Reviewerly/exHarmony huggingface dataset:
Gaussian Pre-Activations in Neural Networks: Myth or Reality?

The study of feature propagation at initialization in neural networks lies at the root of numerous initialization designs. An assumption very commonly made in the field states that the pre-activations are Gaussian. Although this convenient Gaussian hypothesis can be justified when the number of neurons per layer tends to infinity, it is challenged by both theoretical and experimental works for finite-width neural networks. Our major contribution is to construct a family of pairs of activation functions and initialization distributions that ensure that the pre-activations remain Gaussian throughout the network's depth, even in narrow neural networks. In the process, we discover a set of constraints that a neural network should fulfill to ensure Gaussian pre-activations. Additionally, we provide a critical review of the claims of the Edge of Chaos line of works and build an exact Edge of Chaos analysis. We also propose a unified view on pre-activations propagation, encompassing the framework of several well-known initialization procedures. Finally, our work provides a principled framework for answering the much-debated question: is it desirable to initialize the training of a neural network whose pre-activations are ensured to be Gaussian?
1Cademy at Semeval-2022 Task 1: Investigating the Effectiveness of Multilingual, Multitask, and Language-Agnostic Tricks for the Reverse Dictionary Task

This paper describes our system for the Se-mEval2022 task of matching dictionary glosses to word embeddings.We focus on the Reverse Dictionary Track of the competition, which maps multilingual glosses to reconstructed vector representations.More specifically, models convert the input of sentences to three types of embeddings: SGNS, Char, and Electra.We propose several experiments for applying neural network cells, general multilingual and multitask structures, and language-agnostic tricks to the task.We also provide comparisons over different types of word embeddings and ablation studies to suggest helpful strategies.Our initial transformer-based model achieves relatively low performance.However, trials on different retokenization methodologies indicate improved performance.Our proposed Elmobased monolingual model achieves the highest outcome, and its multitask, and multilingual varieties show competitive results as well.
How A Student Develops Paragraphs : A Thematic Progression Analysis of Student Works on Short Story

The issue of theme and rheme has attracted several researchers to do researchon theme and thematic progressions especially writing skill in English Language Teaching. Thematic progression is essential in writing due to its role in maintaining the continuity and information flow of the text. In other words, thematic progression highly contributes to the cohesion and coherence of a text. This study aims at exploring how a student develops a short story. The writer selected entire paragraphs from the short narrative in order to demonstrate developmental technique. The short narrative was then studied using theme progression analysis to determine how it progressed throughout the story. This study was conducted in descriptive qualitative. The researcher used Coding the paragraph, Analyzing the type of thematic progression of each Paragraph and Classifying and calculating the percentage of each type of thematic progression. In analyzing the thematic progression, there are three kinds of thematic progression: theme reiteration, the zig-zag pattern, and the multiple- rheme patterns. The findings show that the multiple- rheme pattern as the most dominant organization used within the short story, realized in 16 times (66,67%), theme reiteration is the second realized in 5 times (20,83%), and the zig-zag pattern is realized in 3 times (12,50%). The conclusion was that all types of thematic progression were used in short story.
Learning Perceptive Mental Processes in Angkola Language

This article aims to reveal the learning of patterns and cultural influences of perceptive mental processes in Angkola language with a Systemic Functional Linguistics (SFL) approach. This is because learning research tends to offer research related to language learning models and language learning media from various perspectives. Meanwhile, the content of the learning is still limited to be analyzed in certain grammar. This research offers perceptive mental process learning based on one of the regional languages in Indonesia, namely Angkola language which needs to be raised considering that this language still includes native speakers. Thus, the Angkola language must be included in the list of documentation of languages and oral traditions that should be preserved in order to maintain the wealth of the archipelago. The method used is descriptive qualitative with transitivity analysis. The results of the analysis show that the Angkola community in expressing perceptive mental processes produces two patterns, one sequential pattern and one non-sequential pattern. However, for non-sequential patterns, after the process is not followed by sensing but is followed by a phenomenon then sensing afterwards. The uniqueness and symptoms of this strangeness are found in the study of perceptive mental processes in the Angkola language. Therefore, according to the presentation of the analysis, it can be proven the consistency, prevalence and acceptance of this pattern in transitivity in the Angkola language.&#x0D; Keywords: Angkola Language, Mental Process Language, Systemic Functional Linguistics
The Autocorrelation Distribution and 2-Adic complexity of a Class of Binary Generalized Cyclotomic Sequences with Period pq

