Reviewerly/exHarmony huggingface dataset:
Can Transformer Models Measure Coherence In Text? Re-Thinking the Shuffle Test

The Shuffle Test is the most common task to evaluate whether NLP models can measure coherence in text. Most recent work uses direct supervision on the task; we show that by simply finetuning a RoBERTa model, we can achieve a near perfect accuracy of 97.8%, a state-of-the-art. We argue that this outstanding performance is unlikely to lead to a good model of text coherence, and suggest that the Shuffle Test should be approached in a Zero-Shot setting: models should be evaluated without being trained on the task itself. We evaluate common models in this setting, such as Generative and Bi-directional Transformers, and find that larger architectures achieve high-performance out-of-the-box. Finally, we suggest the k-Block Shuffle Test, a modification of the original by increasing the size of blocks shuffled. Even though human reader performance remains high (around 95% accuracy), model performance drops from 94% to 78% as block size increases, creating a conceptually simple challenge to benchmark NLP models. Code available: https://github.com/tingofurro/shuffle_test/
On Search Complexity of Discrete Logarithm

In this work, we study the discrete logarithm problem in the context of TFNP - the complexity class of search problems with a syntactically guaranteed existence of a solution for all instances. Our main results establish that suitable variants of the discrete logarithm problem are complete for the complexity class PPP, respectively PWPP, i.e., the subclasses of TFNP capturing total search problems with a solution guaranteed by the pigeonhole principle, respectively the weak pigeonhole principle. Besides answering an open problem from the recent work of Sotiraki, Zampetakis, and Zirdelis (FOCS'18), our completeness results for PPP and PWPP have implications for the recent line of work proving conditional lower bounds for problems in TFNP under cryptographic assumptions. In particular, they highlight that any attempt at basing average-case hardness in subclasses of TFNP (other than PWPP and PPP) on the average-case hardness of the discrete logarithm problem must exploit its structural properties beyond what is necessary for constructions of collision-resistant hash functions. Additionally, our reductions provide new structural insights into the class PWPP by establishing two new PWPP-complete problems. First, the problem DOVE, a relaxation of the PPP-complete problem PIGEON. DOVE is the first PWPP-complete problem not defined in terms of an explicitly shrinking function. Second, the problem CLAW, a total search problem capturing the computational complexity of breaking claw-free permutations. In the context of TFNP, the PWPP-completeness of CLAW matches the known intrinsic relationship between collision-resistant hash functions and claw-free permutations established in the cryptographic literature.
MAJORITY-3SAT (and Related Problems) in Polynomial Time

Majority-SAT is the problem of determining whether an input $n$-variable formula in conjunctive normal form (CNF) has at least $2^{n-1}$ satisfying assignments. Majority-SAT and related problems have been studied extensively in various AI communities interested in the complexity of probabilistic planning and inference. Although Majority-SAT has been known to be PP-complete for over 40 years, the complexity of a natural variant has remained open: Majority-$k$SAT, where the input CNF formula is restricted to have clause width at most $k$. We prove that for every $k$, Majority-$k$SAT is in P. In fact, for any positive integer $k$ and rational $\rho \in (0,1)$ with bounded denominator, we give an algorithm that can determine whether a given $k$-CNF has at least $\rho \cdot 2^n$ satisfying assignments, in deterministic linear time (whereas the previous best-known algorithm ran in exponential time). Our algorithms have interesting positive implications for counting complexity and the complexity of inference, significantly reducing the known complexities of related problems such as E-MAJ-$k$SAT and MAJ-MAJ-$k$SAT. At the heart of our approach is an efficient method for solving threshold counting problems by extracting sunflowers found in the corresponding set system of a $k$-CNF. We also show that the tractability of Majority-$k$SAT is somewhat fragile. For the closely related GtMajority-SAT problem (where we ask whether a given formula has greater than $2^{n-1}$ satisfying assignments) which is known to be PP-complete, we show that GtMajority-$k$SAT is in P for $k\le 3$, but becomes NP-complete for $k\geq 4$. These results are counterintuitive, because the ``natural'' classifications of these problems would have been PP-completeness, and because there is a stark difference in the complexity of GtMajority-$k$SAT and Majority-$k$SAT for all $k\ge 4$.
COSPEX: A Program Comprehension Tool for Novice Programmers

