Reviewerly/exHarmony huggingface dataset:
Small Language Models Improve Giants by Rewriting Their Outputs

Despite the impressive performance of large language models (LLMs), they often lag behind specialized models in various tasks. LLMs only use a fraction of the existing training data for in-context learning, while task-specific models harness the full dataset for fine-tuning. In this work, we tackle the problem of leveraging training data to improve the performance of LLMs without fine-tuning. Our approach directly targets LLM predictions without requiring access to their weights. We create a pool of candidates from the LLM through few-shot prompting and we employ a compact model, the LM-corrector (LMCor), specifically trained to merge these candidates to produce an enhanced output. Our experiments on four natural language generation tasks demonstrate that even a small LMCor model (250M) substantially improves the few-shot performance of LLMs (62B), matching and even outperforming standard fine-tuning. Furthermore, we illustrate the robustness of LMCor against different prompts, thereby minimizing the need for extensive prompt engineering. Finally, we show that LMCor can be seamlessly integrated with different LLMs at inference, serving as a plug-and-play module to improve their performance.
ISP meets Deep Learning: A Survey on Deep Learning Methods for Image Signal Processing

The entire Image Signal Processor (ISP) of a camera relies on several processes to transform the data from the Color Filter Array (CFA) sensor, such as demosaicing, denoising, and enhancement. These processes can be executed either by some hardware or via software. In recent years, Deep Learning has emerged as one solution for some of them or even to replace the entire ISP using a single neural network for the task. In this work, we investigated several recent pieces of research in this area and provide deeper analysis and comparison among them, including results and possible points of improvement for future researchers.
A teaching concept for school experiments on radioactivity using augmented reality methods

Abstract Digital media are becoming increasingly influential in society, especially among the younger generation. Therefore, an augmented reality (AR) app was developed that simulates experiments with radioactive sources. The app runs experiments on the range and penetration power of alpha, beta and gamma radiation. It assigns virtual radiation sources, shielding materials or a detector to printed image markers, and superimposes their 3D images on the camera image. Alpha, beta and gamma radiation are clearly distinguishable by choosing different visualizations. The detector displays the measured count rates. At school, the app can be used in different ways. A concept for a teaching unit in Grade 10 was developed and tested in several classes based on a prototype of the app. The learning progress from the AR experiments was examined. Furthermore, an evaluation of the app was carried out. The most recent version of the app can be found here: https://seafile.projekt.uni-hannover.de/d/dd033aaaf5df4ec18362/
Unsupervised ASR via Cross-Lingual Pseudo-Labeling

Recent work has shown that it is possible to train an $\textit{unsupervised}$ automatic speech recognition (ASR) system using only unpaired audio and text. Existing unsupervised ASR methods assume that no labeled data can be used for training. We argue that even if one does not have any labeled audio for a given language, there is $\textit{always}$ labeled data available for other languages. We show that it is possible to use character-level acoustic models (AMs) from other languages to bootstrap an $\textit{unsupervised}$ AM in a new language. Here, "unsupervised" means no labeled audio is available for the $\textit{target}$ language. Our approach is based on two key ingredients: (i) generating pseudo-labels (PLs) of the $\textit{target}$ language using some $\textit{other}$ language AM and (ii) constraining these PLs with a $\textit{target language model}$. Our approach is effective on Common Voice: e.g. transfer of English AM to Swahili achieves 18% WER. It also outperforms character-based wav2vec-U 2.0 by 15% absolute WER on LJSpeech with 800h of labeled German data instead of 60k hours of unlabeled English data.
MILENIAL SISTEM PENYIRAMAN OTOMATIS DI PERKEBUNAN TOMAT MENGGUNAKAN ANDROID BERBASIS APLIKASI APP INVERTOR

