Reviewerly/exHarmony huggingface dataset:
APPLICATION OF A GENRE-BASED APPROACH WITH AUDIO VISUAL AID TO IMPROVE THE WRITING ABILITY OF CLASS 11 STUDENTS OF SERDANG BEDAGAI MADRASAH ALIYAH

The purpose of this study was to determine the effectiveness of applying GBA with Audio Visual Media in Teaching Listening to improve writing skills in grade 11 students at MANSB. The research subjects were all students of class XI MANSB. The procedure for this research includes: Preparing the GBA learning model; Determination of the treatment class/group, namely the control group and the experimental group, conducting pre-tests, conducting teaching and learning activities (KBM) in the experimental class and control class with the GBA learning model, Conducting Post-tests, and Analysing data. The learning outcomes in the experimental class (Pre-Test) were 36 students, 60.00.and in the control class (Pre-Test) of 35 students, most students (13 students or 37%) got scores in the range50.01 - 60.00. The learning outcomes in the experimental class (Post-Test) were 36 students, the majority (8 students or 22%) got the core in the82.51 - 88.33.and in the control class (Post-Test) of 35 students, most of the students (12 students or 34%) got scores in the62.51 - 70.00.
Foreground Guidance and Multi-Layer Feature Fusion for Unsupervised Object Discovery with Transformers

Unsupervised object discovery (UOD) has recently shown encouraging progress with the adoption of pre-trained Transformer features. However, current methods based on Transformers mainly focus on designing the localization head (e.g., seed selection-expansion and normalized cut) and overlook the importance of improving Transformer features. In this work, we handle UOD task from the perspective of feature enhancement and propose FOReground guidance and MUlti-LAyer feature fusion for unsupervised object discovery, dubbed FORMULA. Firstly, we present a foreground guidance strategy with an off-the-shelf UOD detector to highlight the foreground regions on the feature maps and then refine object locations in an iterative fashion. Moreover, to solve the scale variation issues in object detection, we design a multi-layer feature fusion module that aggregates features responding to objects at different scales. The experiments on VOC07, VOC12, and COCO 20k show that the proposed FORMULA achieves new state-of-the-art results on unsupervised object discovery. The code will be released at https://github.com/VDIGPKU/FORMULA.
Motion Aware Self-Supervision for Generic Event Boundary Detection

The task of Generic Event Boundary Detection (GEBD) aims to detect moments in videos that are naturally perceived by humans as generic and taxonomy-free event boundaries. Modeling the dynamically evolving temporal and spatial changes in a video makes GEBD a difficult problem to solve. Existing approaches involve very complex and sophisticated pipelines in terms of architectural design choices, hence creating a need for more straightforward and simplified approaches. In this work, we address this issue by revisiting a simple and effective self-supervised method and augment it with a differentiable motion feature learning module to tackle the spatial and temporal diversities in the GEBD task. We perform extensive experiments on the challenging Kinetics-GEBD and TAPOS datasets to demonstrate the efficacy of the proposed approach compared to the other self-supervised state-of-the-art methods. We also show that this simple self-supervised approach learns motion features without any explicit motion-specific pretext task. Our results can be reproduced on $github$.
MODEL REGRESSION COX PROPORTIONAL HAZARD WITH BAYESIAN METHOD FOR SURVIVAL ANALYSIS OF COVID-19 PATIENT CASES AT RSUD Dr. PIRNGADI KOTA MEDAN

&lt;p&gt;Survival analysis is a statistical procedure for analyzing data by observing the response variable in the form of event time data from the beginning of recording to the end of the event. Survival analysis is used in many fields of medicine. The cox proportional hazard model aims to look at the factors of the recovery rate on patient survival. In this study using Bayesian data with Lognormal distribution in Covid-19 patients at Dr. Pirngadi, Medan City. The predictor variables are Age, gender, employment status, and other diagnose. Based on the research, the cox proportional hazard model was obtained with the influential variables based on the credible interval it is known that the age and genderare significant variables. Among the two variables that have the most influence is the age because it obtains a larger coefficient, namely&lt;/p&gt;
Pushing the Efficiency Limit Using Structured Sparse Convolutions

