Reviewerly/exHarmony huggingface dataset:
Penggunaan Media BIP Video Call pada Kelas Speaking

Based on the results of research in November 2021 concerning the use of BIP video call media in the Speaking for everyday communication course, researchers found their abilities were at the poor level. As a continuation of this research, researchers have used BIP Video Calls to improve students' Speaking skills in the Speaking for Social Media course in the form of dedication. This activity has been carried out for half a semester using several procedures; Planning, Action, Observation, and Reflection. Students who have been involved in this community service activity are Semester II students of English Education FADIKSI UNILAK who are taught in the Speaking course, especially Speaking for Social Media. In this activity there are two types of data that have been obtained; quantitative and qualitative data. Qualitative data were obtained using interview instruments. Meanwhile, quantitative data was obtained through a test instrument, namely the speaking ability test. The results that have been obtained from this study are that there is an increase in their average speaking score from 52 to 53.2. still poor category. There are two factors that influence the change in the average value; firstly the sound quality produced by BIP Vidio Call is clearer and secondly the video produces clearer visualizations. In conclusion, the use of BIP Vidio Call in the Speaking course which has been carried out in the form of research and community service has the same result, namely that it can help students expedite their communication process.
Pedagogies innovations for Sustainable development: educational intervention based on the natural and cultural heritage topics in the English language class.

This article aims to contribute to the innovations of pedagogies for sustainable development since English language class. This research adscript to the postmodern paradigm and the mixed approach of the socio-educational research. The research team designed an educational intervention that combines topics related to natural and cultural Ecuadorian heritage with flipped classrooms and Content and Language Integrated Learning methodologies. The participants are 23 people; 9 instructors and 14 students between 12 and 48 years old. The research instruments were: the Likert scale questionnaire, created by the University of San Pedro in Peru, to assess students' motivations for practicing the English language; a knowledge rubric to evaluate students' listening skills, and focus groups on collecting participants' opinions about the educational intervention introduced in this research process. The results show significant changes in the student's motivation for practicing the English language but not in listening skills. It concluded that there were no correlations between the factors students' motivation for practicing the English language and listening skills when the educational intervention uses natural and cultural topics.
Computing NP-hard Repetitiveness Measures via MAX-SAT

Repetitiveness measures reveal profound characteristics of datasets, and give rise to compressed data structures and algorithms working in compressed space. Alas, the computation of some of these measures is NP-hard, and straight-forward computation is infeasible for datasets of even small sizes. Three such measures are the smallest size of a string attractor, the smallest size of a bidirectional macro scheme, and the smallest size of a straight-line program. While a vast variety of implementations for heuristically computing approximations exist, exact computation of these measures has received little to no attention. In this paper, we present MAX-SAT formulations that provide the first non-trivial implementations for exact computation of smallest string attractors, smallest bidirectional macro schemes, and smallest straight-line programs. Computational experiments show that our implementations work for texts of length up to a few hundred for straight-line programs and bidirectional macro schemes, and texts even over a million for string attractors.
Securing Optimized Code Against Power Side Channels

Side-channel attacks impose a serious threat to cryptographic algorithms, including widely employed ones, such as AES and RSA. These attacks take advantage of the algorithm implementation in hardware or software to extract secret information via side channels. Software masking is a mitigation approach against power side-channel attacks aiming at hiding the secret-revealing dependencies from the power footprint of a vulnerable implementation. However, this type of software mitigation often depends on general-purpose compilers, which do not preserve non-functional properties. Moreover, microarchitectural features, such as the memory bus and register reuse, may also leak secret information. These abstractions are not visible at the high-level implementation of the program. Instead, they are decided at compile time. To remedy these problems, security engineers often sacrifice code efficiency by turning off compiler optimization and/or performing local, post-compilation transformations. This paper proposes Secure by Construction Code Generation (SecCG), a constraint-based compiler approach that generates optimized yet secure against power side channels code. SecCG controls the quality of the mitigated program by efficiently searching the best possible low-level implementation according to a processor cost model. In our experiments with twelve masked cryptographic functions up to 100 lines of code on Mips32 and ARM Thumb, SecCG speeds up the generated code from 75% to 8 times compared to non-optimized secure code with an overhead of up to 7% compared to non-secure optimized code at the expense of a high compilation cost. In summary, this paper proposes a formal model to generate power side channel free low-level code.
Investigation of $(g-2)_μ$ anomaly in the $μ$-specific 2HDM with Vector like leptons and the phenomenological implications

