Reviewerly/exHarmony huggingface dataset:
Annotation Method for Human Activity and Device State Recognition Based on Smartphone Notification Removals

With the increasing spread of smartphones and wearable devices equipped with various sensors, human activities, biometric information, and surrounding situations can be recognized. The process of human activity recognition must construct a model that has learned annotated sensor data, i.e., ground truth, labels, or answer activity, in advance. Therefore, a large and diverse set of annotated data is required to improve and evaluate model performance. It is difficult to judge a user's situation even after observing acceleration data; thus, it is necessary to annotate the collected acceleration data. In this paper, we propose a method to estimate user and device situations from the user's response to a notification generated by a device, e.g., a smartphone. The user and device situations are estimated from the user's response time to the notification and the device's acceleration values. An estimation result with high confidence is given to the sensor data as an annotation. Increasing the frequency of notifications, response to the notifications can be used as a sensor. We assume that acceleration values are affected by a user and device situation when the device notifications are taken instantly after its generation. The system pursues a high precision of estimation by selecting input acceleration data based on the interaction to the notification so that the estimations can be used as annotations. Through an evaluation experiment, for seven types of annotation classes, an average precision of 0.769 and 0.963 for user-independent experiments and user-dependent experiments were achieved, respectively. We also tested the proposed method in a natural environment, where 25 correct annotations were given for 45 responses to notifications, no annotations were given for 19 responses, and only one incorrect notification was observed.
Noonomics. Experience of Creative Continuation of S.D. Bodrunov’s Ideas

The article presents the main provisions of S.D. Bodrunov’s theory of noonomics and synthesizes them with the leading theories of the leaders of the Frankfurt school: Jürgen Habermas and Axel Honneth. Noonomics refers to a new stage in the development of society as a whole, in which people will be forced out of material production, which will allow everyone to freely develop their creative powers. However, on the way to noonomics, humanity must avoid falling into a state of “digital concentration camp,” which is possible only by transforming human nature itself, moving “from zoo- to noo-state.” This implies a synthesis of science and culture and the highest value of moral self-improvement for each person. Therefore, it is the development of the human mind that will allow the transition to noonomics. It is the study of the content and possibilities of the mind that will allow us to creatively develop the theory of noonomics by using J. Habermas’s concept of communicative rationality and A. Honneth’s new theory of socialism. Communicative rationality is a special capability which makes possible to achieve mutual understanding between representatives of con-flicting social classes and develop universal norms of activity that allow for the sustainable development of society as a whole. This capability can be developed within a special institutional environment based on solidarity activities. Thus, each person will consider the successful implementation of the plans of others as a condition for the possibility of implementing their plans. This network of social institutions based on solidarity activity will be the realization of freedom in its social form. Within the framework of solidarity activities, new universal meanings of social development arise, which the communicative community will be able to formulate. Further, these meanings will replace the existing ones, which are focused on profit and unlimited economic growth, and thus transform the existing institutional system.
EXISTENTIAL BASES OF GOOD

The article is devoted to the consideration of the good nature existential foundations. Good, as a transcendental phenomenon, reveals itself in a person as a powerful mechanism of its internal development – spiritual needs. Need, unlike desire, is not just a requirement of the human body. Need is a way of relationship, that is, communication with objective reality. This life aspiration is responsible for the personality realization as an active, creative, responsible part of co-existence. Therefore, all aspects of human life and communication, and productivity, and harmony, depend on the state of the needs system satisfaction. It is these existential conditions that correspond to the principles of ethical absolutism. Thus, the intersection point of ethics and human (ethical and anthropological principles), the condition for the interaction and implementation of the principles of ethics is concentrated in the development of our soul needs. The soul seeks to go beyond the egoistic desires of the flesh. Therefore, to hear the “voice” of the soul (both one’s own and that of a loved one), to respond to its call, a person can only when the desire to know the world around him conquers the desire to possess this world. In this regard, we are talking about the fact that the basis for the spiritual needs of humans is the need for love. The need to love resonates with the basic ethical principle “love of one’s neighbor”. Therefore, working on our own egoism, we realize the whole complex of spiritual needs: in knowledge, communication, freedom, creativity. So, the need to love is the highest metaphysical force in which the nature of good is concentrated, both on the ontological and existential levels.
PERBANDINGAN PENINGKATAN KADAR GLUKOSA DARAH PUASA SEBELUM DAN SESUDAH PEMBERIAN MADU HUTAN DAN GULA PASIR MAHASISWA ANGKATAN 2015 FAKULTAS KEDOKTERAN UNIVERSITAS MUHAMMADIYAH SUMATERA UTARA

