Reviewerly/exHarmony huggingface dataset:
A Semantic and Smart Framework for Handling Multilingual Linguistic Knowledge

The authors propose a semantic and smart assistance framework for handling linguistic knowledge, called LingFramework. It targets both expert and novice users. It aims to assist the user in understanding the different aspects of the linguistic domain and ease the process of proposing lingware applications. LingFramework is based on a multilingual linguistic domain ontology called LingOnto. It allows (1) representing linguistic data, linguistic processing functionalities and linguistic processing features, and (2) reasoning, via a SWRL-based reasoning engine, about the linguistic knowledge. Currently, it covers English, French, and Arabic languages. To facilitate the interaction with LingOnto, an ontology visualization tool called LingGraph is proposed. It offers an easy-to-use interface for users not familiar with ontologies. It provides a SPARQL pattern-based approach to allow a smart search interaction functionality. LingFramework is applied to assist the user in identifying valid linguistic processing pipelines related to lingware applications. The evaluation results are promising.
A Design Space of Educational Authoring Tools for Augmented Reality

Recently, numerous authoring tools for Augmented Reality (AR) have been proposed, in both industry and academia, with the aim to enable non-expert users, without programming skills, to scaffold educational AR activities. This is a promising authoring approach that can democratize AR for learning. However, there is no systematic analysis of these emerging tools regarding what AR features and modalities they offer (RQ1). Furthermore, little is known as to how these emerging tools support teachers’ needs (RQ2). Following a two-fold approach, we first analyzed a corpus of 21 authoring tools from industry and academia and formulated a comprehensive design space with four dimensions: (1) authoring workflow, (2) AR modality, (3) AR use, and (4) content and user management. We then analyzed two workshops with 19 teachers to understand their needs for AR activities and how existing tools support them. Ultimately, we discuss how our work can support researchers and designers of educational AR authoring tools.
Signature Codes for a Noisy Adder Multiple Access Channel

In this work, we consider q-ary signature codes of length k and size n for a noisy adder multiple access channel. A signature code in this model has the property that any subset of codewords can be uniquely reconstructed based on any vector that is obtained from the sum (over integers) of these codewords. We show that there exists an algorithm to construct a signature code of length $k = \frac{{2n\log 3}}{{(1 - 2\tau )\left( {\log n + (q - 1)\log \frac{\pi }{2}} \right)}} + \mathcal{O}\left( {\frac{n}{{\log n(q + \log n)}}} \right)$ capable of correcting τk errors at the channel output, where $0 \leq \tau < \frac{{q - 1}}{{2q}}$. Furthermore, we present an explicit construction of signature codewords with polynomial complexity being able to correct up to $\left( {\frac{{q - 1}}{{8q}} - \varepsilon } \right)k$ errors for a codeword length $k = \mathcal{O}\left( {\frac{n}{{\log \log n}}} \right)$, where ε is a small non-negative number. Moreover, we prove several non-existence results (converse bounds) for q-ary signature codes enabling error correction.
Quality Metrics

Software engineering is as much about teamwork as it is about technology. This introductory textbook covers both. For courses featuring a team project, it offers tips and templates for aligning classroom concepts with the needs of the students' projects. Students will learn how software is developed in industry by adopting agile methods, discovering requirements, designing modular systems, selecting effective tests, and using metrics to track progress. The book also covers the 'why' behind the 'how-to', to prepare students for advances in industry practices. The chapters explore ways of eliciting what users really want, how clean architecture divides and conquers the inherent complexity of software systems, how test coverage is essential for detecting the inevitable defects in code, and much more. Ravi Sethi provides real-life case studies and examples to demonstrate practical applications of the concepts. Online resources include sample project materials for students, and lecture slides for instructors.
References

Software engineering is as much about teamwork as it is about technology. This introductory textbook covers both. For courses featuring a team project, it offers tips and templates for aligning classroom concepts with the needs of the students' projects. Students will learn how software is developed in industry by adopting agile methods, discovering requirements, designing modular systems, selecting effective tests, and using metrics to track progress. The book also covers the 'why' behind the 'how-to', to prepare students for advances in industry practices. The chapters explore ways of eliciting what users really want, how clean architecture divides and conquers the inherent complexity of software systems, how test coverage is essential for detecting the inevitable defects in code, and much more. Ravi Sethi provides real-life case studies and examples to demonstrate practical applications of the concepts. Online resources include sample project materials for students, and lecture slides for instructors.
Requirements Analysis

