Reviewerly/exHarmony huggingface dataset:
PENINGKATAN KEMAMPUAN MENULIS DESKRIPSI DENGAN METODE OBSERVASI TERPADU SISWA KELAS X SMK PGRI PAKISAJI MALANG

Writing is a skill that language is used to communicate indirectly and not face-to-face with other people. Writing skills do not come naturally, but it requires adequate exercises. This study examines the learners’ problems in essay writing descriptions using the integrated observation learning methods. The lack of ability of the students in writing a description is due to lack of interest of students to learn, teachers’ traditional methods in teaching, and the theory – oriented activities without practice writing especially writing descriptions. The use of an integrated observation method proved to increase the ability of students to write descriptions. It can be taken from the test given to the students to write descriptions. With integrated observation learning, learners are able to generate ideas into writing descriptions by conducting an observation during the learning takes place. An observation was done outside of the classroom and school environment as well as just around the backyard of the school, so the students have a lot of good ideas to compose a good essay.&#x0D; &#x0D; Key Words: Improved, writing, descriptions, integrated observation method.
Multiset Structural Attack on Generalized Feistel Networks

In this paper, we present new generic multiset attacks against generalized Feistel networks, by which we can recover all the unknown round functions completely instead of deciding whether an unknown encryption oracle is such network or a random permutation. With one <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mrow><mml:mi>r</mml:mi></mml:mrow></mml:math>-round multiset distinguisher, we can recover the outermost round functions for <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M2"><mml:mi>r</mml:mi><mml:mo>+</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:math>-round block cipher. Next we propose the dummy-round technique , which allows us to make a full-round decomposition if the outermost round is recovered. Moreover, the dummy-round technique barely increases the complexity of our attack. Using this generic method, we propose attacks on 7-round RC6-like and 7-round CLEFIA-like structures. Our attacks can recover all the secret round functions, requiring only <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M3"><mml:mi>O</mml:mi><mml:mo stretchy="false">(</mml:mo><mml:mn mathvariant="normal">10</mml:mn><mml:mo>×</mml:mo><mml:msup><mml:mrow><mml:mn mathvariant="normal">2</mml:mn></mml:mrow><mml:mrow><mml:mn mathvariant="normal">0.7</mml:mn><mml:mi>n</mml:mi></mml:mrow></mml:msup><mml:mo stretchy="false">)</mml:mo></mml:math> time complexity and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M4"><mml:mi>O</mml:mi><mml:mo stretchy="false">(</mml:mo><mml:mn mathvariant="normal">5</mml:mn><mml:mo>×</mml:mo><mml:msup><mml:mrow><mml:mn mathvariant="normal">2</mml:mn></mml:mrow><mml:mrow><mml:mi>n</mml:mi><mml:mo>/</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup><mml:mo stretchy="false">)</mml:mo></mml:math> chosen plaintexts, where <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M5"><mml:mrow><mml:mi>n</mml:mi></mml:mrow></mml:math> indicates the block size of the cipher. For 64-bit ciphers of these two structures, our results will lead to a practical attack.
A BENCHMARK STUDY OF KGCS OPTIMIZATION ALGORITHM

This paper presents the study conducted on the optimization algorithm called KGCS (Knowledge Gradient Cuckoo Search) using benchmark functions. The algorithm is highly effective due to the combination of the specific characteristics of the Cuckoo Search algorithm and the ones of the Knowledge Gradient policy. The paper also presents the benchmark mathematical functions usually used to test optimization algorithms such as Rosenbrock, Griewank or Ackley’s function. The results of the conducted tests are compared to the results obtained using the unenhanced evolutionary algorithms in order to prove efficiency of the KGCS algorithm.
3D Measurement Based on Row-wise LT Matrix Estimation

3D Measurement is an essential element of robotics for industrial usage. Many methods have been proposed so far, but some objects with specular reflections or subsurface scatterings are difficult to measure the shape accurately. We have developed a new method by using projector-camera Light Transport (LT) Matrix. LT Matrix is often used in computer graphics to make relighting images, light path understanding, and 3D measurement. It is useful for describing light paths on projector-camera system because it includes all light reflection information. However, it takes a long time to measure LT Matrix accurately. This paper first proposes how to obtain 3D shape from LT Matrix. Then we propose fast LT Matrix estimation method by using its sparseness. Our method can estimate accurate LT Matrix to obtain 3D shape in short time. Finally, we compare our results and previous 3D measurement methods, and we conclude our methods performs much better than other methods for metallic or transparent objects.
Research on Satellite Power Subsystem Anomaly Detection Technology Based on Health Baseline

