Reviewerly/exHarmony huggingface dataset:
PROBLEMS FACING TEACHERS IN ONLINE LEARNING AT STATE ELEMENTARY SCHOOL IN GORONTALO CITY

The formulation of the problem in this research are (1) What are the problems faced by third grade teachers at SDN 75 Kota Tengah Gorontalo City in the implementation of online learning ; and (2) what efforts are made by third grade teachers to overcome problems in online learning. The purpose of this study was (1) know what are the problems faced by third grade teacher at SDN 75 Central City of Gorontalo in the implementation of online learning ; and (2) Knowing what efforts are being made by the teacher class III to solve problems in online learning . The type of research used is qualitative research. The research subjects were third grade teachers at SDN 75 downtown Gorontalo . The results showed that online learning at SDN 75 downtown Gorontalo, in its implementation, third grade teachers still had problems (1) problems faced by third grade teachers, namely, firstly, students had difficulty understanding learning materials (especially mathematics) and secondly, not all third-grade students had facilities. , ( of 22 students, 10 students are actively participating in online learning) the three parents are busy with their work so that children do not receive assistance when participating in online learning. the four constraints of network disturbances (internet speed access is not yet as needed); (2) The efforts of third grade teachers to overcome problems that arise in the implementation of online learning at SDN 75 Central City Gorontalo City . First, the teacher provides students with a theme book, the second, the teacher applies offline learning to students who do not have facilities. the three teachers conveyed to the parents of students to motivate students to be more diligent in studying and asked parents to pay attention to their children while they were at home. the four teachers see the situation and conditions, if the network disruption lasts a long time then the teacher continues learning using the whatsapp application .
Time series model building with Fourier autoregressive model

This paper presents time series model building using Fourier autoregressive models. This model is capable of modelling and forecasting time series data that exhibit periodic and seasonal movements. From the implementation of the model, FAR(1), FAR(2) and FAR(3) models were chosen based on the periodic autocorrelation function (PeACF) and periodic partial autocorrelation function. The coefficients of the tentative modelwere estimated using a discrete Fourier transform estimation method. The FAR(1) model was chosen as the optimal model based on the smallest value of periodic Akaike and Bayesian information criteria, and the residuals of the fitted models were diagnosed to be white noise using the periodic residual autocorrelation function. The out-sample forecasts were obtained for the Nigerian monthly rainfall series from January 2018 to December 2019 using the FAR(1) and SARIMA(1,1,1)x(1,1,1)₁₂ models. The results exhibited a continuous periodic and seasonal movement but the periodic movement in the forecasted rainfall series was better with FAR(1) because its values showed a close reflection of the original series. The values of the forecast evaluation for both models showed that the forecast was consistent and accurate but the FAR(1) model forecast was more accurate since its forecast evaluation values were relatively lower. Hence, the Fourier autoregressive model is adequate and suitable for modelling and forecasting periodicity and seasonality in Nigerian rainfall time series data and any part of the world with rainfall series that are mostly characterised with periodic variation.
Spatial Dependency Analysis to Extract Information from Side-Channel Mixtures.

Practical side-channel attacks on recent devices may be challenging due to the poor quality of acquired signals. It can originate from different factors, such as the growing architecture complexity, especially in System-on-Chips, creating unpredictable and concurrent operation of multiple signal sources in the device. This work makes use of mixture distributions to formalize this complexity, allowing us to explain the benefit of using a technique like Scatter, where different samples of the traces are aggregated into the same distribution. Some observations of the conditional mixture distributions are made in order to model the leakage in such context. From this, we infer local coherency of information held in the distribution as a general expression of the leakage in mixture distributions. This leads us to introduce how spatial analysis tools, such as Moran's Index, can be used to significantly improve non-profiled attacks compared to other techniques from the state-of-the-art. Exploitation of this technique is experimentally shown very promising, as demonstrated by its application to ASCAD dataset.
Impact of Mobile Phone on Sustainable Framing

The information and communication is a vital resource for agriculture and may contribute considerably to make sure food security and property by making awareness and talent development through access to information. The initial and most distinguished player of information delivery is public sector extension services that from past few years are sometimes criticized for their ineffective targeting, poor reach and also the vast body value of delivering information. Since past few years, the forceful increase in mobile penetration even in rural areas has result in evolution of ICT-based extension services models to publicize agriculture connected information. The goal of discrimination the mobile phone-enabled info delivery mechanism is to possess inclusive growth by reducing the information gap between enormous and little farmers and by making awareness. With this end, this paper analysis specific objectives excluding distinguishing potential desires of data and also the existing sources, includes the meta analysis of mobile impact studies chiefly in India in terms of up farmers socio-economic conditions by being higher connected to extension services, improved access to markets and higher science info.
PENERAPAN ALGORITMA FLOYD WARSHALL UNTUK MENENTUKAN JALUR WIFI TERPENDEK DI STUDENTCOMP

