Reviewerly/exHarmony huggingface dataset:
Thirumoolarin Thirumanthira Thiruvarutkaatchi

This article looks at the various street game of the lord through the thirumandra Thiruvarut scenario. The essence of this article is to know the greatness of Siva, Siddhu, Siddhu games through Thirumanthiram. Through this article, the Principles of the life Style, Yoga, Ethical, and Piety which Thirumoolar illustrates through three thousand songs are researched. Thirumoolar’s Thirumandhiram (Patham Thirumurai) is a part of Panniru Thirumurai. This book includes many divine play of Lord Shiva and divine appearance of god to his devotees. A review of this book reveals the spiritual faith of Thirumoolar in Lord Shiva. The aim of this paper is to tell about spiritualism of Thirumoolar and his extreme belief in the mantra “OM NAMA SHIVAYA” to blend his soul with the supreme power. In Thirumanthiram, Thirumoolar has mentioned about Shivam, Bhathi, Yoga, Meditation, Shakthi in human physiology, Maya, Prayers, Belief in god, method of worshipping god. He categorized all these characteristics into science, psychology, spiritualism and exchange of soul from one body to another. he explained the presence of Lord Shiva in living and non-living things, blending of spiritualism with psychology, attitude of human beings towards spiritualism. Thirumanthiram insisted that the great five letters mantra “OM NAMA SHIVAYA” covers the entire universe with love and affection of Lord Shiva.
학술적 텍스트 쓰기를 위한 문법의 발견 학습 항목 선정 및 적용 연구

As an extension of previous research stating that discovery learning can be used in teaching grammar, this study predicted that this teaching method can be used effectively with “advanced Korean learners for academic purposes” who are actively engaged in metacognition activities, and focused on discovery learning of Korean grammar for academic text writing. First, this study analyzed the grammar items of writing textbooks for Korean learners for academic purposes and selected 60 discovery learning items of “grammar for academic text writing” by considering items that can be the subject of discovery learning. Moreover, the patterns of grammatical errors and frequency of selected grammar items are examined by analyzing the academic texts produced by the learners, and the scope of grammar discovery learning is presented to be applied to classes. Finally, a survey was conducted on the learners that provided the texts, through which their perception on “grammar in academic texts” and “discovery learning” is examined, and thereby presents ways to apply this knowledge to classes. (Kyung Hee University)
Информация в контексте современной радиожурналистики: основные значения термина

The definition of information is investigated both in general context and in relation to journalism. The concept of «information» is considered from the point of view of various scientific theories, the authors of which are, including authoritative foreign sociologists and philosophers. Emphasis is placed on such concepts as news and infotainment. The main sociocultural functions of the infotainment are considered, as well as the main criteria characterizing the notion «news information».
Modified Binary Artificial Bee Colony Algorithm with New Exploration-Exploitation Strategies

In this study, a novel binary optimization algorithm which addresses the exploitation problem of Artificial Bee Colony (ABC) algorithm is presented and named as Scoutless Rule-driven binary Artificial Bee Colony (SRABC). The algorithm exhibits competitive performance through comparison to recent binary ABC variants applied in feature selection problems. Similarly, an experimental verification is conducted for actual case scenario which showed that the algorithm is efficient in increasing the prediction accuracy and discovered the highly important predictors for on-time graduation. The better performance of SRABC is attributed to the new strategies applied in the employed and onlooker bee phases and the turning back of food sources in initialization phase.
In Search of the Fourth Dimension of Space

This is a scientific speculation that presents an unusual, but at the same time intuitive, idea of a cosmological model. The mathematical construction foresees a Universe of finite dimensions, in expansion, homogeneous and isotropic. Here all the points are equivalent and from each one there are no preferential directions. Gravity is needed to clarify some aspects of the model but is treated only at a qualitative level. An explanation is given to Galactic recession and the Lorentz transformations but math used is fairly simple. Definitions, data and formulas used can be easily found on the internet. To complete the whole, there is also a simple verification based on astronomical observations. The next step would be to add gravity, building a physical model with matter and energy. In the following publication [viXra:2008.0015] you can find the resulting model as an approximation for the Galaxy Epoch. It is based on the Einstein’s solution for weak fields to the field equation of General Relativity. You can use this only in the context of observable Universe, during the lasts 10 billion years. Finally, it is important to point out that this speculation leads to a falsifiable theory.
Video Playback Rate Perception for Self-supervisedSpatio-Temporal Representation Learning

