Reviewerly/exHarmony huggingface dataset:
Unsupervised Context Aware Sentence Representation Pretraining for Multi-lingual Dense Retrieval

Recent research demonstrates the effectiveness of using pretrained language models (PLM) to improve dense retrieval and multilingual dense retrieval. In this work, we present a simple but effective monolingual pretraining task called contrastive context prediction (CCP) to learn sentence representation by modeling sentence level contextual relation. By pushing the embedding of sentences in a local context closer and pushing random negative samples away, different languages could form isomorphic structure, then sentence pairs in two different languages will be automatically aligned. Our experiments show that model collapse and information leakage are very easy to happen during contrastive training of language model, but language-specific memory bank and asymmetric batch normalization operation play an essential role in preventing collapsing and information leakage, respectively. Besides, a post-processing for sentence embedding is also very effective to achieve better retrieval performance. On the multilingual sentence retrieval task Tatoeba, our model achieves new SOTA results among methods without using bilingual data. Our model also shows larger gain on Tatoeba when transferring between non-English pairs. On two multi-lingual query-passage retrieval tasks, XOR Retrieve and Mr.TYDI, our model even achieves two SOTA results in both zero-shot and supervised setting among all pretraining models using bilingual data.
Explanations for Negative Query Answers under Inconsistency-Tolerant Semantics

Inconsistency-tolerant semantics have been proposed to provide meaningful query answers even in the presence of inconsistent knowledge. Recently, explainability has also become a prominent problem in different areas of AI. While the complexity of inconsistency-tolerant semantics is rather well-understood, not much attention has been paid yet to the problem of explaining query answers when inconsistencies may exist. Recent work on existential rules in the inconsistent setting has focused only on understanding why a query is entailed. In this paper, we address another important problem, which is explaining why a query is not entailed under an inconsistency-tolerant semantics. In particular, we consider three popular semantics, namely, the ABox repair, the intersection of repairs, and the intersection of closed repairs. We provide a thorough complexity analysis for a wide range of existential rule languages and for several complexity measures.
Automatic Ceiling Fan Control Using Temperature and Room Occupancy

This paper presents the design and implementation of an automatic ceiling fan speed regulator using web camera and a temperature sensor. Fans have become a very important aspect of our daily lives to present us with comfort especially in hot climates. However, they come with some attendant issues such as a person having to move to where the fan regulators are placed to be able to adjust the speed of the fan. This can be difficult as temperatures change during the day as well as at night when one is asleep. This also poses a problem for physically challenged individuals with mobility difficulties. This project seeks to design a solution that involves automatic fan regulation. This was achieved using a temperature sensor, a camera that captures images, and a system intelligent unit that processes the captured images to detect occupancy. The speed of the fan is then automatically adjusted based on the room temperature and occupancy. The system was implemented on a raspberry pi, a resource constrained edge computing environment.
Formation of media competence of future teachers using media texts

The article is devoted to the problem of forming the media competence of future teachers, where the authors propose to use media texts of different types as the main tool. It provides detailed analysis of the views of scientists on the essence and content of the definition of “media competence of the individual”, which is interpreted today in line with the psychological, pedagogical, and technological approaches. As a result of the ascertaining section, a predominantly low level of the formation of the media competence of future teachers was determined, which necessitated the theoretical substantiation and implementation of a number of pedagogical conditions. These include: the formation of a positive motivation among future specialists for the use of media in the educational process; organization of an educational media environment in higher education institutions aimed at developing media competence among future teachers; attraction of future specialists to purposeful, creative media activity and the creation of their own media product. The research introduced the testing of such conditions which provided for the systematic work of students with media texts of various types (posts on social networks and comments to them, movies, cartoons, videos of classes, lessons, and other forms of work with students, webinars, scientific, educational, and other texts in the open access, audio recordings (music, songs, audio books), iconic signs (photos, drawings, infographics)). A number of effective media texts have been identified and introduced into the educational process from the point of view of the formation of media competence of future teachers
Improving the Security of ChaCha against Differential-Linear Cryptanalysis