Developers often encounter unfamiliar code during software maintenance which consumes a significant amount of time for comprehension, especially for novice programmers. Automated techniques that analyze a source code and present key information to the developers can lead to an effective comprehension of the code. Researchers have come up with automated code summarization techniques that focus on code summarization by generating brief summaries rather than aiding its comprehension. Existing debuggers represent the execution states of the program but they do not show the complete execution at a single point. Studies have revealed that the effort required for program comprehension can be reduced if novice programmers are provided with worked examples. Hence, we propose COSPEX (Comprehension using Summarization via Program Execution) - an Atom plugin that dynamically extracts key information for every line of code executed and presents it to the developers in the form of an interactive example-like dynamic information instance. As a preliminary evaluation, we presented 14 undergraduates having Python programming experience up to 1 year with a code comprehension task in a user survey. We observed that COSPEX helped novice programmers in program comprehension and improved their understanding of the code execution. The source code and tool are available at: https://bit.ly/3utHOBM, and the demo on Youtube is available at: https://bit.ly/2Sp08xQ.
Novel energy-preserving splitting integration for Hamiltonian Monte Carlo method

Splitting schemes are numerical integrators for Hamiltonian problems that may advantageously replace the St\"ormer-Verlet method within Hamiltonian Monte Carlo (HMC) methodology. However, HMC performance is very sensitive to the step size parameter; in this paper we propose a new method in the one-parameter family of second-order of splitting procedures that uses a well-fitting parameter that nullifies the expectation of the energy error for univariate and multivariate Gaussian distributions, taken as a problem-guide for more realistic situations; we also provide a new algorithm that through an adaptive choice of the $b$ parameter and the step-size ensures high sampling performance of HMC. For similar methods introduced in recent literature, by using the proposed step size selection, the splitting integration within HMC method never rejects a sample when applied to univariate and multivariate Gaussian distributions. For more general non Gaussian target distributions the proposed approach exceeds the principal especially when the adaptive choice is used. The effectiveness of the proposed is firstly tested on some benchmarks examples taken from literature. Then, we conduct experiments by considering as target distribution, the Log-Gaussian Cox process and Bayesian Logistic Regression.
Test for non-negligible adverse shifts

Statistical tests for dataset shift are susceptible to false alarms: they are sensitive to minor differences when there is in fact adequate sample coverage and predictive performance. We propose instead a framework to detect adverse dataset shifts based on outlier scores, $\texttt{D-SOS}$ for short. $\texttt{D-SOS}$ holds that the new (test) sample is not substantively worse than the reference (training) sample, and not that the two are equal. The key idea is to reduce observations to outlier scores and compare contamination rates at varying weighted thresholds. Users can define what $\it{worse}$ means in terms of relevant notions of outlyingness, including proxies for predictive performance. Compared to tests of equal distribution, our approach is uniquely tailored to serve as a robust metric for model monitoring and data validation. We show how versatile and practical $\texttt{D-SOS}$ is on a wide range of real and simulated data.
Students’ Foreign Language Anxiety and English Reading Comprehension: A Correlational Study at Junior High School

ABSTRACTThe primary objective of this study was to examine the correlation between students’ foreign language anxiety and English reading comprehension. This study was a correlation research design. The sample was Junior High School students at the ninth grade of Junior High School 04 Dayun. Due to the small number of population in this study, which was 39 students, total sampling was taken. The study used a questionnaire to assess students’ foreign language anxiety and a test to find out students’ reading comprehension in collecting the data. To examine the relationship between two variables, this study employed the Pearson Product-Moment Correlation coefficient through SPSS 23.0. From the analysis, the result indicated that sig. (2-tailed) value was 0.001. It showed that Ho is rejected and Ha is accepted. The correlation coefficient (r) value was -0.762. It reveals that there is significant correlation between students’ foreign language anxiety and reading comprehension. To conclude, the students’ foreign language anxiety leads to reading comprehension, which means higher foreign language anxiety results in lower comprehension in reading and vice versa.
The Use of Duolingo in Enhancing Students' Vocabulary Mastery at SMA Negeri 3 Bangko Pusako During Pandemic Covid-19

Abstract Based on the writer’s observation in teaching and learning process, the students’ frequently encounter obstacles to memorize the words, confuse the meaning of the words, and difficulty in pronunciation. To solve this problem, the writer used a media to improve the students’ mastery in vocabulary. The media was using Duolingo. The aim of this research was to find out any significant difference of students’ vocabulary mastery between students’ taught by using Duolingo and without using Duolingo at SMA Negeri 3 Bangko Pusako During Pandemic Covid-19. This research was a quantitative research by an quasi-experimental design. In this research, there were two classes as a sample, that classes were an experimental class and control class. The population of this research were tenth grade of SMA Negeri 3 Bangko Pusako was 156 students’ which were 30 students as sample of this study using purposive sampling technique. The result of the research showed that the students’ on vocabulary mastery in experimental class was very good category and in control class was good category. On the independents sample T-test, the significant value was 0.000 lower than alpha 0.05, which meant the alternative hypothesis (Ha) was accepted while null hypothesis (HO) was rejected. It means that, there was any significant difference of students’ vocabulary mastery between students’ taught by using Duolingo and without using Duolingo at SMA Negeri 3 Bangko Pusako. Keywords: Vocabulary Mastery, Duolingo, Covid-19
The Anxiety Level between Extrovert and Introvert Students in Speaking English

