Reviewerly/exHarmony huggingface dataset:
VLMbench: A Compositional Benchmark for Vision-and-Language Manipulation

Benefiting from language flexibility and compositionality, humans naturally intend to use language to command an embodied agent for complex tasks such as navigation and object manipulation. In this work, we aim to fill the blank of the last mile of embodied agents -- object manipulation by following human guidance, e.g., "move the red mug next to the box while keeping it upright." To this end, we introduce an Automatic Manipulation Solver (AMSolver) system and build a Vision-and-Language Manipulation benchmark (VLMbench) based on it, containing various language instructions on categorized robotic manipulation tasks. Specifically, modular rule-based task templates are created to automatically generate robot demonstrations with language instructions, consisting of diverse object shapes and appearances, action types, and motion constraints. We also develop a keypoint-based model 6D-CLIPort to deal with multi-view observations and language input and output a sequence of 6 degrees of freedom (DoF) actions. We hope the new simulator and benchmark will facilitate future research on language-guided robotic manipulation.
Asset Tracking System using Blockchain

Abstract— The technique of following a product or a batch of things throughout the supply chain to ensure that the products that reach clients are authentic and tamper-proof is known as asset tracking. The ultimate goal of an asset monitoring system is to track products along the supply chain, verifying that they haven't been tampered with and, if they have, pinpointing where the tampering took place. Traditional tracking technologies, such as BLE (Bluetooth Low Energy Beacon), which works within a limited range, RFID, and above-mentioned systems, are expensive and centralised. So, for this project, we'll use Blockchain Technology, which is an immutable, tamper-proof, decentralised distributed ledger with security features that allows us to establish an asset tracker that can follow our product along the supply chain. Ethereum is used to implement the system. Unlike other methods, there are no hardware components or large gadgets that may be removed from the original object and attached to the copy. Keywords— Blockchain, Supply Chain, Smart Contract, Keccak-256, Ethereum,GUI
Organization of Modular Training in Education

Annotation: Modular learning is a method of organizing the learning process based on the modular presentation of educational information. The essence of modular teaching is that the content of teaching is divided into autonomous organizational and methodological modules, the content and scope of which can vary depending on the didactic goals, profile and level of students. The combination of modules should provide the necessary degree of flexibility and freedom in teaching (and independent learning) a particular category of students and in selecting and assembling specific learning material needed to achieve specific didactic and professional goals. Keywords: credit module system, educational skills, credits, educational content, knowledge, skills and competencies.
Image Style Transfer Using Machine Learning

Abstract: The principle of Image style transfer is to define two distance functions, one that describes the content image and the other that describes the style Image. By using these content and Style Images[5][6] as inputs we will begetting the desired output which has the content image merged with style image. The output will be in the graphical model of the content image. In summary, we’ll take the base input image, a content image that we want to match, the style image that we want to match by undergoing the process of convolutional neural network [7] firstly the content image is undergoing the process of content loss and style image as style loss after content loss and style loss it will undergo the process of gram matrix and the final image will be formed. Keywords: Content Image, Style Image, Content Loss, Style Loss, Convolutional Neural Networks, Gram Matrix Deep Lab Semantic Segmentation.
THORN: Temporal Human-Object Relation Network for Action Recognition

Most action recognition models treat human activities as unitary events. However, human activities often follow a certain hierarchy. In fact, many human activities are compositional. Also, these actions are mostly human-object interactions. In this paper we propose to recognize human action by leveraging the set of interactions that define an action. In this work, we present an end-to-end network: THORN, that can leverage important human-object and object-object interactions to predict actions. This model is built on top of a 3D backbone network. The key components of our model are: 1) An object representation filter for modeling object. 2) An object relation reasoning module to capture object relations. 3) A classification layer to predict the action labels. To show the robustness of THORN, we evaluate it on EPIC-Kitchen55 and EGTEA Gaze+, two of the largest and most challenging first-person and human-object interaction datasets. THORN achieves state-of-the-art performance on both datasets.
Optimal Extragradient-Based Bilinearly-Coupled Saddle-Point Optimization

We consider the smooth convex-concave bilinearly-coupled saddle-point problem, $\min_{\mathbf{x}}\max_{\mathbf{y}}~F(\mathbf{x}) + H(\mathbf{x},\mathbf{y}) - G(\mathbf{y})$, where one has access to stochastic first-order oracles for $F$, $G$ as well as the bilinear coupling function $H$. Building upon standard stochastic extragradient analysis for variational inequalities, we present a stochastic \emph{accelerated gradient-extragradient (AG-EG)} descent-ascent algorithm that combines extragradient and Nesterov's acceleration in general stochastic settings. This algorithm leverages scheduled restarting to admit a fine-grained nonasymptotic convergence rate that matches known lower bounds by both \citet{ibrahim2020linear} and \citet{zhang2021lower} in their corresponding settings, plus an additional statistical error term for bounded stochastic noise that is optimal up to a constant prefactor. This is the first result that achieves such a relatively mature characterization of optimality in saddle-point optimization.
Effect of Lean and Agile Supply Chain Practices on the Organizational Performance of Manufacturing Companies in Oman

