Reviewerly/exHarmony huggingface dataset:
Research on Spatial Target Classification and Recognition Technology Based on Deep Learning

With the progress of human space technology, mankind stepped into more distant space. Due to the long distance from the earth in deep space exploration, higher requirements were put forward for intelligent cognition of targets and environment. In this paper, the space target classification and recognition technology based on deep learning was studied by taking the classification of three types of satellites as an example. A satellite simulation sample set for deep learning was established, and a ResNet multi-layer convolutional neural network model suitable for spatial target characteristics was constructed. The training and test of satellite intelligent classification were completed, and the feature extraction results of the neural network were visualized. The accuracy rate of satellite classification identification for the remote sensing satellites, communication satellites and navigation satellites reached 90%, which provided a reference for the development of intelligent classification and identification technology of space targets in the field of deep space exploration.
Education and knowledge are fundamental to social justice and economic growth

This paper tries to explain that both knowledge and education are the way to increase economic growth and social justice. We have used the panel data to check the relationships between four indicators: knowledge, education, economic growth, and social justice. These data are from the Social Progress Imperative Organization (2018). We have used the statistic method (mode, quartile, and decile) to analyze our data though they are not enough. So, we found that 54 countries in the world have the lowest revenue between $600 and $9,300. They set forth almost 43% among 126 countries. In this modal class, about 6% have the lowest rate SPI (Social Progress Index) in the world - it is between 20 and 40-, and more than 94% have a rate SPI between 40 and 80. The results of the OLS regressions show that the improvement of social progress can increase GDP per capita to seven times what it was. On the other hand, both improvements in knowledge and education can increase GDP per capita to thirteen times what it was.
Enotes: Note Taking Tool for Online Learners

ENotes is a note-taking tool specifically targeted towards online learners. Note-taking in general help students to have a better understanding of what they learn. It also helps the students to improve their writing skills. There are many sophisticated and simple note-taking tools available on the market. Sophisticated tools like Evernotes and OneNote need extra learning for setup and some functionalities are only available as micro transactions. Simple tools like Sticky notes and SimpleApp don't support some basic functionalities required for taking notes such as rich text formatting. ENotes combines the features from both these sophisticated and simple tools to meet the needs of the online learners. This tool is built using Chrome extensions technology in pure JavaScript. It involves no cost, no complex setup, and is user friendly. It covers the basic features like rich text formatting and math formula editor, download, print, search, tool access time, dictionary, speech to text conversion and translations.
Optimally Efficient Bidirectional Search

A* is optimally efficient with regard to node expansions among unidirectional admissible algorithms — those that only assume that the heuristic used is admissible. This paper studies algorithms that are optimally efficient for bidirectional search algorithms. We present the Fractional MM algorithm and its sibling, the MT algorithm, which is simpler to analyze. We then develop variants of these algorithms that are optimally efficient, each under different assumptions on the information available to the algorithm.
Remove me from this list: A case study of trolling in an academic mass email thread

This work examines in detail trolling behaviour that occurred during the mass email “reply allpocalypse” of 2019 at a university in southwestern Ontario. Whereas internet trolling is generally thought of as anonymous, antisocial behaviour, this event defies such characterizations in three ways: 1) all respondents participated on a real-name basis, 2) the majority of trolling messages sent were non-malicious attempts at humour, and 3) the email trolling seemed to have at least some pro-social, community-building effects. This study challenges assumptions about who engages in internet trolling and for what purpose by presenting an example of benign trolling in academia.
Using Stereoscopic 3D Images for Effective Learning in Primary School

This study aims to determine the effect of using stereoscopic 3D image on learning effectiveness This research was conducted through a quasi-experiment in primary schools by using control class and experimental class. This research was joined by 52 participants (26 students in control class and 26 students in experimental class). The research conclusions indicate that, 1) stereoscopic 3D images can be used through integration into textbooks as illustrations increasing the primary school students’ perception about classroom activities (i.e., motivation, interest, challenge and excitement). and 2) textbooks integrated with stereoscopic 3D images are proven effective in improving the students' concept mastery, as seen from the independent sample t-test by using SPSS resulting in a probability (p) value of 0.000 with a significance level of 0.05 so that p &lt; 0, 05.
Pembelajaran Mata Kuliah Japanese Vocabulary 2 dengan Metode Gambar

