Reviewerly/exHarmony huggingface dataset:
Teaching Narrative Reading Texts by Using MURDER Method to the Eleventh Grade Students

Mood, understand, recall, detect, elaborate and review (MURDER) method is an alternative method which enables the students comprehending reading texts, particularly narrative texts, by collaboration working between two groups. The objectives of this study were to find out (1) the significant improvement on the eleventh grade students’ reading comprehension achievement in narrative reading texts before and after being taught by using MURDER method and (2) the significant difference on the eleventh grade students’ reading comprehension achievement in narrative reading texts between those who were taught by using MURDER method and those who were not. This study used quasi experimental design by using pretest and posttest non-equivalent groups design. There were 111 eleventh grade students of SMA Muhammadiyah 2 Palembang in academic year 2016/2017 were used as the population of this study. 57 students from two classes were taken as sample by using convenience sampling. 28 students from class XI IPA 2 were as the experimental group and 29 students from class XI IPA 1 were as the control group. In collecting the data, multiple choice tests were used in pretest and posttest to experimental and control groups. The data of pretest and posttest were analyzed by using independent sample t-test and paired sample t-test in SPSS program. The findings showed that the p-output from independent sample t-test was lower than 0.05 and the result of p-output from paired sample t-test was lower than 0.05. It means that MURDER method can be implemented as one of alternative method in teaching narrative reading texts.
Students’ and Teachers’ Beliefs on English Language Teaching: A Study in One Islamic Boarding School

This study was done to find out (1) whether there was a significant difference between students and teachers belief in one Islamic boarding school in Palembang, (2) the teacher beliefs on English language teaching in Islamic boarding school in Palembang, and (3) students’ beliefs on English language teaching in one Islamic boarding school Palembang. This study employed a mixed method research design. Participants for collecting quantitative data were 55 students and 1 teacher, meanwhile the participants for qualitative data were 6 students and 1 teacher. In order to collect the quantitative data, questionnaire was used, and for qualitative data, interview was used. These instruments were used to find the difference of beliefs between students and teacher on English language teaching. From this study, it was found out the difference beliefs between students and teacher on English language teaching toward communicative language strategy and target language use. Moreover, from the interview results, the differences between students and teachers’ beliefs in communicative language strategies and target language use were also found.
The Link between Personality Types and Reading Comprehension Achievement of the Eleventh Grade Senior High School Students

The aims of this study were (1) to find out whether each type of personality types had any significant correlation to reading comprehension achievement of the eleventh grade students of SMA Muhammadiyah 1; 2) to find out whether each type of personality types influenced reading comprehension achievement, and (3) which type of personality that became the best predictor of reading comprehension achievement. The method of this research was correlational research. The population of this research was all of the active students of SMA Muhammadiyah 1 Palembang in the academic year of 2018-2019 with total number of 1.298 students. However, there were only 132 students involved as sample in this research taken by using convenience sampling method. The students’ personality type score was taken by distributing questionnaire by Golberg (1992), while the students’ reading comprehension achievement was obtained by conducting reading test. To answer the first problem, Pearson Product Moment Correlation Coefficient was employed. The result of this study showed that there was no significant correlation between each type of personality types and reading comprehension achievement. Since there was no significant correlation, further analyses were eliminated.
Teachers' Perspectives towards Validity of Teacher-Made Test

Some studies that had been conducted showed that teacher-made tests were good and satisfactory. However, the majority of teachers do not validate their tests administering them to the students. This study would describe the perspective of teachers towards their-own.-made (teacher-made) tests they have made to know that to what extent their agreement regarding their attitudes, quality, and use of the tests. Five English teachers participated in this research. Their view on the test they have made would be analyzed and described. The results showed that (1) the teachers agreed about the appropriateness of the test they administered; (2) the teachers believed that the data quality obtained during research was useful and meaningful, and; (3) the teachers used the test to identify and to evaluate their learning objectives, students’ learning needs, students’ learning difficulties, and school evaluation.
Using KWL (Know Want Learn) Reading Strategy to Teach Reading Comprehension: A Case in One Public Senior High School in Palembang

KWL reading strategy is one of the strategies to improve the ability of comprehending reading text, especially expository texts. The study was conducted to find out whether or not there was a significant difference in the students’ reading achievement in comprehending expository texts between the students who were taught by using KWL Reading Strategy and those who were not. It used one of the quasi-experimental designs--pretest-posttest non-equivalent control group design. There were 79 students of SMA N 4 Palembang participating in this study. In selecting the sample, purposive sampling technique was used. The data were gathered through the use of reading comprehension test. T-test analyses namely paired sample t-test and independent sample test were applied to examine the hypotheses. The results of t-test revealed that there was significant improvement in students’ reading comprehension after the intervention. KWL reading strategies helped students to comprehend the expository text and gave a positive influence to the students’ improvement. Furthermore, teachers could apply this strategy as a variation in teaching reading in his/her class to avoid students’ boredom.
The Effectiveness of Kahoot Online Media in Learning Personal Pronoun at a State Senior High School in Jambi City

