Reviewerly/exHarmony huggingface dataset:
VortexNet: Learning Complex Dynamic Systems with Physics-Embedded Networks

In this paper, we present a novel physics-rooted network structure that dramatically facilitates the learning of complex dynamic systems. Our method is inspired by the Vortex Method in fluid dynamics, whose key idea lies in that, given the observed flow field, instead of describing it with a function of space and time, one can equivalently understand the observation as being caused by a number of Lagrangian particles ----- vortices, flowing with the field. Since the number of such vortices are much smaller than that of the Eulerian, grid discretization, this Lagrangian discretization in essence encodes the system dynamics on a compact physics-based latent space. Our method enforces such Lagrangian discretization with a Encoder---Dynamics---Decode network structure, and trains it with a novel three-stage curriculum learning algorithm. With data generated from the high precision Eulerian DNS method, our alorithm takes advantage of the simplifying power of the Lagrangian method while persisting the physical integrity. This method fundamentally differs from the current approaches in the field of physics-informed learning, and provides superior results for being more versatile, yielding more physical-correctness with less data sample, and faster to compute at high precision. Beyond providing a viable way of simulating complex fluid at high-precision, our method opens up a brand new horizon for embedding knowledge prior via constructing physically-valid latent spaces, which can be applied to further research areas beyond physical simulation.
Kesiapan Lulusan S1 Akuntansi Universitas di Bandung Dalam Menghadapi Era Teknologi Revolusi Industri 4.0 Untuk Karir Sebagai Auditor

This study aims to find out how the readiness of Accounting graduate University in Bandung in facing the technological era of the industrial revolution 4.0 to prepare themselves to become auditors. Readiness Accounting graduate University in Bandung can be seen from the presence or absence of differences between technological expertise required by industry and those that have been run by Undergraduate Program in Accounting .This type of research is qualitative research, data collection by interviews, questionnaires, documentation and descriptive analysis. The population of this research is the Head of Undergraduate Program in Accounting and lecturers in the audit, system and financial accounting University in Bandung, which is Accredited A and the Auditor who works at the Jakarta Public Accountant Office.The results of this study indicate that there are still differences between the auditor`s need for industry revolution 4.0 technology expertise with the aim of learning industrial revolution 4.0 technology expertise related to the career of the auditors carried out at the Bachelor Program in Accounting, University in Bandung. The results of this study are a form of analysis of interviews and questionnaires conducted with indicators from reference books / related articles.
Shaping a creative environment to improve language proficiency and communication skills of Bauman University students

The paper discusses advantages of the informal approach to learning a foreign language participating in "Literature in the context of different cultures" salon organized at the Department of English for Mechanical Engineering at BMSTU. According to BMSTU educational standards, communication skills in oral and written forms both in Russian and in English are the key competencies for BMSTU students. Bauman educators of the English department came up with the idea of a literary salon to encourage their engineering students to communicate in English despite the fact that their focuses are sciences and engineering subjects. Its primary purpose is to shape the creative environment and to enhance students’ language learning possibilities. BMSTU students’ schedule is very concentrated, therefore literary salon activities tend to be flexible and agile. The mission of the literary salon is cross-cultural interaction, spiritual and moral development, soft skills cultivation, fostering communication, and mastering a language. A stage performance helps to remove a psychological barrier in communication and to develop students’ cognitive skills, first, a memory. English literary salon as a kind of non-formal, extra-curricular activity can affect English language learning positively and become a fabulous teaching tool and reinforcement. Both formal and informal education settings offer different strengths to the educational process. While both curricular and extra-curricular programs serve students, many of them who feel disenfranchised in classes, blossom in after-classes settings. Real learning can happen in a setting where students feel less intimidated or more comfortable than they do in a formal classroom. The ultimate goal is that their success in an informal setting can lead to greater confidence in the formal classroom.
EFFECT OF MOBILE BANKING ON CUSTOMERS’ TRANSACTION COST IN SELECTED BANKS, MAIDUGURI METROPOLIS, BORNO STATE, NIGERIA:

The study assessed the effect of mobile banking on customers’ transaction cost in selected banks in Maiduguri Metropolis, Borno State, Nigeria. The study is survey in nature, the target population of the study is the customers of four selected commercial banks, data was obtained from the respondents through a structured questionnaire measured on a five point likert scale. The study employed inferential statistical analysis to analyse the data obtained where simple regression analysis was used with the aid of statistical package for social sciences (SPSS) version 20. The findings of the study revealed that there is positive significant effect of mobile banking on transaction cost to customers on transaction cost and computers on queue in the help desk. based on the findings the study recommends that commercial banks should ensure that they always put in enough efforts to support mobile banking in order to reduce the transaction cost of end users, Government and the financial institutions should provide infrastructural facilities like power and electricity to provide support for mobile banking.
Penggunaan Aplikasi Whatsapp Grup Untuk Pembelajaran Daring Pada Siswa SD Kelas 2 SD Negeri 2 Kesimpar