Software engineering is as much about teamwork as it is about technology. This introductory textbook covers both. For courses featuring a team project, it offers tips and templates for aligning classroom concepts with the needs of the students' projects. Students will learn how software is developed in industry by adopting agile methods, discovering requirements, designing modular systems, selecting effective tests, and using metrics to track progress. The book also covers the 'why' behind the 'how-to', to prepare students for advances in industry practices. The chapters explore ways of eliciting what users really want, how clean architecture divides and conquers the inherent complexity of software systems, how test coverage is essential for detecting the inevitable defects in code, and much more. Ravi Sethi provides real-life case studies and examples to demonstrate practical applications of the concepts. Online resources include sample project materials for students, and lecture slides for instructors.
STUDY OF DRAINAGE, PANORAMIC HOUSING, CEMENGKALANG VILLAGE, SIDOARJO DISTRICT

Panorama Residence housing which has an area of 8000 m2 is located in a plain area with a slope of about 0-1%. The survey results on the Panorama Residence Housing, Cemengkalang Village, Sidoarjo District, have an elevation of -0.20 m, slightly above the flood level – 0.30 m. This area has a high probability of flooding due to overflow from the Pucang River, which runs off (run-off water) from other areas if it rains with high intensity. Moreover, the Panorama Residence area is a dense residential area with roads and parking lots, so rainwater has a smaller chance of infiltrating and running off. After analysis, The flood discharge at the 25-year return period on the Pucang River was 72,561 m3/sec. At the same time, the cross-sectional capacity of the Pucang River was 64,402 m3/sec, so the cross-section of the Pucang River at the Panorama Residence Housing location experienced overflow. The run-off volume is 102.6 m3, while the total capacity is 565.68 m3, so the extended storage capacity is quite adequate. In rainy conditions, t = 30 minutes, the run-off volume that occurs = 30.96 m3, and the total channel length = 493.12 m, the total drainage channel capacity = 184.92 m3 is greater than the run-off volume, 30.96 m3.
Partially latent factors based multi-view subspace learning

Multi-view subspace clustering always performs well in high-dimensional data analysis, but is sensitive to the quality of data representation. To this end, a two stage fusion strategy is proposed to embed representation learning into the process of multi-view subspace clustering. This paper first propose a novel matrix factorization method that can separate the coupling consistent and complementary information from observations of multiple views. Based on the obtained latent representations, we further propose two subspace clustering strategies: feature-level fusion and subspace-level hierarchical strategy. Feature-level method concatenates all kinds of latent representations from multiple views, and the original problem therefore degenerates to a single-view subspace clustering process. Subspace-level hierarchical method performs different self-expressive reconstruction processes on the corresponding complementary and consistent latent representations coming from each view, i.e. the prior constraints imposed on different types of subspace representations are related to the appropriate input factors. Finally, extensive experimental results on real-world datasets demonstrate the superiority of our proposed methods by comparing against some state-of-the-art subspace clustering algorithms.
The Success of Using a Chain Writing Method With Comic Strip to Teach Writing to Junior High School Students

The purpose of this study is to evaluate the chain writing technique for teaching how to write descriptive text using comic strips. This study employed a quasi-experimental methodology. Both the experimental class and the control class participated in the study four times each. A test is the instrument in use. Based on the analysis of the data, the experimental class's test results for creating an English paragraph had an average score of 86.22. While the control group's test results yielded an average score of 74.13. For degrees db = 5%, the value of thitung is 4.78, while the value of ttabel is 3.15. The use of the chain writing approach is significantly impacted since thitung &gt; ttabel. The chain writing technique significantly improves the descriptive text writing abilities of first grade junior high school students. This demonstrates that learning to write more effectively through chain writing than through lecturing. It is recognized that the chain writing learning method can enhance learning outcomes based on the outputs of data processing.
The Research and Analysis of Data Mining Technology

With the rapid development of information technology, data analysis, machine learning, artificial intelligence and other technologies arises at the historic moment, followed by the exponential growth of all kinds of information, in the current era of big data, the human brain has been unable to deal with huge amounts of daily data, which leads to the phenomenon of rich data but lack of information, thus prompted the emergence of data mining technology. Computer data mining technology has greatly improved people's quality of life, met people's material and spiritual needs, and promoted the progress and development of the society.
Teaching Reform of Computer Science in Combination with Artificial Intelligence