Abstract A class of binary sequences with period pq is constructed using generalized cyclotomic classes, and their autocorrelation distribution and 2-adic complexity are determined using Gauss sum and group ring theory. The results show that the autocorrelation function of the new sequences is 3-level if p ≡ 3 (mod 4) and q ≡ 3 (mod 4) which is very close to the optimal and the 2-adic complexity of these sequences is maximum if p &lt; q &lt; 2p − 1. According to the rational approximation algorithm(RAA), these sequences have quite good cryptographic properties in the aspect of autocorrelation and 2-adic complexity.
Body perception in virtual worlds: The case of Second Life

Researchers have studied the body at first as a biological subject and then as a social one. At the same time, with the evolution of technology, a new way of viewing the body is proposed, namely the virtualization of the body resulting in the emergence of the “virtual body” (avatars, cyborgs). Thanks to the “virtualized” body, the body that man now has, can be the subject of prediction, control and therefore experimentation with infinite possibilities - as everyone wishes, in virtual environments and worlds. The current study examines body-perception in the context of Second Life (SL); a virtual social world. Data is presented from the first content analysis of YouTube comments by SL users. Data are also presented from the second content analysis of ten (10) interviews of people having experienced worlds similar to Second Life. The results show that Second Life users seem more willing to experiment with the avatar and consider Second Life an environment that inspires creativity and facilitates the expression of desires regarding to the appearance of the avatar. Participants introduced to the virtual world of Second Life for the first time, claimed that SL and its avatars are attractive, with many features and in some cases very "close to reality". However, they stressed the inability of the virtual body to take on a completely “real” state and function. Finally, some limitations are mentioned as well as ideas for future research.
Design and Development of Chatbot Request System

The Web-based Chatbot Request System is Chatbot system that will handle the requests of the users to process the requested files and documents through an online website. This study will make the process less time consuming and requires minimal effort which will help and benefit the user and the university. The system is designed to handle the request of the end-users via online by making a query. The Web-based chatbot request system currently runs on a free hosting website with two sets of account:(1) the administrator which are intended to be handle by employee who will process the requests, (2) the users account for the students of NEUST. The system has different functions and level of access based on the respective accounts. The system was developed using the Agile Model as the standard development method of the system. The system uses HTML, CSS as its front-end and PHP, JavaScript, and MySQL as its programming language for the back end. Based on the review of IT Experts and end-users, the Web-based chatbot request system obtained a rating of 3.54 with a qualitative description of highly effective.
Event Management using End-to-End Image Encryption: A Review

Abstract: Encryption-then-Compression (EtC) systems are used to securely transmit images over an untrusted channel provider, and a novel grayscale-based block scrambling image encryption method is developed to improve the security of EtC systems. This approach is intended to make encryption-then-compression (EtC) systems more secure. In comparison to the new encryption technology, the suggested scheme allows for smaller block sizes and a greater number of blocks.Despite the fact that the original image has three colour channels, photos encrypted using the suggested method contain less colour information due to the usage of grayscale images to encrypt the data. These features boost security against threats like jigsaw puzzle solvers and brute-force attacks, among other things. Apart from that, despite the fact that the encrypted photos do not include any colour information, it enables for colour sub-sampling, which can improve the compression speed of the images. In a test, encrypted photographs were posted to and later downloaded from social networking sites, and the findings demonstrated that using advanced compression algorithms, the suggested strategy is successful for ETC systems while still keeping excellent compression performance. Keywords: Event Management, image compression, non-local network, attention mechanism.
Analisis Penerapan Metode Scrum Pada Pengembangan Sistem Informasi Akuntansi Koperasi

Koperasi are one of the drivers of the economy in Indonesia. But in the operations of the koperasi, there are many problems such as lack of information, unrecorded deposits, the amount of credit that exceeds capacity, and lack of accuracy in accounting calculations. The study used the object of the employee koperasi of SWCU (Satya Wacana Christian University) Salatiga by conducting an observation process on the ongoing koperasi business system. The design of a koperasi accounting information system using a web platform with the basic model of the Scrum Process. The Scrum process model is a software development management framework with iterative and incremental characteristics and properties. The koperasi accounting information system that is built based on Scrum can reduce previous processing errors and can increase the speed and accuracy of data processing so that in the short term it can improve koperasi performance. System performance is tested by black box testing method to ensure all features can work properly. The test results showed that the system built can help reducing problems occurred in the operational process of koperasi, particularly in the accounting process. The results show that the system is more efficient to reduce problems occurred in the operational process of koperasi, reduce time in transaction processing, increase accuracy in the accounting process, and make it easier for users to produce reports with high validity.
THE USE OF INFORMATION AND COMMUNICATION TECHNOLOGIES IN DISTANCE TEACHING OF PHYSICAL AND MATHEMATICAL DISCIPLINES IN THE TRAINING OF ENVIRONMENTAL SPECIALISTS