Weight pruning is among the most popular approaches for compressing deep convolutional neural networks. Recent work suggests that in a randomly initialized deep neural network, there exist sparse subnetworks that achieve performance comparable to the original network. Unfortunately, finding these subnetworks involves iterative stages of training and pruning, which can be computationally expensive. We propose Structured Sparse Convolution (SSC), that leverages the inherent structure in images to reduce the parameters in the convolutional filter. This leads to improved efficiency of convolutional architectures compared to existing methods that perform pruning at initialization. We show that SSC is a generalization of commonly used layers (depthwise, groupwise and pointwise convolution) in "efficient architectures." Extensive experiments on well-known CNN models and datasets show the effectiveness of the proposed method. Architectures based on SSC achieve state-of-the-art performance compared to baselines on CIFAR10, CIFAR-100, Tiny-ImageNet, and ImageNet classification benchmarks. Our source code is publicly available at https://github.com/vkvermaa/SSC.
A Syntactical Analysis of Sentences Written by Deaf Students at the Senior High Level of a Public Special School in Sumbawa Regency

The purpose of this study was to determine the syntactic ability and the form of syntactic errors at the writing of deaf students at the senior high school level of Public Special School (SLBN) 1 Sumbawa. Participants in this study were five students consisting of 1 of the10th grade, 3 of the 11th students, and 1 of the 12th grade. The research was qualitative, while the data were collected using written tests. For the data analysis, the researchers used the theory of Chaer about syntactic functions and devices. The results of the study show that the forms of errors in the student's writing consist of errors on the use of subjects, predicates, objects, and adverbs. Other forms of errors lie in the order of words, word forms, and use of conjunction. Another finding is that some students were able to compile sentences based on S + Adv + P, while the other students were only able to compile sentences with the S + Adj pattern. Based on these findings, it is expected that parents or teachers play a role to teach children or students how to compose sentences with a simple pattern so that children who suffer from deafness are able to convey what they want to convey.
Corporate social responsibility and financial performance – a comparative analysis of listed deposit money banks in nigeria and ghana

The goal of this research was to look into the relationship between corporate social responsibility and financial performance by doing a comparative analysis of listed Deposit Money Banks in Nigeria and Ghana from 2009 to 2018. In the study, secondary data from yearly reports, descriptive statistics, and the hausman test were used. The first objective was met by utilizing graphs to explain the trend of CSR donations in Nigeria and Ghanaian listed deposit money banks. Panel regression was used to achieve goal two. It was discovered in Nigeria and Ghana that there is a negative and significant relationship between corporate social responsibility and DMB financial performance. According to the research, listed deposit money banks should create a department to manage their companies' expenditure in connection to the allowed budget for CSR donations and the company's earnings.Furthermore, the Central Bank of Nigeria and the Bank of Ghana should limit the sums of money donated to corporate social responsibility activities by listed deposit money institutions to avoid excessive amounts being committed to CSR courses in the name of gratifying stakeholders. It also advocated that listed deposit money banks spend moderately on CSR courses to guarantee that they continue in excellent financial health and long-term viability.
THE INTRODUCTION OF DIGITAL TECHNOLOGIES IN HIGHER EDUCATION: TRENDS AND RISKS (BY THE REPUBLIC OF KAZAKHSTAN)

Б.Х.Толеубекова¹, Т.Б.Хведелидзе¹
Emotional Keyboard: To Provide Adaptive Functionalities Based on the Current User Emotion and the Context

Improving the User Experience (UX) of mobile devices is of vital importance due to the advent of emerging technologies and the prevalence of using mobile devices. This research aims to develop a model for a mobile device that can suggest adaptive functionalities, based on the current user emotion and the context by changing the user’s negative emotions (sadness and anger) into positive ones. As a proof of concept, a keyboard named “Emotional Keyboard” was developed through five prototypes iteratively using Evolutionary Prototyping. Action Research was adopted as the methodology along with User-Centered Design (UCD) which further included two user surveys. The first three prototypes were implemented to decide the most optimal perception from facial expressions and text analytics. Subsequent prototypes provided affective functions to the user such as listening to music, playing a game, chat with friends, based on the detected negative emotion and the context. The evaluation of each of the prototypes was performed iteratively with user participation. The final (fifth) prototype evaluation was done in two phases, an individual analysis (to measure the performance of each user separately), and an overall analysis (a general analysis that averaged all the results from individual analysis and measured the performance of the overall model). Results of both analyses showed that eventually the Emotional Keyboard was able to predict the adaptive functions correctly to the user and it did not terminate its learning process where the users’ feedback was continuously used to improve its performance. In conclusion, an “Adaptive System with User Control” was developed thus improving the acceptability and usability of a mobile device which aligns with the research aim.
DIFFICULTIES IN ONLINE LEARNING DURING COVID-19 PANDEMIC: PERCEPTIONS OF EFL STUDENTS OF UIN ALAUDDIN MAKASSAR