There is a huge amount of data in the satellite power subsystem, and the information and knowledge related to the operating status of the power subsystem in these data is an important for the abnormal state detection of the power subsystem. In order to make data mining of satellite power subsystem and set the reference for its anomaly detection, a satellite power subsystem anomaly detection technology based on the health baseline is proposed. According to the core operating conditions of the satellite power subsystem, health baselines are constructed respectively, and the effectiveness of the proposed method is verified by the telemetry data of the satellite power subsystem. With robustness, the test results show that anomaly detection of the onboard power subsystem can be achieved based on the constructed health baseline.
IMPROVING STUDENTS IN WRITING SKILL BY USING SCRAMBLED PICTURE IN NARRATIVE TEXT

Writing is one of four basic skills that students in junior high school have to learn. While a writing is complicated because there are many aspects such as mechanics, vocabulary and grammar, and writing activities.The students must be able to combine word and sentences grammatically into written text. Based on junior high school curriculum which is designed by Indonesia government, the students should understand and create various functional texts, monologues and essays in the form of descriptive, procedure, report, recount and narrative text. The student should be able to develop their skill to express the meaning and the structure of the text. In this research the researcher founds some problem faced by the students in the eighth grade of SMP Islam Al Amin Malang. They don’t know how to start writing and organize their ideas. Second, they still had difficulties to understand conjunction and punctuation, third they were also low of vocabulary mastery. Beside that the teacher still used conventional technique to teach writing, especially in narrative text.The researchers used classroom action research. In this research, the researcher conducted one cycle in implementing the method by using Scrambled Picture. The researcher conducted in one cycle because in cycle one the criteria of success had been achieved. The success of this research is influenced by two factors; the researcher’s factor and the student’s factor. The researcher’s factor was the researcher’s classroom management and the researcher’s explanation. The students also happy to used Scrambled Picture in writing narrative text during teaching and learning process.&#x0D; Key Words: Improving, scramble, narattive
Komparasi Algoritma Klasifikasi Dengan Menggunakan Anaconda untuk Memprediksi Ramai Penonton Film di Bioskop

In the interest of Moviegoers with trendy films,cinemas also play a major role in attracting audiences towatch films they like. But changes that are quite dynamicfrom audience interest take turns, sometimes it issometimes not crowded. Thus sometimes the cinemamanager experiences an error in placing the film to beaired, so the number of viewers in the cinema is not asexpected. From this problem, researchers are interested inanalyzing data relating to film audiences in the cinema.By using CART classification, NBC (Naive BayesClassifier) algorithm, SVM (Support Vector Machine), LR(Logis Text Regression) and LDA (Linear DiscriminantAnalysis) which will be compared which accuracy is thebest for predicting the absence or absence of theaudience. Researchers use Anaconda to compare sixalgorithms and will see the highest results from theConfusion Matrix and ROC Curve
Cloud Mobile Storage for Mobile Applications

The data storage in mobile cloud computing domain is an important subject because of the large amount of data devices can provide. Different kinds of sensors retrieve information and send them to data storages. But the storage location can move even dynamically during their uses. So, these changes must be managed at runtime. In the other part, Android devices are good computers to acquire information and send them to a storage area. These devices are well-known, ergonomic and useful machines sorely used. In this paper, we present a software architecture from Android devices to Cloud storage areas to put down data when the data stores are dynamically moving. The different parts of these distributed applications are built around Android with JSON messages for REST services and moving NoSQL databases in the Google app engine. The exchanges between the cloud and the Android devices use the Google Cloud Messaging (GCM) protocol. Furthermore, even without network access, the saving is made locally in the smartphone. The synchronization with distant databases is automatically made when the network becomes again available.
Improving the Accuracy of the Naïve Bayes Classifier Using Feature Selection

Machine learning history has a long list of problems regarding classification. One of the simplest and well performing classifier is Naïve Bayes Model. However, a natural issue that occurs with this classifier is that all attributes used to explain an instance are assumed to be conditionally independent given the class. This inevitably results is a decrement in the accuracy of the classifier and also due to interaction omission. In this paper, we focus to put more importance on more accurate model using feature selection technique which focuses on eliminating low information feature.Chi square method is explained which boosts the process of feature selection thereby improving efficiency of the system.
Test-framework: performance profiling and testing web search engine on non factoid queries

&lt;p&gt;Performance profiling and testing is one of the interesting topics in the big data management and Cloud Computing. In testing, we use test cases composed to different type of queries to evaluate the performance aspects of the information retrieval system for large scale information collection. This test scenarioperforms the evaluation ofretrieval accuracy for all kind of ambiguity and non factoid queries with result set as Training data. This stands difficult to evaluate the retrieval method in order to schedule or optimize the Recommendation and prediction technique of the IR method to the Real time queries. The Queries is considered as requirement specification which has to supply to search engine or web information provider applications for information or web page retrieval. In this paper, we propose a novel technique named as “Test Retrieval Framework“a performance profiling and testing of the web search engines on the information retrieved towards non factoid queries. In this technique, we apply expectation maximization algorithm as an iterative method to find maximum likelihood estimate.We discuss on the important aspects in this work based on Recommendation models integrating domain and web usage, Query optimization for navigational and Transactional queries, Query Result records.The Experimental results demonstrates the proposed technique outperforms of state of arts approaches in terms of set based measures like Precision, Recall and F measure and rank based measures like Mean Average Precision and Cumulative Gain.&lt;/p&gt;
PENINGKATAN KETERAMPILAN MENULIS MENGGUNAKAN PENDEKATAN KOMUNIKATIF BAGI SISWA KELAS X SMK MULTIMEDIA NURUL HUDA PONCOKUSUMO MALANG