Students’ performance in speaking English can be influenced by students’ anxiety. This research aimed to find out the difference of anxiety level between extrovert and introvert students in speaking performance. This research was conducted at one of senior high schools in Pekanbaru, Riau Province, Indonesia by using cluster random sampling technique. The method of the research was not experimental but causal-comparative research. There were two types of questionnaires used to collect the data. The Eysenck Personality Inventory questionnaire was used to classify the extrovert and introvert students, while to find out the speaking anxiety level between extrovert and introvert students, the questionnaire of Foreign Language Classroom Anxiety Scale (FLCAS was used.. By using product moment formula through SPSS 2.4 in analyzing the data, it was found that the sig.t was 0,000, smaller than the sigma alpha of 0,05 (sig.t &lt;0,05). It means that there is a significant difference of speaking anxiety level between extrovert and introvert students. The percentage score of anxiety level in speaking performance of extrovert students was 106%%. It was categorized as "Low" level. The percentage score of anxiety level in speaking performance of introvert students was 122%. It was categorized as "Medium" level.
Current and Emerging Laboratory Techniques for Malaria Diagnosis

Effective diagnostic methods must continue to be developed due to the effects of malaria on world health. Malaria is an infectious disease spread by mosquitoes that affects both people and other animals. It is the product of Plasmodium parasites, which are transmitted through bites from infected female Anopheles mosquitoes. Other sporozoan species responsible for malaria infections include the sporozoan parasites Plasmodium falciparum, Plasmodium ovale, Plasmodium vivax, Plasmodium malaria, and Plasmodium knowlesi. Routine diagnosis of malaria is impeded in areas where the disease is endemic by technical and infrastructure issues with laboratories. Prompt and accurate diagnosis is essential since good disease management is one of the primary actions of the Global Malaria Control Strategy. Accurate malaria detection is also crucial in order to inform malaria control efforts through epidemiologic screening and surveillance, for research reasons to evaluate the effectiveness of antimalarial medications and vaccines, and for blood bank screening. This study's main goal is to show some of the new and effective ways to diagnose malaria that go beyond the gold standard, light microscopy, which has some problems.
EFL Lecturers’ and Students' Perception towards Online Learning in Riau context: Using Technology Acceptance Model (TAM) as the Organizing Framework

Online learning in the pandemic has been conducted with less preparation by both the teachers and the students. Whether or not it has been effective, little is known. The research aims to conduct research on EFL lecturers’and students’ perception toward online learning from the perspective of technology acceptance model by Davis et al. (1989). The design of the reserch is descriptive quantitative. There were 14 EFL lecturers and 121 EFL students recruited in the study. Data collection method was a questionnaire with a 5-Likert scale. Data analysis was descriptive statistics. The findings reveal that the lecturers’perceived usefulness and the perceived ease-of-use fall on high category (respectively, 72,95% and 71,1%) and the students’ lecturers’perceived usefulness and the perceived ease-of-use fall on high category (respectively, 79.10% and 72.50%). Out of all items, the lecturers mostly appreciated the flexibility of online learning in term of time and place (82.86%); and the students mostly appreciated the online learning’s opportunity to study English ((77,19%). Some suggestions are given to future researchers, namely (1) the next researcher can recruit more participants, (2) the next researcher can use different instruments to collect the data, like observation, interview and tests. Keywords: online learning, perceived usefulness, perceived ease-of-use, face-to-face.
Investigating Students’ Reading Habit in Learning English at Islamic Boarding Senior High School Babussalam Pekanbaru

Reading habit refers to the behavior which expresses the likeness of reading of individual types of reading and tastes of reading (Sangkaeo 1999) cited in Chettri and Rout (2011). However, the students at the Eleventh Grade Students of Islamic Boarding Senior High School in Pekanbaru were not always go to the library to read books or may borrow books, but sometimes they go. This research wanted to describe the students’ reading habit. The design of this research is descriptive quantitative research. The population of the research was the eleventh grade of Islamic Boarding Senior High School in Pekanbaru and the sample were 26 students. The number of sample is selected by using simple random sampling technique. To get the data, the writer employed a close-ended questionnaire. The result showed that majority students at the eleventh grade of Islamic Boarding Senior High School in Pekanbaru had a good reading habit. Meanwhile, some of them showed that they have fair reading habit and of them don’t have good reading habit it is categorized as poor. It can be concluded that the students at the eleventh grade of Islamic Boarding Senior High School in Pekanbaru had various reading habit.
RETELLING STORY THROUGH PICTURE SERIES TO IMPROVE STUDENTS' SPEAKING SKILL AT ASSALAM ISLAMIC JUNIOR HIGH SCHOOL NAGA BERALIH AIR TIRIS KAMPAR REGENCY

