Reviewerly/exHarmony huggingface dataset:
A Learned Compact and Editable Light Field Representation

Light fields are 4D scene representation typically structured as arrays of views, or several directional samples per pixel in a single view. This highly correlated structure is not very efficient to transmit and manipulate (especially for editing), though. To tackle these problems, we present a novel compact and editable light field representation, consisting of a set of visual channels (i.e. the central RGB view) and a complementary meta channel that encodes the residual geometric and appearance information. The visual channels in this representation can be edited using existing 2D image editing tools, before accurately reconstructing the whole edited light field back. We propose to learn this representation via an autoencoder framework, consisting of an encoder for learning the representation, and a decoder for reconstructing the light field. To handle the challenging occlusions and propagation of edits, we specifically designed an editing-aware decoding network and its associated training strategy, so that the edits to the visual channels can be consistently propagated to the whole light field upon reconstruction.Experimental results show that our proposed method outperforms related existing methods in reconstruction accuracy, and achieves visually pleasant performance in editing propagation.
LibGuides: Tips on Studying and Reading for College: Reading

Improve your techniques for listening and taking notes, reading on a college level, studying and memorizing, and prepping for exams.
Searching by Generating: Flexible and Efficient One-Shot NAS with Architecture Generator

In one-shot NAS, sub-networks need to be searched from the supernet to meet different hardware constraints. However, the search cost is high and $N$ times of searches are needed for $N$ different constraints. In this work, we propose a novel search strategy called architecture generator to search sub-networks by generating them, so that the search process can be much more efficient and flexible. With the trained architecture generator, given target hardware constraints as the input, $N$ good architectures can be generated for $N$ constraints by just one forward pass without re-searching and supernet retraining. Moreover, we propose a novel single-path supernet, called unified supernet, to further improve search efficiency and reduce GPU memory consumption of the architecture generator. With the architecture generator and the unified supernet, we propose a flexible and efficient one-shot NAS framework, called Searching by Generating NAS (SGNAS). With the pre-trained supernt, the search time of SGNAS for $N$ different hardware constraints is only 5 GPU hours, which is $4N$ times faster than previous SOTA single-path methods. After training from scratch, the top1-accuracy of SGNAS on ImageNet is 77.1%, which is comparable with the SOTAs. The code is available at: https://github.com/eric8607242/SGNAS.
Study on Safety in Integrated Manufacturing System

In order to automate operations, many factories today use IMS (Integrated Manufacturing System). Safety in this manufacturing system must take into account the interrelationships between machines. However, safety of IMS depends on the integrator's skill. Therefore, this study considerate the theorization of safety ensuring and the requirements for ensuring both safety and productivity based on ISO 11161, the International Standard for integrated manufacturing system. The safety issue in the IMS are to detect person in the blind spots in a large workspace and how to determine the span of control. SSS (Safeguarding supportive system) is available detection the person in it. To determine the span of control, the Boolean logic is applied. The case study is carried out on the model IMS. The IMS for the case study consists of a minimum number of machines according to ISO 11161.
Facial expression recognition using switch instance-batch normalization

Facial expression recognition is widely used in video surveillance, assisted driving, and distance education. With the application of deep learning technology in facial expression recognition, many previous studies have shown good performance, but they are mainly identified in small-scale datasets with limited samples, lacking generalization ability for a wide range of scenes, and can’t meet the practical application needs. Previous studies have shown that Instance Normalization (IN) exhibits strong performance in terms of appearance invariance. In this paper, the normalization layer of facial expression recognition network is studied extensively, and a Switchable Instance-Batch Normalization (SIBN) method is proposed to balance feature appearance variance and content semantic information. The method was verified in three commonly used expression datasets CK+, Oulu-CASIA, and MMI. The experimental results show that SIBN stability improves the recognition accuracy of the model on a single dataset, and greatly enhances the performance of network cross-domain identification. The experimental results demonstrate the superiority of the proposed method.
THE USE THINK PAIR SHARE TO IMPROVE STUDENTSâ€™ READING COMPREHENSION AT THE NINTH GRADE STUDENTS OF JUNIOR HIGH SCHOOL ERA IBANG MEDAN