In self-supervised spatio-temporal representation learning, the temporal resolution and long-short term characteristics are not yet fully explored, which limits representation capabilities of learned models. In this paper, we propose a novel self-supervised method, referred to as video Playback Rate Perception (PRP), to learn spatio-temporal representation in a simple-yet-effective way. PRP roots in a dilated sampling strategy, which produces self-supervision signals about video playback rates for representation model learning. PRP is implemented with a feature encoder, a classification module, and a reconstructing decoder, to achieve spatio-temporal semantic retention in a collaborative discrimination-generation manner. The discriminative perception model follows a feature encoder to prefer perceiving low temporal resolution and long-term representation by classifying fast-forward rates. The generative perception model acts as a feature decoder to focus on comprehending high temporal resolution and short-term representation by introducing a motion-attention mechanism. PRP is applied on typical video target tasks including action recognition and video retrieval. Experiments show that PRP outperforms state-of-the-art self-supervised models with significant margins. Code is available at github.com/yuanyao366/PRP
3D Data compilation in Geoscience Analyst: How to - examples from the NW Mineral Province Deposit Atlas

In this webinar, Dr Paul Gow gives a demonstration of how to import various different common types of exploration into the free Geoscience Analyst program. Examples of Geoscience Analyst datasets of deposits from the NW Mineral Province can be downloaded here.
LibGuides: Graphic Novels: Fiction Books

This guide shows the value of Graphic Novels not only as a source of entertainment for kids, but as a tool for increasing learning skills. Fiction Books
PERANCANGAN SISTEM INFORMASI PENYALURAN BERAS (RASKIN) PADA DESA BALONGGANDU JATISARI

The problem of poverty is one of the fundamental problems that is the center of attention of the government in any country. Government programs used to tackle poverty are Raskin (Rice for poor families) organized by BULOG. The Raskin program (distribution program for poor families) is a program from the Government. The program is an effort to reduce the burden of disbursement from poor households as a form of support in improving food security by providing social protection of cheap rice with a maximum of 15kg / poor household / month with each price Rp.1.600,00 per kg (net ) at the distribution point. In this case the distribution mechanism of poor rice distribution in the village of Kosar there are still many processes that have problems such as data collection recipients of rice raskin are still classified as less effective as in the recording of recipients RASKIN, still conventional. This causes the vulnerable data to be lost or corrupted. As well as data processing using Microsoft Excel, if the device used damaged data lost and no data backup, data processing must be repeated again. the information system of Raskin rice distribution effectively and efficiently and make it easier for the staff so that they can achieve the competitive advantage. The system can be developed and applied in fields that require computerization of existing data. the information system of Raskin rice distribution effectively and efficiently and make it easier for the staff so that they can achieve the competitive advantage. The system can be developed and applied in fields that require computerization of existing data.
Distillation of neural network models for detection and description of key points of images

Image matching and classification methods, as well as synchronous location and mapping, are widely used on embedded and mobile devices. Their most resource-intensive part is the detection and description of the key points of the images. And if the classical methods of detecting and describing key points can be executed in real time on mobile devices, then for modern neural network methods with the best quality, such use is difficult. Thus, it is important to increase the speed of neural network models for the detection and description of key points. The subject of research is distillation as one of the methods for reducing neural network models. The aim of thestudy is to obtain a more compact model of detection and description of key points, as well as a description of the procedure for obtaining this model. A method for the distillation of neural networks for the task of detecting and describing key points was tested. The objective function and training parameters that provide the best results in the framework of the study are proposed. A new data set has been introduced for testing key point detection methods and a new quality indicator of the allocated key points and their corresponding local features. As a result of training in the described way, the new model, with the same number of parameters, showed greater accuracy in comparing key points than the original model. A new model with a significantly smaller number of parameters shows the accuracy of point matching close to the accuracy of the original model.
Business secrets: The French Administrative Supreme Court declines jurisdiction to deal with an appeal against a decision of the French Competition Authority to include, within its interim measures decision, information that has benefited from the protection granted to business secrets (Google)

The period is decidedly rich with regard to the litigation surrounding the protection of business secrecy of companies. After the two rulings of the Court of Cassation of 29 January 2020 (see…
Rapid Structural Pruning of Neural Networks with Set-based Task-Adaptive Meta-Pruning

