Reviewerly/exHarmony huggingface dataset:
Epitome of Media Education with the Educational Process and its Impact on Developing Students’overall Knowledge

The work itself embodies a conceptual highlight of the new approach of the global education, which is the epitome of media education with the educational process. Media education is an indispensable need and an inevitable requirement of global education with a particular role in the development of students' overall knowledge and skills, in particular the creation of a new educational culture and the creation of shared values. The media education at the time of the rapid changes in the field of global education, occupies a special place in achieving qualitative and effective education. The purpose of this paper is to get acquainted with the basic concepts of media education, the possibility of the epitome of media education with educational content during the educational process, the role and effects of this education with the aim of informing relevant school stakeholders on the importance of integrating this education towards the improvement of quality in education.
FAKTOR-FAKTOR PENGHAMBAT LITERASI DI SD NEGERI 55/1 SRIDADI

Literacy is the ability to identify, create, interpret, communicate and count, and read in daily life in order to develop social, economic, and cultural potential in modern life so that it can become a quality and virtuous person. The purpose of writing this article is to find out what are the inhibiting factors of literacy in Sridadi 55 / I Elementary School. The method used uses a phenomenological approach to the type of case study. The results of this study are students at Sridadi 55 / I Elementary School already have a fairly good interest in reading, but the lack of reading books available in libraries and reading corners makes students less enthusiastic about reading.
LibGuides: Instructional Services: Library Support for Online Instruction: Need Help? Contact Library Instruction

This guide provides information on how Idaho State University libraries supports faculty who teach online courses. Too many choices for you? Please contact a librarian to discuss your options.
β-VARIATIONAL AUTOENCODERS FOR LEARNING INVERTIBLE LOCAL IMAGE DESCRIPTORS

In this paper, we propose an e ffi cient method for learning a local image descriptor and its inversion function using a modified version of a variational autoencoder (VAE) - a β -VAE. We examine di ff erent values of β in the loss function of the β -VAE to find the an optimal balance between incentivising the similarities between input patches to be preserved in latent space, and ensuring good reconstruction of the patches from their encodings in latent space. Our proposed descriptor demonstrates patch retrieval comparable to the reference autoencoder-based local image descriptor, and also shows improved reconstruction of patches from their encodings.
ANALISA PENYEBAB RUSAKNYA CARGO OIL PUMP GUNA MENUNJANG DISCHARGE CARGO PERTAMAX DI ATASKAPAL MT. PATRA TANKER 2

When discharging the Pertamax cargo at the port at 10:25 a.m. local time, the on-duty engineer received information from the cargo control room that a problem had occurred, the engineer immediately went to the cargo pump room to check the condition of the cargo oil pump. The engineer is see a leak in the pump room which causes the pump room to be full of spills of Pertamax oil transported by the ship. This research is based on a case study on the ship MT. Patra Tanker 2. The data collection method was carried out by direct observation on the ship for one year and then conducted discussions and interviews with the ship's crew responsible for the cargo pump, as well as data from literature such as instruction manuals and standard operational procedures (SOP). The analysis approach was carried out in a descriptive qualitative manner based on data and various literatures used as a reference or comparison. From the results of the analysis it is stated that the cause of the damage to the cargo oil pump is due to the influence of the quality of the mechanical seal that does not meet the standard, the ball bearing is damaged or worn on the cargo oil pump, the ceramic sleeve shaft (bushing) is thinning or worn, and damage to the cargo oil pump shaft. The cause of damage to the cargo oil pump can be avoided by carrying out routine maintenance and controlling it regularly when the cargo oil pump is running.
A Variety Theorem for Relational Universal Algebra

We consider an analogue of universal algebra in which generating symbols are interpreted as relations. We prove a variety theorem for these relational algebraic theories, in which we find that their categories of models are precisely the definable categories. The syntax of our relational algebraic theories is string-diagrammatic, and can be seen as an extension of the usual term syntax for algebraic theories.
Prosedur Fuzzy Tahani Menggunakan Fungsi Representatif Kurva Segitiga dan Trapesium

Fuzzy Tahani is one of the developments of fuzzy logic applications. This study will explain the fuzzy Tahani procedure using representative membership functions of triangular and trapezoidal curves with fuzzification steps, determining fuzzy domains, membership functions and degrees, compiling criteria, determining fire strength values, and determining recommendation results. The fuzzy Tahani method uses the AND operation so as to produce a minimum fire strength value that affects the recommendation results. Then the research variables used are price, dimensions, weight, battery capacity, and screen display variables. For the triangular curve there are 3 fuzzy sets, namely small, medium, and large, while the trapezoidal curve consists of 4 fuzzy sets, namely small, medium, large, and very large. The data used in this study is secondary smartphone data, branded Oppo, Xiaomi, Samsung, Vivo, and Asus. From the results of smartphone data analysis according to the Fuzzy Tahani method used, these variables are processed by entering the rules, amounting to 243 for triangular curves and 1,024 for trapezoidal curves and then processed using AND operation and the conclusion is that triangular curves are better than trapezoidal curves. in recommending the purchase of a smartphone
Federated Multiple Label Hashing (FedMLH): Communication Efficient Federated Learning on Extreme Classification Tasks

