Reviewerly/exHarmony huggingface dataset:
Modern english teachers – innovators

To start with, the word innovation has been quite a buzzword across-the-board and in the context of ELT in particular. Teaching is an old trade though it is constantly refined through myriads of approaches, philosophies and techniques. Similarly, the task remains to be the same before the teachers of present times which is to blend teaching with innovation and harness its benefits to enhance learning and teaching experiences in the long run. To put that in perspective, modern English teachers are the ones who are multifaceted in terms of skillset and are ready to embrace novelties and the challenges that come along down the path.
Ekstraksi Fitur Menggunakan Haar Wavelet Transformation Pada Klasifikasi Jenis Bakteri Air

Bacteria is one of the species that live in groups and is on some media close to humans. As the media closest to humans, water has become one of the most expensive and mutating places for bacteria. Various kinds of bacteria live in raw water that comes from some sources of water that often cause various diseases for humans. Many good diseases that transmit and do not transmit are often found in water, especially in households. With the various problems that arise, there needs to be a system that can detect and determine the type of bacteria in the water. The researchers built a bacterial classification system in water to facilitate the filter and sterilization process from these problems. This system utilizes the haar wavelet method, which has a good reputation in the transformation process. The accuracy results obtained in this study are very satisfactory, with an accuracy rate of 90% in detecting the type of bacteria.
Pendekatan Analisis Derau Putih untuk Arus Stokastik dari Gerak Brown Subfraksional

The subfractional Brownian motion is a Gaussian generalization of the Brownian motion whose increments are not stationary. In this paper we study the stochastic current of the one dimensional subfractional Brownian motion. For this purpose we use the method from white noise analysis by representing the subfractional Brownian motion as stochastic functionals of white noise. As the main result we prove that the stochastic current of the one dimensional subfractional Brownian motion is a generalized function in the space of Hida distributions.
IMPLEMENTASI FUZZY INFERENCE SYSTEM (FIS) METODE TSUKAMOTO UNTUK MONITORING KUALITAS UDARA

The lack of air quality monitoring equipment in areas in Indonesia will have a negative impact on health if there is an unconscious decrease in air quality. This study aims to design an air quality monitoring tool using a fuzzy inference system using the Tsukamoto method to provide information in the form of air quality values. By using 3 different types of pollutant sensors, namely MQ2 to detect smoke, MQ7 to detect carbon monoxide (CO) and Sharp GP2YAUF to detect flying dust levels, the data from the readings of each sensor is processed using the fis tsukamoto method to get the result value and category. air quality which then the results will be displayed on a monitoring website as a medium of information. In the process, a series of tools need to be connected to the network in order to be able to carry out the process of sending sensor data into the database, after the data is stored in the database then the website will perform calculations using the Tsukamoto method automatically to get the results of values and categories of air quality that are read by the sensor which then the results will be displayed on the monitoring website. From this research will produce an air quality monitoring tool using the fuzzy inference system Tsukamoto method as a method to determine the results of values and categories. Keywords: Air Quality Monitoring; FIS Tsukamoto method; Fuzzy Logic
A Semantic Model of Internet of Things for Intelligent Translation and Learning

There were a lot of multisource data and heterogeneous devices in the intelligent system of the Internet of things, and the existing methods were difficult to meet the service needs of users for intelligent entities. Therefore, this paper proposed a semantic model construction method of the Internet of things based on intelligent translation and learning. Firstly, on the basis of summarizing the relevant theories of semantic Internet of things, this paper analyzed the semantic data and its characteristics, and expounded the common ontology matching methods. Secondly, according to the characteristics of service ontology and user ontology in intelligent Internet of things system, a method of matching two different ontologies based on string and semantic relationship was proposed, and the cyclic neural network method was used to organically integrate the semantic data of ontology. Finally, in order to realize the perception and representation of the context information of the Internet of things, a semantic model of the Internet of things based on intelligent translation and learning was constructed. Through experimental comparative analysis, the results showed that compared with the traditional methods based on semantic similarity and semantic distance, the semantic model of the Internet of things proposed in this paper had better performance in accuracy and recall, and can achieve better application effect of the Internet of things system. The model proposed in this paper will provide a theoretical reference for further exploring the sharing and service of heterogeneous devices and data in the intelligent Internet of things system.
The error term in the truncated Perron formula for the logarithm of an $L$-function

We improve upon the traditional error term in the truncated Perron formula for the logarithm of an $L$-function. All our constants are explicit.
Pengembangan Media Pembelajaran Interaktif Berbasis PPT untuk Meningkatkan Hasil Belajar IPS Materi Perubahan Sosial Budaya dan Globalisasi Di SMP Negeri 3 Kroya