The main purpose of this study is to investigate the effect of lean and agile supply chain practices on the performance of the manufacturing companies in Oman.In recent years, research on supply chain sustainability is still scarce.as a competitive priority, where companies are struggling with how to balance the effectiveness of the supply chain and the pressures of strengthening the supply chain.The study used quantitative data collected through survey of 130 respondents from the manufacturing companies in Oman.The analysis revealed that lean management play an important role in improving organizational performance as compared to the agile management.We further asserted that lean and agile firms need to underpin with different strategies to gain competitive advantage within the industry.There is great importance in the presence of agile and lean Management in companies, which helps supply chains to perform their work in a flexible and rapid manner.
The Society 5.0 Landscape and Research Agenda

Different approaches are adopted in this paper to develop a conceptual Society 5.0 landscape overview as well as a roadmap and a preliminary research agenda. In the first place, we employed Social Network Analysis (SNA) on Twitter to identify the communities and communication around Society 5.0, followed by content analysis of two collected document repositories, one a set of academic publications and one a set of popular press articles on Society 5.0. We used the results of these investigations to develop a conceptual landscape overview of Society 5.0 using the themes that were identified during the analysis. The landscape model was subsequently used as a baseline to develop an initial research agenda for Society 5.0 studies. Anyone interested in doing research or adopting the Society 5.0 vision should benefit from our contributions.
Classical Musicians v. Copyright Bots

The COVID-19 pandemic forced classical musicians to cancel in-person recitals and concerts and led to the exploration of virtual alternatives for engaging audiences. The apparent solution was to livestream and upload performances to social media websites for audiences to view, leading to income and a sustained social media presence; however, automated copyright enforcement systems add new layers of complexity because of an inability to differentiate between copyrighted content and original renditions of works from the public domain. This article summarizes the conflict automated copyright enforcement systems pose to classical musicians and suggests how libraries may employ mitigation tactics to reduce the negative impacts when uploaders are accused of copyright infringement.
Active Fairness Auditing

The fast spreading adoption of machine learning (ML) by companies across industries poses significant regulatory challenges. One such challenge is scalability: how can regulatory bodies efficiently audit these ML models, ensuring that they are fair? In this paper, we initiate the study of query-based auditing algorithms that can estimate the demographic parity of ML models in a query-efficient manner. We propose an optimal deterministic algorithm, as well as a practical randomized, oracle-efficient algorithm with comparable guarantees. Furthermore, we make inroads into understanding the optimal query complexity of randomized active fairness estimation algorithms. Our first exploration of active fairness estimation aims to put AI governance on firmer theoretical foundations.
FRONESTICAL APPROACH TO THE FORMATION OF PROFESSIONAL RESPONSIBILITY OF FUTURE SPECIALISTS OF TECHNICAL SPECIALTIES: MONITORING BY MEANS OF INFORMATION AND COMMUNICATION TECHNOLOGIES

The rapid development of information and communication technologies (ICT) and their active use in the educational process has been hugely intensified by the COVID-19 pandemic. In the process of acquiring generic and specific competencies and determining learning outcomes, it is important to develop a system of observations that will allow to respond quickly to problems arising in educational practice. The article presents the results of monitoring the ability to make responsible decisions by future specialists of engineering specialties. The virtual educational environment ATutor of Ternopil Ivan Pulyuy National Technical University (Ukraine), created on the basis of the learning management system, has been used for data collection. The results of the study led to identifying the differences in the algorithm of responsible decision-making by students of engineering specialties depending on gender, year of study and the specifics of the chosen specialty. All these factors are to be taken into account in pedagogical practice for the formation of professional responsibility. A phronestic approach to understanding the content and essence of professional responsibility in the anthropogenic environment has been discussed. This approach takes into consideration the specifics of ethical knowledge and focuses on sustainable individual priorities to determine personal responsibility in a particular situation in accordance with social needs. The necessity of reconsideration of responsibility as an element of phronestic knowledge is substantiated; its importance in the training of future engineering specialists is specified. Prospects for further research on the use of the phronestic approach in professional pedagogy are formulated, the results of which can serve as guidelines for modernizing the strategy of teaching social sciences in higher education.
Developing "EMBER": A Fantasy Puzzle Adventure Game with An Approach to Agile by Applying Game-Scrum Methodology

