Reviewerly/exHarmony huggingface dataset:
A comparative analysis of lexical-based automatic evaluation metrics for different Indic language pairs

&lt;p&gt;With the rise of machine translation systems, it has become essential to evaluate the quality of translations produced by these systems. However, the existing evaluation metrics designed for English and other European languages may not always be suitable or apply to other Indic languages due to their complex morphology and syntax. Machine translation evaluation (MTE) is a process of assessing the quality and accuracy of the machine-translated text. MTE involves comparing the machine-translated output with the reference translation to calculate the level of similarity and correctness. Therefore, this study evaluates different metrics, namely, BLEU, METEOR, and TER to identify the most suitable evaluation metric for Indic languages. The study uses datasets for Indic languages and evaluates the metrics on various translation systems. The study contributes to the field of MT by providing insights into suitable evaluation metrics for Indic languages. This research paper aims to study and compare several lexical automatic machine translation evaluation metrics for Indic languages. For this research analysis, we have selected five language pairs of parallel corpora from the low-resource domain, such as English–Hindi, English-Punjabi, English-Gujarati, English-Marathi, and English-Bengali. All these languages belong to the Indo-Aryan language family and are resource-poor. A comparison of the state of art MT is presented and shows which translator works better on these language pairs. For this research work, the natural language toolkit tokenizers are used to assess the analysis of the experimental results. These results have been performed by taking two different datasets for all these language pairs using fully automatic MT evaluation metrics. The research study explores the effectiveness of these metrics in assessing the quality of machine translations between various Indic languages. Additionally, this dataset and analysis will make it easier to do future research in Indian MT evaluation.&lt;/p&gt;
PENGGUNAAN MEDIA PAPAN BERHITUNG PADA PEMBELAJARAN MATEMATIKA UNTUK SISWA KELAS II SDN 6 WONOGIRI

Mathematics is a natural science that has an important role in the development of science and technology. Many learners in school view maths as the most difficult subject. In fact, until now there are still students who are less interested in mathematics and the results of learning mathematics have not shown optimal results. This type of research is Research and Development (R&amp;D), which is research to produce new products or perfect existing products. that the counting board product is "Very Feasible" to use, so it can be concluded that the counting board media product is effectively used as a mathematics learning medium in grade II SD Negeri 6 Wonogiri
ANALISIS TINGKAT LITERASI MEMBACA CERITA JATAKA DI SMA BHAKTI KARYA KECAMATAN KALORAN KABUPATEN TEMANGGUNG

This study aims to determine the level of literacy in reading jataka stories. The type and approach of research used in this study is a quantitative approach. In this study, the target of the study was Buddhist students in grades 10, 11, and 12 at SMA Bhakti Karya Kaloran District, Temanggung Regency with a total of 46. Techniques in data collection using questionnaires. The results showed that literacy activities at SMA Bhakti Karya were classified in the medium category with the largest number, namely 34 students in the medium category with a percentage of 74% while the level of reading jataka stories at SMA Bhakti Karya was also included in the medium category with the largest number of 35 students entering the medium category with a percentage of 76%.
Media Pembelajaran Mata Pelajaran Bahasa Indonesia SD Di Era Digital

Education is very important in the development of children`s knowledge and insight. Education is a conscious effort in the process of changing a person`s attitude, the knowledge possessed by each individual, both his knowledge and the things he does in his life to be better than his thoughts and attitudes through teaching and training efforts. Moreover, the education of elementary school-age children in this era of digital development. The developing digital era has indeed utilized in education as a means and infrastructure for pasticipation between teachers and students. Then social science is needed for students in social life and socializing as well as adapting to the surrounding environment. Moral attitudes need to be taught from an early age so that children can face the problems they will face later. The method in this study uses the library study method. Elementary Indonesian language subjects relate to 4 aspects, namely listening, speaking, writing and reading. Elementary school Indonesian language learning requires learning media that supports teaching and learning. Digital-based learning media can help teachers and facilitate student learning.
Nanosensors from Logistics and Supply Chain Perspective: A Literature Review

