Reviewerly/exHarmony huggingface dataset:
The Use of Pacamat Media to Improve Learning Outcomes of Inheritance in Class IX 1 Student of SMPN 17 Kendari

This study aims to (1) improve the mastery of the concept of inheritance in class IX.1 SMPN 17 Kendari through the use of Pacamat media; (2) activating students in learning using Pacamat media; (3) activate the teacher in learning using Pacamat media. The research design used was a classroom action research design which was carried out in two cycles, with stages in each cycle: (1) planning; (2) implementation of the action (action); (3) observation and evaluation; and (4) reflection. The final results of the study indicate that the use of Pacamat media can improve student learning outcomes about inheritance, with classical completeness reaching 88%. Learning with the use of Pacamat media can improve the learning outcomes of the inheritance of the students in class IX.1 SMPN 17 Kendari.
THE INFLUENCE OF READ COVER REMEMBER RETELL (RCRR) TOWARDS STUDENTS’ READING ABILITY AT THE FIRST SEMESTER OF ELEVENTH GRADE OF MAS NURUL ISLAM JATI AGUNG IN 2020/2021

This research aimed to know the influence of Read Cover Remember Retell towards students’ reading ability. The writer used the Pre-test and Post-test as the research design. The population of this research was the eleventh grade students of MAS Nurul Islam Jati Agung. In taking the sample, the writer used cluster random sampling. To analyze the data, the writer used paired sample t-test formula. The result showed that ttest is 3. From the distribution table at the significance level of 5%, is known that ttable = t ( 1 - α ) (df) = 2.02 and at the significance level of 1% is known ttable = t ( 1 - α ) (df) = 2.70. It means that ttest > ttable , it can be said that there is an influence of Read Cover Remember Retell (RCRR) towards students’ reading ability at the first semester of eleventh grade of MAS Nurul Islam Jati Agung in 2020/2021. Whereas, the average score of the students’ reading ability after treatment is higher (71.9) than the score before the treatment given (71.3). It means that there is influence of RCRR strategy towards students’ reading ability.
Dynamical Decomposition and Mapping of MPMCT Gates to Nearest Neighbor Architectures

We usually use Mixed-Polarity Multiple-Control Toffoli (MPMCT) gates to realize large control logic functions for quantum computation. A logic circuit consisting of MPMCT gates needs to be mapped to a quantum computing device that has some physical limitation; (1) we need to decompose MPMCT gates into one or two-qubit gates, and then (2) we need to insert SWAP gates such that all the gates can be performed on Nearest Neighbor Architectures (NNAs). Up to date, the above two processes have been independently studied intensively. This paper points out that we can decrease the total number of the gates in a circuit if the above two processes are considered dynamically as a single step; we propose a method to inserts SWAP gates while decomposing MPMCT gates unlike most of the existing methods. Our additional idea is to consider the effect on the latter part of a circuit carefully by considering the qubit layout when composing an MPMCT gate. We show some experimental results to confirm the effectiveness of our method.
Improving the Authentication with Built-In Camera Protocol Using Built-In Motion Sensors: A Deep Learning Solution

In this paper, we propose an enhanced version of the Authentication with Built-in Camera (ABC) protocol by employing a deep learning solution based on built-in motion sensors. The standard ABC protocol identifies mobile devices based on the photo-response non-uniformity (PRNU) of the camera sensor, while also considering QR-code-based meta-information. During registration, users are required to capture photos using their smartphone camera. The photos are sent to a server that computes the camera fingerprint, storing it as an authentication trait. During authentication, the user is required to take two photos that contain two QR codes presented on a screen. The presented QR code images also contain a unique probe signal, similar to a camera fingerprint, generated by the protocol. During verification, the server computes the fingerprint of the received photos and authenticates the user if (i) the probe signal is present, (ii) the metadata embedded in the QR codes is correct and (iii) the camera fingerprint is identified correctly. However, the protocol is vulnerable to forgery attacks when the attacker can compute the camera fingerprint from external photos, as shown in our preliminary work. Hence, attackers can easily remove their PRNU from the authentication photos without completely altering the probe signal, resulting in attacks that bypass the defense systems of the ABC protocol. In this context, we propose an enhancement to the ABC protocol, using motion sensor data as an additional and passive authentication layer. Smartphones can be identified through their motion sensor data, which, unlike photos, is never posted by users on social media platforms, thus being more secure than using photographs alone. To this end, we transform motion signals into embedding vectors produced by deep neural networks, applying Support Vector Machines for the smartphone identification task. Our change to the ABC protocol results in a multi-modal protocol that lowers the false acceptance rate for the attack proposed in our previous work to a percentage as low as 0.07%. In this paper, we present the attack that makes ABC vulnerable, as well as our multi-modal ABC protocol along with relevant experiments and results.
PENGARUH PENGGUNAAN MEDIA GAMBAR TERHADAP KEMAMPUAN MENULIS KARANGAN DESKRIPSI SISWA KELAS IX SMP PGRI 3 BANDAR LAMPUNG