This study is aimed at finding the effectiveness of Kahoot online media in learning personal pronoun for senior high school students. There were 30 social sciences students taken as participants in control class, and 30 natural sciences students were taken as experimental participants. There were five (5) topics given to the students; objective, subjective, possessive pronoun, possessive adjective, and reflexive as mains materials in English subject. The results of the research were proven effective by using t-test. Students’ scores in learning personal pronoun were significant after implementing Kahoot online media. The average pre-test control class 37,1 and post-test control class 48,7. Average pre-test experimental class 41,5 and post-test experimental class 83,5. Kahoot online media makes learning process more interesting. The value of t-test higher than the value of t-table (26,11&gt; 2,001).
IN- SERVICE TRAINING: ENGLISH TEACHER'S ASSESSMENT FOR LEARNING (AFL) PRACTICE AT SMPN 9 RUTENG, FLORES

Teaching is an integrated activity with learning goals or objectives and assessment process. As such, it is conducted on the basis of particular learning goals which subsequently requires assessment activities to look into the impact of teaching on students learning process. The aim of this community service is to furnish the knowledge regarding the assessment process, particularly Assessment for Learning (AfL) of English teachers involving in MGMPS of English Subject at SMPN 9 Ruteng. The method used was in- service training employing Information Processing Theory namely information encoding, information decoding, infromation storing, and information rehearsal. The results have indicated that the English teachers involving in MGMPS SMPN 9 Ruteng were able to make a good instructional design along with the Assessmenf for Learning (AfL). It was proven on their works as they did the task provided by the community service team. Yet, they need to have a further professional development on curriculum and asessment following the changes and goverment policies on education.
BCI-Algebras and Related Logics

Kabzinski in [6] first introduced an extension of BCI-logic that is isomorphic to BCI-algebras. Kashima and Komori in [7] gave a Gentzen-style sequent calculus version of this logic as well as another sequent calculus which they proved to be equivalent. They used the second to prove decidability of the word problem for BCI-algebras. The decidability proof relies on cut elimination for the second system, this paper provides a fuller and simpler proof of this. Also supplied is a new decidability proof and proof finding algorithm for their second extension of BCI-logic and so for BCI-algebras.
Paraconsistent resolution

Digraphs provide an alternative syntax for propositional logic, with digraph kernels corresponding to classical models. Semikernels generalize kernels and we identify a subset of well-behaved semikernels that provides nontrivial models for inconsistent theories, specializing to the classical semantics for the consistent ones. Direct (instead of refutational) reasoning with classical resolution is sound and complete for this semantics, when augmented with a specific weakening which, in particular, excludes Ex Falso. Dropping all forms of weakening yields reasoning which also avoids typical fallacies of relevance.
Hardware method parallel prefix and suffix search on an array of fixed-ength substrings

The work consists in the development of hardware-oriented methods for restoring the structure of the target word. The reconstruction storation is performed by constructing its prefix and suffix from a set of private words, understood as patterns. The reconstruction of the unknown word is performed by formation its prefix and suffix from a set of private words, understood as standards. The goal is to reduce the recovery time of the structure of the target word by parallel processing of pairs of words stored in the matrix of the original partial words. Solution method. The method consists of 4 stages. They include the stage of parallel processing of fragments of pairs of words for their intersection and selection of mismatched characters. These characters are candidates for the current prefix and suffix characters. A distinctive feature of the proposed method is the hardware support of the main operations in the form of a homogeneous computational PIM structure and the use of a string data structure rather than tuples. For a tuple, the minimum work item is a single character, so the processing of an m-tuple is sequential element-by-element. For a word, the minimum work item is a string of characters that can be processed in parallel without losing the generality of properties. The meaning of the PIM structure is the integration of register memory blocks and functional units for comparing character strings, which allows parallel processing of an array of elements without wasting time on intermediate transfers. Results and discussions. Algorithms are modeled based on the known method and the developed method, using variable parameters: the number of private words, the length of the private word, the cardinality of the alphabet. Modeling showed that the developed method has a time advantage from 1,25 to 9,97. Conclusion. The developed hardware-oriented method for restoring the target word based on the analysis of a set of private words that have a structural relationship with each other has shown its temporal efficiency with increasing values of the varied parameters. This property testifies to the prospects of using the method in search-analytical problems of a real level of complexity.
Kernel-based Sampling of Graph Signals via Graph Sampling Expansion Theorem