A spoken language is important to human life, if we would like to have a good speaking, we should have a good speaking skill. However, after observing and conducting inerview an English teacher at MTs Assalam Naga Beralih. In general, students have difficulty at retelling story through picture series, especially in speaking skill such as pronounciation, vocabulary, grammar, fluency and comprehension. The purpose of this study was to determine the significant improvement in students' speaking skills through retelling story using a series of pictures. This research used quantitative research. One Group Pre-Test Post-Test method used in this research. This research was held on October until November 2021 at MTs Assalam Naga Beralih Air Tiris Kampar Regency. The sample consisted of 25 students. Thus, speaking test was used to gather the data. The results showed that the average score of students after being taught to retell stories using a series of pictures (81.20) was higher than before being taught to retell stories using a series of pictures (63.90). Keywords: Retelling Story, Picture Series, Speaking Skills.
THE EFFECT OF USING SELF-EXPLANATION READING TRAINING (SERT) STRATEGY ON STUDENTS’ READING COMPREHENSION

The aim of this study was to analyze the effect of using self-explanation reading training (sert) strategy on students’ reading comprehension. This research applied a Quasi-experimental research. There were 44 students as sample from 153 students of eleventh grade at MA Darul Hikmah Pekanbaru by using cluster random sampling technique. This researcher used multiple choice test. T-test was used to analyze the data. This research used an independent t-test formula by using SPSS 16 version. Based on the analysis of T-test Formula, Ha is accepted because the sig. value is 0.000&lt;0.05. The research was conclude that there is significant difference of using Self-Explanation Reading Training (SERT) Strategy on reading comprehension in report text of the eleventh grade students at MA Darul Hikmah Pekanbaru.
Modifikasi Tanda Tangan Digital Pada Skema Esign Berbasis Kurva Eliptik

Digital signature has an important role in the digital era, where more and more people are joining the paperless life. Many cryptographic researchers support digital development by creating cryptographic schemes that are safe to use, and one of them is digital signature. This paper proposes a digital signature scheme based on an elliptic curve defined over with , where and are private keys of prime number elements. This scheme utilizes the advantages of elliptic curve cryptography in terms of security by using points that satisfy the elliptic curve equation. Additionally, the shorter key size increases the speed, making this scheme faster in signature values generation and verification process.This research was conducted to determine the differences between the modified ESIGN scheme based on elliptic curve and the original ESIGN scheme. The process of finding the point on the ring , with a large , resulted in a more complex key generation algorithm. However, the selection of two points in this key generation is precomputed. This means the actual signature value generation algorithm took significantly less time than the original. This is one of the advantages of the proposed scheme.
Analisis Kualitas Website E-Learning Universitas dengan Metode WebQual 4.0 dan Importance Performance Analysis

E-learning services are currently needed to support learning activities. Since the coronavirus pandemic, the existence of e-learning is very important for online learning activities. This e-learning service is to facilitate for college who must be learned from home. This makes e-learning need to be measured its effectiveness. The purpose of this research is to analyze the quality of the e-learning website at University using the WebQual 4.0 and the Importance Performance Analysis to find out the gaps and what parts should be prioritized for improvement for better e-learning quality. The variables used are usability, information quality, and service interaction quality. The results of this research are based on the achievement value, the quality of usability variable is 80% (very good), information quality is 80% (very good) and service interaction is 79% (good). Gap analysis produces an overall gap value of (- 0.30) which means that the quality of e-learning is not in accordance with user expectations. From quadrant analysis, it is found that the indicators regarding interaction with the website are obvious and easy to understand, the website appearance is attractive, and security of user's private information is included in quadrant I, which means that these indicators are the first priority for improvement of the e-learning website of University.
The Application of the Blowfish Algorithm and the Least Significant Bit Method for Securing Student Transcripts

Academic transcripts are a summary of a student's high-value achievement score and must be guaranteed in their authenticity, as well as the source from which they are issued. It was found that some universities were using technology to falsify transcripts. An example of a university in yogyakarta's special region that falsified academic transcripts. Several diplomas from makassar have been forged so that a civil servant can pass his exam, whereas in banda aceh evidence of equipment for creating fake diplomas has been found. This study seeks to prevent transcripts from being modified or falsified by locking data into student photos using blowfish and least significant bit algorithms. The purpose of this study is to keep transcripts from being easily modified or falsified. The methods of this study are data collection (student code data, gpa value, photo), encryption with blowfish, conversion of encryption results into binary form, insertion of binary values into the least significant bit method into photos, capture of encryption values from least significant bit photos, and returning messages encrypted with blowfish. In this study, the results show that this system was able to secure data and enter information into student photos with an accuracy of 100% after testing on 60 transcript value data. We can conclude that the application of blowfish and least significant bit algorithms to secure data and enter data into student photos is extremely effective in transkrip value.