Federated learning enables many local devices to train a deep learning model jointly without sharing the local data. Currently, most of federated training schemes learns a global model by averaging the parameters of local models. However, most of these training schemes suffer from high communication cost resulted from transmitting full local model parameters. Moreover, directly averaging model parameters leads to a significant performance degradation, due to the class-imbalanced non-iid data on different devices. Especially for the real life federated learning tasks involving extreme classification, (1) communication becomes the main bottleneck since the model size increases proportionally to the number of output classes; (2) extreme classification (such as user recommendation) normally have extremely imbalanced classes and heterogeneous data on different devices. To overcome this problem, we propose federated multiple label hashing (FedMLH), which leverages label hashing to simultaneously reduce the model size (up to 3.40X decrease) with communication cost (up to 18.75X decrease) and achieves significant better accuracy (up to 35.5%} relative accuracy improvement) and faster convergence rate (up to 5.5X increase) for free on the federated extreme classification tasks compared to federated average algorithm.
Tourist Places Recommender System Using Cosine Similarity and Singular Value Decomposition Methods

Tourism in the city of Bandung has various potentials in the field of culture, regional specialties, buildings, and other tourist attractions. On the Tripadvisor page there are many reviews from users who have visited tourist attractions in the city of Bandung. In this case, user reviews are an important element for analysis. The analysis process is carried out using rule-based sentiment analysis. In conducting the review analysis, we use vaderSentiment to weight the positive and negative values. Positive values are subtracted from negative values to get a compound value and converted to a rating value. The rating value obtained is then processed using the Cosine Similarity and Singular Value Decomposition methods to obtain recommendations for tourist attractions in the city of Bandung. For this method, we use the Root Mean Square Error method as a measure of the level of accuracy between the predicted values. The results of the measurement of the level of accuracy produce a value of 3,489 in the Cosine Similarity method, while the Singular Value Decomposition method gets a value of 1,231. The value in the Singular Value Decomposition method is smaller than the Cosine Similarity method with a difference of 2,258 values
Training Deep Neural Networks via Branch-and-Bound

In this paper, we propose BPGrad, a novel approximate algorithm for deep nueral network training, based on adaptive estimates of feasible region via branch-and-bound. The method is based on the assumption of Lipschitz continuity in objective function, and as a result, it can adaptively determine the step size for the current gradient given the history of previous updates. We prove that, by repeating such a branch-and-pruning procedure, it can achieve the optimal solution within finite iterations. A computationally efficient solver based on BPGrad has been proposed to train the deep neural networks. Empirical results demonstrate that BPGrad solver works well in practice and compares favorably to other stochastic optimization methods in the tasks of object recognition, detection, and segmentation. The code is available at \url{https://github.com/RyanCV/BPGrad}.
PERUBAHAN LAHAN KRITIS MENJADI LAHAN HIJAU SEBAGAI SUMBER ENERGI (STUDI KASUS DAS ARAU KOTA PADANG)

This study examines a flood control model by analyzing the area of critical land which is the land that causes flooding to become green land. Indonesia is a country that has 2 seasons, namely the dry season and the rainy season. Padang City, from 2008 - 2020, there were frequent floods. From research on the Arau watershed, there are 8 Arau sub-watersheds experiencing flooding. To reduce flooding, critical land use is converted into green land. Rainfall calculations use rainfall data from 5 stations. Rainfall plans using the Thiessen theory. Discharge plan using a rational formula. From the water discharge will be determined the amount of energy. The energy produced by the discharge of critical land use is 168,960 kwh.
Competency Level of MAPEH Teachers in Teaching Performing Arts Based on K to 12 Curriculum in Secondary Public Schools

The quality of education depends on the teacher as well as to the curriculum. As the prime movers to attain the addressed goals in the curriculum, teachers must have the desire to grow and improve through professional development and constant learning towards students ‘academic achievement. The descriptive method of research was utilized in this study to assess the competency level of the MAPEH teachers in teaching performing arts based on the K to 12 Curriculum. Results of the study revealed that majority of the respondents were females, married and 40 years old and below. They earned units/finished their master’s degree, held a teacher position, and had 10 years and below teaching experience. With regard to artistic inclinations particularly in terms of dancing, majority of them have potential in folk dance and modern dance. In terms of music, some teachers could play musical instruments skillfully such as guitar and piano/organ. They were highly competent in using assessment data, monitoring students’ data and achievement, using ICT resources for the teaching-learning process, giving feedbacks, making good use of allotted time and employing design. Individual or group experiential learning, cooperative learning, project method and collaborative activities were most commonly used strategies in teaching performing arts. Meanwhile, lack of facilities and equipment and limited seminars, workshops, and trainings attended were the common problems encountered.
Chapter 4. Challenges for Library IT