Preventing the COVID-19 spreading and transmitting widely, the educational institution has forced to make transition from conventional learning to online learning. The adaptation of online learning has presented many difficulties. Students in online learning faced difficulties that they might never encountered before in a traditional teaching and learning environment. This research investigated the difficulties in online learning during the COVID-19 pandemic according to students’ perception. The method of this research is qualitative and the instruments used were questionnaire and interview involving ten participants from the fifth semester students at EED of UIN Alauddin Makassar. The findings show that all the participants had difficulties during online learning and those difficulties affected their learning performance. There are nine areas of online learning difficulties; (1) difficulty to focus due to distractions, (2) problem with internet connectivity, (3) difficult to understand learning content, (4) lack motivation due to absence face to face contact, (5) various learning method employed by lecturers, (6) slow personal devices, (7) lack of technical skill in using online learning, (8) limited broadband data, and (9) difficult to work in group.
The meaning of zero nouns and zero verbs

We carry out a large-scale study of noun-verb zero derivation pairs in English in order to identify possible semantic contrasts between the two derivational directions: V-to-N (zero nouns) and N-to-V (zero verbs).We compile a dataset of 4,879 N-V word sense pairs from the Princeton WordNet, which are annotated for noun and verb semantic classes and are assigned a morphosemantic relation.These sense pairs are labelled with a derivational direction from the Oxford English Dictionary.This makes it possible to investigate, on the one hand, the morphosemantic relations and, on the other hand, the noun and verb semantic classes that typically associate with each direction of zero derivation with the aim of offering a better understanding of the semantics involved in this morphological process.
Scrum method assessment in Federal Universities in Brazil

Goal: Assess the Agile Methodology Scrum in a software development project at Federal universities in the Southeast Brazil. Design / Methodology / Approach: The method in this paper is multiple case studies and a qualitative approach. The data collection was performed using a questionnaire with open and closed questions based on the constructs of the literature review. Six Federal universities were selected in two states in the Southeast Region, based on previous contacts with institutions, and the analysis unit was the Information of Technology Centers or the Superintendent of Information Technology. Results: It was noticed a low level of maturity in the use of agile methods in a great part of the universities and a high turnover of the team components, due to the scholarship students who participated in the research. In the open questions, it was noticed a very strong relationship between a set of subattributes: improvement in response time, cost and time reduction, increased of equipment performance and increase in added value. In the closed questions, it was noticed that Scrum had a better performance in the following sub-attribute samples: communication, collaboration, productivity, and time reduction. Limitations of the investigation: The number of interviewers in the universities, to provide deeper analysis for the case studies. Practical implications: The subattributes can be indicators to measure the performance of Scrum in corporations. Originality/Value: While previous studies focus on the application in large companies and in classes of Graduation Programs at universities, this paper focuses on administrative operations in the universities.
Sub-Synchronous Oscillation Recognition Based on Extreme Learning Machine

In recent years, sub-synchronous oscillation (SSO) occurs frequently in wind power systems in many countries, which seriously affects the safety and stability of power systems. In order to monitor and warn sub-synchronous oscillations when they occur and avoid further escalation of accidents, it is urgent to carry out wide-area monitoring for SSO. Therefore, a sub-synchronous oscillation identification method based on Extreme Learning Machine (ELM) is proposed in this paper. Through the analysis and observation of PMU signal waveform images, this paper found that SSO can be identified from three aspects: the trend of PMU signal waveform, the fluctuation of envelope and the length of stationary subsequence. Thus, the SSO identification problem can be transformed into a Classification problem. In this paper, the classical ELM algorithm is adopted to realize the fast and accurate recognition of SSO. The proposed method is verified in detail by the synthetic signal, and compared with the Support Vector Machines (SVM) algorithm. The results show that the proposed method can effectively identify SSO even in the case of large noise. Therefore, the theoretical results are expected to provide technical support for SSO real-time warning in the future.
CNN Acceleration based on Dynamic Pruning and FPGAs Implementation

Convolutional Neural Networks (CNNs) have achieved exciting performance and are widely used in various fields such as industry, cultural heritage protection, etc. However, CNNs are computational-intensive and resource-consuming, which limits the applications, especially for embedded systems. Therefore, this paper proposes a dynamic pruning method for compacting the mainstream CNNs model. Furthermore, we implement the compacted models on FPGAs for acceleration. Experimental results show that the proposal compress at most 80% parameter and FLOPs, and 80% inference time reduction on FPGAs.
Adaptive Grey Wolf Optimizer for Global Numerical Optimization