This research was conducted because teachers need ICT-based learning media, namely interactive PowerPoint adapted to the KTSP, to be used in the learning process. The purpose of this study was to develop a learning media in the form of interactive PowerPoint for class IX in social studies subject matter of Socio-Cultural Change and Globalization at SMP Negeri 3 Kroya Kab. Cilacap. This type of research is research and development. This study uses a nine-step development research procedure proposed by Borg and Gall, namely: 1) potential and problems, 2) data collection, 3) product design, 4) design validation, 5) design revision, 6) product trials, 7 ) product revision, 8) use trial, and 9) product revision which will then become the final product in the form of interactive PowerPoint learning media for class IX students of SMP Negeri 3 Kroya. The subjects in this study were students of class IX SMP Negeri 3 Kroya. The instruments used in this study were a list of interview questions and questionnaires. The list of questions is used to conduct a needs analysis of subject teachers at SMP Negeri 3 Kroya. Questionnaires were used to validate the interactive PowerPoint learning media conducted by two learning media experts and two social studies teachers.
Quantum Simulation and Dynamics

Today Quantum Computers have a wide range of applications, one of the prominent is quantum simulation. Simulations are used for many industrial and research purposes. Here we understand how can we simulate three atoms heisenberg model interaction on three qubits using real NISQ(Noisy Intermediate-Scale Quantum Computing) device ‘ibmq_jakarta’ first we perform simulation by classical method after that we will go on quantum approach,for 3 qubit simulation its represented by 8×8 matrix. This is because there are 2³ = 8 states in the N =3(N represents number of qubits used) system, if the simulation were 50 particles(N=50) then it would be approx 10¹⁵×10¹⁵! Well beyond the capacity of today's classical computers, but for quantum computers this task will require only 15 qubits.
DPSNN: A Differentially Private Spiking Neural Network with Temporal Enhanced Pooling

Privacy protection is a crucial issue in machine learning algorithms, and the current privacy protection is combined with traditional artificial neural networks based on real values. Spiking neural network (SNN), the new generation of artificial neural networks, plays a crucial role in many fields. Therefore, research on the privacy protection of SNN is urgently needed. This paper combines the differential privacy(DP) algorithm with SNN and proposes a differentially private spiking neural network (DPSNN). The SNN uses discrete spike sequences to transmit information, combined with the gradient noise introduced by DP so that SNN maintains strong privacy protection. At the same time, to make SNN maintain high performance while obtaining high privacy protection, we propose the temporal enhanced pooling (TEP) method. It fully integrates the temporal information of SNN into the spatial information transfer, which enables SNN to perform better information transfer. We conduct experiments on static and neuromorphic datasets, and the experimental results show that our algorithm still maintains high performance while providing strong privacy protection.
The Development of Android-based Augmented Reality Learning Media for Three Dimensional Curved Surface

The objective of this study are developing the valid Augmented Reality (AR) learning media in Android platform for three dimensional curved surface and getting the students responses. This study was using the type of Research and Development (R&amp;D) with the ADDIE model ( Analysis, Design, Development, Implementation, Evaluation). The data collection technique was using the questionnaire, which used to validating the media and getting the students responses. The validation was obtained from lecturer in State University of Medan as the material experts and media experts. The media have been implement to the students in the 3rd grade of SMP Negeri 35 Medan. The result of this study show that the AR learning media is the very valid learning media in accordance to the total score percentage of material experts (81,25%) and media experts (82,14%). The students was responsing that the AR learning media in excelent category in accordance to the total score percentage of students responses (85,88%). Therefore, based on the validation, the validity of the android-based augmented reality learning media for three dimensional curved surface has been tested
UTTS: Unsupervised TTS with Conditional Disentangled Sequential Variational Auto-encoder

In this paper, we propose a novel unsupervised text-to-speech (UTTS) framework which does not require text-audio pairs for the TTS acoustic modeling (AM). UTTS is a multi-speaker speech synthesizer that supports zero-shot voice cloning, it is developed from a perspective of disentangled speech representation learning. The framework offers a flexible choice of a speaker's duration model, timbre feature (identity) and content for TTS inference. We leverage recent advancements in self-supervised speech representation learning as well as speech synthesis front-end techniques for system development. Specifically, we employ our recently formulated Conditional Disentangled Sequential Variational Auto-encoder (C-DSVAE) as the backbone UTTS AM, which offers well-structured content representations given unsupervised alignment (UA) as condition during training. For UTTS inference, we utilize a lexicon to map input text to the phoneme sequence, which is expanded to the frame-level forced alignment (FA) with a speaker-dependent duration model. Then, we develop an alignment mapping module that converts FA to UA. Finally, the C-DSVAE, serving as the self-supervised TTS AM, takes the predicted UA and a target speaker embedding to generate the mel spectrogram, which is ultimately converted to waveform with a neural vocoder. We show how our method enables speech synthesis without using a paired TTS corpus. Experiments demonstrate that UTTS can synthesize speech of high naturalness and intelligibility measured by human and objective evaluations. Audio samples are available at our demo page https://neurtts.github.io/utts_demo.
Design of Load Balancing Using Static Route Address List Method In The Case Study of Tambakrejo Village Tulungagung