The role of physical and mathematical disciplines in the formation of professional competencies of ecologists is considered. The main provisions of the program of scientific and methodological research of the Department of General and Medical Physics of International Sakharov Environmental Institute of Belarusian State University on the use of information and communication technologies in distance teaching of physical and mathematical disciplines in the training of environmental specialists. The results and prospects of the research are discussed.
Improving Knowledge Graph Embedding via Iterative Self-Semantic Knowledge Distillation

Knowledge graph embedding (KGE) has been intensively investigated for link prediction by projecting entities and relations into continuous vector spaces. Current popular high-dimensional KGE methods obtain quite slight performance gains while require enormous computation and memory costs. In contrast to high-dimensional KGE models, training low-dimensional models is more efficient and worthwhile for better deployments to practical intelligent systems. However, the model expressiveness of semantic information in knowledge graphs (KGs) is highly limited in the low dimension parameter space. In this paper, we propose iterative self-semantic knowledge distillation strategy to improve the KGE model expressiveness in the low dimension space. KGE model combined with our proposed strategy plays the teacher and student roles alternatively during the whole training process. Specifically, at a certain iteration, the model is regarded as a teacher to provide semantic information for the student. At next iteration, the model is regard as a student to incorporate the semantic information transferred from the teacher. We also design a novel semantic extraction block to extract iteration-based semantic information for the training model self-distillation. Iteratively incorporating and accumulating iteration-based semantic information enables the low-dimensional model to be more expressive for better link prediction in KGs. There is only one model during the whole training, which alleviates the increase of computational expensiveness and memory requirements. Furthermore, the proposed strategy is model-agnostic and can be seamlessly combined with other KGE models. Consistent and significant performance gains in experimental evaluations on four standard datasets demonstrate the effectiveness of the proposed self-distillation strategy.
IMPLEMENTATION PERSONALLY FOCUS-BASED LEARNING COMPUTER TECHNOLOGIES

In article to be considered problems personally focused training at use of computer technologies, a method of telecommunication projects.
FINDING'S AND RECOMMENDATIONS FOR THE FUTURE GROWTH OF LIBRARY SCIENCE AND COMMUNITY INFORMATION CENTRES IN THE STATE (WITH SPECIAL REFRENCE TO THE KARNATAKA STATE)

Library and the information science can be said as the right of the Indian citizens to know by getting the information through the information science or library science. Although Government of India and Government of Karnataka have made efforts in developing e-governance projects with a noble mission to provide right information to the right user pertaining to social, economical, political, cultural and educational aspects using Information and communication Technology in the form of kiosks or community Information Center’s website. In spite of all these efforts, on the country, the present result of the study shows lack of automated Community Information Centers to support the rural society in meeting their timely information needs pertaining to agriculture, education, health and family welfare and women and child welfare. The Government agencies have family welfare and women and child welfare .The Government agencies have been providing huge amount of resources but for the implementation of the pragrammes have not been up to the mark. And the lack of information science infrastructure in rural and remote parts of Karnataka has been hurdle for the poor regions of the state.
Incorporating Cross-Cultural Competence into the ISOL Programme through Cultural-Based Materials and Corpus-Based Approach

This paper discusses the integration of cross-cultural competencies in the ISOL teaching programme based on the materials used during learning. ISOL is an Indonesian language learning programme for foreign speakers that often establishes materials on cultural and socio-humanistic aspects of Indonesian culture. The paper data were in the forms of discourse construed in the textbooks as learning materials. The data sources were three textbooks from three well-established ISOL learning institutions in Indonesia. Based on the qualitative content analysis, it can be stated that the incorporation of cross-cultural competence in ISOL was realized not only through the integration of competence in learning materials but also through the aspects of learning preparation as well-designed in the syllabus and teaching goals. In addition, cross-culture competence was also manifested in grammar teaching and skills mentoring activities. There was evidence regarding the evaluation aspect, namely the concept of competence already used as essential guidance in the final project. Moreover, I also extended the discussion of the results concerning the corpus-based approach to determine the way to collect and manage materials that contained cultural value as a part of the programme.
A multimedia recommendation model based on collaborative graph