Writing for most students is a language skill that is difficult to master. This research on writing skills is based on observations and experiences of researchers towards the low ability of SMK students in writing. This is because learning to write at school is still conventional. The selection of learning models has not been a top priority by teachers. The communicative model can be used to improve writing learning to foster a sense of writing and improve learning outcomes. The results of the act of using a communicative approach to writing activities at SMK Multimedia Nurul Huda Poncokusumo showed an increase when compared to conventional writing learning. Improving the ability of students in writing occurs through several stages carried out in three cycles using the communicative model. Keyword : writing, communicative model, learning
Breaking Communication Stereotypes: The Discourse of Armenian Velvet Revolution

In its most basic sense, communication – the transmission and reception of information between the addresser and addressee, the generation of certain meaning, and the powerful source of information in the society – is a social multidimensional semi­otic sys­tem which today, along with traditional oral and written discourse modes, is realized through numerous other media or modes – live-streaming and online text messaging as well as pictures, graphic designs, cartoons, colors, music, clothing, theatre-like scenes/actions, etc. The collection of these modes or elements, contributes to how multimodality affects different rhetorical situations, or opportunities for increasing the audience’s reception of an idea or concept. Hence, the present paper aims at outlining the different modes of multidisciplinary communication tactics with a focus on the complex nature of language/discourse/text and other multimodal communication practices in terms of the aural, spatial and visual resources or modes used to compose the message of the 2018 Armenian Velvet Revolution. The case study shows that the Armenian Velvet Revolution is a master-class in the application of multimodality, i.e. various modes of communication to convey information and impact the public, thus securing the success of the Revolution
Deleting Method on Duplicated Recommending Commodities Based on Shopping Records of Users

Leading e-commerce websites typically now have commodity recommendation functionality. Most users will notice that their recommendation list will contain the commodities purchased previously, despite them no longer need the item. Aimed at resolving this situation, a model has been developed which is able to remove such duplicated recommendations. This paper provided a series of comprehensive optimization schemes to delete duplicated items, based on previous filtering schemes, to include in any repurchase cycle.
The Effectiveness of Think Talk Write Model in English Essay Writing

The aim of this study is to examine the effect of think talk writes learning model on English essay writing ability of English Education Program Study at STKIP Bandar Lampung.The research sample was 22 semester IV students.The process of collecting data through observation, interviews and tests.The technique of data analysis is t-test independent.While the process of data validity used credibility, transferability, dependability, and conformability.The results of the research show that the mean of the pre-test was 52.2 and the mean of post-test was 76.9.While the t-test result was 8.566.It shows the differences in students' English essay writing ability before and after using think talk write learning model.
Searches for electroweak SUSY and for long-lived particles at the LHC

four years of data-taking in
INNOVATION ECOSYSTEM AND INTELLECTUAL PROPERTY PROTECTION AT THE UNIVERSITY

Appears in: INTED2019 Proceedings Publication year: 2019Pages: 1189-1198ISBN: 978-84-09-08619-1ISSN: 2340-1079doi: 10.21125/inted.2019.0381Conference name: 13th International Technology, Education and Development ConferenceDates: 11-13 March, 2019Location: Valencia, Spain
Motivating Low-Achieving Learners to Use Mobile Assistive Courseware through Signaling Principle

Developing a courseware is easy. However, making a courseware usable for its target user requires a scientific process. As a response to that, a study has been carried out in making courseware usable for low-achieving learners. As part of the study, this paper aims to describe the application of signaling principles in the developed courseware specifically for low-achieving learners. The prototype has been developed through user-centered approach. It involved users during the designing and development process. Then, it was delivered to users. Their experience dealing with the developed prototype was observed in their natural context with assistance of their teachers. Eventually, it was found that they were highly motivated to use the courseware.
Meningkatkan Prestasi dan Keaktifan Belajar Siswa SMP Negeri 13 Madiun melalui Program Adiwiyata

Jurnal Tadris Matematika is a scientific publication in mathematics education and learning including: (1) mathematical thinking process, (2) mathematics models, media, and teaching materials development, (3) pedagogical content knowledge, (4) mathematics theoretical study and learning practice, (5) mathematics learning evaluation, and (6) the integration of mathematics and Islamic value. This journal is published twice a year, June and November, both in print and online version.
Ordered Subspace Clustering for Complex Non-Rigid Motion by 3D Reconstruction