The anomalous magnetic moment of muons has been a long-standing problem in SM. The current deviation of experimental value of the $(g-2)_μ$ from the standard model prediction is exactly $4.2σ$. Two Higgs Doublet Models can accommodate this discrepancy but such type of model naturally generate flavor changing neutral current(FCNC). To prevent this it was postulated that 2HDM without FCNC required that all fermions of a given charge couple to the same Higgs boson but the rule breaks in Muon Specific Two Higgs Doublet Model where all fermions except muon couple to one Higgs doublet and muon with the other Higgs doublet. The Muon Specific Two Higgs Doublet model explain muon anomaly with a fine tuning problem of very large $\tanβ$ value with other parameters. We have found a simple solution of this fine tuning problem by extending this model with a vector like lepton generation which could explain the muon anomaly at low $\tanβ$ value with a heavy pseudo scalar Higgs boson under the shadow of current experimental and theoretical constraints. Moreover, with the help of the cut based analysis and multivariate analysis methods, we have also attempted to shed some light on the potential experimental signature of vector lepton decay to the heavy Higgs boson in the LHC experiment. We have showed that a multivariate analysis can increase the vector like leptons signal significance by up to an order of magnitude than that of a cut based analysis.
A Literature Review on How the Mind Map Method Helps Students Remember School Lessons

Students' ability to receive information is low, and they have a boring learning experience.The best effort that can be made is to use appropriate learning strategies.A mind map is a fun strategy.Thinking activities involving both the right and left brain, as well as writing skills, are thought to be effective in improving students' ability to remember lessons.The mind map method can increase student activity and participation in learning in elementary social studies material.It is effective to develop students' verbal-linguistic intelligence and visual-spatial intelligence using the mind map method.Furthermore, mind maps are used in problem-solving methods to make learning more interesting and enjoyable.Mind maps, in addition to being a learning tool, can also be used as an evaluation tool.The mind map method also increased students' attention and motivation to learn Islamic History subjects.The results of the observations show that using mind mapping can improve students' reading comprehension of descriptive texts.Other studies, in addition to history and language materials, demonstrate the success of the mind map method in precise lessons in high school and science in elementary school.
Evaluation of Stress State and Fracture Strain of High-Strength Steel Using Stereo Image Correction

A method for evaluating the stress state and fracture strain of the thin sheet of high-strength steel is studied in this chapter. Displacements and strains on the surface of high-strength steel plates are measured using stereo image correlation (DIC). The stress–strain relation after the necking is obtained from the load and strains by inverse problem analysis using the virtual field method. The stresses obtained by the proposed method are well balanced with the external forces.
Innovative Work Behaviour in Bureaucratic Organizations: The Effect of Leadership and Self Efficacy in the Ministry of Home Affairs

This study aims to determine whether there is an influence of leadership and self-efficacy towards innovative work behaviour in the Ministry of Home Affairs.The sample of this research is 183 State Civil Apparatus who work in the Ministry of Home Affairs.This study uses three measuring tools, namely the Individual Innovative Behaviour scale by Kleysen & Street to measure the implementation of new ideas in the workplace, the global transformational leadership scale (GTL) scale by Podsakoff, MacKenzie, Moorman, and Fetter to measure leadership patterns that motivate subordinates to do things beyond what they have planned and the Indonesian adaptation of the general self-efficacy scale developed by Born, Schwarzer, & Jerusalem to measure the individual's belief that they able to control the situation.The data analysis used was parametric statistics with multiple linear regression test.The results of the data analysis of this study indicate that leadership and self-efficacy have a significant effect towards innovative work behaviour (R 2 = 0.637, Sig.= 0.000).In other words, the influence of the variation of the independent variable (leadership variable and self-efficacy variable) is able to explain 63.7% variation of dependent variable (innovative work behaviour) in the Ministry of Home Affairs.Based on the research findings, the authors recommend State Civil Apparatus to continuously develop innovative ideas on an ongoing basis while still referring to the plans that have been prepared to manage the situation that occurs and are also supported by leadership figures who have an innovative spirit to facilitate the creative ideas of their subordinates.
The Effect of Snakes and Ladders Game on Adolescent Knowledge Levels about Leucorrhoea for Class VIII atSMP Negeri 1 Sukoharjo Pringsewu Lampung

