Reviewerly/exHarmony huggingface dataset:
New Trend of Information Literacy from Leisure Reading Behavior and Experiences of Junior High School Students

Information literacy education in school libraries is based on abilities of personal reading and learning. The research was used semi-structured interview in qualitative research to understand the reading behavior and experiences of junior high school students who are leisure reading lover. The analysis of qualitative data included both hermeneutic phenomenology and axial coding in grounded theory. According to research obtained, leisure reading behavior of junior high school students have several conclusion. First, The interesting content is the main motive. Second, the purposes of leisure reading behavior may divide into the tool goal and the non- tool goal. Third, internet is acting both important information source and channel. The analysis of leisure reading experiences of junior high school students have several conclusions. First, there are three kinds of reading styles that included comprehensive reading, tool reading and the non- tool reading. Second, participants often use internet communication software to exchange their reading information in internet reading. Third, participants often read datas which they searched or browsed, E-mail, internet literature and book description in the internet. According to research conclusions, this article discussed how to develop information literacy in junior high school students. These ways includes that use internet technologies to improve interaction, have library instruction classes depend on reading purposes, integrate reading information in school effectively and promotes software and hardware equipment in school to reduce the imformation divide. Finally, this article thought new trend of information literacy.
VEDIC TO VIRTUAL - THE PARADIGM SHIFT OF FORMAL EDUCATION SYSTEM IN INDIA AFTER CORONA PANDEMIC

The Education which was developed first in quite a while is known as the Vedic System of instruction. As it were, the old arrangement of instruction was dependent on the Vedas, and therefore it was the given name of Vedic training framework. A few researchers have partitioned Vedic instructive period into Rigveda period, brahman period, Upanishads period, sutra(hymn)period, Smriti period,etc. yet, all these period due to pre-strength of the Vedas, there was no adjustment in the points and standards for instruction. The training arrangement of Vedic period has one of a kind attributes and characteristics which were not found in the people of old instruction arrangement of some other nation of the world. In the expressions of Dr.P.N. Prabha, “Education in old India was liberated from any outer control like that of the state and government or any gathering commonwealths. It was the king‟s obligations to see that educated intellectuals, sought after their examinations and played out their obligation of giving information without obstruction from any source what show ever.
A Study on Fourier descriptor recognition algorithm of gesture trajectory

Focused on the time-domain problem, limitation of gesture track length and time scale in gesture trajectory recognition, in this paper, Gesture Fourier Descriptor algorithm is proposed for non-closed trajectory curves, called GFD below. First of all, we extract the gesture track sequence from the video, close the non-closed track curve, and generate a new closed track binary curve. The new closed curve is further described by Fourier. In order to obtain the invariance of scaling, scale and rotation, normalization processing is carried out with Fourier descriptor. Then, the obtained Fourier descriptor is used to match the template, experiments show that it has good recognition ability to some extent. In this paper, deformation coefficient is used as the output threshold of gesture recognition to shield some recognition errors. Experimental tests show that the robustness of gesture recognition is improved.
Almost sure convergence rates for Stochastic Gradient Descent and Stochastic Heavy Ball

We study stochastic gradient descent (SGD) and the stochastic heavy ball method (SHB, otherwise known as the momentum method) for the general stochastic approximation problem. For SGD, in the convex and smooth setting, we provide the first \emph{almost sure} asymptotic convergence \emph{rates} for a weighted average of the iterates . More precisely, we show that the convergence rate of the function values is arbitrarily close to $o(1/\sqrt{k})$, and is exactly $o(1/k)$ in the so-called overparametrized case. We show that these results still hold when using stochastic line search and stochastic Polyak stepsizes, thereby giving the first proof of convergence of these methods in the non-overparametrized regime. Using a substantially different analysis, we show that these rates hold for SHB as well, but at the last iterate. This distinction is important because it is the last iterate of SGD and SHB which is used in practice. We also show that the last iterate of SHB converges to a minimizer \emph{almost surely}. Additionally, we prove that the function values of the deterministic HB converge at a $o(1/k)$ rate, which is faster than the previously known $O(1/k)$. Finally, in the nonconvex setting, we prove similar rates on the lowest gradient norm along the trajectory of SGD.
Generative and Discriminative Deep Belief Network Classifiers: Comparisons Under an Approximate Computing Framework

