Reviewerly/exHarmony huggingface dataset:
ANALISIS KEMAMPUAN BERBICARA SISWA KELAS II MELALUI MODEL PEMBELAJARAN THINK TALK WRITE DI SDN 007 SUNGAI PINANG SAMARINDA

The research aimed at finding out speaking ability of second grade elementary students by using Think Talk Write learning model. The data retrieval was carried out for four days. The problem was lack of teachers’ innovation in improving students’ speaking ability so the researcher decided to carry out this model. The research method was descriptive qualitative. Primary data was taken from this research result and secondary data was taken from published journals. Data analysis techniques were triangulation and data reduction from interview, observations, students’ activities, and students’ presentation results. The result of this study showed that on the first day of observation the students were still in low category, while on the second day to the fourth day, 25 students were in fast category and only 2 students were in medium category. Based on this result, it can be concluded that Think Talk Write learning model can improve speaking ability of second grade elementary students.
THE EFFECT OF GAMIFICATION BASED ON BALINESE LOCAL STORIES AS TEACHING MEDIA TOWARD FIFTH GRADE STUDENTS’ SELF REGULATION IN PRODUCTIVE SKILLS

This research aimed to investigate the effect of Gamification based on Balinese Local Story toward students’ self-regulation in productive skills. The design of this research was one group pretest-posttest. The research population consisted of 150 students of SD Negeri 1 Tukadmungga. Then, the research sample was the 5th-grade students consisted of 20 students. The result shows the writing mean score of the pretest was 0000 and writing mean score of the posttest was 0000. While speaking mean score of the pretest was 0000 and speaking mean score of the posttest was 0000 and the result of the effect size of both writing and speaking was 000 that was the large effect. The result of those analyses showed Gamification based on Balinese local story could improve students’ self-regulation in productive skills. This result also supports by the result of the questionnaire that the motivation of students was increased after implemented gamification in their learning process.
High Bit-Depth Seismic Data Compression: A Novel Codec Under the Framework of HEVC

Motivated by the superior performance of High Efficiency Video Coding (HEVC), and driven by the rapid growth in data volume produced by seismic surveys, in this work we explore a 32 bits per pixel (b/p) extension of the HEVC codec for compression of seismic data.We propose to reassemble seismic slices in a format that corresponds to video signal and benefit from the coding gain achieved by HEVC inter mode, besides the possible advantages of the (still image) HEVC intra mode.To this end, we modify almost all components of the original HEVC codec to cater for high bit-depth coding of seismic data: Lagrange multiplier used in optimization of the coding parameters has been adapted to the new data statistics, core transform and quantization have been reimplemented to handle the increased bit-depth range, and modified adaptive binary arithmetic coder has been employed for efficient entropy coding.Even though the new codec after implementation of the proposed modifications goes beyond the standardized HEVC, it still maintains a generic HEVC structure, and it is developed under the general HEVC framework.Thus, we tailored a specific codec design which, when compared to the JPEG-XR and commercial wavelet-based codec, significantly improves the peak-signal-to-noise-ratio (PSNR) vs. compression ratio performance for 32 b/p seismic data.Depending on a configuration, PSNR gain goes from 3.39 dB up to 9.48 dB.Also, relying on the specific characteristics of seismic data, we proposed an optimized encoder that reduces encoding time by 67.17% for All-I configuration on trace image dataset, and 67.39% for All-I, 97.96% for P2-configuration and 98.64% for B-configuration on 3D wavefield dataset, with negligible coding performance losses.
On the Need of Understanding the Failures of Smart Contracts

When the execution of smart contracts fails, the transaction will not be recorded to provide hints for analysts to improve their automated analyzers. To mitigate this, we present ExecuWatch to watch the execution of smart contracts and report the execution details.
Improving Students Vocabulary Mastery through Guess My Move Game Gender-Based

In learning a language, vocabulary is the most important thing that should be mastered by learners. The English ability of primary school students is very closely related to the vocabulary mastery that they have. This research aims to find the answer to the following questions: 1) How is the application of Guess My Move Game model in learning English in primary grade school students? 2) How the students' English vocabulary mastery improve by using the Guess My Move Game model? and 3) Are there differences in the mastery of English vocabulary in male and female students using Guess My Move Game model? The research method was used in this study is Classroom Action Research with Kemmis and McTaggart design. The total population was 24 students of first primary school grade. The group was divided by gender. Based on the performance of group scores, it indicates that the female group gets the highest score, but the average highest score is achieved by the male groups. The result of this research shows that the Guess My Move Game learning model can improve students’ English vocabulary mastery both in individual and group scores.
STRATEGI PERPUSTAKAAN MENERAPKAN LITERASI UNTUK MENINGKATKAN IMAJINASI, KREATIVITAS, INOVASI

