Reviewerly/exHarmony huggingface dataset:
Pemanfaatan Jeruedu Sebagai Media Pembelajaran Pada Masa Pandemi Covid-19 di SMPN 19 Bogor

This study aims to determine the use of the Jeruedu application as a learning medium for SMPN 19 Bogor students during the pandemic. The research method used is the literature study method in the form of a series of activities related to the method of collecting library data, reading and taking notes, and managing research materials. The results of the study show that Jeruedu has a positive impact which can be seen from the student learning outcomes which are increasing every day through assignments and quizzes. Students' perceptions of subjects carried out Online using the Jeruedu application show that students feel happy using Jeruedu because it is easy and the teacher/educator is not burdensome by giving many assignments, Jeruedu is flexible, that is, easy to access anywhere and anytime, but the weakness of using the Jeruedu application as a learning media that is constrained by internet access from the absence of a data network or smartphones that are used to support all students for the implementation of e-learning learning. In conclusion, the use of the Jeruedu application in subjects has proven effective because it can improve student learning outcomes through planning, process, results and evaluation of student learning.&#x0D; &#x0D; Keywords: Jeruedu application, learning media, Online.
Analysis and Design of Incoming Mail Filing Information Systems at universities, by Optimizing the Use of Google Drive

The purpose of this research is to create and implement an incoming mail archiving information system in a university environment by optimizing and integrating several applications from Google. For inputting and distributing incoming mail, Google Forms will be used, which will be integrated with Google Calendar to help schedule an online agenda for managing activities / events according to the contents of the letter. This research includes descriptive research with a practical and applicable approach, starting with data collection followed by the stage of developing an information system. The information system development stage is carried out as follows: 1). System Analysis, which is carried out based on the results of the data collection stage. The analysis is carried out by taking into account the existing problems, the purpose of building the information system, identification of data input, and identification of outputs which are the needs of the desired information report/display. 2). System Design. At this stage, a detailed information system design will be made based on the desired specifications at the analysis stage. 3). Programming, namely the process of making information systems 4). Testing, carried out the internal testing stage (unit testing and system testing). Based on the results of the research that has been done, it can be concluded that the incoming mail management system using the Google Drive application coupled with other applications can be used as an optimal and integrated management of incoming mail in universities. The impact of this application is that it can help the secretariat of the study program to manage and distribute incoming mail properly, for lecturers and study program leaders it can help remind activities or deadlines for work to be done
Challenges to the higher education to ensure sustainable development

New challenges in the field of digital transformation and content conveyed in the education process, in particular engineering sciences, triggered a discussion on the identification of issues focused on forms of cooperation with recipients using the available tools and taking into account the individual predispositions and knowledge of students related to their soft and hard competences. The subject of the paper is an attempt to identify students' soft competences on the basis of observations during the digital transformation period in 2020-2021. Technology has a significant impact on education, but also human and social factors have a significant impact on shaping the new future of universities, especially those with an engineering profile. The experience of the last 2 years shows the need for an integrated approach to the education process, which should take into account the content provided in combination with a properly selected form of cooperation with recipients using the available tools and taking into account the individual predispositions and knowledge of students (attention should be paid to the so-called soft and hard skills).
Pengaruh Penggunaan Media Sosial Terhadap Prestasi Belajar Siswa Kelas V SD

This study aims to determine the effect of using social media on learning achievement in fifth grade students at SDN Kaliabang Tengah VIII Bekasi. This research was conducted in the even semester of the 2021/2022 academic year. The research method used is quantitative correlation. The instrument used for data collection is a questionnaire in the form of a statement in the form of a Likert scale for the use of social media and the average value of student report cards in the even semester of the 2021/2022 academic year for learning achievement. The results of the research, namely the calculation of the Normality test using Kolmogrof Smirnov, showed a significance value greater than 0.05, namely 0.200 &gt; 0.05, then the sample data was normally distributed. And the Linearity test using the Simple Linear Regression test obtained a significant value of 0.000 &lt; 0.05, it is concluded that the data sample is linearly distributed or related. In testing the hypothesis used Product Moment correlation test with a significant level of 0.05 obtained r table = 0.444. Significance is usually seen in the results of Sig. (2-tailed) the value = 0.000 &lt; 0.05 and the correlation magnitude (r) 0.444 &gt; 0.254 is greater than rtable, meaning that the correlation or relationship between the two variables is significant at the 0.05 level and can be seen from the number of the correlation coefficient. So Ha is accepted and Ho is rejected. The conclusion of this study states that there is a significant influence between the use of social media and the learning achievement of fifth graders at SDN Kaliabang Tengah VIII Bekasi.
Penerapan Model Pembelajaran Numbered Head Together Pada Mata Pelajaran IPS Siswa Kelas IV SD