The use of Deep Learning hardware algorithms for embedded applications is characterized by challenges such as constraints on device power consumption, availability of labeled data, and limited internet bandwidth for frequent training on cloud servers. To enable low power implementations, we consider efficient bitwidth reduction and pruning for the class of Deep Learning algorithms known as Discriminative Deep Belief Networks (DDBNs) for embedded-device classification tasks. We train DDBNs with both generative and discriminative objectives under an approximate computing framework and analyze their power-at-performance for supervised and semi-supervised applications. We also investigate the out-of-distribution performance of DDBNs when the inference data has the same class structure yet is statistically different from the training data owing to dynamic real-time operating environments. Based on our analysis, we provide novel insights and recommendations for choice of training objectives, bitwidth values, and accuracy sensitivity with respect to the amount of labeled data for implementing DDBN inference with minimum power consumption on embedded hardware platforms subject to accuracy tolerances.
Explaining AI Through Critical Reflection Artifacts

Artificial intelligence algorithms – and data that feed them – are increasingly imbued with agency and impact and are empowered to make decisions in our lives in a wide variety of domains: from search engines, information filtering, political campaigns, health to the prediction of criminal recidivism or loan repayment. Indeed, algorithms are difficult to understand, and explaining “how they exercise their power and influence” and how a given input (whether or not consciously released) is transformed into an output. In the computer science field, techniques of explainable artificial intelligence (XAI) have been developed for disclosing and studying algorithmic models, using data visualization as visual language to let experts explore their inner workings. However, current research on machine learning explainability empowers the creators of machine learning models but is not addressing the needs of people affected by them. This paper leverages on communication and information design methods (or competences) to expand the explainable machine learning field of action towards the general public.
Sistem Informasi Geografis Pemetaan Museum Di Bali Berbasis Android

A museum is an institution that maintains and exhibits a collection of objects of cultural and scientific value for research, educational and entertainment purposes. The purpose of the creation of the museum is a means of educational tourism, interesting and informative for society. Thus, the museum plays a very important role because the existence of the museum will provide a broad understanding for the community. But here the problem is the lack of comprehensive information about Bali's museums, especially museums that are rarely visited by tourists. So that people only know about famous museums. With this Android-based Bali Museum Map Information System, it can help both the public and tourists to find information about museums in Bali, ranging from well-known or frequently visited museums to rarely visited museums. The existence of this information system also helps to find information about the history of the museum, its location and the history of the existing collections in each museum. The method used in this study uses the prototype method, where every process that we have tested the user to what we are doing, met the user's expectations.
The Study of Thermodynamics First Law inside the Modified Heron's Fountain

Various points of view are important and valuable in solving problems and cognition of world. In this article, the modified Heron's fountain is introduced, and inside it the imaginable violation of thermodynamics first law is investigated. The modified Heron's fountain converts the gravity of mass into a mechanical energy. Here, a probable paradox between conservation of mass and conservation of energy or a probable conversion method of graviton into energy is discussed.
A Model for Mapping Combined Effects of Quality of Service Parameters and Device Features on Video Streaming Quality of Experience

Maintaining quality of streaming video is challenged by network faults resulting into freezes and rebufferings on the video. On top of the network effects, device features have impacts on the image of the video frames displayed during streaming. Despite the simultaneous impacts of video quality from network and device, previous studies considered individual impact of network parameters or devices as influencing factors to propose Quality of Experience (QoE) models. This study proposed QoE model by mapping combined effects from both network and device on video streamed QoE. An experiment to study the effects of video quality from combined effects of network and device over the wireless involved 35 subjects. Combination of packet loss, packet reordering, and delay were emulated using network emulator following Design of Experiment methodology. Through analysis of variance, the study found that packet loss had the highest impact, followed by device features, reordering, and delay on the video QoE. From the combined effects, two-way interactions and three-way interactions had significant effects on the video QoE. Through additive and linearity behavior of the input factors from network and device on video streaming QoE, a multi-factor model was derived.Keywords: Design of Experiment (DOE); Mean Opinion Score (MOS); Quality of Experience (QoE); Quality of Service (QoS); Video Quality Assessment
Triple M: A Practical Neural Text-to-speech System With Multi-guidance Attention And Multi-band Multi-time Lpcnet.