This research is conducted in order to improve studentsâ€™ reading comprehension in the easiest way through using think pair share of the ninth grade students of Junior High School Era Ibang Medan, and it also help the English teacher of the ninth grade students of Junior High School Era Ibang Medan to managed activities in classroom.In conducting this research, the researcher used Classroom Action Research (CAR) as the method of research. This research consisted of two cycles and each cycle consisted of four steps, they were planning, action, observation and reflecting. Each cycle was conducted in three meetings, so the researcher conducted this researcher in six meetings for one month and two weeks. The data were in the form of qualitative and quantitative data. The qualitative data was analyze the learning teaching process. The quantitative data was to count the studentsâ€™ score in pre-test and post-test.The result of this research shows that using think pair share of the ninth grade students of Junior High School Era Ibang Medan could improve their reading skills. The studentsâ€™ responses showed that they were interested in learning reading through think pair share. Morever, the studentsâ€™ achievements in pre-test and post-test showed a significant improvement. The studentsâ€™ average score in pre-test was 53,19%, while in the formative test in cycle I, the studentsâ€™ average score is 60,03, and in the post-test cycle II, the studentsâ€™ average score is 76. That means the think pair share can improve the studentsâ€™ reading skill.
Memanfaatkan Algoritma K-Means Dalam Memetakan Potensi Hasil Produksi Kelapa Sawit PTPN IV Marihat

Based on data on the results of oil palm production in PTPN IV Marihat displays several locations with fruit yields that vary in number. For this reason, grouping of potential fruit-producing locations is needed to know which locations produce large or small numbers of palm fruit. The production sharing is usually done based on the location or block of harvesting oil palm fruit. Therefore, a method is needed to facilitate the grouping of fruit producing locations. With the K-Means clustering approach, the division of location groups can be done based on harvested area (Ha), production realization (kg) and harvest year. In this research, clustering of potential fruit-producing areas was carried out using the K-Means algorithm. By using K-Means aims to facilitate the grouping of a block with a lot of fruit production, and low. The result of this research is that C1 (highest) is 14 Harvest Block data, and C2 (lowest) is 11 Harvest Block data.
User Friendliness: Ensuring UI Quality

Making an application user friendly is sadly often the last thing on a programmer’s mind.
EDUCATION IN MULTICULTURAL CLASSROOM: CHALLENGES AND RESPONSES

E. Sachkova 1, N. Ovchinnikova1, O. Mokhova2 1Russian University of Transport (RUSSIAN FEDERATION) 2Moscow University for Industry and Finance «Synergy» (RUSSIAN FEDERATION)
The Adaptive Roles of Positive and Negative Emotions in Organizational Insiders’ Engagement in Security-Based Precaution Taking

Protecting organizational information is a top priority for most firms. This reality, coupled with the fact that organizational insiders control much of their organizations’ valuable information, has led both researchers and practitioners to acknowledge the importance of insiders’ behavior for information security (InfoSec). Until recently, researchers have employed only a few theories to understand these influences, and this has generated calls for a broadened theoretical repertoire. Given this opportunity, we incorporate the framework of emotions developed in the information systems (IS) discipline by Beaudry and Pinsonneault (2010) and add the broaden-and-build theory (BBT) to understand the influence of discrete positive and negative emotions on insiders’ precaution-taking activities. Our findings demonstrate that the relationship between both positive and negative emotions and precaution taking is mediated by insiders’ (1) psychological capital (PsyCap), a higher-order, work-related construct of positive psychological resource capabilities, and (2) psychological distancing, a coping mechanism characterized by insiders’ attempts to detach themselves psychologically from a situation. By considering these factors, our model explains 32 percent of the variance in insiders’ precaution taking in organizations. Researchers and practitioners can use these findings to develop effective insider InfoSec training, including emotional appeals that increase insiders’ precaution taking.
COVID-19 Pandemic and Balance of Constitutional Rights: doi: 10.7417/CT.2021.2297

In 2020 the World Health Organization declared the Covid-19 to be a pandemic. Governments around the world are facing a tough challenge that could jeopardise the national healthcare systems. Safeguarding the rights of Covid patients and all citizens – especially those who are now even more vulnerable than they were before – is part of this challenge.This work aims to examine the issues arising from the current emergency in terms of how individuals’ constitutional rights have been balanced and how much people at the highest risk amid this pandemic – the homeless, the inmates in prison, geriatric and psychiatric patients, and doctors on the Covid frontline - have been protected. This analysis focuses mostly on one of the worst-hit countries by the SARS-CoV-2: Italy.
Quality of Service in Software Defined Networks for Scientific Applications: Opportunities and Challenges

Scientific applications require to process, analyze and transfer large volumes of data in the shortest possible time from distributed data sources. In order to improve their performance, it is necessary to provide them with specific QoS parameters. On the other hand, SDN is presented as a new paradigm of communications networks that facilitates the management of the communications infrastructure and consequently allows to dynamically incorporate QoS parameters to the applications running in this type of network. With both these paradigms in mind, we conducted this research to answer the following questions: Do scientific applications that are running in an SDN-Enabled distributed data centers improve their performance? Do they consider network QoS parameters for job scheduling? The methodology used was to consult articles in specialized databases containing the keywords SDN and for scientific applications: HPC and Big Data. Then, we analyzed the articles where these keywords intersect with some of the parameters related to QoS in communications networks. Also, we reviewed QoS proposals in SDN to identify the advances in this research area. The results of this paper are: i) QoS is an open issue to incorporate in scientific applications that are running in an SDN ii) we identified the challenges to join both these paradigms, and iii) we present a strategy to provide QoS to scientific applications that are being executed among SDN-Enabled distributed data centers.
Early Grade Reading Assessment for Primary School Students in Serang Banten