In today's life, we need something simple, fast and effective. Humans are required to be efficient in time in various things and activities. The agricultural sector is no exception. Difficulty in caring for and managing plants is one of the factors in the lack of greenery around community settlements. Water content and adjustment of soil contours also make maintenance difficult, because tomato plants have different water and humidity requirements for each type of plant. Tomato plantations are all activities that cultivate certain tomato plants on soil or other planting media in an appropriate ecosystem, to process and market goods and services produced from these plants, with the assistance of technology, capital and management to create prosperity for tomato plantation business actors. and society. Tomato plants are vegetables that we consume in this life and tomatoes can nourish our bodies. To produce quality tomato plants, good tomato plant maintenance is needed. The irrigation system that has been used so far is manual. Therefore, an automatic watering system was created using an Invertor-based Android application so that we can control watering and make it easier for tomato garden owners when they are out of town and then we can control it from Android and become more time efficient so that they can do other things. In today's life, we need something simple, fast and effective. Humans are required to be efficient in time in various things and activities. The agricultural sector is no exception. Difficulty in caring for and managing plants is one of the factors in the lack of greenery around community settlements. Water content and adjustment of soil contours also make maintenance difficult, because tomato plants have different water and humidity requirements for each type of plant. Tomato plantations are all activities that cultivate certain tomato plants on soil or other planting media in an appropriate ecosystem, to process and market goods and services produced from these plants, with the assistance of technology, capital and management to create prosperity for tomato plantation business actors. and society. Tomato plants are vegetables that we consume in this life and tomatoes can nourish our bodies. To produce quality tomato plants, good tomato plant maintenance is needed. The irrigation system that has been used so far is manual. Therefore, an automatic watering system was created using an Invertor-based Android application so that we can control watering and make it easier for tomato garden owners when they are out of town and then we can control it from Android and become more time efficient so that they can do other things.
Perancangan Tata Letak Toko Ritel Berdasarkan Pola Belanja Konsumen Dengan Market Basket Analysis (Studi Kasus: Indomaret Sukatani)

&lt;p&gt;&lt;strong&gt;During the pandemic in early 2020, consumer behavior in shopping at retail stores changed. Some of the main factors taken into consideration that can influence consumer shopping behavior are facilities, layout, and time spent shopping. This can affect product sales at Indomaret Sukatani which has an ineffective layout so that it is difficult for customers to reach and customers need to spend a long-time shopping. To solve these problems, it is necessary to do data mining using the Market Basket Analysis method with the Apriorist and FP-Growth Algorithm so that customer shopping patterns can be known in order to design new layouts. Then the effectiveness test can be done by calculating the rectilinear distance to find out the most optimal layout design, namely the layout design based on the FP-Growth Algorithm with the smallest total rectilinear distance value of 2353.5 in the first scenario, 2313 in the second scenario, and 1609.5 in the third scenario.&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Keywords&lt;/em&gt;&lt;/strong&gt; – &lt;em&gt;Customer Behaviour, Layout, Market Basket Analysis&lt;/em&gt;&lt;/p&gt;
Indonesian Territory Clustering Based On Harvested Area and Rice Productivity Using Clustering Algorithm

Rice (Latin: Oryza sativa) is one of the most important cultivated plants in civilization. This plant is the main commodity for almost all Indonesian people. Indonesia is in third place as the largest rice producing country in the world. However, based on data from the Statistics Indonesia, Indonesia will still import rice until 2022. The transfer of paddy fields is one of the reasons why Indonesia is still importing rice to this day. Many lands that used to be paddy fields have turned into airports, industrial land, housing, and so on. Rice production is one of the important topics to be discussed in order to develop rice production in areas that are still relatively low. The purpose of this research is to classify cities/regencies in Indonesia based on rice production data in 2021. In this study, three clustering methods were used, namely, Partitioning Around Medoid (PAM), Clustering Large Applications (CLARA) and Fuzzy C-Means (FCM). Then the three methods are compared based on their silhouette coefficient values. The best obtained method is FCM method with two clusters and a silhouette value of 0.828. Results clustering with the best method is used as a reference in making maps clustering. Areas that are still relatively low are expected to increase rice productivity.
SISTEM PENJUALAN TIKET PADA KAWASAN KONSERVASI BERBASIS WEBSITE (STUDI KASUS: KAWASAN KONSERVASI, INDONESIA)

Website e-commerce, also known as electronic commerce or online commerce, refers to the purchasing and selling of products and services via websites on the internet, as well as the transmission of money and data required to complete these transactions. There are many conservation areas in Indonesia, both on land and at sea, where payment system procedures, buying admission tickets, and providing information about current conservation areas are still done in the traditional way, namely Conservation Areas in managing and recapitulating income finances. sales to organizations or residents in the vicinity of conservation areas in a transparent manner while continuing to keep paper records, making them less effective and efficient. Tourists also have no idea how many quotas are available. As a result, if visitors visit the conservation area and the quota is not available, they will be unable to access. And then there's the news - whether it's true or not, news that casts doubt on the Conservation Area. Based on the challenge, a waterfall technique was used to create an Application for Making a Website-Based Automatic Conservation Area Ticket Sales System, which included analysis, design, program code, program testing, and program implementation. The application's results show that it can assist Conservation Areas and tourists in managing and recapping money more effectively and efficiently, and that tourists can read information directly provided by Conservation Areas as well as the amount of available quotas&#x0D; &#x0D; Keywords: Application, E-commerce, Conservation Area, Indonesia, Website, Waterfall
Commerce Middle Office Management System Based on Springboot