Sampling expansion theorem (SET) plays an important role in discrete signal processing (DSP) for recovering bandlimited signals, while its counterpart in graph signal processing (GSP) has not been thoroughly investigated. In this paper, we will propose one graph SET (gSET) for signals lived in kernel space and then derive one fast sampling algorithm. Specifically, we at first define gSET using kernel-based reconstruction of graph signals lived in reproducing kernel Hilber space (RKHS). We then utilize the defined gSET of bandlimited graph signals as special case with ideal low-pass kernel to combine the proposed gSET in GSP with SET in DSP. Finally, based on the proposed gSET, we will derive one fast graph sampling scheme to select sample with minimal coverage energy. Experiments on realworld temperature graph data will validate the superiority of the proposed sampling method.
Chinese Word Segmentation based on Word boundary Classificatioin

As one of the basic tasks in natural language processing (NLP), Chinese word segmentation (CWS) is a necessary and key preprocessing step for many natural language processing tasks. The performance of CWS directly affects the final performance of subsequent tasks. Traditional word segmentation approaches mainly use conditional random field (CRF) decoder and BIO tags for sequence labeling, and the recent mainstream approaches normally employ the pre-trained bidirectional encoder representations from transformers (BERT) model as text encoder. This greatly affects the speed of word segmentation. Different from the existing approaches, this paper proposes a Chinese word segmentation approach based on word boundary classification, which utilizes a lite BERT (ALBERT) model as the text encoder. This approach directly determines whether the position between characters is the boundary between two potential words without using CRF decoding. Experimental results show that our proposed approach can achieve significant improvements, and significantly reduces the training and testing time of CWS.
Intent AI Mediator (Mintent) for High-satisfaction-level Services

This article introduces the intent AI (artificial intelligence) mediator called Mintent that coordinates and cooperatively controls networks, cloud servers, and applications on the basis of the respective requirements (intents) of service providers and users.This technology can be used to provide services on the basis of such intents.
Technology Review: Fluent Forever

Fluent Forever is a mobile device app dedicated to language learning through pronunciation, vocabulary acquisition, grammar exposure, and speech fluency practice. The application is based on user-created flashcards and repetition schedules to learn quickly and effectively. At the time of this review, only ten options are available as Target Languages (TL): German, Spanish (two dialects), French, Italian, Russian, Korean, Brazilian, Japanese, and Mandarin. The basic plan is $9.99 per month. The review was completed using Spanish (Latin America) and Russian as the TL with a proficiency level of "new." The choice to complete the review with these two languages is motivated by the reviewer's intent to evaluate the app with a known L2 (Spanish) and an unknown L2 (Russian). In doing so, the reviewer wishes to control for bias and review the application for the language content and not aesthetics. This review concentrates on the pronunciation training module of the application. The module guides its users to focus on three main aspects of pronunciation for the TL: "basics of spelling," "new sounds," and "ear training." After describing the features of this module, an evaluation is presented considering the principles of pronunciation learning and instruction found in Celce-Murcia et al. (2010).<style>@font-face{font-family:"Cambria Math";panose-1:2 4 5 3 5 4 6 3 2 4;mso-font-charset:0;mso-generic-font-family:roman;mso-font-pitch:variable;mso-font-signature:-536870145 1107305727 0 0 415 0;}@font-face{font-family:Calibri;panose-1:2 15 5 2 2 2 4 3 2 4;mso-font-charset:0;mso-generic-font-family:swiss;mso-font-pitch:variable;mso-font-signature:-469750017 -1073732485 9 0 511 0;}@font-face{font-family:"Times New Roman \(Body CS\)";panose-1:2 11 6 4 2 2 2 2 2 4;mso-font-alt:"Times New Roman";mso-font-charset:0;mso-generic-font-family:roman;mso-font-pitch:auto;mso-font-signature:0 0 0 0 0 0;}p.MsoNormal, li.MsoNormal, div.MsoNormal{mso-style-unhide:no;mso-style-qformat:yes;mso-style-parent:"";margin:0in;mso-pagination:widow-orphan;font-size:12.0pt;font-family:"Times New Roman",serif;mso-fareast-font-family:Calibri;mso-fareast-theme-font:minor-latin;mso-bidi-font-family:"Times New Roman \(Body CS\)";mso-bidi-font-weight:bold;}.MsoChpDefault{mso-style-type:export-only;mso-default-props:yes;mso-fareast-font-family:Calibri;mso-fareast-theme-font:minor-latin;mso-bidi-font-family:"Times New Roman \(Body CS\)";mso-bidi-font-weight:bold;}div.WordSection1{page:WordSection1;}</style>
Federated learning for 5G-enabled infrastructure inspection with UAVs