Introduction: Nanosensors are one of the most recent technologies obtained from the nanoworld. They have enhanced properties with potential applications in a wide spectrum of sectors. They exhibit exceptional properties in temperature monitoring, hazardous gas and vapor detection, humidity detection, as well as pathogens, toxins, and chemical contaminant detection. Among various nanosensor applications, one of the most recent usages of nanosensor technology is in logistics and supply chain management (SCM). Aim: This study aims at investigating the potential of nanosensor technology from logistics &amp; SCM perspective, and specifically questions how can this technology contribute to food supply chains. Method: A systematic comprehensive literature review was conducted with the keywords: nanosensors &amp; logistics, nanosensors &amp; supply chain, nanosensors &amp; smart packaging, and nanosensors &amp; food logistics for the date range 2001-2022, covering a broad set of references. Findings revealed that nanosensors have significant potential in providing smart packaging, and improving traceability and visibility across all the logistics and SCM processes including end-to-end transportation and storage activities Result: Hybrids of different types of nanosensors with the existing material identification systems provide new levels of traceability and visibility in SCM, enabling accurate tracking of a variety of parameters. The study has shown that the intersection of nanotechnology and logistics &amp; SCM domains is still immature. Conclusion: This intersection is especially critical for food supply chains for meeting their special traceability requirements, and for serving food safety and organic food traceability across all stages of logistics.
role of digital reading corner in increasing the community's reading interest in Bekasi district

Background: A culture of interest in reading or literacy movement must be fostered in Indonesian society.&#x0D; Purpose: The aim is to describe the existence of a Digital Reading Corner (POCADI) managed by the Bekasi Regency Archives and Library Service, which shows an increase in people's interest in reading in the Bekasi Regency.&#x0D; Design and methods: This article uses qualitative research and a literature review. Data collection techniques in the field are observation and interviews. The research objects in the field are visitors and officers at the Digital Reading Corner location. Collections of digital media such as computers, Android tablets, e-books, LED TV, and Wi-Fi increase visitors' enthusiasm to increase their interest in reading. The efforts of the Bekasi Regency Archives and Library Service in managing POCADI include outreach to the community, educational visits from schools to POCADI and storytelling activities.&#x0D; Results: The results of the research can be concluded that the Digital Reading Corner provides benefits in increasing people's interest in reading in the Bekasi district, namely as a place to read with a collection of reading materials equipped with digital media, a place to read for people who are located far from the Bekasi Regency Public Library
Optimizing University Libraries in Palangkaraya City as a Supporting Facility for Independent Campuses

Background: Libraries play an essential role by meeting students' needs, offering a variety of library resources, facilitating access to study spaces, managing lending services, and providing information services. Kampus Merdeka is a support and effort to encourage students to obtain a variety of helpful information for their future job prospects. Purpose: This study aims to know extend on how to optimize libraries to facilitate independent campuses. Design and methods: This article uses a qualitative descriptive methodology, utilizing library reference materials as the primary means of data collection and analysis. According to Sugiyono (2018), qualitative research methods are research methods based on philosophy, which are used to research scientific conditions (experiments) where the researcher is the instrument, data collection techniques, and qualitative analysis emphasize meaning. Results: The role of libraries is in line with the government's program for national education, as stated in Law No. 2 of 2003, which states that education is a conscious and planned effort to realize the teaching and learning process so that students actively develop their potential. Optimizing university libraries in the city of Palangkaraya by utilizing information technology can be used as a means of supporting independent campuses to utilize library resources. Steps that university libraries can take to optimize libraries include: 1) Optimizing the use of information technology and 2) Promotion of libraries by utilizing websites and social media networks to improve service quality. Librarians should strive to facilitate as many opportunities as possible for students to develop into competent individuals.
Website-based Gray Literature Collection Management Darmajaya Repository

Background: College libraries not only provide printed collections such as books for lecture materials, but some of them provide collections not published to the public, usually called Gray Literature. The Gray Literature Collection is one of the main factors to consider when assessing a university library. The Gray Literature Collection contains various research results that the library/user needs. The Repository is an archival storage place designed to collect, preserve, and disseminate digital copies, especially the Darmajaya Repository Gray Literature Collection..&#x0D; Purpose: This research aims to describe how the Repository is managed at the IIB Darmajaya Library and the obstacles librarians face during the management stage.&#x0D; Design and methods: This research uses a qualitative descriptive method using case study research. Data collection uses observation and interviews. Data analysis in this research includes data reduction, data presentation, and conclusion, while a triangulation approach is used to measure validity.&#x0D; Results: Based on the findings of this research, Repository management at the IIB Darmajaya Library is carried out by determining management policies, preparing hardware and software, Human Resources, and procedures for receiving collections. The final stage is uploading files into the Darmajaya Repository system. Problems are faced in managing the Darmajaya Repository because it is still in the development process, so there are still areas for improvement in management, implementation, and presentation.
TN-MR: topic-aware neural network-based mobile application recommendation