This article describes new strategies in teaching reading skills to primary school students based on the finding of Early Grade Reading Assessment instruments implemented in primary schools in Serang Banten, Indonesia. The authors describe the obtained results of the students’ skills in reading components. For example, we illustrate the proposed technique of teaching reading to primary school students. Our method shows that improvement in the students’ reading ability is moderate; the children are less able to recognize words; meaningless words are still hard to spell; and the students can understand the story well. The new strategy's effectiveness in evaluation is confirmed by calculating how the students recognize letters with a low reading speed of about 2.24 minutes for 100 letters. They could read 30 meaningful words in 3 minutes, but when reading something meaningless the students only read difficult 15 words in 15 minutes. General student reading was good at 86 percent, with only a few students who could not read the text. The students could understand 78 percent of the content of the reading by listening to the story and retelling the story orally. The children who were guided by parents or brothers or sisters had better reading skills. Another finding pertained to the availability of reading books besides textbooks for their reading sources. The new research results develop the students’ reading skills and can be used for developing the strategies in teaching student reading skills.
Some Regrettable Grading Scale Effects Under Different Versions of Evaluative Voting

Many voters seem to appreciate the greater freedom of expression afforded by alternative voting rules; in evaluative voting, for example, longer grading scales and/or negative grades seem desirable in so far as, all other things being equal, they allow greater expressivity. The paper studies to what extent the behavior of voters, and the outcomes of elections, are sensitive to the grading scale employed in evaluative (or “range”) voting. To this end, we use voting data from an experiment conducted in parallel with the 2017 French presidential election, which aimed to scrutinize the negative grade effect and the length effect in grading scales. First, this paper confirms that the introduction of a negative grade disfavors “polarizing” candidates, those whose political discourse provokes divisive debate, but more generally we establish that it disfavors major candidates and favors minor candidates. Second, under non-negative scales, polarizing candidates may be relatively disfavored by longer scales, especially compared with candidates who attract only infrequent media coverage and who are little known among voters. Third, longer scales assign different weights to the votes of otherwise equal voters, depending on their propensity to vote strategically. Overall, we observe that the benefits of the expressivity provided by longer scales or negative grades need to be balanced against the controversial advantage these give to minor candidates, and their tendency to undermine the principle that each vote should count equally in the outcome of the election.
Evaluating Strategic Marketing in Higher Education through Social Media: A Study with Reference to Saudi Arabia

This paper explains the strategic approach of Universities in promoting their profile through various social media tools such as facebook, twitter, etc.
Creating a Database from Code

So far we have created our entities and their metadata to instruct Entity Framework Core 5 what to create. As you will soon see, the process of taking those instructions and having them be interpreted by Entity Framework Core 5 to create your database is as simple as creating an initial migration and running that migration using Visual Studio. We will primarily be using the Microsoft SQL Server provider for Entity Framework Core in this book and thus will be creating a SQL Server database.
PHOTO CHRONICLE OF THE SCIENTIFIC LIFE OF THE BURYAT INSTITUTE OF SOCIAL SCIENCES ON THE ARCHIVAL MATERIALS OF THE TSVRK (1970–1980S)

The article presents the results of the search, identification, attribution and systematization of photographic materials on the history of academic science in Buryatia in 1970s – 1980s. Several blocks of images are highlighted – portraits (individual and group), official photo chronicle of meetings and events, photographs from expeditions, unofficial meetings. The characteristics of paleographic features of some photographs and albums are given. The differences in the methods of recording field-work results of different periods are determined.
THE EFFECT OF PICTURE AND PICTURE ON STUDENTS' ACHIEVEMENT IN WRITING DESCRIPTIVE TEXT

This study aims to determine whether the picture and picture method has a significant effect on the text description writing skills of students at SMP Al-Hidayah Medan or not. This study used quantitative method. The results of this study were obtained from the t test with a significance level of α = 0.05 and the accumulated results of two different groups, namely the experimental group (which applied picture and picture) and the control group (which did not use picture and picture). In the pre-test experimental group the average result obtained was 51.15 while the average post-test result was 83.75. In the pre-test control group the average result obtained was 53.45, while the average post-test result was 79.65. The results of the hypothesis obtained are ttest = 2.831 ≥ ttable = 1.685. This proves that the value of the experimental group is better than the control group, so it can be concluded that the use of pictures and picture methods can have a significant impact on students' descriptive writing skills.
Receding Horizon Motion Planning for Multi-Agent Systems: A Velocity Obstacle Based Probabilistic Method