The stream cipher ChaCha has received a lot of attention and recently is being used as a new cipher suite in TLS 1.3, as a random number generator for operating systems (Linux, FreeBSD, OpenBSD, NetBSD, and DragonFly BSD), a proposed standardization in RFC 7634 for use IKE and IPsec, and by the WireGuard VPN protocol. Because of that, it is very important to understand and study the security of this algorithm. Previous works showed that it is possible to break up to 7 of the 20 rounds of ChaCha. In this paper, we show that a simple modification in the algorithm, namely changing the rotation distances in the Quarter Round Function, makes ChaCha more secure against all the most effective known attacks without any loss in performance. In fact, we show that with these changes, it is only possible to break up to 6 rounds of ChaCha. Therefore, it would be no longer possible to break 7 rounds of ChaCha with the best-known attacks.
The Effectiveness of Herringbone and Buzz Group Techniques to Teach Reading Comprehension for Students with High and Low Reading Habits

This research which is based on the condition that the students often find difficulties in comprehending English text aims to investigate the effectiveness of Herringbone and Buzz Group techniques in teaching reading comprehension to students with high and low reading habits. An experimental research with 2x2 factorial designs was applied in this study. The samples of this research were the students of X Busana 1 and X Boga 1 of SMK Assaâ€™idiyah 2 Kudus. Observation, questionnaires, and tests were the instruments of the research. In analyzing the data were used T-test and ANOVA. The results revealed that there was significant difference of the studentsâ€™ participation on the post-test result after being taught by using Herringbone and Buzz group techniques. Then, the result of the significance value (p value) of teaching technique and student reading habit was 0.00 &lt; 0.05. Thus, it can be stated that there is effective interaction among strategies and participation to enhance studentsâ€™ reading comprehension.
An Analysis of Logical Fallacy on Prabowo Subianto's Argumentation during 2019 Indonesia Presidential Debate

There have been a considerable number of studies of fallacy concerning with presidential debates in Western countries particularly on American presidential debates. However, the study is still rarely concerned with presidential debates in Eastern countries particularly Indonesia. Therefore, this study attempted to find the types of logical fallacies on Indonesian presidential debates committed especially by one of the presidential candidates, Prabowo Subianto, during 2019 Indonesian presidential debates. The data are utterences containing logical fallacies and the source of the data is the transcripts of four debate videos. The theory of fallacy classification by Damer (2009) was employed in this research. There were thirteen types of fallacies found in this research. The most dominant one was the fallacy of false alternatives with the percentage of 31.25%, and followed by the fallacy of drawing the wrong conclusion and appeal to irrelevant authority with the percentage of 15.62% and 9.37% respectively.
Factors Affecting the PeduliLindungi User Experience Based on UX Honeycomb

With background of Covid-19 pandemic, Indonesian state trying to make various efforts, so people comply health protocols. One of them is through PeduliLindungi application. PeduliLindungi has 3 main functions, namely tracing, tracking, warning and fencing. However, PeduliLindungi is deemed unable to meet user needs in terms of appearance and experience provided. This study aims to find factors that affect user experience in PeduliLindungi app based on UX Honeycomb. UX Honeycomb is a tool that can explain various aspects of user experience design in 7 indicators and grouped into 3 variables. The 3 variables are Think (useful, valuable, credible), Feel (desirable, credible), and Use (findable, accessible, usable). This study uses primary data by distributing online questionnaires to 404 respondents contains 15 statements that represent all UX Honeycomb variables, with 5 scales of answer choices namely strongly disagree/disagree/neutral/agree/strongly agree. From the calculation results, it is found that all variables and indicators significantly affect user experience with greatest level of influence being on the Think variable at 0,418, the second Use at 0,219, and the last is Feel at 0,151. Further research is expected can measure the level of influence on user experience by making direct comparisons with similar health apps.&#x0D;
Studentsâ€™ Attitudes toward Teachersâ€™ Written Corrective Feedback and Their Writing Skill

This study aims to explain the studentsâ€™ behavioral, cognitive, and emotional attitudes toward teachersâ€™ written corrective feedback, as well as the studentsâ€™ competence in writing skill. It is a quantitative research which was designed to prove the hypothesis with statistical analysis. The population of this study is the 3rd semester students of the English Education program of UNISNU Jepara Indonesia in the academic year of 2018/2019. The questionnaire participants are fifty students of two classes participating as the sample. The interview utilized open-ended questions. To collect data, questionnaire, interview and writing test were applied. In analyzing the data, this study uses SPSS software. The result shows that in the term of the studentsâ€™ writing skill, the mean score of first test from 50 test takers was 71.1 with the lowest score 52 and highest score 92. The second test shows the mean score was 77.8 and increased 6.7 points. The third test shows the mean score was 80.3 and increased 2.5 points. Thus, there was significant increased mean score from first test to last test. There was positive treatment that given by teacher and the participantsâ€™ positive attitude toward teachersâ€™ corrective feedback. Then, the correlation result shows that score with 95% significant level and 50 participant is 0.572. Thus, the correlation between both variables can be categorized as moderate correlation. Therefore, studentsâ€™ attitudes can give moderate impact to studentsâ€™ writing skill. In sum, knowing studentsâ€™ attitude helps the teacher to achieve learning goals.
Cohesion and Coherence in Undergraduate Studentsâ€™ Argumentative Essays