Abstract Electricity infrastructures include assets that require frequent maintenance, as they are exposed into heavy use, in order to produce energy that satisfies customer demands. Such maintenance is currently performed by specialized personnel that is scaffolding to spot damages or malfunctioning equipment. Scaffolding is time-consuming and incurs accident risks. To tackle this challenges, grid operators are gradually using Unmanned Aerial Vehicles (UAVs). UAV trajectories are observed by a centralized operation center engineers for identifying electrical assets. Moreover, asset identification can be further automated through the use of Artificial Intelligence (AI) models. However, centralized training of AI models with UAV images may cause inspection delays when the network is overloaded and requires Cloud environments with enough processing power for model training on the operation center. This imposes privacy concerns as sensitive data is stored and processed externally from the infrastructure facility. This article proposes a federated learning method for UAV-based inspection that leverages a Multi-access Edge Computing platform installed in edge nodes to train UAV data and improve the overall inspection autonomy. The method is applied for the inspection of the Public Power Corporation's Innovation Hub. Experiments are performed with the proposed method as well as with a centralized AI inspection method and demonstrate the federated learning benefits in reliability, AI model processing time and privacy conservation.
Succinct Non-interactive Arguments of Knowledge from Supersingular Isogenies

A succinct non-interactive argument of knowledge (SNARK) enables a party to convince another of some statement (typically, knowledge of some information) by means of a short argument, while ensuring it is infeasible for an adversary to create a short argument of the opposite statement. We hereby describe a SNARK for CSI-FiSh signatures, whose security stems from hard problems involving supersingular isogenies. Although the scheme looks analogous to a SNARK for conventional Schnorr signatures, it is non-trivial in that, as we also show, a similar SNARK for another isogeny-based signature scheme (SQISign) is not viable. As a bonus, we also discuss how to drastically reduce the memory needed to implement the CSIDH framework required by CSI-FiSh signatures.
Efficient Gaussian sampling for RLWE-based cryptography through a fast Fourier transform

Quantum computing threatens classical cryptography, leading to the search for stronger alternatives. The cryptographic approach based on lattices is considered as a viable option. Schemes with that approach use Gaussian sampling, a design which brings along two concerns: efficiency and information leakage. This work adresses those concerns in the RLWE formulation, for digital signatures. Efficiency mitigation uses the central limit theorem, and the Walsh–Hadamard transform, whereas the information leakage risk is reduced via isochronous implementation. Up to 223 samples are queried, and the results are compared against those of a cumulative distribution table sampler. Statistical metrics show the suitability of the presented sampler in a number of contexts.
Effects of Using Command and Reciprocal Teaching on Skill Achievement of Students of Gymnastics Course at School of Sports Sciences at University of Jordan

Objectives: This study aims to identify the effect of using command and reciprocal styles on achievement of students studying gymnastics at School of Sports Sciences at the University of Jordan.&#x0D; Methods: The researcher used a quasi-experimental approach. The sample of the study consisted of (42) male students from Gymnastics (1) course. Two sections were selected intentionally. The first section (the control group) consisted of (19) male students who learned through a command style. The second section (the experimental group) consisted of (23) male students who learned through a reciprocal style.&#x0D; Results: The results of the study showed a positive effect for the reciprocal style on skill achievement students.&#x0D; Conclusions: The researcher recommends diversifying teaching strategies during lectures of gymnastics at the University of Jordan, especially by including reciprocal learning style in teaching gymnastic skills to students as it proved to be effective in building the skills of students compared to the command style method.
Alat Pendeteksi Ketepatan Penggunaan Masker Berbasis Arduino Menggunakan Bahasa Pemrograman Python

In early March 2020, Indonesia experienced an outbreak of the virus known as Corona Disease 2019 or covid-19 and has been declared by the World Health Organization as a pandemic on March 9, 2020. To prevent the transmission of the virus, the use of masks is a solution that is considered effective and efficient enough to prevent the spread of the covid-19 virus. But the use of this mask is sometimes still an unusual thing among the public. Detection of the use of masks so far is only done manually through observation by officers and this has some limitations that cannot be done every time and every place. For this reason, researchers make a mask-using precision detection tool made using machine learning. Machine learning works to classify data in the form of images then matched with the image of the face that has been captured, after which the data is sent to arduino as an output. If the facial data is not masked then LCD, red LED and Buzzer will light up. This python program is able to detect mask wearers with an accuracy of 100% at a distance of 50 cm. These results indicate that the problem can be solved properly.