In this paper, a novel and innovative methodology for feasible motion planning in the multi-agent system is developed. On the basis of velocity obstacles characteristics, the chance constraints are formulated in the receding horizon control (RHC) problem, and geometric information of collision cones is used to generate the feasible regions of velocities for the host agent. By this approach, the motion planning is conducted at the velocity level instead of the position level. Thus, it guarantees a safer collision-free trajectory for the multi-agent system, especially for the systems with high-speed moving agents. Moreover, a probability threshold of potential collisions can be satisfied during the motion planning process. In order to validate the effectiveness of the methodology, different scenarios for multiple agents are investigated, and the simulation results clearly show that the proposed approach can effectively avoid potential collisions with a collision probability less than a specific threshold.
三經에 나타난 ‘古’의 時期 解釋

‘古’ represented by old time has various meanings such as the past, ancient, or ancestors. For a long time, 古 had been vaguely used to mean old times. We need to look at this problem from a new angle. In this study, we compared and analyzed 古 from an ancient time perspective in the three representative classical scriptures(三經). The 古 in MengZi (孟子) was used to express the era of XiaYinZhou (夏殷周) dynasties and Chunqiu (春秋) period in various ways, but especially to praise figures related to the Zhou (周) dynasty. This explains that the background of the MengZi (孟子) period was the Zhou (周) dynasty. The ancient times shown in the book ShuJing (書經) are often referred to as Yin (殷) and the next is the story of (堯舜) period. Based on this, the main background of the book is YaoShunXiaYin (堯舜夏殷). Because the background of Poetries of The ShiJing (詩經) is Zhou (周), the ShiJing (詩經) mainly refers to the era of Zhou (周) dynasty. The book does not mention much of the times as 古. The times of FuXi (伏羲), YaoShun (堯舜), and Zhou (周) are coming out once each. It is often said to be 古 when talking about some instructive story. Depending on which era these lessons are considered to be from, the timing of many of them is different. Based on this evidence, one can also guess the historical background of the book. The research achievements of this study will not only help specify the period of 古 that was simply interpreted as mean the old times in the research and interpretation, but will also clarify the time influence and relationship between cultures, the origin and development process of institutions, and the activities of characters.
Data mining and decision support techniques for patients’ treatment management: A case of Parkinson’s disease

Computer-assisted management of patients' treatment is a challenge, especially for chronic diseases where patients are exposed to treatments with multiple medications. While the exposure to prescribed medications aims at reducing the severity of symptoms, it can have adverse effects on patients' quality of life due to the potential side effects of prolonged medication treatments. This tutorial aims to present a selection of methods and tools to empower the tutorial participants in using appropriate data mining and decision support tools for managing treatment and drug management of patients with chronic diseases. We will present the case of utilizing the power of data mining and decision support models for the treatment management of Parkinson's disease (PD) - a chronic neurodegenerative disease affecting people worldwide. The methodologies presented in the tutorial are based on short time-series data of patients' clinical symptoms and their medications treatments. The tutorial will contain a presentation of the data mining methodologies developed for determining patterns of disease progression and patterns and justification of antiparkinson medication therapy modifications. We will conclude the tutorial with the demonstration of a decision support model for antiparkinson medication modifications developed in coordination with clinicians specializing in PD. The presented methods are tested on the data from the Parkinson's Progression Markers Initiative (PPMI) (https://www.ppmi-info.org/). The tutorial is intended for both the health-care and informatics community researchers and practitioners. The audience will be familiarized with some of the challenges of PD, the potential of the PPMI study, the developed short time series methodologies and their possible application to other health problems. The tutorial will be presented by Anita Valmarska, a researcher at the Faculty for Computer and Information Science in Ljubljana, Slovenia. She developed methodologies for the analysis of short time series for determining patterns of PD progression and therapy modifications. Currently, she is working on the development of multi-view based methods for determining subtypes of PD patients.
Securing Sensitive Data with Ansible Vault

Some data that we need to use within our Playbooks may contain data that is sensitive and needs to be secured in some way, shape, or form. Rather than storing this sensitive data in cleartext directly in the Playbook, we can use ansible-vault to create a cyphertext file that we use with the Playbook. A simple requirement for this would be the user.yml file that we created earlier in the $HOME/ansible/setup directory; the user's password is stored in the Playbook in cleartext, which is not exactly ideal. By using a variable for the password, we can include reference to an encrypted variables file to secure the Playbook operation, allowing us to rest more peacefully at night.