This research discusses the library strategy of applying literacy to increase imagination, creativity and innovation. Various libraries carry out various literacy programs, including GLN and GLS. However, the results have not looked encouraging. UNESCO in 2017 stated that out of a total of 61 countries, Indonesia ranked 60th at a low literacy level. Literacy activities, namely activities that empower the movement of reading and writing, can make someone create imagination, creativity, and innovation. Libraries must have effective and efficient literacy implementation strategies, based on 6 types of literacy, namely literacy, numeracy literacy, scientific literacy, ICT literacy, financial literacy, and cultural and citizenship literacy. Librarians need to pay attention to the process of developing literacy, namely: text and facilities; literacy type and purpose, learning context, and learner character. Librarians determine the competencies to be achieved, then determine the quality of character and type of literacy. In the application process, librarians introduce methods of reading books and storytelling, creating a safe and pleasant atmosphere, letting users experiment, and playing roles.
Enhancing the NTRU Cryptosystem

NTRU is an open-source public key cryptosystem that uses lattice-based cryptography to encrypt and decrypt data.Unlike other popular public-key cryptosystems, it is resistant to attacks using Shor's Algorithm and its performance has been shown to be significantly greater.This paper talks about how Koblitz encoding from Elliptic Curve Cryptography (ECC) can be used to convert each character in a dataset to a point on an elliptic curve.A sum of squares analogy is pitted against the cantor pairing function to turn the point to a single number, which is converted to a sequence of coefficients in .A polynomial is then generated for each of these characters.Then the polynomial is reduced, and then shown that choosing appropriate parameters for the cryptosystem can make it highly secure and that the decryption algorithm turns out taking linear time.Since each character is represented by its own polynomial, it increases obscurity thereby increasing the complexity for decryption and thus the security level.A form of data compression has also been implemented and it has been tested whether data compression and expansion during the encryption-decryption process results in original data with no or minimal loss.
REAL TIME EYE TRACKING FOR PASSWORD AUTHENTICATION

The Generality of today's authentication systems, including password , fingerprint scanners and Personal Identification Number(PIN) entry, are based on one time, static authentication methods which are prone to attacks.Real time eye tracking contributes significantly for Patients who are incapacitated, internet study , gaze based password entry as well as house hold security applications.The use of real time eye tracking and password authentication system has a wider possibility for reliability, but in this case the system must be secure and restrained for Eye Detection and Tracking.For the user's security and validation (authentication) personal identification numbers are used abroad thereby reducing the chances of being attacked.In static authentication methods , since the password has to be entered physically using PIN's there are possibilities for tracking the password using shoulder surfing, in order to avoid this spy game of tracking the password , hands off gaze-based PIN entry techniques are used.The smart camera is used to detect the eye position and for Gaze-based PIN Identification thereby doing the data processing.This project is focused on a real time hands off and gaze based PIN entry , detecting the eye position and tracking the eye movement using the smart camera.
Inference-Proof Monotonic Query Evaluation and View Generation Reconsidered

The concept of inference-proofness has been introduced for capturing strong confidentiality requirements—including privacy concerns—of an information owner, communicating with a semi-honest partner by means of their message exchanging computing agents according to some agreed interaction protocols. Such protocols include closed-query evaluation and view generation by the information system agent under the control of the information owner, and the corresponding request preparation by the client agent. The information owner employs a security mechanism for controlled interactions, shielding the epistemic state of the information system agent and suitably altering messages sent to the client agent. The alterings provably guarantee that the partner cannot infer the validity of any piece of information that the information owner has declared as being prohibited. Based on selected previous work, we carefully describe and inspect the underlying function and attack scenario and summarize and analyze basic approaches for controlled interactions within an abstract framework for epistemic states.
Status of derivative works of scientific publications under copyright law and publication standards

Introduction. The article aims to present the principles of derivative works (including translations) of original and others’ scientific publications in copyright law and publication standards. Material and methods. The analysis concerns the legal status of derivative works as so-called derivative (dependent) works under copyright law, with the indication of the practice of regulating dependent rights relevant to derivative works in publishing contracts and publication guidelines. Results and discussion. Works prepared on the basis of original work and translations of works have a special status in copyright law. On the one hand, they are subject to the personal and economic copyrights of the person who created them, while on the other, the exploitation of such derivative works is subject to the consent of the author of the original work based on the construction of the so-called dependent copyrights. In practice, this category of work may create un­certainty as regards the proper grounds for exploitation of such modified scientific publications by other authors, as well as problem of unreliable duplication of one’s scientific achievements in the form of modified versions of previous work. Summary. The condition for the authorised preparation and exploitation of derivate works by other authors requires an awareness of the regulations concerning this category of work, as well as consideration of previous contractual provisions concerning the disposal of dependent rights to the original works on which they were based.
Assessing Construct Reliability of Human Resources Management Practices (HRM) and Employee Loyalty: A Preliminary Evidence from the Omani Logistic Sector