Abstract This topic takes Vue framework as the front-end framework of e-commerce middle office management system, uses springboot framework as the construction mode of back-end framework, and uses Java to write function code. [1] The data of the system is stored in MySQL database, which can be provided to the employee end of registered employees and the management end of managers. Employees can complete registration and login through the e-commerce middle office management system, and then view department information, store information Warehouse information and view order information and add, view commodity file information. The system administrator manages employee information, department information, store type information, store information, warehouse information, commodity file information and order information through the management end. Through the realization of the different functions of the above employees and administrators, the normal operation of the system is ensured, and the process involving stores, commodities and orders is monitored, So as to make a complete set of e-commerce middle office management system that can be provided to all kinds of users.
Graphical Password Authentication

Abstract: A graphical password authentication is a form of authentication where users select a picture, image, or sequence as their password. Graphical passwords are an alternative to alphanumeric passwords in which users click on graphical images rather than typing alphanumeric characters to authenticate their identity. This method has gained popularity due to its ease of use and ability to provide better security than traditional alphanumeric passwords. This research paper provides a comprehensive study of graphical password authentication, including its history, types, advantages and disadvantages, security concerns, and future developments. The paper also includes a review of related research on graphical password authentication and its effectiveness in different settings.
The Effect of Smart Negligence on the Accounting Credibility Information in Light of the Current Crises

This study aims to reveal how financial managers succeed in managing companies in the light of the present crises caused by Corona pandemic, which negatively affected most companies and organizations through methods of smart negligence to ensure the continuity of the truthfulness of accounting information based those surrounding crises, and the continuity of growth of the companies before the challenges and risks that surround them. They incorporated a sample comprising financial managers in companies and organizations in Jordan. (80) questionnaires were distributed to the members of the sample. (74) questionnaires were used for the purposes of research and analysis, with a rate of (92%) of the distributed questionnaires. The study concluded the following: the commitment of the financial managers to the behavior of smart negligence in providing appropriate information to be relied upon to serve decision users in the light of the current crises, in addition to the application of the financial managers to the method of smart negligence in providing useful information with a high degree of confidence to serve the accounting processes in the company. The study recommended the need for the financial manager to strive to give honest and appropriate information in light of the current crises. Also, the financial manager should consider the reliability and credibility of accounting information in the light of the current crises, and for the financial manager to be keen on his efficiency, skill, and impartiality in providing information so that it does not serve one party at the expense of another one.
A Research on Coding Quiz Application

Abstract: Development of android-based Quiz application is mainly required by students and learners to prepare themselves. One of the major goal of our project is to facilitate students in learning, gaining and improving their knowledge skills. Users can prepare for interviews, entrance tests or any other corresponding purposes in a fresh mood and can’t get bored or frustrated due to dullness of application. We designed the application to facilitate the users to be able to take short quizzes using portable devices such as smart phones and tablets. This work deals with development of android-based multiple-choice question examination system namely Quiz. The main goal of the application is to enable users to practice for the subjective tests conducted for admissions and recruitment, with focus on Computer science field.
Importance of Digital Technology in English Language Learning

The development of &nbsp;a modern digital educational &nbsp;environment, which has an inexhaustible opportunity to improve the quality of education, has become relevant&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; in &nbsp;the &nbsp;21st &nbsp;century. Digital technologies &nbsp;are an important component &nbsp;of &nbsp;English language teaching in high school. The relevance of using digital resources in English language teaching ensures a high quality of education. Modern information and communication technologies allow the teacher to effectively manage the teaching of all language components (speaking, listening, writing and reading). Indeed, modern information and communication technologies are a necessary and comprehensive tool in the process of learning/teaching English. They allow to make the learning process more interesting, diverse and dynamic. Use of digital technology in&nbsp; English learning contributes to: Raising motivation of learning; Cognitive skills activation of students; Variety of teaching methods; Timely monitoring of training results; Student-oriented learning... Modern information and communication technologies are a necessary and comprehensive tool in the&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; process of teaching English.
Digital Museum Experience: Exploring Opportunities in Mixed Media Storytelling Using Augmented Reality

