Reviewerly/exHarmony huggingface dataset:
Stratified Alignment Using Attention Mechanism for Video Captioning

Video captioning is one of the flourishing tasks in the emerging world. The new phenomena of combining computer vision and natural language processing are playing an important role in transforming the everyday world into a more technological pool. Natural language processing and computer vision are at the forefront of artificial intelligence, and their huge potential is already controlling more industries. Cancer screening, surgical simulation, visual characteristics description, visual retrieval, and visual description, among other things, are hot topics in NLP and CV research. In recent years, we've seen promising progress in video captioning, which is considered a hard task as it is difficult to capture the semantic congeniality between visual material and verbal descriptions. Varying granulose of visual elements corresponds to different granulose of language components (e.g., words, phrases, and sentences) (e.g., objects, visual relations, and interested regions). For converting visual content to linguistic descriptions, these congenialities can give multilevel alignments and complementary information. The proposed stratified alignment using attention mechanism (SAAM) model extracts interesting and vital features as visual highlights, object, connection explicit, event, spatial, temporal, and area and also global features by Multilevel Scene Description Network (MSDN) and Region Proposal Network (RPN). The attention mechanism is utilized here to differentiate various visuals from video to intensify the video captioning task. The model demonstrates with the benchmark datasets MSVD and MSR-VTT and evaluated by popular metrics BLEU, CIDEr, METEOR, and ROUGH-L.
IMPROVEMENT TO STUDENTS' ACHIEVEMENT IN PROCEDURAL TEXT COMPOSITION THROUGH PROCESS APPROACH-BASED MIND MAPPING EMPLOYMENT

The purpose of this study was to investigate whether there is a significant improvement in students' writing achievement after being taught using Process Approach-Based Mind Mapping, as well as which aspect of students' writing enhances the most. A quantitative study using a pre-experimental design was carried out which involved 15 ninth-grade students of SMPN 38 Bandar Lampung. The instruments used in this research were writing tests whichwere analyzed using Paired Sample T-test through SPSS 16.0. The results demonstrated that students' writing achievement significantly improved from pretest to posttest after being taught using Process Approach-Based Mind Mapping and the most enhancement aspect of writing was content. Process Approach-Based Mind Mapping could be utilized to assist students organize their thoughts by allowing for individual brainstorming using graphics and providing students with a structured writing direction. Process Approach emphasizes four key stages: planning, drafting, editing (reflecting and revising), and final version.
Learning Roles with Emergent Social Value Orientations

Social dilemmas can be considered situations where individual rationality leads to collective irrationality. The multi-agent reinforcement learning community has leveraged ideas from social science, such as social value orientations (SVO), to solve social dilemmas in complex cooperative tasks. In this paper, by first introducing the typical "division of labor or roles" mechanism in human society, we provide a promising solution for intertemporal social dilemmas (ISD) with SVOs. A novel learning framework, called Learning Roles with Emergent SVOs (RESVO), is proposed to transform the learning of roles into the social value orientation emergence, which is symmetrically solved by endowing agents with altruism to share rewards with other agents. An SVO-based role embedding space is then constructed by individual conditioning policies on roles with a novel rank regularizer and mutual information maximizer. Experiments show that RESVO achieves a stable division of labor and cooperation in ISDs with different complexity.
DeFi and NFTs Hinder Blockchain Scalability

Many classical blockchains are known to have an embarrassingly low transaction throughput, down to Bitcoin's notorious seven transactions per second limit.Various proposals and implementations for increasing throughput emerged in the first decade of blockchain research. But how much concurrency is possible? In their early days, blockchains were mostly used for simple transfers from user to user. More recently, however, decentralized finance (DeFi) and NFT marketplaces have completely changed what is happening on blockchains. Both are built using smart contracts and have gained significant popularity. Transactions on DeFi and NFT marketplaces often interact with the same smart contracts. We believe this development has transformed blockchain usage. In our work, we perform a historical analysis of Ethereum's transaction graph. We study how much interaction between transactions there was historically and how much there is now. We find that the rise of DeFi and NFT marketplaces has led to an increase in "centralization" in the transaction graph. More transactions are now interconnected: currently there are around 200 transactions per block with 4000 interdependencies between them. We further find that the parallelizability of Ethereum's current interconnected transaction workload is limited. A speedup exceeding a factor of five is currently unrealistic.
Toward a Scoping Review of Social Intelligence in Virtual Humans