At the highest levels increase after consuming food. While fasting gold content is the gold content obtained after the patientfasts for 8-10 hours. Carbohydrates that have a low glycemic index cause a slight increase in blood sugar levels, whilecarbohydrates with a high glycemic index will cause a high increase in blood glucose. Honey has a low glycemic index.To determine the increase in the amount of reserves after the honey and granulated forest in the 15th in the 2015 studentforce FK UMSU who fasts for 8 hours. This study used the True Experiment method by designing pretest-posttest withcontrol group design to find out the difference in increase fasting blood glucose level after given honey and granulated sugarin the 15th minute of the 2015 student force FK UMSU. This study showed an increase in blood glucose levels after theadministration of honey with a mean value of 115.91 and standard deviation of 9,731 with P values = 0,000. Increased bloodglucose levels after giving sugar with a mean value of 118.36 and standard deviation of 9.212 with P value = 0,000.The increase blood glucose levels in 2015 student force FK UMSU 15 minutes after being given honey is slightly higher thanthose given sugar.
Telecommand encryption for intercommunication of substation control centers

Abstract New technologies are constantly generated and advanced every day and, with them, the need to use them to maintain constant communication with different people located anywhere in the world is also increasing. But this exponential growth also generates a very important security problem, since any information that is found in a device connected to the communications network or that travels through it, can be susceptible to being detected or intercepted by an unauthorized person that can be used improperly, causing large economic losses to companies or personal problems. For this reason, it is essential to use some mechanism that helps to protect the information from a malicious attack, one of the most used is cryptography that is responsible for writing in secret, providing confidentiality to the information through an encryption method.
Persian Translated and Nontranslated News: How Translation Changes Thematic Structure

Scrutinizing translated and nontranslated texts in a language reveals the characteristics of translationese. Additionally, thematic structure is among the most widely used tools for doing so; therefore, the research aim was to examine how thematic structure was presented in the Persian translated news, translated from English into Persian, and to compare it to the thematic structure in the Persian nontranslated news texts taken from 2: UTPECC and Persica. A total of 2,190 clauses were chosen to examine their thematic structure, employing mainly Halliday and Matthiessen’s (2014) classification of the thematic structure as the functional model. Results of the chi-square test revealed no significant difference between the application of the different thematic elements in both corpora, meaning that the Persian translation of news texts reflects the Persian language thematic structure, rather than the original English texts. Moreover, further analysis showed that the 4 categories of the thematic structure present characteristics of the third code.
Tunable Tradeoff between Quantum and Classical Computation via Nonunitary Zeno-like Dynamics

We propose and analyze a nonunitary variant of the continuous time Grover search algorithm based on frequent Zeno-type measurements. We show that the algorithm scales similarly to the pure quantum version by deriving tight analytical lower bounds on its efficiency for arbitrary database sizes and measurement parameters. We also study the behavior of the algorithm subject to noise, and find that under certain oracle and operational errors our measurement-based algorithm outperforms the standard algorithm, showing robustness against these noises. Our analysis is based on deriving a non-hermitian effective description of the algorithm, which yields a deeper insight into components responsible for the quantum and the classical operation of the protocol.
The Turkish Competition Authority publishes guidelines on the examination of digital data during on-site inspections

(1) Introduction The Turkish Competition Authority (“ TCA ”) recently published its Guidelines on Examination of Digital Data during On-site Inspections (“ Guidelines ”), which set forth the general…
THE EFFECT OF LEARNING STRATEGY AND INITIAL KNOWLEDGE ON THE ABILITY TO DEVELOP WRITING SKILLS ASSESSMENT INSTRUMENTS

This study was aimed at identifying the the effect of learning strategies and initial knowledge on the ability in developing writing skills assessment instruments for students in the Indonesian Language and Literature Education Study Program, FBS, UNJ. The method used in this research was experimental research with 46 samples. Sample 3 PB1 was treated with metacognition strategy and sample 3 PB2 was treated, with strategy advance organizer. The research instrument was a test of the ability to develop writing skills assessment instruments and a test of initial knowledge. After testing the hypothesis with the ANOVA test, in the 2 X 2 calculation table, Fcount (Inter-A) 6.008&gt; Ftable 4.200 at the level of α = 0.05, indicating that H1 is accepted and Ho is rejected. This means that there are differences in ability to develop writing skills assessment instruments between students who are treated with metacognition strategies and strategies advance organizer. Furthermore, testing the hypothesis about the effect of the interaction of learning strategies and initial knowledge on the ability to develop writing skills assessment instruments and testing prior knowledge, data shows arithmetic (AxB interaction) = 5.485&gt; ftable = 4,200 on the level of α = 0.05, H1 accepted and Ho rejected. That is, there is an interaction effect between learning strategies (metacognition strategies and strategies advance organizer) and initial knowledge (high and low) on the ability to develop writing assessment skills instruments. The learning outcomes of the ability to develop students' writing assessment skills instruments are influenced by learning strategies and initial knowledge.
Outlier-robust Kalman Filter in the Presence of Correlated Measurements