In the communication process there are 4 different but interrelated skills, the components of these language skills are listening, speaking, reading, and writing. Description writing skills need to be instilled in students. Composing in principle is telling about something that exists in the imagination. The story can be written orally or in writing. So to be able to write well, one must have the ability to write. The ability to write can be achieved through the process of learning and practicing. Based on the reality that there is an effect of using image media on the ability to write descriptive essays for class IX students at SMP PGRI 3 Bandar Lampung, there is data on the low ability to write descriptions for class IX students, it can be seen from students' essays that have not been able to create an impression of readers through their writings. Students' essays have not succeeded in bringing the reader as if they really saw the object in front of their eyes. The low writing skill is also caused by the difficulty of students expressing ideas or ideas into writing. The research method used in this research is experimental research. The results of the ANOVA calculation above show that Fcount = 18.78* which is greater than Ftable = 4.08 at a = 0.05 and Fcount at a = 0.01. The obtained value of Fcount = 31.23 which is greater than Ftable = 4.08 at a = 0.05 and Ftable = 7.31 at a = 0.01. This means Ho is rejected. Obtained 9.18 and Ttable = 6.038 for T(0.05) = 6.038 T (0.01) = 2.750 turns To > Ttable . Ho is rejected and H1 is accepted. There is an influence of low learning independence on students who have high learning independence between the application of image media and those who do not apply image media, namely by looking at the results of To = 1.16 < T table = 6.038; Ho is rejected.
«God is dead» as an apophatic text of the borderline consciousness

The main theme of the article is the borderline conscious-ness; the subject is the novella «God Is Dead» (1922) by S. D. Krzhizhanovsky as a reflection of the borderline consciousness. The purpose of the article is to reveal the specifics of the borderline conscious-ness in general and its features in the culture of the late 19 th and early 20 th centuries using the example of the analysis of the novella «God Is Dead», as well as of other texts similar in content and the time of writing. The main methods are ontological, historical-cultural, analytical, and com-parative. The introductory part defines the main characteristics of the bor-derline consciousness and also clarifies the etymology and the immanence of the process in development of the human society. Further, the author of the article identifies the substantive aspects in the concept of «apophati-cism», draws on the names of philosophers that are relevant to the thoughts of S. D. Krzhizhanovsky, (F. Nietzsche, A. Schweitzer, M. Heidegger), emphasizes that negation has nothing to do with God, from the point of view of Dionysius the Areopagite. The common and different aspects of philosophical and artistic views on apophaticism are also analyzed (F. Nietzsche, K. K. Sluchevsky). Further, the researcher carries out a de-tailed analysis of the novella «God Is Dead»by S. D. Krzhizhanovsky: the compositional structure is examined, an overview of the characters and their peculiarities is given, biblical and artistic allusions, their correlation with the specificity of the Soviet regime are revealed. The author of the article specially emphasizes that S. D. Krzhizhanovsky resorts to apophaticism as a characteristic of this time. The polemic part designates different approaches in the modern interpretation of apophaticism in the novella by S. D. Krzhizhanovsky, which do not coincide with the understanding of the author of this article. In the final observations, it is emphasized: the border-line consciousness thinks within the boundaries, which is reflected in art and outlook on the world.
The Interplay Between Local and Global Strategies in Navigational Decisions

Author(s): DeStefani, Serena; Sohn, Samuel S; Kabir, Adeeb; Kapadia, Mubbasir; Feldman, Jacob | Abstract: Although the Traveling Salesman Problem (TSP) is an NP-hard problem, human schedulers can find strategies that are comparable if not better than existing algorithms. However, it is still unclear what heuristics they adopt in order to select an approximate solution (Schaefer, 2018). In solving a navigational problem in 3D, the directional heading is an essential factor because changes of direction require additional energy expenditure. In our study, we focus on the connection between local choices minimizing distance and local choices minimizing the turning angle. We then examine human solutions to the TSP in light of the tradeoff between local and global optimization of distance and turning angle. We conducted two experiments showing that while subjects were more likely to move to the nearest node when they plan the next step ahead, they also take the turning angle into consideration and overall adopt a strategy that combines local and global heuristics.
Younger and Older Speakers' Use of Linguistic Redundancy with a Social Robot

Author(s): Saryazdi, Raheleh; Nuque, Joanne; Chambers, Craig | Abstract: Social robotics has shown expansive growth in areas related to companionship/assistance for older adults. Critically, everyday interactions with artificial agents often involve spoken language in the context of a shared visual environment. Therefore, language interfaces for these applications must account for the distinctive nature of visually-situated communication revealed by psycholinguistic studies. In traditional frameworks, rational speakers were thought to avoid redundancy, yet human-human communication research shows that both younger and older speakers include redundant information (e.g., color adjectives) in descriptions to facilitate listeners' visual search. However, this cooperative use of redundant expressions hinges on beliefs about listeners' perception (e.g., pop-out nature of human color processing). We explored the incidence and nature of younger and older speakers' redundant descriptions for a robot partner in different visual environments. Whereas both age groups produced redundant descriptions, there were important age differences for when these descriptions occurred and for the properties encoded in them.
Supervised category learning: When do participants use a partially diagnostic feature?