This study aims to investigate cohesion and coherence in argumentative essays written by undergraduate students at Syekh Nurjati state Islamic institute of Cirebon, West Java, Indonesia. This study used discourse analysis as a research design. Five argumentative essays were chosen based on purposive sampling. The five argumentative essays were analyzed using Halliday and Matthiessen (2014) theory that contributing to the cohesion of the text, namely cohesive devices. Then, it was analyzed using Thornbury (2005) theory about coherence. The results of this study showed that undergraduate students at Syekh Nurjati state Islamic institute of Cirebon tend to use reference more frequently than the other grammatical cohesive devices. From 755 occurrences of grammatical cohesive devices which presented in the five argumentative essays, 532 of them were in the form of reference. Besides, they also tend to use repetition more often than the other lexical cohesive devices in their argumentative essay. It always present in the five argumentative essays. Furthermore, the thematic progressions were organized well. It is showed by the occurrence of two or more thematic progressions in each argumentative essay.
Essential characteristics of personalization of learning: environmental approach

The article discusses the essential characteristics of a personified learning environment as a condition and at the same time a result of personification of the educational process; reveals school practices of personification of teaching from the positions of organization of educational communication as a productive dialogue, nonlinearity of the educational process and eventfulness of teaching. The features of personification of education in the context of digitalization of education are analyzed.
t-SNE: A Dimensionality Reduction Tool for Design Data Visualisation

One can argue that data is the 'new oil'.Yet more important than the sheer quantity of data is the question, in the context of architecture and design, how data is represented in design, as this is becoming a more relevant question to the architecture profession.We argue that data, in particular n-dimensional, is often hidden even in BIM models.Hence we propose a new way of understanding the space by (1) generate and integrate space analytics data using space syntax method as well as space usage data and (2) visualise the data using t-Distributed Stochastic Neighbour Embedding (t-SNE), an unsupervised learning and dimensionality reduction tool to help intuitively display high dimensions of data.This approach may help to discover the 'hidden layers' of the building information that may be otherwise omitted.This investigation, its proposed hypothesis, methodology, implications, significance and evaluation are presented in the paper.
Intelligent Data Processing and Optimization of University Logistics Combined with Block Chain Storage Algorithm

The traditional Hadoop-based logistic data processing platform of universities cannot fully collect and control remote data in the process of data processing and has defects such as poor efficiency, high error, and difficult query. In existing designs, devices often need to store complete block data. When retrieving or verifying specific data on the chain, a large number of blocks need to be traversed to find the corresponding data, which reduces the response speed on the user side. In addition, the traditional consensus algorithm is not suitable for resource-constrained terminal devices. Therefore, this paper proposes an intelligent data processing and optimization method of university logistics combined with block chain storage algorithm. For unstructured data on the cloud storage network, the storage information can be obtained through domain analysis, and the storage frequency can be dynamically adjusted based on the estimated data flapping. Moreover, a data storage audit scheme is designed on the cloud storage network to improve data storage efficiency. In order to ensure the integrity verification efficiency of unstructured big data cloud storage, a multilayer block chain network model suitable for university logistics data is designed by introducing block chain technology. The throughput and average occupancy under the same conditions in different environments are evaluated and analyzed, and it is verified that the proposed method is not affected by the initial priority distribution and has good stability and optimization performance. The results show that the proposed method can significantly improve the cloud storage efficiency of unstructured data, can effectively respond to a large number of requests to access data, and has good big data processing capability.
Medical Record Information System with Rapid Application Development (RAD) Method

Computer technology that is increasingly developing has created a situation that demands everything to be computerized. Science from technology has also changed the way of life of most Indonesians. The presence of information and communication technology affects the technology applied in information systems, especially the input and output mechanisms. One of them is at the Clinic which requires computer technology in its operations. The design of this website also uses 3 stages of Rapid Application Development (RAD) system design, the result of which is a website for a medical record information system. In order for clinical activities to run smoothly at the Clinic, an information system using the Rapid Application Development (RAD) method is needed because the software development process model is classified as an incremental technique and emphasizes short, short, and fast development cycles. Medical record system testing will be tested using Blackbox Testing and User Acceptance Test (UAT) testing.
The Impact that social media has had on Today's Generation of Indian Youth: An Analytical Study