Studentcomp is one of the service providers engaged in the IT field. Studentcomp is located at Jl. Raya Lekong, Gandukepuh, Sukorejo, Ponorogo. Studentcomp offers several services, one of which is wireless wifi service. In these services, there are often obstacles in terms of billing to the customer's place. this often makes the billing department wrong in determining which path to take and which customers have not paid and which have paid. then a system is made that can help the employees of the wifi billing department in determining the shortest path to the customer's place using the floyd warshall algorithm. the floyd warshall algorithm itself uses a dynamic system so that it guarantees in terms of determining the optimum solution in terms of determining the shortest path. The results obtained by applying this algorithm to the system are assisting employees in determining the shortest path that must be taken to the customer's place and being able to find out which customers have or have not paid.
How to Manage Multiple Cloud Collaboration Tools in a WFH World

A surge of cloud-based collaboration and conferencing platforms in the remote workplace has left organizations struggling with security, compliance, cost and integration issues. Here's advice from ...
Future of Data Protection in India

The world is overflowing with data – data is being shared, processed and used at unimaginable speeds globally. For protection from misuse and breach of any data sharing process, it is imperative for the law of the land to embrace certain provisions to effectively curb such practices, and implement forces that keep a check on such trepidations. In light of this, the paper attempts to analyse the upcoming laws and policies that will regulate data protection and processing in India, in the drafts of Data Empowerment and Protection Architecture, released by NITI Aayog and expected to be executed starting fall of 2020, and the Personal Data Protection Bill, 2019. For such purposes, the paper shall contemplate recent cases of data protection breach in order to highlight the dire need for such laws in the contemporary society. It aims to comprehensively gain a view on what will be the future of data protection in the world’s largest democracy, India.
MosAIc: Finding Artistic Connections across Culture with Conditional Image Retrieval.

We introduce MosAIc, an interactive web app that allows users to find pairs of semantically related artworks that span different cultures, media, and millennia. To create this application, we introduce Conditional Image Retrieval (CIR) which combines visual similarity search with user supplied filters or conditions. This technique allows one to find pairs of similar images that span distinct subsets of the image corpus. We provide a generic way to adapt existing image retrieval data-structures to this new domain and provide theoretical bounds on our approach's efficiency. To quantify the performance of CIR systems, we introduce new datasets for evaluating CIR methods and show that CIR performs non-parametric style transfer. Finally, we demonstrate that our CIR data-structures can identify blind spots in Generative Adversarial Networks (GAN) where they fail to properly model the true data distribution.
EventPoint: Self-Supervised Local Descriptor Learning for Event Cameras

We proposes a method of extracting intrest points and descriptors using self-supervised learning method on frame-based event data, which is called EventPoint. Different from other feature extraction methods on event data, we train our model on real event-form driving dataset--DSEC with the self-supervised learning method we proposed, the training progress fully consider the characteristics of event this http URL verify the effectiveness of our work,we conducted several complete evaluations: we emulated DART and carried out feature matching experiments on N-caltech101 dataset, the results shows that the effect of EventPoint is better than DART; We use Vid2e tool provided by UZH to convert Oxford robotcar data into event-based format, and combined with INS information provided to carry out the global pose estimation experiment which is important in SLAM. As far as we know, this is the first work to carry out this challenging task.Sufficient experimental data show that EventPoint can get better results while achieve real time on CPU.
ORGANIZATION OF EDUCATION IN TECHNOLOGY AND ENTREPRENEURSHIP IN A CLOUD ENVIRONMENT

ORGANIZATION OF EDUCATION IN TECHNOLOGY AND ENTREPRENEURSHIP IN A CLOUD ENVIRONMENT Emilia Tosheva PhD, Southwest University &ldquo;Neofit Rilski&rdquo;, Tehnical faculty, Bulgaria, Blagoevgrad &nbsp; ABSTRACT The use of cloud tech
Understanding Model Drift in a Large Cellular Network.