Author(s): Thomas, Sujith; Kapoor, Aditya; Srinivasan, Narayanan | Abstract: We report a supervised category learning experiment in which the training phase contains both classification and observation learning blocks. To explain the use of different categorization strategies, we propose an account in which use of a stimuli dimension depends on how well the dimension is learned. Our results show that there is an overall preference for a unidimensional categorization based on the perfectly diagnostic dimension. The preference for unidimensional categorization is negatively correlated with how well participants learn the partially diagnostic dimensions. Preference for unidimensional categorization is also negatively correlated with the mean response time. Bayesian modeling results show that participants use a partially diagnostic dimension only when it is learned with a very high level of accuracy. Different strategies are used for categorization depending on how well the perfectly and partially diagnostic dimensions are learned.
Appraisal for chromite exploration through ground magnetic and very low frequency Electromagnetic data analysis in Sittampundi layered complex, Tamilnadu, India

Abstract Summary Appraisal for chromite exploration through ground magnetic and very low frequency Electromagnetic data analysis in Sittampundi layered complex, Tamilnadu, India.
An Efficient Ranking Model for Multiuser Social Media applications using Customized Page Rank Method

It has been found that the web is being used as a tool by radical or extremist groups and users to carry out a variety of acts with hidden agendas and promote their ideas in every part of the world. Some web forums are mainly used for open discussion on serious issues influenced by radical ideas. Influential users dominate and influence newly connected innocent users through their radical ideas. This paper introduces a principle for identifying radically influential users in web forums. Posts commented with a list of threats are captured by the user by a criterion based on the degree of match. This web forum basically identifies influential users. Eleven different collocation metrics are formulated to identify the association between users, and they are finally embedded in a customized page rank algorithm to create a numbered list of basic influential users. Connection theory is more effective in dealing with such ranking problem than measures based on tactical and temporal equality.
FOCUS-GROUP IN PROFESSIONAL TRAINING OF POLITICAL SCIENCE STUDENT (EXAMPLE OF PROJECT TRAINING IN RUSSIAN UNIVERSITIES)

FOCUS-GROUP IN PROFESSIONAL TRAINING OF POLITICAL SCIENCE STUDENT (EXAMPLE OF PROJECT TRAINING IN RUSSIAN UNIVERSITIES)
To the question of the importance of self-organization and self-development in professional pedagogical activity

The article clarifies the importance of self-organization and self-development for the professional activity of a teacher in the context of the fourth industrial revolution from the standpoint of competence-based and analytical approaches. The reasonableness of the general formulation of a single “Self-organization and self-development” competence in the Russian Federation Federal State Educational Standards of Higher Education is shown. The article describes the empirical study results of the peculiarities of understanding by pedagogical university students separately the competences of self-organization and self-development, as important factors of their general professional expertise. The novelty of the research is based on the identification of motivational, cognitive, and activity components. It was revealed that the highest generalized mean values were obtained for the cognitive and motivational components of the future teachers’ ideas about professional self-development, self-organization and the achievement of professional expertise. The lowest mean values were obtained for the action-oriented component. The obtained results of empirical research can be used in the development of training courses, aimed at increasing the level of students’ competences in this area.
The Omniglot Jr. challenge; Can a model achieve child-level character generation and classification?

Author(s): Kosoy, Eliza; Belyi, Masha; Snell, Charlie Victor; Lake, Brenden; Tenenbaum, Josh; Gopnik, Alison | Abstract: Lake 2015 presented the Omniglot dataset to study how people generate and classify characters. They proposed a model for one-shot-learning of new concepts based on inferring compositionally structured generative models, and could transfer from familiar concepts to new ones. Their Bayesian-Programming-Language model was able to both classify and generate characters similar to adults. However, adults have years of experience, would a similar model apply to children without this prior knowledge? We introduce a new dataset called Omniglot_Jr., composed of Omniglot letters generated by children aged 3-6. Our results of training BPL with children's data in classification and generation find that BPL achieves higher classification accuracy and generates more adult looking letters. We propose the challenge of reproducing children's distinctive pattern of mistakes. Skills such as character recognition depend on child-like learning; this challenge should help us understand how that learning is possible, and how to simulate it in computational systems.
NEW PEDAGOGY: ONLINE LEARNING PROCESS AS SEQUENTIAL EVENTS