In this work, a robust and efficient text-to-speech system, named Triple M, is proposed for large-scale online application. The key components of Triple M are: 1) A seq2seq model with multi-guidance attention which obtains stable feature generation and robust long sentence synthesis ability by learning from the guidance attention mechanisms. Multi-guidance attention improves the robustness and naturalness of long sentence synthesis without any in-domain performance loss or online service modification. Compared with the our best result obtained by using single attention mechanism (GMM-based attention), the word error rate of long sentence synthesis decreases by 23.5% when multi-guidance attention mechanism is applied. 2) A efficient multi-band multi-time LPCNet, which reduces the computational complexity of LPCNet through combining multi-band and multi-time strategies (from 2.8 to 1.0 GFLOP). Due to these strategies, the vocoder speed is increased by 2.75x on a single CPU without much MOS degradatiaon (4.57 vs. 4.45).
Federated Acoustic Modeling For Automatic Speech Recognition

Data privacy and protection is a crucial issue for any automatic speech recognition (ASR) service provider when dealing with clients. In this paper, we investigate federated acoustic modeling using data from multiple clients. A client's data is stored on a local data server and the clients communicate only model parameters with a central server, and not their data. The communication happens infrequently to reduce the communication cost. To mitigate the non-iid issue, client adaptive federated training (CAFT) is proposed to canonicalize data across clients. The experiments are carried out on 1,150 hours of speech data from multiple domains. Hybrid LSTM acoustic models are trained via federated learning and their performance is compared to traditional centralized acoustic model training. The experimental results demonstrate the effectiveness of the proposed federated acoustic modeling strategy. We also show that CAFT can further improve the performance of the federated acoustic model.
Clustering human development index data with gravitational search algorithm-fuzzy 4-means (GSA-F4M)

Human Development Index (HDI) is the indicator which measures the efforts of the human life’s successful quality in Indonesia. The description of Human development’s condition is used to evaluate the achievements of human development in each region in Indonesia, thus the analysis is needed. The analysis of the description can be solved using the clustering method which to group each provinces in Indonesia based on four HDI indicators. Fuzzy C-Means is one of clustering algorithm which is commonly used and has a high accuracy level. FCM has a limitation that is easily trapped in minimum local conditions when calculating the objective function in determining the the center of clusters, and causing the result is not the lowest value of the solution sets. The Gravitational Search Algorithm (GSA) algorithm approach is used so that the results obtained are optimum globally. The use of the GSA algorithm in FCM aims to optimize objective functions so as to overcome minimum local problems and obtain optimal cluster results. This research aims to apply GSA-FCM to cluster HDI data in Indonesia. The results of this research are the four clusters, the first cluster consists of 5 provinces, the second cluster has 9 provinces, the third cluster has 14 provinces, and the fourth cluster has 6 provinces.
Implementasi Kebijakan Pencegahan Pencemaran Air Permukaan oleh Air Limbah Industri di Daerah Aliran Sungai Brantas Kediri

&lt;p&gt;&lt;em&gt;The City Government of Kediri in an effort to preserve the environment forms a legal basis namely the City Regulation of Kediri Number 3 of 2009 cocerning Environmental Management. One of the targets in the regional regulation is to preserve the watershed and water sources. In accordance with the 2015-2019 Medium Term Development Plant , there are 15 watersheds that are prioritized to be restored first and one of them is the Brantas watersheds. This study aims to identify the implementation of the Kediri City Government policy in preventing surface water pollution by industrial wastewater in the Brantas River Basin, Kediri District. The method used in this research is descriptive. Collecting data by conducting in-depth interviews with industrial waste water treatment officers and officers in the field of environmental damage pollution in the Departement of Environment, Hygiene and Gardening of Kediri City. Based on the research results, it is known that most of the industries have carried out wastewater treatment and not ith a dilution process and most of the industries have IPLC. Based on the wuality standards, it is known that the quality standards of industrial waste are in accordance with the standards set&lt;/em&gt; &lt;em&gt;by the government and the industry routinely conducts wastewater quality tests, but the industry is still lacking in reporting the results of wastewater quality tests. In wastewater treatment facilities and infrastructure, the government has provided rubbish place for industrial estates and most industries have their own rubbish place. &lt;/em&gt;&lt;/p&gt;
Fast and Stable Interval Bounds Propagation for Training Verifiably Robust Models

We present an efficient technique, which allows to train classification networks which are verifiably robust against norm-bounded adversarial attacks. This framework is built upon the work of Gowal et al., who applies the interval arithmetic to bound the activations at each layer and keeps the prediction invariant to the input perturbation. While that method is faster than competitive approaches, it requires careful tuning of hyper-parameters and a large number of epochs to converge. To speed up and stabilize training, we supply the cost function with an additional term, which encourages the model to keep the interval bounds at hidden layers small. Experimental results demonstrate that we can achieve comparable (or even better) results using a smaller number of training iterations, in a more stable fashion. Moreover, the proposed model is not so sensitive to the exact specification of the training process, which makes it easier to use by practitioners.
Euclidean volume ratios of separable and entangled states in two-qubit and qubit-qutrit systems