As deep neural networks are growing in size and being increasingly deployed to more resource-limited devices, there has been a recent surge of interest in network pruning methods, which aim to remove less important weights or activations of a given network. A common limitation of most existing pruning techniques, is that they require pre-training of the network at least once before pruning, and thus we can benefit from reduction in memory and computation only at the inference time. However, reducing the training cost of neural networks with rapid structural pruning may be beneficial either to minimize monetary cost with cloud computing or to enable on-device learning on a resource-limited device. Recently introduced random-weight pruning approaches can eliminate the needs of pretraining, but they often obtain suboptimal performance over conventional pruning techniques and also does not allow for faster training since they perform unstructured pruning. To overcome their limitations, we propose Set-based Task-Adaptive Meta Pruning (STAMP), which task-adaptively prunes a network pretrained on a large reference dataset by generating a pruning mask on it as a function of the target dataset. To ensure maximum performance improvements on the target task, we meta-learn the mask generator over different subsets of the reference dataset, such that it can generalize well to any unseen datasets within a few gradient steps of training. We validate STAMP against recent advanced pruning methods on benchmark datasets, on which it not only obtains significantly improved compression rates over the baselines at similar accuracy, but also orders of magnitude faster training speed.
LibGuides: Movies & More Guide: Home

Need a break? The Movies & More Guide helps you find online movies, literature, art, museums, animal webcams, and puzzles from LUC, public libraries, and Internet sources.
MEASUREMENT OF DISPLACEMENT STATE FOR RC APARTMENT BUILDINGS AT HASHIMA ISLAND USING SATELLITE POSITIONING INFORMATION

Low cost GNSS sensors were installed on old RC buildings at Hashima Island, Nagasaki, JAPAN to measure deteriorated state. A statistical population moving average method was applied to those GNSS data as residual deformation measurement technique and analyzed in chronological orders. And temperature related expansion and contraction deformation were found in those buildings indicating their elastic behavior. Furthermore, the data can be continuously recorded and transferred in harsh measurement environment.
A Preliminary Exploration into Effectively Combining Computer Technology with English Teaching

Abstract Since the reform and opening up, the number of people learning English is soaring in China, and great attention has been attached to English learning. However, the achievement of large investment is not so satisfying. Chinese English learners are labeled as “dumb users of English”. After analyzing the status of English teaching in China, this paper discusses the problems and proposes several computer-assisted English teaching methods, such as hierarchical teaching, tiered exercises and guidance outside the school and “Internet +”, to tackle these problems.
Unitary Operators Over Quantum Systems with Several Levels

Abstract High-dimensional quantum states generalise multi-valued logics. The analogous of Pauli transformations acting on these quantum states determine a subgroup structure in U( n ), which acts over the maximally entangled Bell states. These properties are suitable to produce superdense coding communication protocols.
StatAssist & GradBoost: A Study on Optimal INT8 Quantization-aware Training from Scratch.

This paper studies the scratch training of quantization-aware training (QAT), which has been applied to the lossless conversion of lower-bit, especially for INT8 quantization. Due to its training instability, QAT have required a full-precision (FP) pre-trained weight for fine-tuning and the performance is bound to the original FP model with floating-point computations. Here, we propose critical but straightforward optimization methods which enable the scratch training: floating-point statistic assisting (StatAssist) and stochastic-gradient boosting (GradBoost). We discovered that, first, the scratch QAT get comparable and often surpasses the performance of the floating-point counterpart without any help of the pre-trained model, especially when the model becomes complicated.We also show that our method can even train the minimax generation loss, which is very unstable and hence difficult to apply QAT fine-tuning. From extent experiments, we show that our method successfully enables QAT to train various deep models from scratch: classification, object detection, semantic segmentation, and style transfer, with comparable or often better performance than their FP baselines.
Development of an interactive application for the virtual reality

This project is an attempt to get expert knowledge of VR technology and have a clear perception of the Linator as an example.The main purposes are helping to gain knowledge of this engine, concepts and mechanism, how its animation works and identify each part (geometries and tasks) by using VR-headset.The idea of this project is to find the way to fully understand this machine and to link the theoretical science to practical reality for educational and industrial purposes in three main steps: Digitalization, Data reparation and acquisition and Animation.The presentation ways depend on the capabilities of both the software and hardware.Thus, this is also an attempt to generalize presentation ways which can be used to apply on other mechanical machines.
Penerapan Model Pembelajaran Discovery Learning Muatan Matematika Sebagai Upaya Meningkatkan Hasil Belajar Siswa Di Kelas IV SDN 137/IX Petaling

This research aims to obtain information and discuss the Implementation of Discovery Learning Model of Mathematics Content as an effort to improve student learning outcomes in Grade IV SDN 137/IX Petaling. This type of research is class action research. This research was conducted at SDN 137/IX Petaling in the even semester of the 2018/2019 school year. The subjects in this study were grade IV students of SDN 137/IX Petaling with a total of 28 students with a male number of 18 men and 10 women. These research procedures include planning, implementation, observation, and reflection. The study was conducted in two cycles, each cycle consisting of two meetings. Techniques used in data collection are observations, tests, field records and documentation. Data is analyzed through percentage and data reduction. The results of this study show that the results of students' mathematics content in the learning process improved by using discovery learning models with the act of giving praise.
Use of Video Lessons in Distance Learning