internet plays a very important role today, both to search for information and knowledge. In the development of internet networks, many factors influence it, such as the geographical location of the area, supporting facilities such as signal towers, construction costs, and Internet Service Providers (ISP) that cover the area. The purpose of this study is to build an internet network in Tambakrejo village, which has very difficult internet access due to its geographical location which is very far from urban areas and very few supporting facilities in the construction of internet networks, so the authors develop a solution using devices such as the Router Router, hubs, dongle modems, and bolic e-goen pans, and uses a load balancing method to stabilize the activity load of all connected devices. the final result expected by the authors in this study is so that people who live in the Tambakrejo village of Tulungagung city can feel internet access that is easier and more stable, and the construction of their internet network does not cost much.
Epeolatry: The Practice of Language Learning Strategies in Reading among Lower Secondary School Students

Learning approaches utilised by the learners of a second language to ease their learning process may vary in each individual.Reading skills are crucial in a language classroom which comprises five requisite components namely phonemic phonics, awareness, vocabulary, fluency and comprehension.Each component is crucial to muster effective reading instruction.Nonetheless, discrepancies in executing the language learning strategies may result in multiple issues in reading achievement.Limited studies were conducted in regards to language learning strategies in reading in the English classrooms previously.Henceforth, the researchers conducted a study to investigate the archetypal language learning methods used by Kuala Lumpur lower secondary school students when reading in English.To collect data, 40 lower secondary students were given an updated version of the Strategies Inventory for Language Learning questionnaire.The results yielded that the students use all of the categories of language learning strategies.The study also disclosed that metacognitive strategies is the prominent language learning strategy among lower secondary school students and these students engaged less in affective strategies.Thus, utilising relevant language learning strategies in reading in English may promote the successful reading skills in English.In this way, teachers are able to apply strategic-based instruction to enhance the reading skills in English among lower secondary school students.
Geometric graph-theoretic aspects of quantum stabilizer codes

Abstract We propose a systematic procedure for the construction of graphs associated with binary quantum stabilizer codes. The procedure is characterized by means of the following three step process. First, the stabilizer code is realized as a codeword-stabilized (CWS) quantum code. Second, the canonical form of the CWS code is determined and third, the input vertices are attached to the graphs. In order to verify the effectiveness of the procedure, we implement the Gottesman stabilizer code characterized by multi-qubit encoding operators for the resource-efficient error correction of arbitrary single-qubit errors. Finally, the error-correcting capabilities of the Gottesman eight-qubit quantum stabilizer code is verified in graph-theoretic terms as originally advocated by Schlingemann and Werner.
INTERNET TECHNOLOGIES AS a MEANS OF IMPROVING THE QUALITY OF INDEPENDENT WORK

In this work, the tasks of the state program for improving the quality of education and improving scientific research in the field of physics are indicated. The possibilities of Internet technology in teaching the physics corresponding to this program are indicated, the ways and means of improving the quality of self-education are given, and the website address and its possibilities for students of technical universities in the physics course created by the author in the Karakalpak language are given.
Research on the Utilization and Optimal Management of Electronic Information Resources in University Libraries

Through theoretical analysis, this paper expounds the value of strengthening the utilization of electronic information in university libraries and the reasons affecting the utilization rate of information resources in electronic libraries, so as to give better play to the role of university libraries and improve the utilization rate of electronic information in university libraries. In view of the existing problems, this paper puts forward measures to optimize the utilization rate of electronic information resources in university libraries and give full play to the role of electronic information resources, so as to promote information exchange and development.
Conformal Credal Self-Supervised Learning

In semi-supervised learning, the paradigm of self-training refers to the idea of learning from pseudo-labels suggested by the learner itself. Across various domains, corresponding methods have proven effective and achieve state-of-the-art performance. However, pseudo-labels typically stem from ad-hoc heuristics, relying on the quality of the predictions though without guaranteeing their validity. One such method, so-called credal self-supervised learning, maintains pseudo-supervision in the form of sets of (instead of single) probability distributions over labels, thereby allowing for a flexible yet uncertainty-aware labeling. Again, however, there is no justification beyond empirical effectiveness. To address this deficiency, we make use of conformal prediction, an approach that comes with guarantees on the validity of set-valued predictions. As a result, the construction of credal sets of labels is supported by a rigorous theoretical foundation, leading to better calibrated and less error-prone supervision for unlabeled data. Along with this, we present effective algorithms for learning from credal self-supervision. An empirical study demonstrates excellent calibration properties of the pseudo-supervision, as well as the competitiveness of our method on several benchmark datasets.
Omni-Granular Ego-Semantic Propagation for Self-Supervised Graph Representation Learning