As one of the main solutions to the information overload problem, recommender systems are widely used in daily life. In the recent emerging micro-video recommendation scenario, micro-videos contain rich multimedia information, involving text, image, video and other multimodal data, and these rich multimodal information conceals users' deep interest in the items. Most of the current recommendation algorithms based on multimodal data use multimodal information to expand the information on the item side, but ignore the different preferences of users for different modal information, and lack the fine-grained mining of the internal connection of multimodal information. To investigate the problems in the micro-video recommendr system mentioned above, we design a hybrid recommendation model based on multimodal information, introduces multimodal information and user-side auxiliary information in the network structure, fully explores the deep interest of users, measures the importance of each dimension of user and item feature representation in the scoring prediction task, makes the application of graph neural network in the recommendation system is improved by using an attention mechanism to fuse the multi-layer state output information, allowing the shallow structural features provided by the intermediate layer to better participate in the prediction task. The recommendation accuracy is improved compared with the traditional recommendation algorithm on different data sets, and the feasibility and effectiveness of our model is verified.
Remote Run-Time Failure Detection and Recovery Control For Quadcopters

We propose an adaptive run-time failure recovery control system for quadcopter drones, based on remote real-time processing of measurement data streams. Particularly, the measured RPM values of the quadcopter motors are transmitted to a remote machine which hosts failure detection algorithms and performs recovery procedure. The proposed control system consists of three distinct parts: (1) A set of computationally simple PID controllers locally onboard the drone, (2) a set of computationally more demanding remotely hosted algorithms for real-time drone state detection, and (3) a digital twin co-execution software platform — the ModelConductor-eXtended — for two-way signal data exchange between the former two. The local on-board control system is responsible for maneuvering the drone in all conditions: path tracking under normal operation and safe landing in a failure state. The remote control system, on the other hand, is responsible for detecting the state of the drone and communicating the corresponding control commands and controller parameters to the drone in real time. The proposed control system concept is demonstrated via simulations in which a drone is represented by the widely studied Quad-Sim six degrees-of-freedom Simulink model. Results show that the trained failure detection binary classifier achieves a high level of performance with F1-score of 96.03%. Additionally, time analysis shows that the proposed remote control system, with average execution time of 0.49 milliseconds and total latency of 6.92 milliseconds in two-way data communication link, meets the real-time constraints of the problem. The potential practical applications for the presented approach are in drone operation in complex environments such as factories (indoor) or forests (outdoor).
Phonemic Awareness as Predictor of Word Decoding Ability among Bachelor of Science in Information Technology Students

This descriptive correlational study aimed at the level of Phonemic awareness as a predictor of Word Decoding ability among BS-IT students using a total enumeration technique that involves students enrolled in the course program. Moreover, it sought to determine the significant relationship between the two variables. To verify, three different tests were being utilised to collect the necessary data, i.e., a listening test for measuring the respondents' level of awareness of words with critical sounds; a phonetic transcription test to identify the respondents' level of awareness of sound-symbol relationship; and spelling test to know the respondents' level of ability for transcriptions to be translated to its American Standard English spelling. After the data had been collected and tabulated, it was interpreted that the students have a high level of Phonemic awareness with a mean of 3.66. Moreover, their Word Decoding ability resulted in a high level with a mean of 3.93. Further, it is being noticed that there is a tremendous significant relationship between the two variables with a p-value of 0.0000000859. With these findings, the researcher encourages the school, administrators, and teachers to give more exposure to sound-word connections by engaging the students with activities involving speaking, listening, reading, and writing activities and practice-based tasks.
Predicting Embedding Reliability in Low-Resource Settings Using Corpus Similarity Measures

This paper simulates a low-resource setting across 17 languages in order to evaluate embedding similarity, stability, and reliability under different conditions. The goal is to use corpus similarity measures before training to predict properties of embeddings after training. The main contribution of the paper is to show that it is possible to predict downstream embedding similarity using upstream corpus similarity measures. This finding is then applied to low-resource settings by modelling the reliability of embeddings created from very limited training data. Results show that it is possible to estimate the reliability of low-resource embeddings using corpus similarity measures that remain robust on small amounts of data. These findings have significant implications for the evaluation of truly low-resource languages in which such systematic downstream validation methods are not possible because of data limitations.