S. Dugal1A. Barbosa1A. Bikash1A. Botelho1W. Cavaliere1S. Fleser1N. Dougherty1A. Seraichyk1J. Gilman1D. Pawlowski1D. Volpe1H. Veltry1E. Torgersen1L. Waranis1G. Bonaminio1J. Chamberlain1J. Erby1O. Palumbo1C. Sanford1S. Warren1S. Vicedomine1J. Allen1B. Castle1E. Borme1M. Dee1K. Rovella1E. Urban1D. Whitham1S. Singh2M. Troiano3R. Singh4C. Mahoney1M. Horvath1
Forest Tree- An Efficient Proposal Approach for Data Mining

Data Mining (DM) is a way of looking on different models, summaries, & derived values from a given gathered data. DM itself work on the process of looking for analytical information in huge amount of available databases. An illustration of a predictive riddle is targeted marketing. There are many factors that influence the performance of mining on large data sets. In this paper we are going to use forest tree technique in order to improve the way of performance of how the data is to be fetched and when on implementation it will definitely overcome the performance of previous work which includes existing approach decision tree algorithm.
StegoBound: A Novel Image Steganography Technique Using Boundary-Based LSB Substitution

The safe exchange of private information in the current web age is a significant security concern that has come around after developing steganography as a piece of conspicuous information concealing strategy. Steganography methods guarantee secure information by hiding the transmission channel and are described using three key boundaries: specific strength, implanting limit, and intangibility. The cutting-edge steganography strategies anyway neglect to accomplish an ideal compromise among the key steganographic factors. This research study describes a novel image steganography technique StegoBound based on gradient, which efficiently hides the secret message and produces excellent results for the essential steganographic characteristics. To produce top-notch stego-pictures, StegoBound shrouds the restricted information in the sixth, seventh, and eighth least significant bits (LSBs) of the boundary zone pixels in grayscale cover pictures. The nature of the stego-pictures is assessed through primary closeness file (SSIM), widespread picture quality file (UQI), mean square of error (MSE), Peak Signal to Noise Ratio (PSNR), mean qualities, and histogram investigation. The novel method's effectiveness evaluation is confirmed by calculating MSE, SSIM, PSNR, and UQI. Experimental results and comparative studies reveal that our proposed technique achieves state-of-the-art results in hiding the secret data by providing an optimal trade-off between imperceptibility, embedding capacity, and security. Keywords: steganography, data hiding, LSB substitution, MSB, boundary.
Online Food Ordering Management System

The main purpose of the Online Food Ordering Management System is to use it in the food-service industry. This feature helps hotels and restaurants to increase their online food ordering systems. Customers can choose from a wide range of food menu items within just a few minutes. In today’s modern food business, it's also able to deliver fast and easily to a customer’s place. The work presented as Online Food Ordering Management System simplifies the ordering process. The proposed solution presents a user interface and changes the menu to include all available options, creating customer work easier. Allows customers to order any item that they like and adjust the quantity of the food item. The order confirmation is displayed to the customer on the Homepage of the website. The order is put to the queue, updated across both the database and the admin panel, and provided in real-time. This system aids the staff with checking over orders in real-time and executing them effectively and easily with few errors. Here, the customer can also reserve a table at a restaurant of his/her choice and will get the confirmation of their reserved table on the homepage of our website.
Automated Access Communication System

Automated Access Communication System is concerned with the development of a system that is simple and easy to use yet a powerful web application for sharing, managing and controlling enterprise documents on intranet/internet in a secure manner within the particular organization. It enables the communication between all the departments of the company through online. The development of this new system contains the following activities, which try to automate the entire process keeping in the view of database integration approach.
Comparison of Data Augmentation Methods in Pointer–Generator Model

In this research, we proposed a data augmentation method using topic model for Pointer-Generator model.This method is that adding important sentences to an article as extended article.Furthermore, we compare our proposed method with data augmentation methods using Easy Data Augmentation (EDA), LexRank and Luhn.EDA consists of synonym replacement, random insertion, random swap, and random deletion.LexRank is based on Google's search method and Luhn defines sentence features and ranks sentences.We considered which method is suitable for data augmentation.We confirm that most accurate model is the model using data augmentation method by topic model.
Financial time series prediction using wavelet and artificial neural network

This paper focuses on the modelling of financial time series using the coupling of the discrete wavelet transform and nonlinear autoregressive neural network. This hybrid modelling method is based on the use of decomposed time series using the discrete wavelet transform as inputs to the artificial neural networks. This method has been applied to three financial series (exchange rate EUR/USD, the Brent price and NASDAQ composite price). The simulation results using R software show the robustness of the proposed model compared to other modelling methods applied to the same financial time series.