Purpose: In the past few years, industry sector highly dominated the Oman’s economy, as the logistics sector forms the backbone of it, which accounted for 56.6% of GDP in 2019. The logistic sector is expected to provide 80,000 jobs by 2020 and 300,000 by 2040. Review of past literature on issues related to HRM impact on employee loyalty particularly from the Omani logistic sector revealed limited outcome. This paper aims in assessing the construct reliability of human resources management practices (HRM) and employee loyalty as well as the impact of HRM practices on employee loyalty, as HRM practices include recognition, compensation, promotion, training, selective hiring, job rotation, and working environment.Method: To achieve this objective, a quantitative approach was adopted, as questionnaire was distributed to 52 employees who work in logistics sector in Oman as pilot study cohort. Data were analyzed by using SPSS. Items of the research constructs were measured for its reliability value.Results: The results showed that employee loyalty construct obtained the highest mean (3.891), while compensation construct obtained the lowest mean (3.281). In addition, the results showed that reliability statistics for research constructs and their paragraphs achieved high Cronbach alpha, thus met the minimum trajectory of reliability value. The results of regression analysis illustrated that HRM best practices (recognition, compensation, promotion, training, selective hiring, job rotation, and working environment) had a significant impact on employee loyalty.Implications: This paper is expected to be a reference for other studies in other sectors to assess the construct reliability on HRM practices variables as well as employee loyalty.
A new approach to identify similar users based on customer reviews

Abstract Recommender System suggests items of interest to users based on their preferences. These preferences are gauged through various sources such as purchase history, ratings, reviews and browsing behaviour. Collaborative filtering and content based filtering are the two widely used techniques that help in generating recommendations to the target user(s) by identifying similar users to target user or similar items to items of interest. Through this paper a new method to identify similar users based on the similarity of reviews has been proposed.
ESL LEARNERS’ PERCEPTION ON THE USE OF THE GRAPHIC ORGANIZERS (GOs) AS CLASS PRESENTATION STRATEGIES

The study scientifically, empirically, and objectively conducted aims at knowing the ESL learners’ perceptions towards the practices of graphic organizers conveniently used as presentation media or strategies in high class activities (a class-presentation task). In order to achieve the aim of the study, the researcher used a quantitative research technique along with its instrument, a questionnaire. The data was collected through applying a questionnaire, and then analyzed in a descriptive statistic method. The results suggest that the perceptions of low English speakers in using graphic organizers as presentation strategies was moderate (M=3.7). Meanwhile, ESL learners owning a good English proficiency perceived the use of graphic organizers as presentation strategies positively (M=4.5). All in all, the use of Graphic Organizers (GOs) as ESL learners’ presentation media or strategies was perceived favorably.
Dependence of the photon statistics of down-converted field-modes on the photon statistics of the pump field-mode

Using the zero time-delay second-order correlation function for studying the photon statistics, we investigate how the photon statistics of the field-modes generated by parametric down-conversion (PDC) process depends on the photon statistics of the pump field-mode. We derive general expressions for the zero time-delay second-order correlation function of the down-converted field-modes for both multi-mode and single-mode PDC processes. We further study these expressions in the weak down-conversion limit. We show that for a two-photon two-mode PDC process, in which a pump photon splits into two photons into two separate field-modes, the zero time-delay second-order correlation function of the individual down-converted field-modes is equal to twice that of the pump field-mode. Furthermore, for an $n$-photon $n$-mode down-conversion process, in which a pump photon splits into $n$ photons into $n$ separate field-modes, the zero time-delay second-order correlation function of the individual down-converted field-modes is equal to $2^{(n-1)}$ times that of the pump field-mode. However, in contrast to the multi-mode PDC processes, for a single-mode PDC process, in which a pump photons splits into two or more photons into a single mode, the zero time-delay second-order correlation function of the down-converted field-mode is not proportional to that of the pump in the weak down-conversion limit. Nevertheless, we find it to be inversely proportional to the average number of photons in the pump field-mode.
Classification of White Blood Cell Abnormalities for Early Detection of Myeloproliferative Neoplasms Syndrome Based on K-Nearest Neighborr