Crises often pose specific challenges for IT departments. Chapter 4 of Library Technology Reports (vol. 57, no. 7), “Challenges for Library IT,” describes some of those challenges and strategies for confronting them.
Decentralized Asset Custody Scheme with Security against Rational Adversary

Asset custody is a core financial service in which the custodian holds in-safekeeping assets on behalf of the client. Although traditional custody service is typically endorsed by centralized authorities, decentralized custody scheme has become technically feasible since the emergence of digital assets, and furthermore, it is greatly needed by new applications such as blockchain and DeFi (Decentralized Finance). In this work, we propose a framework of decentralized asset custody scheme that is able to support a large number of custodians and safely hold customer assets of multiple times the value of the total security deposit. The proposed custody scheme distributes custodians and assets into many custodian groups via combinatorial designs, where each group fully controls the assigned assets. Since every custodian group is small, the overhead cost is significantly reduced. The liveness is also improved because even a single alive group would be able to process transactions. The security of this custody scheme is guaranteed under the rational adversary model, such that any adversary corrupting a bounded fraction of custodians cannot move assets more than the security deposit paid. We further analyze the security and performance of our constructions from both theoretical and experimental sides and give explicit examples with concrete numbers and figures for a better understanding of our results.
DFL: High-Performance Blockchain-Based Federated Learning

Many researchers have proposed replacing the aggregation server in federated learning with a blockchain system to improve privacy, robustness, and scalability. In this approach, clients would upload their updated models to the blockchain ledger and use a smart contract to perform model averaging. However, the significant delay and limited computational capabilities of blockchain systems make it inefficient to support machine learning applications on the blockchain. In this paper, we propose a new public blockchain architecture called DFL, which is specially optimized for distributed federated machine learning. Our architecture inherits the merits of traditional blockchain systems while achieving low latency and low resource consumption by waiving global consensus. To evaluate the performance and robustness of our architecture, we implemented a prototype and tested it on a physical four-node network, and also developed a simulator to simulate larger networks and more complex situations. Our experiments show that the DFL architecture can reach over 90\% accuracy for non-I.I.D. datasets, even in the presence of model poisoning attacks, while ensuring that the blockchain part consumes less than 5\% of hardware resources.
ODMTCNet: An Interpretable Multi-view Deep Neural Network Architecture for Image Feature Representation

This work proposes an interpretable multi-view deep neural network architecture, namely optimal discriminant multi-view tensor convolutional network (ODMTCNet), by integrating statistical machine learning (SML) principles with the deep neural network (DNN) architecture.
Internet linguistics: a conversational analysis of online synchronous chat and face-to-face conversations of efl undergraduate students in jordan

espanolResumen en espanol: Este estudio tuvo como objetivo arrojar luz sobre el Chatear Sincronico en Linea (CSL) en el chat de Facebook en comparacion con las conversaciones cara a cara (CAC). El corpus se recopilo a partir de la interaccion de cuatro grupos, de 68 estudiantes de tercer curso del Grado de Lengua y Literatura inglesa en el Colegio Universitario de Ajloun (CUA). Los participantes fueron seleccionados deliberadamente y distribuidos aleatoriamente en dos grupos de chat sincronico en linea y dos grupos cara a cara. Las interacciones de los grupos CAC se grabaron un video y sus transcripciones se incrustaron linea por linea en cada conversacion. Mientras que la interaccion en los dos chats de Facebook se descargo a traves de una opcion de Facebook llamada descargar su informacion. Se utilizaron dos instrumentos: una lista de verificacion de la rubrica del acto de habla basada en las maximas de Grice, la lista de verificacion de la rubrica del rendimiento linguistico y una pregunta abierta presentada a los interlocutores. Este estudio investigo si los interlocutores aplican los cuatro principios cooperativos de Grice y tres aspectos linguisticos en diecisiete actos de reparacion y toma de turnos. Por lo tanto, la comparacion fue un intento de investigar el desempeno social y linguistico de los interlocutores de CSL. Los resultados revelaron la importancia de mejorar las caracteristicas de los chats segun a la teoria de los actos de habla y la maxima de Grice. El analisis concluyo que la interaccion en CSL aun necesita mas investigacion. Mas precisamente, los chats de Facebook descuidan en cierta medida las dos teorias. EnglishAbstract: This study aimed to shed light on Online Synchronous chat (OSC) on Facebook chatroom compared with Face-To-Face (FTF) conversations. The corpus was cumulated from the interaction of four groups consisted of (68) third-year English language and literature major students at Ajloun University College (AUC). The participants were selected purposively and distributed randomly into two OSCGs and two FTF groups. The interactions for FTF groups were video-recorded and the transcriptions were embedded line by line in each conversation. While the interaction on the two Facebook chatrooms were downloaded through a Facebook option called download your information. Two instruments were used: a Speech Act Rubric Scale based on Grice's maxims, linguistics performance rubric checklist, and an open-end question had been just presented to the chatters. This study investigated whether interlocutors apply the four Gricean CPs and three linguistic aspects over seventeen turn-taking and repair acts. Thus, the comparison was a try to investigate the social and linguistic performance of OSC interlocutors. Results revealed the importance to improve chatrooms features regarding to speech acts theory and Grice's maxim. The analysis concluded that interaction on OSC still needs more investigation. More precisely, Facebook chatrooms neglects to some extent the two theories.
Bounds on the recurrence probability in periodically-driven quantum systems