The article deals with issues of methodology of establishing distance learning by means of video lessons. It contributes to the resolution of methodological contradictions that can take place while establishing distance learning process. The purpose of the research is to clarify the concept of video lessons as well as to identify organizational and pedagogical conditions for effective use of video lessons in distance learning. The following research methods were used: analysis of scientific and pedagogical literature, conference materials, study of educational Internet portals, analysis of practical experience on the use of video lessons in distance learning for schoolchildren. As a result of the research, the concept of video lesson is clarified, its types are briefly described in terms of form and methodological content, and online learning platforms for distance learning are reviewed. Various options for organizing distance learning for schoolchildren using video lessons, their capabilities and limitations are presented, and detailed methodological recommendations are given. It is concluded that the presence of three mandatory stages in the distance learning process, definition of the interaction mode in each of the stages, based on specific conditions of the learning process (the technical capabilities of the parties, the nature of the educational material, level of preparation and motivation of pupils), the presence of qualitative feedback in the dyad "teacher – student" are related to the organizational and pedagogical conditions for effective use of video lessons in distance learning.
TOWARDS BENCHMARKING A VIRTUAL SCAFFOLD What it Should Be, Can, Cannot be

Cloud computing is becoming vogue among the business firms. The reason behind is - its availability of services over internet anywhere, anytime. Cloud Benchmarking is nothing but fixing standards while developing Multi-Tenant SaaS application, which will result in better and amicable solution for the end- user. Virtualization is an important entity for Cloud based services. The virtual scaffold is virtualized platform to develop Multi-Tenant Software as a Service (SaaS) application. Cloud Pattern is a reusable component which can used in the Virtual Scaffold to develop applications. Benchmarks for Cloud based SaaS application is still involute. This paper proposes a virtual architecture and provides a Pattern for pragmatic implementation of benchmark solution. The aspects discussed in this paper will enlighten the sceptics and researchers to thoroughly understand a set of quantifiers essential to implement the virtual architecture in the seclude tenant perspective and will motivate in tweaking the SaaS applications.
A virtual reality-based language learning environment to teach sentence word order

As part of a larger interdisciplinary research project, the objective of this small-scale study is to develop an engaging Virtual Reality (VR) based language learning task focused on sentence word order.It builds on a previous study of a VR-based language activity targeting prepositions.This study focused on providing an engaging language learning experience through immersive visual effects and tactile feedback from interactive 3D worlds.Furthermore, a new standalone HMD system that allowed users to walk freely around the VR space was procured for the study.University students (n = 17) each completed ive sentences during a single treatment session.A 28 question exit survey was conducted immediately after the experiment.Analysis of the results showed that 11 out of 17 subjects felt the operation of the VR task was intuitive.Subjects found the learning tasks were monotonous.In addition, some found it dificult to move around the VR space using handheld VR controllers while wearing a wired Head Mounted Display (HMD).In addition, all subjects stated that compared to traditional language-learning activities, they enjoyed doing the activity.However, a review of the subjects' behaviors, captured by a video camera, indicated that some subjects were initially confused about physically manipulating the words.Based on the study results presented here, the VR-based language activity was found to be a pleasurable way to study sentence word order.Future goals include the creation of interactive tutorials and a larger set of content.
$E^3$: Visual Exploration of Spatiotemporal Energy Demand

Understanding demand-side energy behaviour is critical for making efficiency responses for energy demand management. We worked closely with energy experts and identified the key elements of the energy demand problem including temporal and spatial demand and shifts in spatiotemporal demand. To our knowledge, no previous research has investigated the shifts in spatiotemporal demand. To fill this research gap, we propose a unified visual analytics approach to support exploratory demand analysis; we developed E3, a highly interactive tool that support users in making and verifying hypotheses through human-client-server interactions. A novel potential flow based approach was formalized to model shifts in energy demand and integrated into a server-side engine. Experts then evaluated and affirmed the usefulness of this approach through case studies of real-world electricity data. In the future, we will improve the modelling algorithm, enhance visualisation, and expand the process to support more forms of energy data.
DEVELOPMENT OF AN ELECTRONIC SCHEDULE OF UNIVERSITY CLASSES

This article discusses the problems of developing an electronic schedule of classes at the University. The main functionality of the application is defined. User groups are identified, their needs and functions are considered