This research was conducted because it saw the social studies learning outcomes of fourth graders at SD Negeri Sukadana which were still low. This study aims to determine the completeness of students' social studies learning outcomes through numbered heads together (NHT) cooperative learning. From the data analysis of student learning outcomes before and after the NHT cooperative learning model was applied, the scores before the NHT cooperative learning model was applied were 100% incomplete. After applying the NHT cooperative learning model, the completeness of the social studies subject learning outcomes were 19 students who completed or 95% and 1 student who did not complete 5%. The data were analyzed using the z-test formula. based on the results of the data analysis test with a confidence level of = 5%, it shows Z_count = 6.42 and Z_(table) = 1.64. Because Z_count &gt; Z_(table ). With that it can be concluded that the learning outcomes of class IV social studies subjects at SD Negeri Sukadana after the application of the numbered head together (NHT) learning model to the learning outcomes of class IV social studies subjects at SD Negeri Sukadana were significantly completed.&#x0D; Keywords: Numbered head together (NHT) learning model, social studies learning outcomes.
Generation Initial Key of the AES Algorithm based on Randomized and Chaotic System

information security is a critical concern and a top priority for many communications networks. Cryptography is a suitable method of data security that can be used to maintain the secrecy and authenticity of information and can improve the privacy aspect of the data. The AES algorithm is one of the most important encryption algorithms and the best in protecting data. In this paper, a comparison was made between two different methods for the generation initial key of the key expansion of the AES-192 algorithm, in the first method, the initial key generated by the user (chose a random key by the user), and in the second method, the initial key generated by the chaotic system (which used the logistic function to generate the numbers chaotically). After testing the two methods, the second method that used a chaotic system is faster and more secure than the first method. Also, the encryption and decryption operations using the key generated by the chaotic system were faster when applying it to various sizes of text files and the plaintext is difficult to discover from the ciphertext. When comparing the proposed method to earlier experiments, it is both quicker and messier than earlier encryption techniques.
Grid Search for SARIMAX Parameters for Photovoltaic Time Series Modeling

The SARIMAX (Seasonal Autoregressive Integrated Moving Average with eXogenous regressors) model is a time series model that can be used to forecast future values of a time series, given its past values. It is beneficial for modeling time series data that exhibits seasonality and incorporating additional exogenous variables (variables that are not part of the time series itself but may affect it). One way to optimize the performance of a SARIMAX model is to use a grid search approach to find the best combination of hyperparameters for the model. A grid search involves specifying a set of possible values for each hyperparameter and then training and evaluating the model using all possible combinations of these values. The combination of hyperparameters that results in the best model performance can then be chosen as the final model. To perform a grid search for a SARIMAX model, you must define the grid of hyperparameters you want to search over. This will typically include the values of the autoregressive (AR) and moving average (MA) terms and the values of any exogenous variables you want to include in the model. We will also need to define a metric to evaluate the model's performance, such as mean absolute or root mean squared error. Once we have defined the grid of hyperparameters and the evaluation metric, you can use a grid search algorithm (such as a brute force search or a more efficient method such as random search or Bayesian optimization) to evaluate the performance of the model using all possible combinations of hyperparameters. The combination of hyperparameters that results in the best model performance can then be chosen as the final model. In this article, we will explore the potential of SARIMAX for PV time series modeling. The objective is to find the optimal set of hyperparameters. Grid Search passes all hyperparameter combinations through the model individually and checks the results. Overall, it returns the collection of hyperparameters that yield the most outstanding results after running the model. One of the most optimal SARIMAX (p,d,q) x (P, D, Q,s) combinations is SARIMAX (0,0,1) x (0,0,0,4).
The Actions of Food Sellers about the Use of Styrofoam Containers