Leucorrhoea is one of Women's Reproductive Health.The problem of Leucorrhoea occurs in adolescents, and it needs more attention.If Leucorrhoea during adolescence is left unchecked, it will cause serious illness.Some women in Indonesia do not know about Leucorrhoea, and they think Leucorrhoea is a common and trivial thing.To determine the snakes and ladders game effect on Leucorrhoea knowledge of the second-years students in SMP Negeri 1 Sukoharjo Pringsewu Lampung.This study was a quasi-experimental design using a pre-post-test with a control group.The sampling technique was carried out using random sampling and obtained 64 respondents.Data were collected through questionnaires.The intervention group's level of knowledge after playing the snake and ladder game treatment increased with a mean of 13.19, median of 13, and SD of 1.38.In contrast, the intervention group in the post-test phase had a mean of 14.63, median of 15, and SD of 1.93.The control group had a mean of 15.03, median of 15, SD of 2.26.At the same time, the control group had a mean of 15.47, median of 15, SD of 2.15.There was an effect of the snake and ladder game on the level of adolescents' knowledge about Leucorrhoea in second years at SMP Negeri 1 Sukoharjo Pringsewu Lampung in the intervention class.The results of this study can be a reference of new teaching methods for adolescents to improve health education.
Movie Lens: Discovering and Characterizing Editing Patterns in the Analysis of Short Movie Sequences

Video is the most widely used media format. Automating the editing process would impact many areas, from the film industry to social media content. The editing process defines the structure of a video. In this paper, we present a new method to analyze and characterize the structure of 30-second videos. Specifically, we study the video structure in terms of sequences of shots. We investigate what type of relation there is between what is shown in the video and the sequence of shots used to represent it and if it is possible to define editing classes. To this aim, labeled data are needed, but unfortunately they are not available. Hence, it is necessary to develop new data-driven methodologies to address this issue. In this paper we present Movie Lens, a data driven approach to discover and characterize editing patterns in the analysis of short movie sequences. Its approach relies on the exploitation of the Levenshtein distance, the K-Means algorithm, and a Multilayer Perceptron (MLP). Through the Levenshtein distance and the K-Means algorithm we indirectly label 30 s long movie shot sequences. Then, we train a Multilayer Perceptron to assess the validity of our approach. Additionally the MLP helps domain experts to assess the semantic concepts encapsulated by the identified clusters. We have taken out data from the Cinescale dataset. We have gathered 23 887 shot sequences from 120 different movies. Each sequence is 30 s long. The performance of Movie Lens in terms of accuracy varies (93% - 77%) in relation to the number of classes considered (4-32). We also present a preliminary characterization concerning the identified classes and their relative editing patterns in 16 classes scenario, reaching an overall accuracy of 81%.
Aspect Oriented Web Service Composition Based Petri Net Model

The concept of aspect-oriented programming is an emerging programming paradigm that stretches across different development phases in different domains. Many researchers have focused on the use of this paradigm in web service composition in different research axes. However, none of them combine aspect-oriented programming and the design by contract to deal with the adaptation of the parameters in the web service composition process based on the Petri net graph technique as a formal method. This paper proposes a web service composition algorithm based on the Petri net graph that incorporates both Aspect-oriented programming and the design by contract concept. Aspect-oriented programming provides explicit support for the separation of cross-cutting concerns in web service composition, and the design by contract approach allows parameters to be executed in pre-condition and post-condition mode by using contracts in order to ensure correct service execution and adaptation to external parameters without affecting properties that can be dealt with through re-construction of web services composition.
Online Learning: The Widespread Use of Google Forms as a Learning Media for Students in the Midst of the Covid-19 Pandemic

The purpose of this study was to determine the use of google form media and its effect on the effectiveness of online fiqh learning at MTs Al-Hidayah during the Covid-19 pandemic. The research uses a quantitative approach with a correlational design. Data collection techniques by distributing questionnaires (questionnaires) Variable X and Y to class VIII MTs Al-Hidayah as many as 68 samples. Based on the results of data analysis, it was concluded that first, the use of google form media was considered good with an average score of 80.66%. Second, the effectiveness of online learning is considered good with an average score of 80.27. Third, there is a significant effect between the use of google form media and the effectiveness of online learning with a correlation value of 0.823 which can be categorized as a very strong correlation. The determination value of 0.673 means that the influence of the X variable with the Y variable is 67.3% and the remaining 32.7% is influenced by other factors besides the use of google form media. With the regression equation Y = 14.056 + 0.771X, it means that if there is an increase in the X variable, it will also affect the Y variable.
Risk Assessment Study of Domestic Wastewater Pollution in Kolaka Utara Regency: Geographic Information System Approach