Japanese Vocabulary 2 courses in Japanese Literature Dian Nuswantoro University are courses that teach Japanese vocabulary which is learned in Kanji letters. This Japanese Vocabulary course is given in semester 3 and semester 4 which is a follow-up course from Japanese Character. However, this study, the author will discuss Japanese Vocabulary 2 learning strategies by using picture slides, drill repetition of words, and Kanji letter vocabulary exercises in Japanese sentences contained in the Goi Nihongo maatome sou N3 textbook and Pea de Oboeru Iroirona Kotoba. The use of this teaching strategy can improve mastery of Japanese Kanji for students to be easy to learn so that learning targets set by Japanese Vocabulary 2 teaching goals can be achieved.
Malang City Polytechnic Web Based Student Attendance Information System Telecommunications Engineering Study Program Using Fingerprint

This research is design of an Attendance Information System titled â€œMalang City Polytechnic Web Based Student Attendance Information System Telecommunications Engineering Study Program Using Fingerprintâ€. Students of Malang City Polytechnic are still using a manual attendance system. The attendance system that is still manual has many disadvantages such as data processing, report making and also difficult to monitor student attendance. Therefore, the existence of this system makes it easy to find out student attendance on that day, because it is timely or real time. This system also makes it easy to make monthly reports about student attendance and delay. The design of this system uses PHP Web and MySQL Database connection. The results of this system can create and display monthly reports that have been processed and can monitor student attendance every day.
Privacy-Preserving Multi-Party Directory Services

In the era of big data, the data-processing pipeline becomes increasingly distributed among multiple sites.To connect data consumers with remote producers, a public directory service is essential.This is evidenced by adoption in emerging applications such as electronic healthcare.This work systematically studies the privacy-preserving and security hardening of a public directory service.First, we address the privacy preservation of serving a directory over the Internet.With Internet eavesdroppers performing attacks with background knowledge, the directory service has to be privacy preserving, for the compliance with data-protection laws (e.g., HiPAA).We propose techniques to adaptively inject noises to the public directory in such a way that is aware of application-level data schema, effectively preserving privacy and achieving high search recall.Second, we tackle the problem of securely constructing the directory among distrusting data producers.For provable security, we model the directory construction problem by secure multi-party computations (MPC).For efficiency, we propose a pre-computation framework that minimizes the private computation and conducts aggressive pre-computation on public data.In addition, we tackle the systems-level efficiency by exploiting data-level parallelism on general-purpose graphics processing units (GPGPU).We apply the proposed scheme to real health-care scenarios for constructing patient-locator services in emerging Health Information Exchange (or HIE) networks.For privacy evaluation, we conduct extensive analysis of our noise-injecting techniques against various background-knowledge attacks.We conduct experiments on real-world datasets and demonstrate the low attack success rate for the protection effectiveness.For performance evaluation, we implement our MPC optimization techniques on open-source MPC software.Through experiments on local and geo-distributed settings, our performance results show that the proposed pre-computation achieves a speedup of more than an order of magnitude without security loss.
The Influence of E-Learning as a Complement on Student Learning Satisfaction in Batam

The utilization of e-learning as a complementary learning requires careful consideration by the Higher Education, so that e-learning can provide benefits and improve student satisfaction, especially employee class students in Batam City. The aim of the study was to find out whether there was an effect of expediency, ease of use, social influence, and conditions of supporting facilities on student learning satisfaction in using e-learning as a complementary learning tool in Batam City. Data was taken from random distribution of questionnaires to 207 respondents of students of Information Systems Study Program Batam International University and Putera Batam University who used e-learning as a complement to learning. Research uses a quantitative approach. Data were analyzed by multivariate multiple regression analysis. The results of the analysis show the significance of Benefit 0,000 with a coefficient of 0.322, significance of Ease of Use 0,000 with coefficient of 0.286, significance of Social Influence 0.002 with coefficient of 0.187 and significance of Conditions of Supporting Facilities 0.001 with coefficient of 0.197. It can be concluded that usefulness, ease of use, social influence and conditions of supporting facilities have a significant positive influence on learning satisfaction.
Games and Simulation on Students’ Speaking Skill

The objective of the research is to see the effectiveness of Games and Simulation in speaking skill on the seventh grade students at SMP Teknologi Pilar Bangsa. The technique applied in this research was quas-experimental research. In this research, there were two classes taught by using different techniques. The experimental class was taught by using Games and Simulation technique while the controlled class was taught by using conventional technique. Futhermore, this research was conducted through the following procedures: giving pre-test, applying treatments, and giving posttest. The sample of this research were 30 students of class 7.1 and 31 students of class 7.3. Normality test was tested by using chi-square. From the calculation of normality showed that the data are normally distributed population. The homogeneity test result of students learning reading comprehension has homogeneous variance. Furthermore, the t-test showed that t-count of experimental class is 3.25, was higher than t-table. The t-test of control class is 3.25, was higher than t-table. It means that finding of this study shows that there is a significance difference in the result between students in class 7 as control class that were taught without games and simulation technique and students in class as experimental class that were taught speaking skill using games and simulation technique.
A Learning-Based Framework for Memory-Bounded Heuristic Search: First Results