It is often found that they use styrofoam and plastic containers by people without the use of banana leaf mats or rice paper, so they do not understand the impact of using styrofoam on the environment and health. As an alternative to styrofoam and plastic food containers, you should use bamboo containers that are environmentally friendly. The purpose of this study was to analyze the relationship between the actions of food sellers regarding the use of styrofoam containers in the Gulun Field Madiun. The research design was quantitative using an analytical survey with a cross-sectional approach. The population was 80 people and asample of 67 subjects. This research was conducted in May 2022. The results showed that there was a significant relationship between independent variables, namely The results of the study found that there was a significant relationship between knowledge (p-value = 0,047) and attitude (p-value = 0,042) towards the action of using styrofoam containers in food vendors in Gulun Field, Madiun City. The conclusion of this study was that there was a significant relationship between the actions of using styrofoam containers in food vendors in the Gulun field in Madiun City. Researchers suggest traders to further enhance good actions by replacing the use of styrofoam containers with environmentally friendly containers and not endangering health.
PENGEMBANGAN MEDIA PEMBELAJARAN MENGGUNAKAN SOFTWARE ADOBE FLASH PROFESIONAL CS8 PADA MATERI SEGI EMPAT

Learning media is important in the learning process, however the use of learning media that is not appropriate to the needs of students will complicate the learning process. At SMPN 1 Mojowarno students are only asked to read textbook then they are given assigments via the whatsapp application. In addition, the rectangular material at the school only explained the formulas without ane explanation of how the formulas could be found, thus make the learning process less meaningfull The aims of this developmen is to produce learning media in the form of Adobe Flash Professioanal CS8 software that is valid, practical, and effective on rectangle material in online learning. The type of research used in this study was Research and Development by adopting the ADDIE development model. The stages carried out in this research are, Analysis, Design, Development, Implementation, and Evaluation. The result of material expert validation showed a percentage of 86,6% with very valid criteria, and the result of media expert validation showed a percentage of 88% with very valid citeria. The result of students response questionnaire showed a percentage of 84,7% in the practical category, and the individual learning outcomes test showed a average 80,9 and percentage of classical test 82,35% with effective category. So it can be concluded that the learningmedia that has been developed using Adobe Flash Professional software on rectangular material in online learning has met valid, practical and effective criteria.&#x0D; Keywords: Adobe Flash Professional CS8, Rectangel, Online learning
Human Blood Grup and Rhesus Detection Tool Prototype Design Based On IoT

Currently, medical practitioners carry out blood type and rhesus examinations by directly observing the agglutination reaction and depending on the examiner's eye. Meanwhile, the effects of eye fatigue and saturation will cause inaccurate data. Therefore, a detection device was made which aims to display information about reading human blood type and rhesus on a digital display which can also store the data into a database. The ABO and rhesus systems were used in this study. This research was made using a real-time method based on the internet of things (IoT). sending data in real-time using WiFi Module ESP-01 and other components such as LCD microcontroller, LDR, LED, battery, and Arduino Uno. based on the results of tool testing, the percentage of success values is 91.67%.
Beyond Shannon Limits: Quantum Communications through Quantum Paths

A crucial step towards the 6th generation (6G) of networks would be a shift in communication paradigm beyond the limits of Shannon's theory. In both classical and quantum Shannon's information theory, communication channels are generally assumed to combine through classical trajectories, so that the associated network path traversed by the information carrier is well-defined. Counter-intuitively, quantum mechanics enables a quantum information carrier to propagate through a quantum path, i.e., through a path such that the causal order of the constituting communications channels becomes indefinite. Quantum paths exhibit astonishing features, such as providing non-null capacity even when no information can be sent through any classical path. In this paper, we study the quantum capacity achievable via a quantum path and establish upper and the lower bounds for it. Our findings reveal the substantial advantage achievable with a quantum path over any classical placements of communications channels in terms of ultimate achievable communication rates. Furthermore, we identify the region where a quantum path incontrovertibly outperforms the amount of transmissible information beyond the limits of conventional quantum Shannon's theory, and we quantify this advantage over classical paths through a conservative estimate.
Foundation Models and Fair Use