We consider the robust filtering problem for a state-space model with outliers in correlated measurements. We propose a new robust filtering framework to further improve the robustness of conventional robust filters. Specifically, the measurement fitting error is processed separately during the reweighting procedure, which differs from existing solutions where a jointly processed scheme is involved. Simulation results reveal that, under the same setup, the proposed method outperforms the existing robust filter when the outlier-contaminated measurements are correlated, while it has the same performance as the existing one in the presence of uncorrelated measurements since these two types of robust filters are equivalent under such a circumstance.
Cross-MPI: Cross-scale Stereo for Image Super-Resolution using Multiplane Images

Various combinations of cameras enrich computational photography, among which reference-based superresolution (RefSR) plays a critical role in multiscale imaging systems. However, existing RefSR approaches fail to accomplish high-fidelity super-resolution under a large resolution gap, e.g., 8x upscaling, due to the lower consideration of the underlying scene structure. In this paper, we aim to solve the RefSR problem in actual multiscale camera systems inspired by multiplane image (MPI) representation. Specifically, we propose Cross-MPI, an end-to-end RefSR network composed of a novel plane-aware attention-based MPI mechanism, a multiscale guided upsampling module as well as a super-resolution (SR) synthesis and fusion module. Instead of using a direct and exhaustive matching between the cross-scale stereo, the proposed plane-aware attention mechanism fully utilizes the concealed scene structure for efficient attention-based correspondence searching. Further combined with a gentle coarse-to-fine guided upsampling strategy, the proposed Cross-MPI can achieve a robust and accurate detail transmission. Experimental results on both digitally synthesized and optical zoom cross-scale data show that the Cross-MPI framework can achieve superior performance against the existing RefSR methods and is a real fit for actual multiscale camera systems even with large-scale differences.
New Progress in Research and Application of Machine Learning

Chinese Journal of ElectronicsVolume 29, Issue 6 p. 991-991 EditorialFree Access New Progress in Research and Application of Machine Learning Guanglu Sun, Professor, ICPCSEE Steering CommitteeSearch for more papers by this author Guanglu Sun, Professor, ICPCSEE Steering CommitteeSearch for more papers by this author First published: 01 November 2020 https://doi.org/10.1049/cje.2020.10.009AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume29, Issue6November 2020Pages 991-991 RelatedInformation
SOLVING THE 106 YEARS OLD 3^k POINTS PROBLEM WITH THE CLOCKWISE-ALGORITHM

In this paper, we present the clockwise-algorithm that solves the extension in $k$-dimensions of the infamous nine-dot problem, the well-known two-dimensional thinking outside the box puzzle. We describe a general strategy that constructively produces minimum length covering trails, for any $k \in \mathbb{N}-\{0\}$, solving the NP-complete $(3 \times 3 \times \cdots \times 3)$-point problem inside $3 \times 3 \times \cdots \times 3$ hypercubes. In particular, using our algorithm, we explicitly draw different covering trails of minimal length $h(k)=\frac{3^k-1}{2}$, for $k=3, 4, 5$. Furthermore, we conjecture that, for every $k \geq 1$, it is possible to solve the $3^k$-point problem with $h(k)$ lines starting from any of the $3^k$ nodes, except from the central one. Finally, we cover a $3 \times 3 \times 3$ grid with a tree of size $12$.
PENGGUNAAN MEDIA PERMAINAN CONGKLAK DALAM PEMBELAJARAN MATEMATIKA MATERI KPK DI KELAS IV