The current COVID-19 pandemic has a huge impact on education in Indonesia. The learning process that was initially carried out in schools has now become online learning that is carried out from home so that it requires teachers and students to be able to use existing information technology. The use of information technology is very helpful in the learning process during the COVID-19 Pandemic. The advancement of information technology which is very advanced today, can connect students with teachers without being limited by distance and time. Through the website, whatsapp group, google class, google doc or google form, which is provided by google distance learning, it can run smoothly. Learning activities at SD Negeri 2 Kesimpar, Abang District during the COVID-19 pandemic were also inseparable from this, the use of information technology through the website, whatsapp group, google class, google doc or google form, was also used to facilitate Darung's learning. The Ministry of Education and Culture also provides a free online learning platform called “Rumah Belajar”. For areas where the internet connection is not very good, the government is working with TVRI, the state television station, to deliver learning materials included in the Learning at Home program. And the government also provides free quotas for students to support Learning from Home activities. At the elementary school level, the upper class applications that are effective in using the online learning process are the google classroom application and the zoom application, while for the lower classes the application that can be used very effectively is the whatshapp application. group. In the online learning process carried out by students, it cannot be separated from the supervision of parents and teachers.
Testing a new browser gave me the ...

Testing a new browser gave me the incentive and opportunity to clean up my pile of bookmarks. Wondering how most people use and organise their
Research on Relation Extraction of Computer Remote Supervision Based on Neural Network

Abstract With the continuous prosperity of China’s computer Internet means and the continuous advancement of information process, we will find that the magnitude of some text information and resources in the network is doubling. A huge information base will be rebuilt in the vast network of our computers. In order to meet people’s more detailed information review, people put forward neural network. In the process of studying the informatization of relation extraction, people find that the concept of neural network can help to realize remote supervision and relationship extraction [1] . In fact, relation representation is an important connection theory between relation extraction and remote supervision. How to use neural network to effectively link and optimize the two has become the primary task and goal of current researchers.
Combined 3D super-resolution, de-noising and partial volume correction for percutaneous ablation

Percutaneous cryoablation is becoming more popular for the treatment of renal cell carcinoma. Interventional computed tomography (iCT) is commonly used for guidance but reducing radiation dose and increasing slice thickness makes super-resolution (SR) essential for improving image quality. The proposed method takes low quality (LQ), thick slice images and converts them to high quality (HQ), thin slice images while performing denoising and partial volume correction in the z-direction. As LQ and HQ iCT images are challenging to pair up, we train a 3D U-Net equipped with an up-sampling module on simulated LQ (sLQ) data and then test on the real LQ (rLQ) images with cubic interpolation and random forest as comparison. During validation on sLQ data, the U-Net outperformed interpolation and random forest (SSIM 0.9991 vs 0.9959 and 0.9985 respectively), but performance suffered when testing on the out-of-distribution rLQ images. The Dice score showed a substantial improvement when used to compare needle segmentations performed on U-Net generated images versus those from interpolation and random forest (0.4073 vs. 0.2919 and 0.3777 respectively), indicating that the U-Net is reducing the z-direction partial volume effect to a greater degree than these techniques. We have shown that a neural network trained to perform SR on simulated data outperforms interpolation and random forest on real data in terms of localisation of clinically relevant objects such as needles, despite the differing data distribution.
PENGARUH KEAKTIFAN MENGIKUTI KEGIATAN EKSTRAKURIKULER TERHADAP KECERDASAN SOSIAL SISWA(Studi Korelasional di Kelas IX SMPN 3 Jatinangor)

The problem of this research is the number of students who do not participate in extracurricular activity and the low value of their social intelligence. The intention of this research is to know the influence of students’ participation in extracurricular activity towards their social intelligence. This research uses quantitative approach with correlational method. The sample of this research included 137 students of 9thgrade of SMP Negeri 3 Jatinangor. This research uses questionnaire to assess/measure students’ participation in extracurricular activity and their social intelligence. The data are analyzed using T-Test assisted with SPSS 22.00 for windows. Based on statistic examination using correlation statistic formula of Rank Spearman is gotten percentage of correlation coefficient 0,717 and thitung11,951. By that result is gotten the conclusion thitung11,951 > ttable1,960 at significant standard 5%. So that there is positive and significant influence from the extracurricullar activity on social intelligence of students grade IX SMPN 3 Jatinangor with sturdy correlation level.
Some aspects of business process modeling of higher education institutions