Many existing boundedly-suboptimal heuristic search algorithms are variants of best-first search. Due to memory limitations, these algorithms are unable to solve problems with extremely large search spaces. In this paper, we present a framework that allows best-first search algorithms to solve problems with such large search spaces given a (reasonable) memory bound while also preserving optimality guarantees in tree-structured search spaces. In our framework, a given algorithm is run several times. In each search episode, the algorithm expands up to a user-defined number of states. After each episode, unless the goal has been found, the heuristic values of the generated states are updated using a linear-time algorithm that preserves consistency in tree-structured search spaces. In subsequent search episodes, only the heuristic values of the states generated in the previous episode need to be kept in memory. We present experimental results where we plug A*, GBFS, and wA* into our framework to solve traveling salesman problems and compare them against benchmark linear-memory algorithms like DFBnB and wDFBnB.
An Autobiography of Novice Teacher in Using Multimodality for Teaching Reading to Young Learners

This study is the author’s autobiography as a novice teacher in teaching fifth-grade students with multimodality. İ have been teaching young learners for five years in one of an elementary school in Indonesia. Until this day, I am still in the quest to find the best method to develop young learners’ reading proficiency. I also want to change their perspective about reading. İt is necessary to create a reading process which is enjoyable and not boring in the classroom. Young learners who were born in the 21st century, digital natives and non-traditional learners. Multimodality consists of several different modes. Each mode is meaningful and has a role. As a teacher, I could design each mode based on her students’ needs and what they were familiar with.
Stochastic Goal Recognition Design

Given an environment and a set of allowed modifications, the task of goal recognition design (GRD) is to select a valid set of modifications that minimizes the maximal number of steps an agent can take before its goal is revealed to an observer. This document presents an extension of GRD to the stochastic domain: the Stochastic Goal Recognition Design (S-GRD). The GRD framework aims to consider: (1) Stochastic agent action outcomes; (2) Partial observability of agent states and actions; and (3) Suboptimal agents. In this abstract we present the progress made towards the final objective as well as a timeline of projected conclusion.
Use of Learning Media in Entrepreneurship Subjects Equality Education Paket C

Learning media used by tutors in the learning process at PKBM Farilla Ilmi are very suitable and attract the attention of the learning community. The results of this study found that the compatibility and attractiveness of the media in learning can increase the motivation of students to learn, so that students' understanding increases rapidly. Likewise the interaction between tutors and students and their peers is more increased because the media provided involves a lot of learning in the learning process. This study has a population of Paket C learners equivalent to high school, amounting to 60 people. While the sample is 30 people, which is half of the research target using classified random sampling techniques so that it is representative in representing each class. The results of this study are in accordance with the researchers' expectations expressed in the preliminary section about the success of the Paket C program in achieving high scores in Entrepreneurship subjects.
Simulasi Daya Harmonik berbasis Transformasi Wavelet dengan Matlab

The progress of power electronics application technology, harmonic pollution in the electrical power system network is increasing seriously, having a serious impact on the energy supply network and equipment. In this discussion, the author studied harmonic characteristics, analysis of harmonic detection methods using wavelet algorithms with Matlab. The results of the simulation show that wavelet transforms can compose harmonic components that are settled in the system according to their needs.
Prioritizing interdependent software requirements using tensor and fuzzy graphs

Owing to the special stance of prioritizing tasks in requirements engineering processes, and as the requirements are not independent in nature, considering their dependencies is essential during the prioritizing process. Although different classifications of dependency types among requirements exist, only a few approaches in the prioritization process consider such valuable data (dependency among equirements). To achieve a practical prioritization, this study proposes a method based on the effects of the requirement dependencies (increase/decrease cost of) on the value of prioritization provided by the tensor concept. Since the strengths of dependencies are also influential factors in the act of prioritization, The algebraic structure of fuzzy graphs is used to model the requirement dependencies and their strengths. Moreover, a weighted page rank algorithm based on the fuzzy concept is provided to determine the final dependency strength of the dependent requirements of the fuzzy graph. To evaluate the proposed approach, a controlled experiment is also conducted. The proposed approach is compared with an analytic hierarchy process-based approach, TOPSIS, and EVOLVE in the experiment. The results analysis demonstrates that our approach is less time-consuming, much easier to use, and highly accurate.
STUDI LITERATURE KESULITAN SISWA SMP/MTs DIPONEGORO WULUHAN DALAM PEMBELAJARAN MATA PELAJARAN BAHASA INGGRIS