According to Trianto, one of the main problems in learning mathematics in schools today is the low absorption of students. The way that can be used to overcome these problems is by using media in learning mathematics. From the results of writing conducted by Luh Made Suriwati, et al, it was found that learning with the help of visual media is more effective in improving student learning outcomes compared to conventional learning methods. One of the media that can be used in learning mathematics is Congklak game media.&#x0D; This type of writing is action research aimed at developing an action plan to improve what is being done now. This writing is descriptive writing, where this writing is writing that really only describes what is contained or occurs in a particular scene, field, or region, namely SD N 1 Toyareka. This writing uses data collection techniques in the form of interviews, observation and documentation while the technical analysis of data uses data reduction, data presentation and data conclusion. The purpose of this writing is to describe the use of Congklak game media in learning mathematics in class IV and the use of Congklak game resources in instilling student character.&#x0D; The results of the writing show that the Congklak media can be used in learning Mathematics of Multiples Small Guilds. Where in the use of the media, the authors modify the game board by giving writing numbers in each hole of the board. Through the use of these media students can actively and enthusiastically participate in chases that have an impact on improving student learning outcomes. In addition, through the use of the Congklak game media can help teachers to convey the concept of Multiple Small Guilds (KPK) easily and at the same time be more acceptable to students. Through the use of congklak game media can also instill the character of students' curiosity. Keywords
LibGuides: How to reference for Senior School: Quick Guide: the basics (Harvard aka author-date)

Constructing references for your assignments can be challenging - use this LibGuide to get help for the more common resource types, as well as for help with how to footnote/endnote.
Behavior Patterns of Teamwork in The Maze Runner by James Dashner (2009): A Behaviorist Approach

This research aims to classify the kind of behavior patterns of teamwork and to show how behavior patterns build teamwork in the novel The Maze Runner. It is a qualitative research. The primary data source is the novel The Maze Runner by James Dashner (2009). The secondary data sources are including references from online books, websites, and research papers related to the research. The researcher uses the documentation method to collect the data. In presenting the data validity, the researcher uses triangulation by Denzin (2009). This research applies the theory of classical conditioning by Ivan Pavlov and the theory of operant conditioning by B.F Skinner to analyze data. Based on the result, the researcher found five kinds of behavior patterns of teamwork in The Maze Runner, namely: communication, commitment, strategy, helping, and discussion. The researcher found behavior patterns built teamwork in The Maze Runner novel through the habit of members and rules in the glade.
How to Exploit the Transferability of Learned Image Compression to Conventional Codecs

Lossy image compression is often limited by the simplicity of the chosen loss measure. Recent research suggests that generative adversarial networks have the ability to overcome this limitation and serve as a multi-modal loss, especially for textures. Together with learned image compression, these two techniques can be used to great effect when relaxing the commonly employed tight measures of distortion. However, convolutional neural network based algorithms have a large computational footprint. Ideally, an existing conventional codec should stay in place, which would ensure faster adoption and adhering to a balanced computational envelope. As a possible avenue to this goal, in this work, we propose and investigate how learned image coding can be used as a surrogate to optimize an image for encoding. The image is altered by a learned filter to optimise for a different performance measure or a particular task. Extending this idea with a generative adversarial network, we show how entire textures are replaced by ones that are less costly to encode but preserve sense of detail. Our approach can remodel a conventional codec to adjust for the MS-SSIM distortion with over 20% rate improvement without any decoding overhead. On task-aware image compression, we perform favourably against a similar but codec-specific approach.
Adaptive Compact Attention For Few-shot Video-to-video Translation

This paper proposes an adaptive compact attention model for few-shot video-to-video translation. Existing works in this domain only use features from pixel-wise attention without considering the correlations among multiple reference images, which leads to heavy computation but limited performance. Therefore, we introduce a novel adaptive compact attention mechanism to efficiently extract contextual features jointly from multiple reference images, of which encoded view-dependent and motion-dependent information can significantly benefit the synthesis of realistic videos. Our core idea is to extract compact basis sets from all the reference images as higher-level representations. To further improve the reliability, in the inference phase, we also propose a novel method based on the Delaunay Triangulation algorithm to automatically select the resourceful references according to the input label. We extensively evaluate our method on a large-scale talking-head video dataset and a human dancing dataset; the experimental results show the superior performance of our method for producing photorealistic and temporally consistent videos, and considerable improvements over the state-of-the-art method.
Angular Embedding: A New Angular Robust Principal Component Analysis

As a widely used method in machine learning, principal component analysis (PCA) shows excellent properties for dimensionality reduction. It is a serious problem that PCA is sensitive to outliers, which has been improved by numerous Robust PCA (RPCA) versions. However, the existing state-of-the-art RPCA approaches cannot easily remove or tolerate outliers by a non-iterative manner. To tackle this issue, this paper proposes Angular Embedding (AE) to formulate a straightforward RPCA approach based on angular density, which is improved for large scale or high-dimensional data. Furthermore, a trimmed AE (TAE) is introduced to deal with data with large scale outliers. Extensive experiments on both synthetic and real-world datasets with vector-level or pixel-level outliers demonstrate that the proposed AE/TAE outperforms the state-of-the-art RPCA based methods.
Diverse Perspectives on Connections that Sustain RRR Communities

Editorial, Issue 3, 2019