Actual aspects of process modeling in HEI’s are considered. Issues related to process modeling in universities were studied. A reference model of the university system is given, on the basis of which business processes can be modeled and implemented at different levels of management. The generalized models of business processes «Staff» and «Scientific activity», as well as KPI are presented, on the basis of which it is possible to improve quality management.The proposed models will allow to timely identify possible problems that require a solution, take measures to transform the university’s business processes.
The place of Synchronic in Education. Reflections from the educational action in Times of Pandemic

We propose to analyze the online teaching mode and the constitution of the IPECAL community, defining what we call P2P circles as an alternative to the MOOC model in education and its reflexes on the role of the educator, from the specificity that synchronicity can fulfill in an educational project. The present theme emerges from the author's experience as coordinator of a Graduate in the middle of the COVID-19 pandemic, which involves more than 100 students from different countries in Latin America, in particular Colombia, Chile, Mexico and Argentina. Keywords: MOOC, P2P, Popular Education, Potential Present, Improvisation, Synchronic.
THE INFLUENCE OF DRTA (DIRECTED READING THINKING ACTIVITY) METHOD ON THE STUDENTS’ READING COMPREHENSION AT SMA TAMAN SISWA BINJAI:

This study is aimed to know the influence of the DRTA (Directed Reading Thinking Activity) method on the student’s reading comprehension. Bauman proposes the DRTA Method. The design of the study is experimental research. In experimental research, the research consists of two classes; there are experiment and control classes. The research includes pre-test and post-test. The population is 107 and the sample 68 students. The author uses simple random sampling to determine the sample of the study. In the pre-test data, the mean score of the experiment class is 52,87, and the mean score of control class is 52,57. In post-test data, the mean score of experimental class is 76,81 and mean score of control class is 69,14.   Based on the analysis the pre-test data, the value of Tcounted is 0,025 which is compared with Ttable is 1.668 or Tcounted Ttable , Ha is accepted. There is an effect of the DRTA (Directed Reading Thinking Activity) method on the student’s reading comprehension.
Exploring the data behind students’ published theses - Analyzing the pride of Lund University

Lund University have for over ten years been using a website called LUP Student Papers where they publish theses from bachelor and master courses. The aim of this thesis is to use visualizations and data mining techniques that will explore and shows interesting aspects of the data. The wide variety of variables in the dataset can be used to gain insight regarding several interesting questions such as are the number of theses increasing for each year? Is a thesis in English becoming more common? How many times have a thesis been downloaded on average? The second purpose of this thesis is to use a Random Forest model and classify the abstract into three faculties, LUSEM, Social Science and Engineering. The aim is to see if the three faculties can be easily classified which would suggest that there is some noticeable difference in the text between the faculties. The abstracts had to be preprocessed with natural language processing techniques such as tokenization and stemming. The classification model achieved a relatively good accuracy around 0.80 and therefore suggest that the abstract can be classified. Further research can focus on different models for text classification. (Less)
Hate Speech: An Analysis of Free Speech Advocacy

The following is a review of Nadine Strossen’s new book, Hate: Why We Should Resist It with Free Speech, Not Censorship. The review provides an analysis of the book’s coverage and also contains constructive criticism in the areas of trigger warnings, private/public distinctions, and overall advocacy tactics.
Decision Tree Learning Approach for Knowledge Acquisition from A Medical Database.(Dept.E)

Automated knowledge acquisition (AKA) tools hold promise of preventing the process of acquiring knowledge from becoming the bottleneck in the development of knowledge base systems (KBSs). Most hospitals keep detailed records of patients containing descriptions of symptoms, diagnosis, prescribed medicine, and observed changes over time. Cumulatively, these records contain a wealth knowledge about medical diagnosis and treatment. The knowledge acquisition process would be significantly simplified if an automated system could look at these records, and extract valuable pieces of knowledge. Doctors would only need to verify the output of these knowledge acquisition tools rather than sit through hours of interview with knowledge engineers. This paper presents a new methodology for knowledge acquisition from databases. The p roposed methodology coincide with RITIO algorithm 13) in the rule induction without drawing the decision tree and in the eliminating less effective attributes. It builds the decision tree when needed. The new methodology differs from the ID3' likes algorithms (15) and RITIO since it Gods the global optimal solutions via back tracking. It is tested on standard example and applied on a real world database.
Augmented Reality for Young Learners