Existing foundation models are trained on copyrighted material. Deploying these models can pose both legal and ethical risks when data creators fail to receive appropriate attribution or compensation. In the United States and several other countries, copyrighted content may be used to build foundation models without incurring liability due to the fair use doctrine. However, there is a caveat: If the model produces output that is similar to copyrighted data, particularly in scenarios that affect the market of that data, fair use may no longer apply to the output of the model. In this work, we emphasize that fair use is not guaranteed, and additional work may be necessary to keep model development and deployment squarely in the realm of fair use. First, we survey the potential risks of developing and deploying foundation models based on copyrighted content. We review relevant U.S. case law, drawing parallels to existing and potential applications for generating text, source code, and visual art. Experiments confirm that popular foundation models can generate content considerably similar to copyrighted material. Second, we discuss technical mitigations that can help foundation models stay in line with fair use. We argue that more research is needed to align mitigation strategies with the current state of the law. Lastly, we suggest that the law and technical mitigations should co-evolve. For example, coupled with other policy mechanisms, the law could more explicitly consider safe harbors when strong technical tools are used to mitigate infringement harms. This co-evolution may help strike a balance between intellectual property and innovation, which speaks to the original goal of fair use. But we emphasize that the strategies we describe here are not a panacea and more work is needed to develop policies that address the potential harms of foundation models.
When Good and Reproducible Results are a Giant with Feet of Clay: The Importance of Software Quality in NLP

Despite its crucial role in research experiments, code correctness is often presumed only on the basis of the perceived quality of results. This assumption comes with the risk of erroneous outcomes and potentially misleading findings. To address this issue, we posit that the current focus on reproducibility should go hand in hand with the emphasis on software quality. We present a case study in which we identify and fix three bugs in widely used implementations of the state-of-the-art Conformer architecture. Through experiments on speech recognition and translation in various languages, we demonstrate that the presence of bugs does not prevent the achievement of good and reproducible results, which however can lead to incorrect conclusions that potentially misguide future research. As a countermeasure, we propose a Code-quality Checklist and release pangoliNN, a library dedicated to testing neural models, with the goal of promoting coding best practices and improving research software quality within the NLP community.
Function Approximation with Randomly Initialized Neural Networks for Approximate Model Reference Adaptive Control

Classical results in neural network approximation theory show how arbitrary continuous functions can be approximated by networks with a single hidden layer, under mild assumptions on the activation function. However, the classical theory does not give a constructive means to generate the network parameters that achieve a desired accuracy. Recent results have demonstrated that for specialized activation functions, such as ReLUs and some classes of analytic functions, high accuracy can be achieved via linear combinations of randomly initialized activations. These recent works utilize specialized integral representations of target functions that depend on the specific activation functions used. This paper defines mollified integral representations, which provide a means to form integral representations of target functions using activations for which no direct integral representation is currently known. The new construction enables approximation guarantees for randomly initialized networks for a variety of widely used activation functions.
Your Diffusion Model is Secretly a Zero-Shot Classifier

The recent wave of large-scale text-to-image diffusion models has dramatically increased our text-based image generation abilities. These models can generate realistic images for a staggering variety of prompts and exhibit impressive compositional generalization abilities. Almost all use cases thus far have solely focused on sampling; however, diffusion models can also provide conditional density estimates, which are useful for tasks beyond image generation. In this paper, we show that the density estimates from large-scale text-to-image diffusion models like Stable Diffusion can be leveraged to perform zero-shot classification without any additional training. Our generative approach to classification, which we call Diffusion Classifier, attains strong results on a variety of benchmarks and outperforms alternative methods of extracting knowledge from diffusion models. Although a gap remains between generative and discriminative approaches on zero-shot recognition tasks, our diffusion-based approach has significantly stronger multimodal compositional reasoning ability than competing discriminative approaches. Finally, we use Diffusion Classifier to extract standard classifiers from class-conditional diffusion models trained on ImageNet. Our models achieve strong classification performance using only weak augmentations and exhibit qualitatively better "effective robustness" to distribution shift. Overall, our results are a step toward using generative over discriminative models for downstream tasks. Results and visualizations at https://diffusion-classifier.github.io/
Provable Robustness for Streaming Models with a Sliding Window

The literature on provable robustness in machine learning has primarily focused on static prediction problems, such as image classification, in which input samples are assumed to be independent and model performance is measured as an expectation over the input distribution. Robustness certificates are derived for individual input instances with the assumption that the model is evaluated on each instance separately. However, in many deep learning applications such as online content recommendation and stock market analysis, models use historical data to make predictions. Robustness certificates based on the assumption of independent input samples are not directly applicable in such scenarios. In this work, we focus on the provable robustness of machine learning models in the context of data streams, where inputs are presented as a sequence of potentially correlated items. We derive robustness certificates for models that use a fixed-size sliding window over the input stream. Our guarantees hold for the average model performance across the entire stream and are independent of stream size, making them suitable for large data streams. We perform experiments on speech detection and human activity recognition tasks and show that our certificates can produce meaningful performance guarantees against adversarial perturbations.