Periodically-driven systems are ubiquitous in science and technology. In quantum dynamics, even a small number of periodically-driven spins leads to complicated dynamics. Hence, it is of interest to understand what constraints such dynamics must satisfy. We derive a set of constraints for each number of cycles. For pure initial states, the observable being constrained is the recurrence probability. We use our constraints for detecting undesired coupling to unaccounted environments and drifts in the driving parameters. To illustrate the relevance of these results for modern quantum systems we demonstrate our findings experimentally on a trapped-ion quantum computer, and on various IBM quantum computers. Specifically, we provide two experimental examples where these constraints surpass fundamental bounds associated with known one-cycle constraints. This scheme can potentially be used to detect the effect of the environment in quantum circuits that cannot be classically simulated. Finally, we show that, in practice, testing an <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>n</mml:mi></mml:math>-cycle constraint requires executing only <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>O</mml:mi><mml:mo stretchy="false">(</mml:mo><mml:msqrt><mml:mi>n</mml:mi></mml:msqrt><mml:mo stretchy="false">)</mml:mo></mml:math> cycles, which makes the evaluation of constraints associated with hundreds of cycles realistic.
비원어민 예비 한국어 교사의 교안 분석 연구

This study aims to analyze lesson plans prepared by prospective non-native Korean language teachers, examine the characteristics of non-native Korean language teachers as a group, and recommend efficient measures for Korean language education practicum. While the interest of researchers in Korean language teachers has increased, they have focused mainly on native teachers. Although research on non-native Korean language teachers has increased recently, previous studies have not examined lesson plans prepared by prospective non-native teachers. Thus, this study analyzed the composition and content of 30 grammar lesson plans prepared by foreign students undergoing Korean language education training at universities in Seoul. The results showed a lack of diversity in types of exercise and task activities from a compositional perspective. Furthermore, the content quality was often attributable to their language proficiency. Based on this, measures were proposed to enhance the educational effectiveness of Korean language education courses for prospective non-native Korean language teachers. (Yonsei University·Pyeongtaek University)
Dynamic Action Facilitates Learning of Non-Adjacent Dependencies in Visual Sequences

Author(s): Lu, Helen Shiyang; Mintz, Toby | Abstract: Many events that humans and other organisms experience contain regularities in which certain elements within an event predict certain others. While some of these regularities involve tracking the co-occurrences between temporarily adjacent stimuli, others involve tracking the co-occurrences between temporarily distant stimuli (i.e., non-adjacent dependencies, NADs). Prior research shows robust learning of adjacent dependencies in humans and other species, whereas learning NADs is more difficult, and often requires support from properties of the stimulus to help learners notice the NADs. Here we report on four experiments that examined NAD learning from various types of visual stimuli. The results suggest that continuous movements aid the acquisition of NADs. We also found that human motion leads to more robust NAD learning compared to object motions, perhaps because of a richer representation. This richer representation could result in better memory and recall, and provide a stronger signal for NAD learning.
Hardware as Policy: Mechanical and Computational Co-Optimization using Deep Reinforcement Learning

Deep Reinforcement Learning (RL) has shown great success in learning complex control policies for a variety of applications in robotics. However, in most such cases, the hardware of the robot has been considered immutable, modeled as part of the environment. In this study, we explore the problem of learning hardware and control parameters together in a unified RL framework. To achieve this, we propose to model the robot body as a "hardware policy", analogous to and optimized jointly with its computational counterpart. We show that, by modeling such hardware policies as auto-differentiable computational graphs, the ensuing optimization problem can be solved efficiently by gradient-based algorithms from the Policy Optimization family. We present two such design examples: a toy mass-spring problem, and a real-world problem of designing an underactuated hand. We compare our method against traditional co-optimization approaches, and also demonstrate its effectiveness by building a physical prototype based on the learned hardware parameters. Videos and more details are available at https://roamlab.github.io/hwasp/ .