In recent years, with the rapid landing application of artificial intelligence in various industries and the strong demand for artificial intelligence professionals, many colleges and universities nowadays respond to national policies and compete to open courses and majors related to artificial intelligence. In order to build first-class application-oriented undergraduate institutions and cultivate first-class talents, higher education institutions should actively cultivate application-oriented and compound skilled talents for the development of the whole society and local economy and industrial transformation and upgrading. In order to promote the intelligence and development of computer majors, this teaching reform proposes the teaching concept of AI + software, project-based teaching reform for courses and independent practical links, introduction of AI, reflecting engineering quality and job competence training, and strengthening the mastery, application and innovation of professional knowledge.
Body Gesture Expression Using Range of Joint’s Movement for Human Computer Interaction

Various methods of computer interaction using the human body have become available in recent times, including the method of using a part of the body or the entire body through the development of input sensors. Depth camera sensors, such as Microsoft
The Devil Hides in the Model: Reviewing Blockchain and BFT Protocols

Recent advances in blockchains and Byzantine Fault Tolerant protocols have been numerous and varied in nature. However, making a fair and consistent comparison of existing protocols is a difficult task that must begin right at the execution model. In this work, we undergo a review of several prominent blockchain protocols including their models, i.e., network synchrony, cryptographic assumptions, corruption, as well as latency and communication cost figures. This review illustrates the issues that can arise due to the lack of standardization on blockchain terminology. For example, we show that in two prominent blockchain protocols, seemingly minor technical details in the formulation leads to the execution model being strictly different from the intended one.
Pengembangan Media Pembelajaran Berbasis Android Menggunakan Ispring Suite 10 Pada Materi Turunan Fungsi Aljabar

Mathematics is the basis for other sciences and students in schools from elementary school to college must learn and master it. But in reality, many students get the results of daily math tests under the minimum achievement criteria, especially on the derivative material of algebraic functions. This study has the aim of producing and developing appropriate learning media products which will then be tested for validity and practicality based on expert validation and student response questionnaires. This research is a research and development on 30 students of class XII PH 2 SMK Negeri 1 Lamongan. This research method uses the ADDIE model. results obtained in this study are as follows: 1) The results of the validity of the media obtained from the validation of media and learning materials, get an average rating of 87.5% in the "Very Valid" category, 2) The results of the student response questionnaire to determine the practicality of the media show a rating of 90.5% in the "Very Practical" category.
Teaching Reading According to Selective Word Clusters among Children with Dyslexia

The problem of not acquiring reading skills is often debated in the education world.The purpose of this study was to develop framework with selective word clusters among children with dyslexia.This study employed survey as its research method.The findings showed that there was no significant difference by gender with t-value = -1.26,p = .211(p> .05) on teaching reading using selective word clusters for children with dyslexia by gender.The findings also showed there is no significant difference on teaching reading using interactive learning materials for children with dyslexia based on gender with a value of t = 1.24, p = .222(p> .05).The result of the Pearson correlation test on teaching reading using selective word clusters and interactive learning materials shows a significant r value = .403** (p <.005).By drawing on evidence from the data, we proposed framework for children with dyslexia which included three major word clusters.We also argue that to overcome the problems associated with reading difficulties, we need to take into account the selection of appropriate words as one of the foremost factors.We conclude that this research outcomes will allow for a richer understanding of learning to read among children with dyslexia.This lays a solid foundation for pedagogic developmental efforts by using mobile application in reading activities.
Unsupervised Domain Adaptation for Cardiac Segmentation: Towards Structure Mutual Information Maximization

Unsupervised domain adaptation approaches have recently succeeded in various medical image segmentation tasks. The reported works often tackle the domain shift problem by aligning the domain-invariant features and minimizing the domain-specific discrepancies. That strategy works well when the difference between a specific domain and between different domains is slight. However, the generalization ability of these models on diverse imaging modalities remains a significant challenge. This paper introduces UDA-VAE++, an unsupervised domain adaptation framework for cardiac segmentation with a compact loss function lower bound. To estimate this new lower bound, we develop a novel Structure Mutual Information Estimation (SMIE) block with a global estimator, a local estimator, and a prior information matching estimator to maximize the mutual information between the reconstruction and segmentation tasks. Specifically, we design a novel sequential reparameterization scheme that enables information flow and variance correction from the low-resolution latent space to the high-resolution latent space. Comprehensive experiments on benchmark cardiac segmentation datasets demonstrate that our model outperforms previous state-of-the-art qualitatively and quantitatively. The code is available at https://github.com/LOUEY233/Toward-Mutual-Information}{https://github.com/LOUEY233/Toward-Mutual-Information
Perancangan Aplikasi Point of Sale (POS) pada Karya Maju Jaya