Purpose With the increasing number of mobile applications, efficiently recommending mobile applications to users has become a challenging problem. Although existing mobile application recommendation approaches based on user attributes and behaviors have achieved notable effectiveness, they overlook the diffusion patterns and interdependencies of topic-specific mobile applications among user groups. mobile applications among user groups. This paper aims to capture the diffusion patterns and interdependencies of mobile applications among user groups. To achieve this, a topic-aware neural network-based mobile application recommendation method, referred to as TN-MR, is proposed. Design/methodology/approach In this method, first, the user representations are enhanced by introducing a topic-aware attention layer, which captures both the topic context and the diffusion history context. Second, it exploits a time-decay mechanism to simulate changes in user interest. Multitopic user representations are aggregated by the time decay module to output the user representations of cascading representations under multiple topics. Finally, user scores that are likely to download the mobile application are predicted and ranked. Findings Experimental comparisons and analyses were conducted on the actual 360App data set, and the results demonstrate that the effectiveness of mobile application recommendations can be significantly improved by using TN-MR. Originality/value In this paper, the authors propose a mobile application recommendation method based on topic-aware attention networks. By capturing the diffusion patterns and dependencies of mobile applications, it effectively assists users in selecting their applications of interest from thousands of options, significantly improving the accuracy of mobile application recommendations.
AI-Based Smart Prediction of Liquid Flow System Using Machine Learning Approach

Predicting the liquid flow rate in the process industry has proved to be a critical problem to solve. To develop a mathematical, in-depth of physics-based prognostics understanding is often required. However, in a complex process control system, sometimes proper knowledge of system behaviour is unavailable, in such cases, the complement model-based prognostics transform into a smart process control system with the help of Artificial Intelligence. In previous research a number of prognostic methods, based on classical intelligence techniques, such as artificial neural networks (ANNs), Fuzzy logic controller, Adaptive Fuzzy inference system (ANFIS) etc., utilized in a liquid flow process model to predict the effectiveness. Due to system complexity, Computational time &over fitting the performance of the AI has been limited. In this work we proposed three machine learning regression model: Random Forest (RF), decision Tree (DT) & linear Regression (LR) to predict the flow rate of a process control system. The effectiveness of the model is evaluated in terms of training time, RMSE, MAE & accuracy. Overall, this study suggested that the Decision Tree outperformed than other two models RF & LR by achieving the maximum accuracy, least RMSE & Computational time is 98.6%, 0.0859 & 0.115 Seconds respectively.
Supply Chain Management in Agriculture using Blockchain

Block chains are now firmly established as a digital technology that combines cryptographic, data management, networking, and incentive mechanisms to support the verification, execution, and recording of transactions between parties. While block chain technologies were originally intended to support new forms of digital currency for easier and secure payments, they now hold promise as a new foundation for all forms of transactions. Agribusiness stands to become a key beneficiary of this technology as a platform to execute ‘smart contracts’ for transactions, particularly for high-value produce. First it is important to distinguish between private digital currencies and the distributed ledger and block chain technologies that underlie them. The distributed and cross- border nature of digital currencies like Bit coin means that regulation of the core protocols of these systems by central banks is unlikely to be effective. Monetary authorities are focused more on understanding ‘on-ramps’ and ‘off-ramps’ that constitute the links to the traditional payments system rather than being able to monitor and regulate the currency itself. In contrast to the digital currency feature of block chain, the distributed ledger feature has the potential for widespread use in agribusiness and trade financing, especially where workflows involve many different parties with no trusted central entity
Multi-objective optimization design of scramjet nozzle based on grey wolf optimization algorithm and kernel extreme learning machine surrogate model

This study delves into the parametric design of the scramjet nozzles, utilizing the Catmull–Rom curve, to meet the high-performance design requirements. It establishes a high-dimensional, multi-objective optimization design method based on a surrogate model for the nozzle. In addition, this research proposes a surrogate model for nozzle performance to enhance the accuracy of the traditional surrogate model and prevent the multi-objective optimization design method from optimizing in an incorrect direction. This model incorporates the grey wolf optimization (GWO) algorithm and kernel extreme learning machine (KELM). Various machine learning algorithms are compared and analyzed, demonstrating that the performance parameters predicted by the GWO-KELM model are the most accurate, and the generalization of GWO-KELM is verified. Utilizing the particle swarm optimization algorithm assisted by GWO-KELM, the multi-objective optimization of the nozzle is further investigated. This study obtains the optimal Pareto front, analyzes the distribution of design variables in the Pareto solution set, and reveals the impact of geometric parameters on nozzle performance. Comparing the representative nozzle from the Pareto front with the truncated maximum thrust nozzle, it is found that the thrust, lift, and outlet Mach number increase by 3.3%, 12.2%, and 0.5%, respectively, while the outlet height decreases by 5.3%. This research contributes to overcoming the limitations of traditional design methods, which are typically time-consuming. The proposed GWO-KELM surrogate model effectively tackles the issue of low prediction accuracy.
Overcoming State and Local Barriers to Stock Inhaler Policy Implementation: Creation of a National Toolkit