Operational networks are increasingly using machine learning models for a variety of tasks, including detecting anomalies, inferring application performance, and forecasting demand. Accurate models are important, yet accuracy can degrade over time due to concept drift, whereby either the characteristics of the data change over time (data drift) or the relationship between the features and the target predictor change over time (model drift). Drift is important to detect because changes in properties of the underlying data or relationships to the target prediction can require model retraining, which can be time-consuming and expensive. Concept drift occurs in operational networks for a variety of reasons, ranging from software upgrades to seasonality to changes in user behavior. Yet, despite the prevalence of drift in networks, its extent and effects on prediction accuracy have not been extensively studied. This paper presents an initial exploration into concept drift in a large cellular network in the United States for a major metropolitan area in the context of demand forecasting. We find that concept drift arises largely due to data drift, and it appears across different key performance indicators (KPIs), models, training set sizes, and time intervals. We identify the sources of concept drift for the particular problem of forecasting downlink volume. Weekly and seasonal patterns introduce both high and low-frequency model drift, while disasters and upgrades result in sudden drift due to exogenous shocks. Regions with high population density, lower traffic volumes, and higher speeds also tend to correlate with more concept drift. The features that contribute most significantly to concept drift are User Equipment (UE) downlink packets, UE uplink packets, and Real-time Transport Protocol (RTP) total received packets.
Collective directional emission from distant emitters in waveguide QED

We study a system of two distant quantum emitters coupled via a one-dimensional waveguide where the electromagnetic field has a direction-dependent velocity. As a consequence, the onset of collective emission is non-simultaneous and, for appropriate parameters, while one of the emitters exhibits superradiance the other can be subradiant. Interference effects enable the system to radiate in a preferential direction depending on the atomic state and the field propagation phases. We characterize such directional emission as a function of various parameters, delineating the conditions for optimal directionality.
Comfort and Sickness while Virtually Aboard an Autonomous Telepresence Robot

In this paper, we analyze how different path aspects affect a user's experience, mainly VR sickness and overall comfort, while immersed in an autonomously moving telepresence robot through a virtual reality headset. In particular, we focus on how the robot turns and the distance it keeps from objects, with the goal of planning suitable trajectories for an autonomously moving immersive telepresence robot in mind; rotational acceleration is known for causing the majority of VR sickness, and distance to objects modulates the optical flow. We ran a within-subjects user study (n = 36, women = 18) in which the participants watched three panoramic videos recorded in a virtual museum while aboard an autonomously moving telepresence robot taking three different paths varying in aspects such as turns, speeds, or distances to walls and objects. We found a moderate correlation between the users' sickness as measured by the SSQ and comfort on a 6-point Likert scale across all paths. However, we detected no association between sickness and the choice of the most comfortable path, showing that sickness is not the only factor affecting the comfort of the user. The subjective experience of turn speed did not correlate with either the SSQ scores or comfort, even though people often mentioned turning speed as a source of discomfort in the open-ended questions. Through exploring the open-ended answers more carefully, a possible reason is that the length and lack of predictability also play a large role in making people observe turns as uncomfortable. A larger subjective distance from walls and objects increased comfort and decreased sickness both in quantitative and qualitative data. Finally, the SSQ subscales and total weighted scores showed differences by age group and by gender.
How does the Educational Supply Chain Management System work in the Engineering Faculty of Universitas Negeri Padang

This study aims to explore the Educational Supply Chain existing in the case faculty by using the sequential mixed methods (qualitative-quantitative). The use of mixed methods in this work not only captures the fully picture of the comprehensive research results but also fills the gap of lacking the use of mixed method in the existing literature. Purposive sampling method and simple random sampling method were used for selecting the participants. The number of participants for qualitative was 48 and 50 respondents for quantitative method. Semi-structured interview with at least 20 questions was used and 40 minutes was consumed in average per interview. Thematic analysis was employed for qualitative data analysis. Based on the qualitative results, themes were developed to build quantitative instruments. Pearson’s R-Table method was used for instrument validity test and Cronbach Alpha Coefficient was applied to test instrument reliability. To analyze the data, researcher utilized the Percentage Analysis method. The study resulted the Educational Supply Chain Management System in which five primary activities and four supporting activities. Primary activities involved input, operation, output, public relations, and services. Supporting functions consisted of procurement, technology management, human resources, and infrastructure management (finance and student affairs).
Cybercrime vs. Cyberwar: Paradigms for Addressing Malicious Cyber Activity

This contribution seeks to identify and assess the frameworks used to describe and deter malicious cyber activity (MCA), and to highlight legal and operational challenges in tackling problems that arise where these frameworks overlap or intersect. To that end, we examine two different models, an “armed conflict model” and a “law enforcement model,” that have been used to address the threat posed by such activity. The terms cyber-war and cyber-crime, respectively, encapsulate each of these models — yet the line separating these categories is not well defined, and both terms have been used by laypersons and experts alike to describe conduct ranging from network intrusions to data ex-filtration to denials-of-service. Our analysis of these ambiguities and their implications proceeds in four parts. Part I describes. Part II explores the assumptions underlying the predominant armed conflict model. Part III discusses the implications of characterizing MCA as cyber-war as opposed to cyber-crime. Part IV concludes by suggesting that these characterizations should be viewed along a continuum, and that the law enforcement model should not be given short shrift by policy-makers or — perhaps most importantly — appropriators.
An Efficient Pairing-Free Identity-Based Certificateless Signcryption