&lt;p&gt;This research project explores opportunities for mobile augmented reality (AR) applications as an alternative means of viewing artifacts. Augmented reality is a promising technology that can greatly improve a visitor’s interactions with artifacts and their contextualized information. However, many museums hesitate to adopt AR due to concerns of gimmickry, detraction of the museum experience, and user cognitive overload (Marques &amp; Costello, 2018). In this project, the usability and perceived usefulness of mobile AR is investigated through a comparative case study of existing AR applications for museums. Using the findings from the case study, a mixed-media storytelling mobile AR application is prototyped to demonstrate how mobile AR can enhance public engagement and improve access to cultural artifacts. By fulfilling the aim of the project, AR can be more readily accepted for museums. This project presents new insights to usability evaluations and the development of mobile AR apps for digital museum experiences. &lt;/p&gt;
Minimizing User Costs in Multi-Broker Mobile Cloud Computing Networks

The success and disruption of cloud computing over the past few years is unparalleled.In order to quickly allocate or reallocate virtual computing as well as storage resources, Infrastructure as a Service (IaaS) providers offer commercially accessible services that enable scaling out or in computing capabilities in response to changing needs.Users can provide new apps using IaaS services without having to manage the supporting infrastructure. In this study, the system takes into account an MCC model in which several brokers allot cloud resources to mobile consumers. The approach is distinguished by a heterogeneous cloud architecture and by the many cloud service providers' pricing models. Both a public cloud and a cloudlet are part of it. A competitive strategy and a compete-then-cooperate approach are investigated by the system as a performance bound. The computer creates a cooperative issue with the restriction that none broker should be required to shell out beyond the dispute price, with the objective of lowering the overall average broker price. The system uses a mix of the branch and bound paradigm with sophisticated convex relaxation techniques to develop a novel globally optimum solution algorithm to handle the ensuing non-convex cooperative issue.
Enhancing MNIST Digit Recognition with Ensemble Learning Techniques

&#x0D; &#x0D; &#x0D; &#x0D; Abstract&#x0D; The classification task known as MNIST digit recognition involves identifying handwritten numbers into their corresponding values. Although there are numerous approaches proposed for this type of task, they typically face issues in achieving high accuracy. One method that can improve single models' performance is through ensemble learning. The goal of this study is to explore the use of various learning techniques, such as boosting and bagging, in combination with random forest models and decision trees, to improve the performance of MNIST digit recognition with regard to accuracy. We then perform evaluations on these methods using various metrics, such as recall, precision, accuracy, and F1. The findings of this study provide valuable insight into the various advantages of ensemble methods for the MNIST digit recognition task. It also highlights the need to explore these techniques in the context of machine learning. The objective of this study is to investigate the use of ensembles in improving the accuracy of MNIST digit recognition. We performed evaluations on two popular methods, namely boosting and bagging, with random forest and decision tree models. The evaluation parameters included F1 score, recall, accuracy, and precision. The results of the evaluations revealed that both boosting and bagging methods performed well in terms of their evaluation metrics. In most cases, the decision tree performed better than the random forest. However, the random forest method was able to achieve the highest accuracy, which is 99 percent. The findings of the evaluation revealed that ensembles can help improve single models' accuracy in MNIST digit recognition. On the other hand, the random forest method is a promising option for this task. The exact results of the evaluations will vary depending on the evaluation and implementation metrics. More research is needed to confirm their generalizability. The study emphasizes the value of exploring ensembles in machine learning systems, as well as the potential advantages of performing MNIST digit recognition using them.&#x0D; &#x0D; &#x0D; &#x0D;
Pelatihan Peningkatan Tumbuh Kembang Anak dalam Kemampuan Berbahasa sebagai Dampak Masa Pandemi Covid-19 bagi Guru dan Orang Tua

The Covid-19 pandemic has significantly impacted life, including the growth and development of children in language skills. Few parents and teachers, especially at the Early Childhood Education level, complained that their children were hampered in language skills (speaking). Therefore, training is needed for teachers and parents to stimulate children's language skills. The purpose of this PkM is to increase the knowledge of teachers and parents about children's growth and development so that they are willing and able to stimulate children's language skills. Methods of implementation: a) analysis of the situation with partners, b) implementation of pre-test, c) provision of materials, 4) implementation of post-test and evaluation of activities. The results of the PkM show increasing in the knowledge of teachers and parents about the growth and development of children's language skills by 75.48 with a significance value of 0.000&gt; 0.05. Thus, in general, teachers and parents are equipped with the knowledge to improve children's language skills due to the Covid-19 pandemic. In addition, the teachers and parents seemed to give a positive response. The positive response is evident from the enthusiasm and attendance of 72.83% of participants despite the rainy weather from early morning until the PkM ended.