Asthma is common, yet many children are undiagnosed or have inadequate access to medications. Seventeen states passed stock inhaler policies which allows schools to stock inhalers to de-escalate asthma emergencies. Since policy implementation is slow, a national stock inhaler toolkit for schools was developed. The School-Based Asthma, Allergy and Anaphylaxis Committee of the American Academy of Allergy, Asthma, and Immunology and Code Ana created a stock inhaler toolkit that pools resources nationwide. The toolkit consolidates evidence-based resources from multiple sources, including model policies from the American Lung Association, Centers for Disease Control and Prevention, and several state-led asthma programs. Components include help with understanding state-specific laws, recognizing respiratory distress, quality evidence-based staff-training, and a comprehensive resource library with documentation examples. A 58-page human-centered design inspired toolkit was produced that involved iterative input from a total of 27 participants. Collaborative agreements were established with the American Academy of Pediatrics, National Association of School Nurses, and the American Lung Association to provide a flexible framework that can be tailored to diverse school environments. Creation of a national toolkit mitigates stock inhaler policy implementation barriers and addresses state-level differences. Guideline concordant school-based asthma care is necessary. Stock inhaler programming provides an infrastructure to accomplish this at schools with varied resources across the US. Collaborative solutions to barriers are necessary to overcome persistent asthma health disparities in children.
Armed with Faster Crypto: Optimizing Elliptic Curve Cryptography for ARM Processors

Elliptic curve cryptography is a widely deployed technology for securing digital communication. It is the basis of many cryptographic primitives such as key agreement protocols, digital signatures, and zero-knowledge proofs. Fast elliptic curve cryptography relies on heavily optimised modular arithmetic operations, which are often tailored to specific micro-architectures. In this article, we study and evaluate optimisations of the popular elliptic curve Curve25519 for ARM processors. We specifically target the ARM NEON single instruction, multiple data (SIMD) architecture, which is a popular architecture for modern smartphones. We introduce a novel representation for 128-bit NEON SIMD vectors, optimised for SIMD parallelisation, to accelerate elliptic curve operations significantly. Leveraging this representation, we implement an extended twisted Edwards curve Curve25519 back-end within the popular Rust library “curve25519-dalek”. We extensively evaluate our implementation across multiple ARM devices using both cryptographic benchmarks and the benchmark suite available for the Signal protocol. Our findings demonstrate a substantial back-end speed-up of at least 20% for ARM NEON, along with a noteworthy speed improvement of at least 15% for benchmarked Signal functions.
Graph convolution networks for social media trolls detection use deep feature extraction

Abstract This study presents a novel approach to identifying trolls and toxic content on social media using deep learning. We developed a machine-learning model capable of detecting toxic images through their embedded text content. Our approach leverages GloVe word embeddings to enhance the model's predictive accuracy. We also utilized Graph Convolutional Networks (GCNs) to effectively analyze the intricate relationships inherent in social media data. The practical implications of our work are significant, despite some limitations in the model's performance. While the model accurately identifies toxic content more than half of the time, it struggles with precision, correctly identifying positive instances less than 50% of the time. Additionally, its ability to detect all positive cases (recall) is limited, capturing only 40% of them. The F1-score, which is a measure of the model's balance between precision and recall, stands at around 0.4, indicating a need for further refinement to enhance its effectiveness. This research offers a promising step towards more effective monitoring and moderation of toxic content on social platforms.
A Survey on Secure Eye: Blink-Based Morse Authentication

Real-time password authentication methods are widely used by people, but they can be exploited or defeated with the help of a hot track or high-speed scan. By using blinding hand motions in place of visible fingerprints, pin verification offers a more secure method of password entry. The procedure of blinking the eyes while taking many picture frames and coming up with a PIN is known as blink-based authentication. This paper provides a range of real-time applications that combine instant-based PIN, facial detection, and One-time Passwords to eliminate shoulder-to-shoulder and scratch tracking
On the Presentation of the Physical and Mathematical Solutions Process of Problems in Physics to Engineering Students

Community College of