As the demand for socially intelligent Virtual Humans (VHs) increases, so follows the demand for effective and efficient cross-discipline collaboration that is required to bring these VHs “to life”. One avenue for increasing cross-discipline fluency is the aggregation and organization of seemingly disparate areas of research and development (e.g., graphics and emotion models) that are essential to the field of VH research. Our initial investigation (1) identifies and catalogues research streams concentrated in three multidisciplinary VH topic clusters within the domain of social intelligence, Emotion, Social Behavior, and The Face, (2) brings to the forefront key themes and prolific authors within each topic cluster, and (3) provides evidence that a full scoping review is warranted to further map the field, aggregate research findings, and identify gaps in the research. To enable collaboration, we provide full access to the refined VH cluster datasets, key word and author word clouds, as well as interactive evidence maps.
SISTEM INFORMASI REGISTRASI KAPAL TANGKAP IKAN PADA DINAS KELAUTAN DAN PERIKANAN NTT

At the Marine Service of East Nusa Tenggara Province, the information system on Classification in the Office of the Marine Service can be said to be not optimal because there are still many applications of the classification system that are still not perfect, namely by grouping fishing vessels. Meanwhile, in terms of time, search for classification files such as types of ships. fishing vessels are still not in accordance with what is needed and also in classifying vessels according to the weight of the vessel and also the standardization of the vessel and its feasibility. So with that, the author wants to provide a solution for the East Nusa Tenggara provincial marine service office in the form of designing a web-based classification information system for fishing vessels. to be able to overcome problems in the form of grouping types of fishing vessels, and also in applying standardization of a ship based on its weight. The benefit of the application of information technology in the classification of types of fishing vessels is that it can group each type of fishing vessel based on standardization, feasibility and weight so that it is easily found and can more easily obtain clear information. The information system that will be made temporarily can be applied to the East Nusa Tenggara Provincial Marine Service.
PENGELOMPOKAN SEKOLAH MENURUT KECAMATAN DI KABUPATEN BELU MENGGUNAKAN K-MEANS BERBASIS WEBGIS

School is an education that is formal, non-formal and in formal. Access to less information about the location of schools and the spread of schools from sub-districts in Belu Regency that have an impact on the community and education implementation parties in searching or seeing related information from these schools. To overcome this problem, a school grouping system is needed based on sub-districts using webgis-based k-means that can provide convenience in seeing the location of the school and the spread of the school. Thus to see the location and spread of schools in each subdistrict in Belu regency using the K-Means method. How the k-means works to group schools by sub-district with this webgis can be more easily displayed a map of schools in Belu regency that completes a review of the school mapping. The results of this study were successfully carried out by obtaining 3 clusters consisting of cluster 1, cluster 2 and cluster 3 with the Mean Squared Error (MSE) testing is 0.035
RANCANG BANGUN E-LEARNIG PADA SMPS KATOLIK MATER INVIOLATA LARANTUKA BERBASIS WEBSITE

The learning process at the Mater Inviolata Larantuka Catholic Junior High School using conventional or face-to-face methods was disrupted due to the Covid-19 pandemic that hit Indonesia, learning at the Mater Inviolata Larantuka Catholic Junior High School which was originally conventional, namely teachers and students carried out the teaching and learning process directly in the classroom. forced to carry out online, namely students learning and teaching teachers must continue even though students are at home. The purpose of this research is to design and build a website e-learning as a medium for student learning. The research methods used in this research are interviews, literature study, observation and questionnaires. Making this application using Adobe Dreamweaver and database. The expected result in making e-learning is to facilitate the learning and teaching process between teachers and students in online. It is hoped that this e-learning can help improve teaching and learning activities at Mater Inviolata Catholic Middle School Larantuka
A Successive Variational Model for Multiplicative Noise and Blur Removal

In this paper, we propose a novel variational formulation for blur and speckle noise removal from images. The proposed model operates on the concept of applying blur removal (deblurring) and noise removal successively on the observed sample. Such successive application of despeckling and deblurring, in a Bayesian framework, is being realized by reformulating the image formation model that we also propose. The proposed optimization problem is then minimized using Euler-Lagrange formulation. Visual results suggest the potential of the proposed method in restoring images corrupted by both blur and speckle noise. Further qualitative and quantitative analysis validate its superiority over the state-of-the-art methods.
A New Quantum-Inspired Salp Swarm Optimization Algorithm for Dynamic Optimization Problem