Karya maju jaya is one of the shops that engaged in the provision of services and goods in the form of workshops. Currently at karya maju Jaya, the process of managing transactions and financial reports still uses paper media as a means of storing data, causing many weaknesses in terms of security, effectiveness from the aspect of time, higher costs to the high possibility of errors in processing and processing information. Therefore, the author decided to conduct a research that the author gave the title point of sale (POS) application design on the work of karya maju jaya with the aim of answering all the problems above. The point of sale (POS) application in this study will be described using use case diagrams and class diagrams modeling. The final product of the research that the author did in this research is a point of sale (POS) application that allows application users to process product data, manage transaction data, manage reports, manage invoices, manage profiles, change passwords, login and logout.
Sistem Pelayanan Akademik Terhadap Keluhan Mahasiswa Pada Perguruan Tinggi Untuk Mencegah Mahasiswa Berhenti Kuliah Dengan Metode Web Responsive Design

The current education industry in Indonesia continues to grow and competition is getting tougher so that more and more universities are competing to be able to provide better academic services to get students or prospective students. To be able to win the competition, universities must be able to provide maximum service quality. Good service will certainly make students feel comfortable and at home in the learning process at college so that it can reduce the number of students who stop studying, leave and drop out. Academic services as the core of business in universities must certainly be improved in order to increase the number of students who will enter the University. If the university does not know what the student's problems / obstacles are in the lecture process, it will certainly be difficult to find reasons why students drop out or why students leave. The purpose of this study is to create an academic service system for student complaints. It is hoped that the upper management of higher education can find out what problems / obstacles students are facing from the start so that they can prevent students from dropping out of college by providing correct solutions according to student needs.
Pengembangan Alat Pendeteksi Kebocoran Liquefied Petroleum Gas dengan Metode Research and Development

Indonesian people already use LPG (Liquefied Petroleum Gas) as the main fuel. LPG has a weakness in the material used is very flammable in air. LPG safety devices are currently ineffective because we cannot know the condition of LPG when we are not at home. The Research and Development method is able to produce and develop products that already exist today and have a high validity value, because they have passed various series of trials. This study develops an LPG leak detector using research and development methods. The result of this study is that the LPG leak detection tool has a call gateway notification feature on two user mobile numbers that have been setup on the microcontroller and have been tested using gas from matches and smoke. The limited test obtained an average score of 80 and is included in the good category, while the wider trial of the developed tool has proven to be more effective than the manual tool currently used. This gas leak detection tool is expected to be able to make it easier for the public to get early notification when an LPG leak occurs and immediately take preventive actions to prevent fires.
Comparison of the Social Welfare Data Classification Algorithm for Bantul Regency

Today, the main problem in the economy sector in Indonesia is related to poverty alleviation. In Bantul Regency, poverty alleviation relies on the poverty data. The Social Welfare Integrated Data set by the Ministry of Social Affairs of the Republic of Indonesia is currently can not describe the classification of the poverty. It is either the causes of the delay in handling the poverty problem in Bantul Regency. Mapping of the poverty data has a major impact to the accuracy of targets for poverty reduction programs. One of the mappings that can be do for the problems of poverty data is by using the classification method. With this classification, the poverty data can be classified into several groups according to their circumstances. These groups include the very poor, the poor, the vulnerable and the near poor. In this study, two classification methods will be tried, called Naive Bayes and K-nearest neighboor (KNN) to compare the best results based on a measurement method.
A Design of A Simple Yet Effective Exercise Recommendation System in K-12 Online Learning

We propose a simple but effective method to recommend exercises with high quality and diversity for students. Our method is made up of three key components: (1) candidate generation module; (2) diversity-promoting module; and (3) scope restriction module. The proposed method improves the overall recommendation performance in terms of recall, and increases the diversity of the recommended candidates by 0.81\% compared to the baselines.
DziriBERT: a Pre-trained Language Model for the Algerian Dialect

Pre-trained transformers are now the de facto models in Natural Language Processing given their state-of-the-art results in many tasks and languages. However, most of the current models have been trained on languages for which large text resources are already available (such as English, French, Arabic, etc.). Therefore, there are still a number of low-resource languages that need more attention from the community. In this paper, we study the Algerian dialect which has several specificities that make the use of Arabic or multilingual models inappropriate. To address this issue, we collected more than one million Algerian tweets, and pre-trained the first Algerian language model: DziriBERT. When compared with existing models, DziriBERT achieves better results, especially when dealing with the Roman script. The obtained results show that pre-training a dedicated model on a small dataset (150 MB) can outperform existing models that have been trained on much more data (hundreds of GB). Finally, our model is publicly available to the community.