As a fundamental and challenging problem, non-rigid structure-from-motion (NRSfM) has attracted a large amount of research interest. It is worth mentioning that NRSfM has been applied to dynamic scene understanding and motion segmentation. Especially, a motion segmentation approach combining NRSfM with the subspace representation has been proposed. However, the current subspace representation for non-rigid motions clustering do not take into account the inherent sequential property, which has been proved vital for sequential data clustering. Hence this paper proposes a novel framework to segment the complex and non-rigid motion via an ordered subspace representation method for the reconstructed 3D data, where the sequential property is properly formulated in the procedure of learning the affinity matrix for clustering with simultaneously recovering the 3D non-rigid motion by a monocular camera with 2D point tracks. Experiment results on three public sequential action datasets, BU-4DFE, MSR and UMPM, verify the benefits of method presented in this paper for classical complex non-rigid motion analysis and outperform state-of-the-art methods with lowest subspace clustering error (SCE) rates and highest normalized mutual information (NMI) in subspace clustering and motion segmentation fields.
A Method of Position Precision Investigation Based on Large Pointcloud Data in Topography Survey

Due to the disordered irregularity of the 3D laser scanning point cloud, the homonymy points of the checkpoint cannot be determined, so the repeated measurement comparison method and the comparison method of different mapping methods cannot be used for position precision investigation of 3D laser scanning topography survey. Therefore, a proposition in this paper is that the proximal-point method is used to detect the position precision of 3D laser scanning topography survey, which realizesthat the point of the same name is replaced by the point closest to the checkpoint in the dense point cloud, and calculate the position precision of the plane and elevation firstly; in addition, find the homonymy points from the super-large point cloud with more than 100 million points. Experiments show that the proposed method can detect the position precision of 3D laser scanning topography survey in ordinary computers.
Analysis of iTeach 2017 Contest Works and Suggestions for Educational Technology Students Training

iTeach contest works is the display window of educational technology students' ability of instruction design, computer programming, software UI, and so on.It can also give out lots of information about China educational technology curriculum implement status, and students training focuses.The analysis of iTeach contest works is not only an inspection of the training quality of educational technology students, it's also a process of communication of training experience of educational technology students.The article takes 196 educational technology students' works from 2017 annual contest as samples, and conducts quantitative statistics from six aspects, including qualifications of contestants, work types, target users, distribution types and authoring tools.The analysis of the works shows there are many fresh work topics, creatively used technologies, specific information technology application in the contest works.The statistics also reveal some points should be paid attention to during the course of educational technology student development.Lastly, based on contest experts' interview, the article puts forward some suggestions for educational technology student training, including the reflection of curriculum structure, the construction of authentic curriculum resources, the implementation of curriculum quality standards, the integration of practical teaching system and scientific research feeding back teaching.
Teaching Material Model of Reading Subject in the Form of Contextual Chinese Literary and Cultural Texts

The cultural and literary knowledge that has been studied in the reading class of the Chinese Language and Culture Study Program at Darma Persada University is not yet maximal and not yet in accordance with the students' needs.Prompted by the issue, this research aims to develop a learning product that is in line with the needs of the study program.The procedure in this study employs Borg and Gall's theory.The data collection is done by distributing a questionnaire, observation, discussion, interview, and test.The validity and reliability tests for the teaching material model employ peer assessment, expert assessment, and testing and questionnaire distribution to the students.The effectiveness test is carried out using a paired sample t-test to compare the data before and after the learning process.The Tcount is (4.060) greater than the T-table (2.101).Thus, it can be concluded that the developed teaching material model is very feasible and can be used for Reading V course in the Chinese Language and Culture study program.
Discriminant Affinity Matrix for Deterministic Motion Trajectory Segmentation

We present a novel algorithm (DAM) for deterministic motion trajectory segmentation by using epipolar geometry and adaptive kernel-scale voting. DAM is based on geometric models and exploits the information derived from superpixels to deterministically construct a set of initial correlation matrices. Then DAM introduces a novel adaptive kernel-scale voting scheme to measure each initial correlation matrix. After that, based on the voting scores, the set of initial correlation matrices is accumulated to generate a discriminant affinity matrix, which is utilized for final grouping. The key characteristic of the DAM is its deterministic nature, i.e., DAM is able to achieve reliable and consistent performance for motion trajectory segmentation without randomness. Experimental results on both several traditional datasets (i.e., Hopkins155, Hopkins12, and MTPV62 datasets) and a more realistic and challenging dataset (i.e., KT3DMoSeg) show the significant superiority of the proposed DAM over several state-of-the-art motion trajectory segmentation algorithms with respect to segmentation accuracy.