Digital games development process is often done using traditional methods. Many digital game developers believe that the game development process cannot be equated and use other software development methods because game development is not only focused on technical processes such as programming and coding but also creative processes such as asset and display design. In this study, the process of developing a fantasy adventure puzzle game was carried out using the Game-Scrum approach, a method modified from the Agile Scrum method. As well as the software development process using the agile method, game development using this method is carried out with an iterative process where each process allows an update of the feedback given to each sprint backlog. At the end of the study it was concluded that although there were still some things that had to be adjusted, basically the Game Scrum method could be adapted for the development of a digital game.
Non-Markovian entanglement dynamics of three independent qubits within atomic-cavity system

Abstract All realistic quantum systems will interact with their environments. This fact presents challenges to the implementation of quantum systems for practical systems. One of the most important quantum resources is the implementation of entanglement. In this paper, we investigate the interplay between the effects of noisy environments and the dynamics of entanglement. The open quantum system model that will be used is cavity quantum electrodynamics (CQED) with three-qubit interacting independently with a variation of environmental model. We use master equation to describe the dynamics of the open quantum system and a lower bound concurrence ( C LBC ) to measure the entanglement of tripartite qubit. We derive the exact dynamics of each model and use C LBC method proposed by Li et.al to visualize entanglement dynamics. By adjusting the environmental parameters, we also found revivals and dark-periods of entanglement which are unique to non-Markovian processes.
Asymptotic behaviour of <i>d</i>-variate absorption distributions, <i>d</i> = 1, 2

Abstract In this work we study the asymptotic behavior of univariate and bivariate absorption discrete q -distributions. Specifically, the pointwise convergence of the univariate absorption distribution to a deformed Gaussian one and that of the bivariate absorption to a bivariate deformed Gaussian one, are provided.
A Web Scraping of Chemical Compounds with an Anti-Drug Feature Using IoT

As a result of the COVID-19 epidemic, there has been an increase in the demand for electronic education apps in schools and colleges in recent years. The purpose of this paper is to develop an educational application for chemistry students at different levels of study that will allow them to obtain precise information on chemical substances in a timely and safe manner. This program uses a web scraping technique by applied a RESRful API to extract information from websites, which is then sent to the student's account. Furthermore, due to the use of the Internet of Things, the application has an anti-explosives and narcotics property using (IOT). The application can retrieve and save information entered by the user on chemical compounds with a high level of security. The medication's chemical formula, as well as the covalent and ionic bonding of compounds, can be displayed. It also has a database that lists all of the hazardous substances. If a user enters a dangerous compound containing narcotics more than four times, an alarm message is sent to the administrator via the Internet of Things.
Databases In The 21’st Century

Abstract: NoSQL databases are the 21’st century databases created to defeat the disadvantages of RDBMS. The objective of NoSQL is to give versatility, accessibility and meet different necessities of distributed computing.The main motivations for NoSQL databases systems are achieving scalability and fail over needs. In the vast majority of the NoSQL data set frameworks, information is parceled and repeated across numerous hubs. Innately, the majority of them utilize either Google's MapReduce or Hadoop Distributed File System or Hadoop MapReduce for information assortment. Cassandra, HBase and MongoDB are for the most part utilized and they can be named as the agent of NoSQL world.
Analisis Indeks Kekeringan Menggunakan Standardized Precipitation Index (SPI) Method pada Daerah Kabupaten Timor Tengah Selatan

Due to the low rainfall, it is relatively uneven in each sub-district in Timor Tengah Selatan (TTS) Regency. It causes some rivers to be drought-prone in the dry season. This study aims to determine the largest drought index and map the drought distribution in the South Central Timor (TTS) Regency. The drought index analysis uses the Standardized Precipitation Index (SPI) Method. The data used is monthly rainfall data for ten years (2009-2018) of ten rain stations. Then, mapping of drought distribution rainfall using ArcGIS Software. The results of the drought index analysis showed that in the 1-month deficit period, the largest drought index was -3.61, which occurred in March 2014 at the Oeekam Rain Station. In the 3-month deficit period, the largest drought index was -3.19, which occurred in March 2010 at the Nulle Rain Station and in November 2015 at the Kesetnana Rain Station. The findings of the drought distribution map study suggest that during the 1-month shortfall period, all sub-districts experienced drought in January, February, and April. Meanwhile, in the 3-month deficit period, drought occurs evenly for all sub-districts only in June.
UTILIZATION OF ANIMATED VIDEOS USING EDPUZZLE APPLICATION IN TEACHING EARTH &amp; SPACE 9