Augmented Reality (AR) is starting to gain its popularity as it is considered to have pedagogical potentials which offer new and meaningful learning experiences for students. AR could cater to children’s curiosity by providing opportunities to explore both real-world and virtual-world in a close-to-authentic way. By accessing some information that was augmented through pictures, texts, videos, and 3D objects to 2D pictures, children can get accessed to virtual learning resources that are hardly accessible in the real world. This article will discuss augmented reality technology in general and then focus on the pedagogical potential of AR for teaching young learners. Some AR applications that have the potential for play and learning activities with young children will be discussed in the final section.
Some aspects regarding the implementation of a Web application in different SAP UI technologies

Abstract Currently, in the development and implementation of an web application, the software developers are turning to those technologies that satisfy the client’s requirements, that can be easily extended and have optimal results in terms of execution time. This scientific paper addresses issues related to the development and implementation of the same application using three different web technologies, existing on the SAP NetWeaver platform. In this context, aspects related to the SAP NetWeaver technological platform and the SAP AS application server ABAP, the facilities offered by these for developing and implementing web applications, as well as the features specific to Web Dynpro ABAP, Floorplan Manager and WebClient UI technologies are highlighted.
Exploring Sub-Pseudo Labels for Learning from Weakly-Labeled Web Videos

Learning visual knowledge from massive weakly-labeled web videos has attracted growing research interests thanks to the large corpus of easily accessible video data on the Internet. However, for video action recognition, the action of interest might only exist in arbitrary clips of untrimmed web videos, resulting in high label noises in the temporal space. To address this issue, we introduce a new method for pre-training video action recognition models using queried web videos. Instead of trying to filter out, we propose to convert the potential noises in these queried videos to useful supervision signals by defining the concept of Sub-Pseudo Label (SPL). Specifically, SPL spans out a new set of meaningful middle ground label space constructed by extrapolating the original weak labels during video querying and the prior knowledge distilled from a teacher model. Consequently, SPL provides enriched supervision for video models to learn better representations for downstream tasks. We validate the effectiveness of our method on four video action recognition datasets and a weakly-labeled image dataset to study the generalization ability. Experiments show that SPL outperforms several existing pre-training strategies using pseudo-labels and achieves competitive results on HMDB-51 and UCF-101 datasets compared with recent pre-training methods.
Got an external Lenovo Compact USB keyboard ...

Got an external Lenovo Compact USB keyboard and really trying hard to get used to using the TrackPoint instead of a separate mouse. It works
A Real-time Algorithm of Task Allocation and Trajectory Planning Considering Task Weights for Drone Swarms

This paper describes a real-time algorithm of task allocation and trajectory planning for drone swarms. The task allocation algorithm is designed based on the CAPT algorithm, and especially, it allocates tasks considering task weights. Also, the trajectory planning algorithm generates minimum snap trajectories which are dynamically feasible for drones of multi-rotor types, and guarantees collision avoidance between neighboring agents. The proposed algorithm is implemented using various libraries, and can be executable in the ROS environment, and simulation results confirm feasibility of the proposed algorithm.
Local Backlight Dimming for Liquid Crystal Displays via Convolutional Neural Network

This paper presents a new local backlight dimming (LBD) for liquid crystal displays (LCD) method based on a convolutional neural network (CNN). Many previous LBD algorithms controlled the backlight intensity relying on hand-crafted features within a local block, that is, statistical information of pixel values in each block. However, they have a lack of generalization ability due to the use of hand-crafted features, which are usually not adaptive to the input properties. Also, they usually disregarded the diffusion property of the backlight that may affect the neighboring blocks. In this respect, we propose a CNN-based LBD algorithm to alleviate these problems. To address the lack of generalization ability of hand-crafted features, we adopt a CNN-based approach that learns the features and thus provides appropriate backlight intensities for the given inputs. Also, the diffusion property of light and leakage property of liquid crystal are considered when training the network, thereby alleviating the loss of details while achieving the high contrast ratio. Experiments show that the proposed method outperforms both quantitatively and qualitatively compared to the other LBD algorithms. Specifically, for the images from the DIV2K dataset, the proposed method achieves at least 1dB enhancement in PSNR, showing the generalization performance.
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Find out what services are currently available from the Library and how they are being delivered.
TENT: Efficient Quantization of Neural Networks on the tiny Edge with Tapered FixEd PoiNT.

In this research, we propose a new low-precision framework, TENT, to leverage the benefits of a tapered fixed-point numerical format in TinyML models. We introduce a tapered fixed-point quantization algorithm that matches the numerical format's dynamic range and distribution to that of the deep neural network model's parameter distribution at each layer. An accelerator architecture for the tapered fixed-point with TENT framework is proposed. Results show that the accuracy on classification tasks improves up to ~31 % with an energy overhead of ~17-30 % as compared to fixed-point, for ConvNet and ResNet-18 models.