Unsupervised/self-supervised graph representation learning is critical for downstream node- and graph-level classification tasks. Global structure of graphs helps discriminating representations and existing methods mainly utilize the global structure by imposing additional supervisions. However, their global semantics are usually invariant for all nodes/graphs and they fail to explicitly embed the global semantics to enrich the representations. In this paper, we propose Omni-Granular Ego-Semantic Propagation for Self-Supervised Graph Representation Learning (OEPG). Specifically, we introduce instance-adaptive global-aware ego-semantic descriptors, leveraging the first- and second-order feature differences between each node/graph and hierarchical global clusters of the entire graph dataset. The descriptors can be explicitly integrated into local graph convolution as new neighbor nodes. Besides, we design an omni-granular normalization on the whole scales and hierarchies of the ego-semantic to assign attentional weight to each descriptor from an omni-granular perspective. Specialized pretext tasks and cross-iteration momentum update are further developed for local-global mutual adaptation. In downstream tasks, OEPG consistently achieves the best performance with a 2%~6% accuracy gain on multiple datasets cross scales and domains. Notably, OEPG also generalizes to quantity- and topology-imbalance scenarios.
Demystifying Bayesian models using Bayesian linear regression

Bayesian models are very important in modern data science. These models can be used to derive estimatesfor noisy and sparse data. This manuscript outlines the basics and derivations of a Bayesian linearregression model. Source code for performing Bayesian linear regression is also provided. I hope this willenable broader understanding of the basics of Bayesian models and help demystify it for scientists.
The Blockchain: The Next Technological Revolution In The World of The Economy

The study aimed to demonstrates that the world is more inclined to take use of blockchain (BC) systems and their favorable effects on all economic sectors, development, and quality of life enhancement. Because many states already have well-developed industries, government agencies, financial organizations, and educational institutions recognized the need to stay up with the trend and begin planning and preparing for the BC revolution. This paper also identifies 3 realistic examples for Institutions that have rated or made recommendations about this technique "BC". The paper explains how blockchain systems function in practice and why their adoption improves development, innovation, and competitiveness by reducing and simplifying operational procedures. It is one of the most important technical topics in our time, especially with the beginning of the twenty-first century, especially in financial technologies because of the major developments and changes that they have witnessed and their important impact on the global economy. This paper reviews the current academic research on BC, especially in the subject area of business and economics. Based on a systematic review of the literature retrieved, explore the most frequently cited publications, the most economic countries, and the most commonly used keywords. BC technology is the main topic of this paper, which has profound effects in most areas, and the paper aimed to analyze the current application and concept of blockchain systems. The use of block technology generally helps the digital transformation of the economy and promotes transparency. The outputs of this technology are compatible with the rules and regulations of many nations in the sphere of banking and business. It is a tool for improving transparency, decentralization, and security while reducing cost and time. Understanding the processes through which it impacts business and market efficiency will necessitate further academic research.
The Use of Memory Strategies Training in Enhancing Speaking Skill among Year 6 ESL Learners

Speaking skill is an intrinsic part of communication among humankind.Undeniably, speaking fluently requires people to have a vast amount of vocabulary as it is important for message interpretation and communication as a whole.In Malaysia, it is undoubtable that learners are able to achieve high proficiency in English in spite of being non-native speakers but the same does not apply to all.The number of learners that struggle to acquire English certainly outnumbers high proficiency level learners.The fundamental problem to this situation leads to the very basics itself, lack of vocabulary knowledge, thus hindering learners from speaking English efficiently.Therefore, this study aims to investigate whether Memory Strategies Training (MST) could help Year 6 ESL learners in speaking skill by enhancing their vocabulary.A quantitative approach was carried out with the participation of 40 Year 6 learners from a primary school in Nilai, Negeri Sembilan.The 15 speaking strategy items questionnaire were adapted from Cohen & Oxford's Young Learners' Language Strategy Use Survey.The outcome of this study shows that this memory learning strategy is crucial in raising the learner's competency to an ideal level.Henceforth, the study was able to identify an appropriate language learning strategy for improving the Year 6 learners' speaking skill thus aids in elevating their confidence in using English in their daily conversation