Many teachers use video to instruct students, whether it's to adopt a distance learning modality or to solve problems during a pandemic situation.They also use it as supplementary material to make the lesson easy to understand.Online teachers provide recorded video discussions to keep those students who are losing interest in attending online classes updated with the lesson discussed.However, the teachers can't notice whether the students watched and understood the recorded video given to them or not.Creating animated videos using Edpuzzle is then chosen as an interesting alternative.The purpose of this study was to determine the acceptability of animated videos using Edpuzzle in teaching Earth & Space 9. So, the experimental design was used.And to select the number of respondents, simple random sampling was done.The respondents were Grade 9 Atlas and Apollo of Cabuyao Integrated National High School.Each section consisted of 40 students giving a total of 80 participants accounted in the study.Grade 9 Atlas (experimental group) utilized the animated videos using Edpuzzle while Grade 9 Apollo (control group) utilized the animated videos without using Edpuzzle.This study showcased some of the topics in Earth and Space specifically, volcanoes.The objectives and topics are similar in both groups but not in the use of Edpuzzle.They were given assessments needed to meet the objectives of the study.Analysis of data revealed that utilization of videos using Edpuzzle is better than the traditional ones.It can really increase the academic performance of the students.Furthermore, it can be quite beneficial to teachers in terms of ensuring that their students have viewed and comprehended the video/s they have provided.
Cyberbullying pada Kolom Komentar Tiktok @Denise_Cariesta dan Implementasinya sebagai Media Pembelajaran

This study aimed to describe cyberbullying actions carried out by users in @denisecariesta TikTok's comment column and its implementation as a learning media. This study used a qualitative descriptive research method with data sources in the form of words and sentences in @DeniseCharista TikTok's comment column. Data were collected using documentation, reading, and note-taking techniques, which were then analyzed using the Analysis Interactive Model from Miles and Huberman. The results obtained from this study are many users who abuse one by using the comment column as a booth to carry out cyberbullying, which can harm other parties. The research result reveals that six forms of cyberbullying were found in @denisecariesta TikTok's comment column. Further, TikTok can be an alternative medium for learning literature and language in schools, especially at the senior high school level.
DEVELOPMENT OF HISTORICAL SCIENCE IN THE HIGHER SCHOOL OF CHUVASHIA (1967–2022): TO THE 55th ANNIVERSARY OF THE I.N. ULYANOV CHUVASH STATE UNIVERSITY

In modern conditions, the formation and evolution of the humanities in Russia is of particular relevance. Among the fundamental foundations of the socio-humanitarian sciences, the historical sphere of scientific knowledge occupies a central place. It is impossible to build the future without understanding the events of the past. The study of the historical science development in our state was conducted both by science institutes and by higher education institutions. Scientists often combined teaching and research. This trend was typical for the whole country, including its regions. The Chuvash Republic was no exception. In general, historical education on the territory of Chuvashia began to emerge in 1930. Between 1930 and 1967, the Chuvash State Pedagogical Institute carried out the professional historical staff training. A new stage in the development of higher historical education in the Chuvash ASSR began in 1967. The opening of the Chuvash State University named after I.N. Ulyanov (CSU) was a landmark event. The article presents the formation and development of historical science at CSU, which included a number of independent areas: opening of new specialties, creation of departments and laboratories, formation of scientific schools, work of the dissertation council and training of scientific and pedagogical staff, holding conferences, publishing scientific journals, proceedings and monographs, implementing grants, etc. Each of these activities is a significant work behind which stand prominent scientists of the Republic. It is pointed out that for its 55th anniversary, the Chuvash State University named after I.N. Ulyanov created a galaxy of talented historians, whose names are known outside Chuvashia. The change of generations is an integral element of the transfer of knowledge and traditions. Any research team, first of all, is a combination of the wisdom and working capacity of leading specialists, as well as acquiring new knowledge by novice researchers. Continuity and traditions are important components of the historical scientific schools of Chuvashia.
Sampling <i>β</i>-normal linear λ-terms

Abstract Leveraging our recent work on the enumeration of β -redices in closed linear λ-terms, we present an algorithm for sampling β -normal closed linear λ-terms and their corresponding maps. Such terms correspond to proofs of tautologies in implicational linear logic and their generation is of interest in various domains, including the testing of linear logic theorem provers.
Fast Population-Based Reinforcement Learning on a Single Machine

Training populations of agents has demonstrated great promise in Reinforcement Learning for stabilizing training, improving exploration and asymptotic performance, and generating a diverse set of solutions. However, population-based training is often not considered by practitioners as it is perceived to be either prohibitively slow (when implemented sequentially), or computationally expensive (if agents are trained in parallel on independent accelerators). In this work, we compare implementations and revisit previous studies to show that the judicious use of compilation and vectorization allows population-based training to be performed on a single machine with one accelerator with minimal overhead compared to training a single agent. We also show that, when provided with a few accelerators, our protocols extend to large population sizes for applications such as hyperparameter tuning. We hope that this work and the public release of our code will encourage practitioners to use population-based learning more frequently for their research and applications.