A certificateless (CL) signcryption scheme is a cryptographic primitive that provides user authentication and message confidentiality at the same time. CL signcryption schemes (as a type of certificateless encryption scheme) have solved problems concerning malicious server presentation, and the server who issues users' partial private keys and certificates cannot obtain users' signing keys. Therefore, the CL signcryption scheme is an excellent choice for protecting users' signing keys and providing user authentication and message confidentiality. Moreover, signcryption schemes have lower computational costs than signature and encryption schemes. The present study presents a short and efficient CL signcryption scheme based on the hyperelliptic curve (HC). Applying HC as the calculation base for designing the presented CL signcryption scheme reduces key-length from 160 bits to 80. The presented CL signcryption scheme is shorter than other recently-proposed ones with regard to communication overhead with its less than one-third shorter length compared to the shortest of the others. Moreover, it is more efficient than other recently-proposed CL signcryption schemes in the user-side computational cost, including the textit{key generation} and textit{user key generation} phases that have been halved in total. Finally, the security of the presented CL signcryption scheme was analyzed in the random oracle (RO) model based on the hardness of the point factorization problem (PFP) on HC.
Using Statistical Analysis Algorithm in Artificial Intelligence for Online Learning

The assessment outcome for many online learning methods are based on the number of correct answers and than convert it into one final mark or grade. We discovered that when using online learning, we can extract more detail information from the learning process and these information are useful for the assessor to plan an effective and efficient learning model for the learner. Statistical analysis is an important part of an assessment when performing the online learning outcome. The assessment indicators include the difficulty level of the question, time spend in answering and the variation in choosing answer. In this paper we will present the findings of these assessment indicators and how it can improve the way the learner being assessed when using online learning system. We developed a statistical analysis algorithm which can assess the online learning outcomes more effectively using quantifiable measurements. A number of examples of using this statistical analysis algorithm are presented.
Relevance Of National Literacy Movement, School Literacy Movement With Strengthening Character Education On MI Subject Matter (Study of MOEC Regulation Number 23 Year 2015 With Presidential Regulation No. 87 of 2017)

The issue of education is one area that is often seen as very vital and decisive in the field of government. One of the problems in education is the decline in the quality of reading among students. Indonesia has the lowest ability in the PISA and TIMSS competitions. This certainly requires innovation and creativity that can encourage the spirit of students to read especially at the Elementary School level. The method used in this paper is the study of literature. The Ministry of Education and Culture through Ministerial Regulation number 23 of 2015 launche an education policy. Educational policy in the form of the National Literacy Movement which has 3 domains, one of which is the School Literacy Movement to foster noble character towards students through language which is the first step to creating a culture of literacy and students' interest in reading. School Literacy Movement is more than just reading and writing but includes thinking skills according to the stages and components of literacy. The school literacy movement is expected to be able to bring change both in terms of behavior, attitudes and responsibilities as well as instilling and growing the values of the nation's character that is religious, nationalism, independent, mutual cooperation, and integrity in elementary school students. The character values are contained in Permendikbud Number 87 of 2017 concerning Strengthening Character Education (PPK). The National Literacy Movement, the School Literacy Movement is very closely related to the Strengthening of Character Education, in the implementation of the School Literacy Movement in schools and the Strengthening of Character Education has not been running optimally but can run when the school institutions and students are active.
Data Comparison among Encrypted Data using AES and Two Fish Algorithm on Cloud Computing Security

Now a day’s cloud security is an important aspects in cloud computing. The cloud usage among the public user increases rapidly. Due to security risk, data reliability and data privacy is lost among the cloud user. In this research we compared two different security algorithms such as AES and TwoFish algorithm with different parameter techniques. The five different parameters which are used to compare these algorithms such as Key length, Key strength, Time taken for Encryption, Encrypting quality by applying different attack such as (Partial attack, Dictionary attack, Brute Force attack, Time taken for Decryption). These two algorithms are most probably used among organization and users on promising manner and this entire algorithm can be worked in 256 bit length. By knowing the result of this parameters we can identify which algorithm is best for security.
Who is Paige Thompson? Alleged Capital One hacker went by alias 'erratic'

Paige A. Thompson, 33, aka “erratic” online, is charged with computer fraud and abuse after authorities said she took advantage of a misconfigured firewall to access the bank’s credit card customer data.