Salp Swarm Optimization (SSO) is designed to solve various stationary optimization problems, including feature selection, neural network learning, and the controller placement problem. Several real-world applications are dynamic optimization problems (DOPs) that cannot be solved similarly to stationary optimization problems. While the SSO approach has been applied to solve many real-world optimization problems, this approach still has difficulty in identifying the optima in the dynamic and uncertain environment. It is mainly because of its original design and formulation, a consistent movement towards global optimum, and diversity losses during the dynamic optimization process. This article attempts to overcome this problem for the first time by integrating the principles of quantum computing in SSO’s equations for dynamic optimization problems. We tried to hybridize two novel paradigms for addressing issues in dynamic and uncertain environments, Viz., Salp Swarm Optimization (SSO), and the principles of quantum mechanics. An intelligent shifting operator is designed to conform to the evolutional individuals for the current environmental state. Principles of quantum computing and a newly designed operator improve SSO’s diversity and search capabilities by finding an optimal compromise between exploration and exploitation. The outcome of the proposed algorithm is evaluated on the Six Generalized Dynamic Benchmarking (GDBG) problems and compared with the results of several cutting-edge algorithms. The experimental results indicate that the performance of the Quantum-inspired SSO (QSSO) algorithm outperforms as compared to other algorithms in this domain.
Proposal for the evaluation of the quality of the Metadata for a Research Data Repository

The article seeks to analyze the current existing rules regarding the normalization of metadata for the publication of research data in a digital / Dataverse repository. For this, it is intended to identify the current proposals related to the generation of metadata for the normalization of research data, as well as to identify the problems linked to the absence of metadata quality standards in digital repositories. The aim is to find possible solutions that allow the improvement of the actual quality of metadata in digital repositories.
Design of English Translation Intelligent Recognition System Based on Data Analysis Algorithm

In the 21th century, the development and study of English translation went through many innovations and changes. With the development of intelligent algorithms, the direct teaching method, which emerged in the middle of the 20th century, became the mainstream teaching method, replacing the traditional grammar-translation teaching method, and translation was gradually rejected in the second and foreign language classes. According to the nature of big data, this paper analyzes the main technologies of the big data platform, deeply discusses the data analysis and visualization tools, puts forward data analysis algorithms, designs and constructs an Intelligent recognition system for English translation. It is expected to be of some help to English translation.
Real-Time Text Extraction from Malaysian Road Direction Signs Using Dashboard Camera

Abstract The road direction sign, which serves as a navigation tool, aids the driver in travelling on the road. A real-time text extraction from road direction signs is investigated, using input video images acquired from a dashboard camera while driving on Malaysian roads. This paper proposed a three-stage approach for real-time text extraction: (i) traffic direction signboard detection; (ii) text detection; and (iii) text recognition. In the direction signboard detection, the YOLOv5s model was applied and achieved a precision of 97%and a recall of 96%. In the text detection stage, three text detection models, EAST, DB and PAN, were investigated to select the best text detection model. The DB model is chosen with the highest IoU of 0.8238 and the shortest inference time of 0.1938s. In the text recognition stage, four models (Pytesseract, CRNN, RobustScanner and ABINet) are employed to perform evaluation and pick the best model. The CRNN is selected with the lowest character error rate of 5.85%, the highest accuracy of 97.84%, and a fast inference time of 0.324s. The proposed models, YOLOv5s, DB, and CRNN are combined to run sequentially in the real-time system during daytime conditions. It is performed by using a laptop that is equipped with a GPU and programmed in Python. The real-time text extraction system can run at an adaptive frame rate of 6.5 frames per second with an accuracy of 97%.
Cryptography based on algebraic perpendicularities

Cryptography, the mathematics of protecting secret or sensitive information, is a continuously evolving area of interest. A concrete example of this is the fact that worldwide spending on information security and risk management technology and services has been estimated to reach over $150 billion in 2021. Modern cryptography is actually not a single separate domain of mathematics but an advanced encryption scheme can be based on applications of results in number theory, such as the Euler–Fermat Theorem, or involve the discrete logarithm problem using either a primitive root of a large prime or an element of an elliptic curve over a prime field. In the background, probability theory, statistics, studies on computational models and finite geometries, etc. play a major role. Recent research has considered even DNA-based molecular cryptography systems.
OCR A level Further Mathematics Statistics (A) by Jean-Paul Muscat, pp. 362, £24, ISBN 978-1-5104-1451-8, Hodder Education (2018)

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Lexicon of medicinal plants in traditional medicine in the Dayak Tamambaloh Tribe (West Kalimantan, Indonesia): An ethnolinguistic approach