Social media has become a daily habit in most people’s lives. People of all ages participate in social media, and the average Indian devotes nearly 2.4 hours per day to this one activity alone. People are able to voice their concerns and share their perspectives through the medium of social media. When it comes to understanding social media, people must first be comfortable with the notion. Users can communicate with one another and share information, thoughts, opinions, images, and videos via Internet-based programmes known as "social media.. In order to access content, share content with other users of that social media platform, and converse with other users of that social media platform, an individual must first sign up for an account and then sign in to that account. Facebook, Twitter, WhatsApp, Snap Chat, Telegram, and LinkedIn are just a few of the most prominent and frequently used social networking platforms today; others include Snap chat etc. It's noteworthy to observe that most of these social networking sites have a disproportionately high proportion of teen users. In India, adolescents and teenagers between the ages of 13 and 19 make up 31 percent of the overall number of people who use social media (Statista, 2021). Users in India between the ages of 18 and 24 make up the majority of Facebook and Instagram users in the country. We take a descriptive and analytical stance when discussing social media and its effects on young people, both good and bad, in this study. We heavily rely on the thematic analysis tool MAXQDA to draw a conclusion. We discuss all facets of social media, including both positive and bad effects. Specific areas including business, education, society, and young people are highlighted.
EVOLUTIONARY COMBINATORIAL OPTIMIZATION FOR WORD EMBEDDING (ECOWE) IN SENTIMENT CLASSIFICATION

Word embedding is widely used in various natural language processing (NLP) tasks, especially sentiment classification. Huge computational costs for training new embeddings from scratch have made pretrained word embeddings such as Word2Vec and Glove popular for reuse of word vectors. Inadequacy of a single embedding necessitated newer techniques to combine two embeddings. However, the combined embeddings proposed in existing works are static and only provide a one-size-fits-all solution regardless of the problem and dataset at hand. Optimization is a more promising technique to overcome the limitations of simplistic techniques in existing works related to combined word embeddings because optimization provides unique and optimal solutions according to the problem and dataset at hand. In this paper, a new genetic algorithm based combinatorial optimization algorithm called Evolutionary Combinatorial Optimization for Word Embedding (ECOWE) is proposed to produce combinations of word embeddings, which yield optimal accuracy for the specific sentiment classification dataset that is used. Results show that absolute percentages of improvement ranging from 1.7% to 12.9%, averaging around 5.5% and relative percentages of improvement ranging from 2.4% to 19.5%, averaging around 8.1% have been achieved over the benchmark model accuracy values for all datasets. The ECOWE accuracy values for all datasets have also been found to be statistically significant compared to benchmark accuracy values with a z-score of -2.2014 using two-tailed Wilcoxon signed rank test with 5% significance level.
Personalized Federated Learning with Moreau Envelopes

Federated learning (FL) is a decentralized and privacy-preserving machine learning technique in which a group of clients collaborate with a server to learn a global model without sharing clients' data. One challenge associated with FL is statistical diversity among clients, which restricts the global model from delivering good performance on each client's task. To address this, we propose an algorithm for personalized FL (pFedMe) using Moreau envelopes as clients' regularized loss functions, which help decouple personalized model optimization from the global model learning in a bi-level problem stylized for personalized FL. Theoretically, we show that pFedMe's convergence rate is state-of-the-art: achieving quadratic speedup for strongly convex and sublinear speedup of order 2/3 for smooth nonconvex objectives. Experimentally, we verify that pFedMe excels at empirical performance compared with the vanilla FedAvg and Per-FedAvg, a meta-learning based personalized FL algorithm.
LOCAL CULTURE-BASED READING MATERIALS FOR EFL CONTEXT

Teaching English to non-native learners is always a challenging task for any teacher in EFL contexts. One perpetual reason is the lack of exposure to the target language both orally and in writing. Debate continues about two opposing views on the utilization of authentic reading materials and the utilization of local-based reading. This paper attempts to defend the latter view by elaborating the potentials of local culture-based materials and their role in the EFL Classroom. This is a library research where the information is gathered from studies by other researchers. In EFL context, where the learners rarely have a direct acquaintance with native speakers, the benefits of making use of authentic reading book are not meaningful especially for the beginner level students due to the issues such as text readability, cultural understanding, and experiential input. Therefore, local culture-based reading materials are recommended to be developed since it suggests many benefits for the students in English as a Foreign Language context.