Euclidean volume ratios characterizing the typicality of entangled and separable states are investigated for two-qubit and qubit-qutrit quantum states. For this purpose a new numerical approach is developed. It is based on the Peres-Horodecki criterion, on a characterization of the convex set of quantum states by inequalities resulting from Newton identities and Descartes' rule of signs and on combining this characterization with standard and Multiphase Monte Carlo algorithms. Our approach confirms not only recent results on two-qubit states but also allows for a numerically reliable numerical treatment of so far unexplored special classes of two-qubit and qubit-qutrit states. However, our results also hint at the limits of efficiency of our numerical Monte Carlo approaches which is already marked by the most general qubit-qutrit states forming a convex set in a linear manifold of thirtyfive dimensions.
RANCANG BANGUN SISTEM INFORMASI PENJUALAN BERBASIS WEB PADA UMKM ZXID DI KOTA BATAM

The development of technology is currently growing, one of them is the online development, which is very fast, many companies have started to offer their online in order to make the most profit, so the competition between companies is growing spare parts services. Company. This is why UMKM ZXID needs to create a web marketing information system so that consumers can easily access information as they can order directly և pay for through the website. The method used is the SDLC waterfall model, which consists of needs analysis, design, software coding, testing, marketing, and maintenance. The result of this research is a web-based marketing information system that allows consumers to easily order products to order and saves employees time and money.
Model of adoption of Information and Communication Technologies of the Universities case of study Technical University of Cotopaxi Latacunga -Ecuador

This investigation is part of a development model to adopt the information and Communication Technologies (ICT) to the teaching-learning process at the Technical University of Cotopaxi. Specifically, to improve the higher education, as a result of the steady advances in the field of digital knowledge and educational technology, for that reason, the Institutions must improve their academic organization and education processes. Through the use of technologies, educational institutions try to integrate information and innovation. In this context and reviewing the problem case through the application of the ICT new Acceptance Model, the student's teaching-learning process will improve. The investigation showed the expected results with the creation of the latest ICT adoption model. Using collaborative tools within a collaborative learning environment (CLE) to elaborate constructs Cronbach's alpha, variance, and correlations and the statistical software were used as the Minitab validated the hypotheses.
The Compatibility of “Guess What” Textbook Based on English Final Exam Framework 2018/2019

This study is used descriptive qualitative because the researcher wants to understand the contexts. The researcher is focused on the analysis of “Guess What” textbook. There are 2 parts of this book; pupils’ book and activity book. The students in this school only use the activity book to do the exercise while the teacher has both. In this study, the researcher took the data from the materials in the textbook to analyze whether this book compatible with the question indicators in English final exam framework or not. The result of this study tells that the compatibility is 62% and the incompatibility is 38% from the total questions 50 numbers, 30 numbers are multiple choice, 15 numbers are short answer and 5 essay questions. It can be concluded that this textbook is compatible with question indicators in English final exam framework 2018/2019.
The constructivist approach (coap) to enhance students comprehension in reading procedure text for students of Universitas Muhammadiyah Sidenreng Rappang

This research aimed to investigate the constructivist approach to enhance students reading comprehension at UMS Rappang. This research employed the pre-experimental method with one group pre-test and post-test design. The population was the second-year students of UMS Rappang in 2018-2019 academic years. The population included 66 students consisting of three classes; one class (I.2) was taken as a sample by using cluster sampling, as many as 22 students. The instrument used in this research was reading test. The result of this research showed that the pre-test got the mean score of 44.50, while the post-test 64.18. It showed that the p-value (0.000) was lower than the level of significance (alpha (α) = 0.05). It means that H1 was accepted. The research concluded that teaching reading comprehension by using a constructivist approach enhances students’ reading comprehension at the First year of UMS Rappang.
CULTURAL CONTENTS IN SPEAKING MATERIALS AND ACTIVITIES FOR TENTH-GRADERS

EFL textbooks should be valued based on their visual illustration and based on their cultural background and goals of EFL learning. The study aimed to report the results of a textbook analysis to identify which type of culture and what themes of culture were introduced in the tenth graders of Indonesian senior high school. Theory of cultures proposed by Cortazzi Jin (1999) and Chen Lee (2004) were adapted for examining specific aspects of culture under formal culture and aspects of life culture. The analysis revealed that the percentage of source culture (45,7%) and unidentified culture (42,9%) is the same in the textbook. The textbook was dominated by source culture content among identified cultural content, while international culture (5,7%) and target culture (5,7%) contained a small percentage. It was also found out that among the 19 cultural themes under formal culture and aspects of life culture, the researcher found four themes such as lifestyle, gestures, and holiday under aspects of life culture and only history under formal culture. The predominant theme was aspects of life culture of lifestyle.