Background: The community in North Kolaka Regency already has an open system of household waste water disposal, but there are still many found in a damaged, cracked and even perforated condition. In addition, there are also those who make the channel not watertight by digging the soil in the form of a ditch. They also still use a stool that is not tight on one side. The purpose of this study was to determine the risk index of domestic wastewater pollution. Method: This type of research is quantitative research with geographic information systems approach. Data was collected by survey method using questionnaires and observation sheets. The sample in this study was 5,320. Data analysis using equal interval on Quantum GIS application version 3.26.0. Result: In the parameters of the safe suspect tank, most of the 5,320 respondents (99%) have an unsafe suspect septic tank, while 1% have a safe suspect tank. For the parameters of pollution due to the disposal of the contents of the septic tank, most of the 5,320 respondents (99.8%) are not safe against contamination of the contents of the septic tank, while 0.2% is classified as safe. And for the parameters of pollution due to waste water discharge channels from 5,320 respondents, most (73%) are classified as unsafe and the remaining 27% are classified as safe. Conclusion: North Kolaka Regency 4 Districts with a risk index value are included in the moderate risk category, namely Tolala, Porehu, Central Pakue, and North Pakue Districts. 6 Districts are included in the high risk category, namely Batu Putih, Ngapa, Tiwu, Lasusua, Ranteangin, and Wawo Districts. While the other 5 sub-districts are in the very high category, namely Pakue, Watunohu, Kodeoha, Katoi, and Lambai sub-districts.
The Effectiveness of Teacher Autonomy Supportive Style on Enhancing Student Engagement in EFL Virtual Classrooms

Promoting students&amp;rsquo; engagement in classrooms is among the most significant challenges faced by teachers in virtual classrooms. Prior research has investigated the effectiveness of using teacher autonomy supportive style (TASS) during in-person classes (Jang et al., 2010; Li et al., 2020; N&amp;uacute;&amp;ntilde;ez &amp;amp; Le&amp;oacute;n, 2019; Reeve et al., 2004). However, limited research has been conducted in virtual classrooms (Bedenlier et al., 2020; Chen &amp;amp; Jang, 2010; Chiu &amp;amp; Hew, 2018). Ryan and Deci (2020), suggested that further research should focus on student engagement within virtual classrooms. Moreover, although EFL teachers often struggle to engage their students (Susanti, 2020), the majority of the related studies have been carried out in various learning contexts (Jang et al., 2010; Li et al., 2020; Shih, 2008). Most of this limited body of literature in the EFL context is composed primarily of quantitative research collected through cross-sectional study designs. Evidence suggests that this gap can be addressed by conducting well-designed qualitative studies investigating student engagement (Fredricks et al., 2016; Harris, 2011; Zyngier, 2008). Thus, there is an urgent need for research that tackles these gaps effectively.
Online multiple object tracker with enhanced features

The online multiobject tracking (MOT), which integrates object detection and tracking into a single network, has made breakthroughs in recent years. However, most online trackers have a more monotonous prediction of the tracking offset in two consecutive frames, which may not be reliable when facing extreme situations such as occlusion and object deformation. Once the tracking offset of an object is biased, its corresponding tracklet will no longer maintain temporal consistency, which will seriously affect the tracking performance. In this paper, we propose a new online multiple object tracker with feature enhancement mechanism, namely En-Tracker. In En-Tracker, a multibranch kinematic analysis network (MKANet) is designed to address the above problems. MKANet estimates the pixel offset and instance offset of the object in parallel based on imitating the human thinking to joint position and appearance representations. Note that these two types of offsets compensate and facilitate each other to effectively deal with some extreme scenarios. In addition, we propose a kinematic-assisted feature synthesis enhancement (KFSE) module, which has a more comprehensive enhancement mechanism. Specifically, KFSE propagates previous tracking information to the current frame based on kinematic trend analysis while enhancing the characterization of detection features and appearance embeddings, which not only assists in object detection but also ensures the uniqueness of the appearance embeddings. Extensive experiments on MOT16 and MOT17 verify the effectiveness and advantage of our model.
Research and Practice on the Construction of Business English Major in Higher Vocational Colleges

This paper summarizes the necessity of the construction of business English major in higher vocational colleges, the demand for professional talents, typical jobs and the overall goal of the construction. Taking Chongqing Vocational Institute of Tourism as an example, this paper expounds the specific measures and steps of personnel training program, professional curriculum system construction, teachers construction, training base construction inside and outside the school, and teaching material construction, so as to effectively guarantee the quality of personnel training.
Research on Detecting Credit Card Fraud Through Machine Learning Methods

The heavy use of credit cards inevitably leads to the escalation of fraud technology and a surge in fraudulent behavior.Machine learning, a multi-interdisciplinary discipline with numerous algorithms, can effectively detect and prevent financial fraud.This study focuses on several common machine learning methods applied to fraud detection and then evaluates how they perform on real data, including Bagging, Random Forest, Decision Tree, and AdaBoost.However, the proportion of fraudulent transactions in real transaction data is extremely unbalanced.SMOTE can determine the data imbalance problem, while confusion matrices visualize the classification results of different classes.The experiment results reveal that Random Forest performs best for both unbalanced and balanced data.It indicates that random forest is better for detecting fraudulent transactions.