Abstract. Susanti Y, Supiandi MI, Julung H, Zubaidah S, Mahanal S. 2023. Lexicon of medicinal plants in traditional medicine in the Dayak Tamambaloh Tribe (West Kalimantan, Indonesia): An ethnolinguistic approach. Biodiversitas 24: 391-398. The Dayak Tamambaloh community in Temau Village, Embaloh Hulu Subdistrict, Kapuas Hulu District, West Kalimantan Province, Indonesia, still maintains local wisdom in utilizing plants as basic ingredients for traditional medicine. In the process of traditional medicine, the Tamambaloh Dayak people use the local lexicon. However, local knowledge related to traditional medicine in the Tamambaloh Dayak tribe is only conveyed orally from generation to generation and does not have written scientific documentation. This study aimed to record local traditional medicinal plants, lexicon, phonetics and the function of medicinal plants used by the Dayak Tamambaloh community. This study used the descriptive qualitative method. Research data were obtained through in-depth interviews and documentation. Informants in this study were traditional leaders, village midwives, shamans, and people who often use medicinal plants. Analysis of research data was to describe the spoken language of the medicinal plant lexicon into written language using elan, classifying, describing, analyzing, and interpreting the results of research on the lexicon and the function of medicinal plants in traditional medicine in the Dayak Tamambaloh community. The results obtained 33 medicinal plant lexicons, 33 medicinal plant functions, and 25 medicinal plant species in 24 families. The most widely used families were Arecaceae (2 species), Asteraceae (2 species), Blechnaceae (2 species), Bombacaceae (2 species), Liliaceae (2 species), Myrtaceae (2 species), Piperaceae (2 species), Rubiaceae (2 species), and Solanaceae (2 species). The results of this study become the basis for preserving traditional medicine in remote tribes that still maintain local wisdom.
Library Services Through Mobile Apps- Development and use by Indian Libraries

This paper aims to report on the adoption and use of mobile apps, including in-house and available in the app store by the Indian libraries for carrying out library services. An online survey was conducted to collect data from 229 LIS professionals from divergent types of libraries across the country. The study found that only 27 libraries developed their dedicated library mobile apps for catering services to the patron. The primary services offered were e-resources facility (92.60%), reference query (88.88%) and SMS alert (77.77%). The study also found the effective integration of social media apps by the libraries for sharing information regarding library services (74.67%) and upcoming events (68.12%), highlighting the library collection (62%), reference advisory (55.45%) and streaming videos lively (26.20%). The most used social media apps were WhatsApp (69.43%), Facebook (66.37%) and YouTube (65.93%). However, the unavailability of apps in offline mode and storage problems were the major hurdles cited by the professionals in using apps. The study results suggest opportunities for libraries to develop their library app to satisfy users’ information needs.
Use Pattern of E-Shodh Sindhu Resources by the Faculty Member and Research Scholar of Bangalore University: A Study

E-Resources are essential components of Library resources. Without e-resources, it is difficult to serve the user’s needs in University Libraries. The majority of Research and University Libraries are providing resources through the Consortium. e-ShodhSindhu is one of the largest Consortiums among the academic libraries; the Consortium is available for all the University and affiliated college Libraries. This paper mainly discusses the usage analysis of e-resources by the faculty through the e-Shodhsindhu Consortium and Bibliographic Databases at Bangalore University.
Reimaging Cybersecurity in Educational Practices

Cybersecurity has become increasingly important in all industries. Universities are developing academic programs in cybersecurity education in response to the demand for professionals with expertise in application areas of cybersecurity. Education should help students to deal with complex cybersecurity problems. We must ensure that cybersecurity education has a balance between breadth and depth, which integrates science, technology, management, and culture. When looking at cybersecurity education from a breadth perspective, it should provide the students with an understanding of the foundations of various components. Nevertheless, the debate can go further when taking into consideration the legal restrictions imposed on the subject. Law advocates to regulate and give a sense of order and peace for avoiding plausible controversies. Consequently, it seeks to regulate human behaviors for ensuring order, and in this case, it does so by stablishing regulations towards privacy and cybersecurity.
“FRUSTRATING AND EXCITING”: IDENTITY, COMPUTATIONAL THINKING, AND THE TEACHER IN CONTINUING EDUCATION

&#x0D; &#x0D; &#x0D; Technologies transformed the way of producing and acquiring knowledge. The pandemic proved that now they ought to be a part of the classroom. However, it is still needed that the teacher experiences using such technologies to, then, work with them. Starting from the notion that it is necessary to develop new abilities in order to be digitally literate (KARCHMER-KLEIN; SHINAS, 2012), and considering that identities are shaped by experience (IVANIC, 1998), this paper aims to understand how five students of a Graduate Program in Applied Linguistics, already experienced teachers, while writing, build their identities and reflect upon technology’s relation with the school. Therefore, it was analyzed the journals produced during a class focused on digital literacy, in which the students had to read the theory and experiment with a digital tool. It is concluded that curiosity is one of the key elements to developing digital literacy and computational thinking, and that it is through attempting that the educator improves their knowledge and acquires confidence to incorporate new digital tools in the classroom.&#x0D; &#x0D; &#x0D;