Abstract&#x0D; Learning difficulty is a condition where students experience learning disruptions as they should, both from internal and external factors. This results in students not being able to develop according to their capacity. From this research can be put forward the formulation of the problem, namely, the types of learning difficulties experienced by junior high school / junior high school students in North Sumatra, what factors that make students difficult to learn in English, and how can efforts solve the problem of student learning difficulties. The purpose of this study was to determine the types of difficulties in understanding completing the material in English subjects, the factors that influence students in understanding completing the material in English subjects and problem solving efforts. The method used in this study is to use qualitative methods. Data collection techniques used were literature studies and interviews with each student were different classes. The results of this study are that there are still some students who still have difficulty in understanding completing the material in English subjects from the aspects of listening, reading, structure, and writing, and which are the factors causing students to experience learning difficulties, namely from cognitive factors (ability to memorize , the ability to master the material and the wrong learning habits, and what efforts will be used by educators using teaching repairs.&#x0D; &#x0D; Keywords: learning difficulties, students, English.
Smart device controlling through voice commands given in malayalam language

In this paper, a new method to read and recognize the voice command given in Malayalam language with the help of advanced language processing algorithms.Tensor flow is taken as the tool for voice processing in python language and various methods to train the signals and test them in second level.The acoustic model will check whether the signal can be recognized by these methodologies for further actions to be taken down.The accuracy is also to be considered with large data set.
Quality-Diversity Automatic Summarization based on Determinantal Point Processes

Information age requires intelligent tools like automatic abstract. We present a unique perspective from unsupervised data driven technology for extractive summaries. Inspired by a novel sampling method based on DPPs, we explore the latent cohesion among sentences through computing Word Mover's Distance (WMD) contrasted to traditional similarity metrics, and build condensing summaries with high quality and low redundancy by selecting diverse sentences from raw documents. We illustrate the advantages of our competing system primarily on the dataset from the 4 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sup> Computational Linguistics Scientific Document Summarization Shared Task and MultiLing 2015 Task, and the performance is evaluated through F-measure from ROUGE family.
The Reliability Assessment of ICS Based on Evidential Reasoning and Semi-quantitative Information

The purpose of this paper is to establish a new reliability assessment architecture for Industrial Control system (ICS), in this assessment architecture, precise data, ignorance and fuzziness are all modelled to describe complicated ICS.A method based on evidential reasoning (ER) rule and semi-quantitative information is proposed, this approach can solve the multiple attribute decision analysis problems which are characterized by both quantitative data and qualitative knowledge.The assessment results of a practical case study of ICS which ER employed to transform multiple attributes and verify more accurate assessment results can be obtained.The impacts of the obtained results the security states of the ICS, which enable engineer betters understand the operation of the ICS, and ultimately reduce the failure of the system, and improve the security and stability of the system.
Generative Adversarial Networks Using Adaptive Convolution

Most existing GAN architectures that generate images use transposed convolution or resize-convolution as their upsampling algorithm from lower to higher resolution feature maps in the generator. We propose a novel adaptive convolution method that learns the upsampling algorithm based on the local context at each location to address this problem. We modify a baseline GAN architecture by replacing normal convolutions with adaptive convolutions in the generator. Our method is orthogonal to others that seek to improve GAN by incorporating high level information. Experiments on CIFAR-10 dataset show that our modified models improve the baseline model by a large margin on visually diverse datasets.
A Core Method for the Weak Completion Semantics with Skeptical Abduction (Extended Abstract)

The Weak Completion Semantics is a novel cognitive theory which has been successfully applied -- among others -- to the suppression task, the selection task and syllogistic reasoning. It is based on logic programming with skeptical abduction. Each weakly completed program admits a least model under the three-valued Lukasiewicz logic which can be computed as the least fixed point of an appropriate semantic operator. The operator can be represented by a three-layer feed-forward network using the Core method. Its least fixed point is the unique stable state of a recursive network which is obtained from the three-layer feed-forward core by mapping the activation of the output layer back to the input layer. The recursive network is embedded into a novel network to compute skeptical abduction. This extended abstract outlines a fully connectionist realization of the Weak Completion Semantics.