Javanese language, examining linguistic innovations, perceived influence, demographic variations, influencer intentions, and ethical considerations. The findings reveal that influencers wield substantial influence, introducing neologisms, unique communication styles, and shifts in syntax within the Javanese language. They play a pivotal role in shaping cultural norms and values within the Javanese-speaking community. However, linguistic evolution brings about consequences and challenges, including dialectal variations, generational divides, and concerns about authenticity and language preservation. To navigate this linguistic landscape, we propose practical recommendations for linguistic education, responsible language promotion, digital preservation, language policy support, and cross-generational engagement. The coexistence of language preservation and evolution underscores the dynamic nature of the Javanese language and emphasizes the need for collaborative efforts to ensure its enduring vitality in the digital era
Equilibrium Optimizer for Emotion Classification from English Speech Signals

Speech emotion recognition and its precise classification are challenging tasks that heavily depend on the quality of feature extraction and selection for speech signals. Many feature selection algorithms have been proposed to achieve recognition, however, their accuracy has not reached a satisfactory level. We introduce an improved equilibrium optimizer (iEO) algorithm and utilize mel frequency cepstral coefficients (MFCCs) and pitch features for emotion recognition. The transfer function is used to complete the binarization of iEO (BiEO), and the algorithm adopts multi-swarm and transfer functions to balance global search and local search. The performance of the proposed algorithm is verified using four English speech emotion datasets, eNTERFACE05, ryerson audio-visual database of emotional speech and song (RAVDESS), surrey audio-visual expressed emotion (SAVEE) and toronto emotional speech set (TESS). The experimental results illustrate that the proposed algorithm obtains an accuracy of 0.4923, 0.5581, 0,5575 and 0.9840 in eNTERFACE05, RAVDESS, SAVEE and TESS based on K-nearest neighbors, and an accuracy of 0.5279, 0.5862, 0.6752 and 0.9941 based on random forest.