The myeloproliferative neoplasms (MPNs) are clonal hematopoietic stem cell disorders characterized by dysregulated proliferation and expansion of one or more of the myeloid lineages. The initial symptoms of MPN is a bone marrow abnormalities when producing red blood cells, white blood cells and platelets in large numbers and uncontrolled. An automatic and accurate white blood cell abnormality classification system is needed. This research uses digital image processing techniques such as conversion to the modified CIELab color space, segmentation techniques based on threshold values and feature extraction processes that produce four morphological features consisting of area, perimeter, metric and compactness. then the four features become input to the K-Nearest Neighborr (KNN) method. The testing process is based on variations in the value of K to get the best accuracy percentage of 94.3% tested on 159 test data.
Markov logic for statistical relation extraction

In today's world, the Internet has become a fast and efficient information provider, although the relevancy or accuracy of the information found is not guaranteed.The web itself presents numerous problems in finding a required piece of information, mainly due to its heterogeneous nature.Therefore, extracting information from the web is still a challenging task despite the fact that numerous work has been cited in the literature.Extracting information in the form of entities and relations has been addressed by various techniques such as machine learning, natural language processing, and statistical methods, etc.In this paper, we present a rulebased method which is hybridized by machine learning and statistical techniques for accurate performance in domain-specific relation extraction.The rules are modeled in Markov Logic Network to enable statistical performance.Our results on two test domains show overall high values in precision.
Movies Emotional Analysis Using Textual Contents

In this paper, we use movies and series subtitles and applied text mining and Natural Language Processing methods to evaluate emotions in videos. Three different word lexicons were used and one of the outcomes of this research is the generation of a secondary dataset with more than 3658 records which can be used for other data analysis and data mining research. We used our secondary dataset to find and display correlations between different emotions on the videos and the correlation between emotions on the movies and users’ scores on IMDb using the Pearson correlation method and found some statistically significant correlations.
PENTINGNYA PEMANFAATAN DATA KEPENDUDUKAN DI ERA DIGITAL

Government Work Units to use a one data policy approach. The purpose of using this data includes the use of data for schools, taking care of data licensing, managing social assistance, all of which must be the same as the data sources in the Population and Civil Registration Office so that no more people have different identities. Based on the Minister of Home Affairs Regulation No. 61 of 2015 concerning Requirements, Scope and Procedures for Granting Access Rights and Utilization of Population Identification Number, Population Data, and Electronic Resident Identity Cards, data utilization access permits are granted by the Regent / Mayor. After submitting the permit to the Regent / Mayor, then the Cooperation Agreement (PKS) is signed. Furthermore, the Regional Apparatus Organization or public service agencies form a Technical Team implementing the cooperation. Furthermore, data access will be given according to their needs and usage. The user access institution will be monitored by the Regent / Mayor through the Department of population and civil registration, and periodic control, supervision and evaluation will be conducted.
Digital pedagogies and biotechnical realities: Education and life after the COVID-19 pandemic

What would have taken years to change in the world we knew, took just a few months during a global pandemic. Millions of teachers, therapists, and other practitioners around the world whose work requires direct contact with people, dived into every synchronous and asynchronous platform they could find. They had to in order to continue their work with students or clients, to maintain connections, to empower people during the crisis, to ensure that nobody felt alone, to protect and strengthen life, and to resist a vicious invisible threat. All these practitioners struggled to ensure physical distancing did not result in social or emotional distancing, and managed to do so through web technologies and digital media. The social pattern of life, the very pattern that allowed coronavirus to threaten humanity, is the same pattern helped maintain life during lockdown by taking advantage of digital media.
An Algorithm Incarnating Deep Integration of Hardware-Software Energy Regulation Principles for Heterogeneous Green Scheduling

Heterogeneous green scheduling in virtual cloud is an urgent need of human sustainable developments. However, on the one hand, there is still considerable space beyond reach of the hardware energy regulation mode; on the other hand, as the core of green software methods, meta-heuristics algorithms are still underperforming in heterogeneous scheduling, although with many achievements in homogeneous scheduling. In this paper, an efficient new meta-heuristics algorithm is presented (i.e., GHSA_di), including the co-evolutionary dynamics equation emphasizing on and taking advantage of the hardware energy-regulation principles. The experimental results show that compared with the other three meta-heuristic scheduling algorithms, GHSA_di algorithm has obvious advantages in overall performance, energy saving and scalability, for both data intensive and computing intensive instances.