As a well-regarded GWO variant, the improved Grey Wolf Optimizer (IGWO) is proven competitive in solving global numerical optimization problems due to its new proposed dimension learning-based hunting (DLH) search strategy. However, the high computational complexity of IGWO limits its potential application prospect. In this paper, a novel adaptive grey wolf optimizer with DLH (AGWO-D) is proposed to alleviate the heavy computational complexity of IGWO. The AGWO-D benefits from an execution probability model for each search agent to adopt the DLH search. By this mechanism, the search areas with more potential are more likely to be exploited, and thus the computational resources are used with higher efficiency. To evaluate the performance of the proposed AGWO-D algorithm, a simulation experiment is run on the CEC 2014 benchmark suite. And the experimental results show that, compared with IGWO, the AGWO-D algorithm has superior search capability with less computational time.
Non-Rigid Point Cloud Matching Based on Invariant Structure for Face Deformation

In this paper, we present a non-rigid point cloud matching method based on an invariant structure for face deformation. Our work is guided by the realistic needs of 3D face reconstruction and re-topology, which critically need support for calculating the correspondence between deformable models. Our paper makes three main contributions: First, we propose an approach to normalize the global structure features of expressive faces using texture space properties, which decreases the variation magnitude of facial landmarks. Second, we make a modification to the traditional shape context descriptor to solve the problem of regional cross-mismatch. Third, we collect a dataset with various expressions. Ablation studies and comparative experiments were conducted to investigate the performance of the above work. In face deformable cases, our method achieved 99.89% accuracy on our homemade face dataset, showing superior performance over some other popular algorithms. In this way, it can help modelers to build digital humans more easily based on the estimated correspondence of facial landmarks, saving a lot of manpower and time.
Security analysis of measurement-device-independent quantum conference key agreement with weak randomness

Quantum conference key agreement (QCKA) allows multiple users to distribute secret conference keys over long distances. Measurement-device-independent QCKA (MDI-QCKA) is an effective QCKA scheme, which closes all detection loopholes and greatly enhances QCKA’s security in practical application. However, an eavesdropper (Eve) may compromise the security of practical systems and acquire conference key information by taking advantage of the weak randomness from the imperfect quantum devices. In this article, we analyze the performance of the MDI-QCKA scheme based on the weak randomness model. Our simulation results show that even a small proportion of weak randomness may lead to a noticeable fluctuation in the conference key rate. For the case with finite-key size, we find that the weak randomness damages the performance of MDI-QCKA to different degrees according to the data size of total pulses transmitted. Furthermore, we infer that QCKA based on single-photon interference technology may perform better in resisting weak randomness vulnerabilities. Our work contributes to the practical security analysis of multiparty quantum communication and takes a further step in the development of quantum networks.
Decision Analysis, SAW, Pandemic Analisis Keputusan Perkuliahan Mahasiswa Pasca Pandemi

During the pandemic, all activities require people to work from home and reduce interactions outside in home. This situation lasted a year. The filed of education, Indonesia does not carry out lectures offline or face to face. Many students feel bored in online lectures. It is not uncommon for students complain about the many assignments from the lecture. Pandemic period is recovering. Not many universities in Indonesia hold lecture offline. There are many consideration for students and even parents to support offline lecture. The sense of anxiety that exists in the minds of students to carry out offline lectures. Based on the results of the ranking 50 respondents who werw carried out randomly, was obtained from the highest vectoe value which became altenative choice of conclusions. The results show that A5 has the highest ranking vector to others. Totally 1.71 students don’t agree to do online lecture after pandemic.
Peningkatan Minat Belajar Matematika Siswa melalui Strategi Pembelajaran Active Knowledge Sharing di Kelas VIII SMPN 03 2x11 Kayutanam Tahun Ajaran 2021/2022

This study aims to determine the increase in interest in learning mathematics for class VIII students of SMPN 03 2x11 Kayutanam through active knowledge sharing learning strategies. This type of research is pre-experimental with a one group pretest posttest research design. The population of this study were all students of class VIII SMPN 03 2x11 Kayutanam. The sampling technique was carried out by means of random sampling, and assigned class VIII A as the sample class. The instruments used in this study were pretest and posttest questionnaires for students' learning interest with an active knowledge sharing strategy. The data analysis technique used to test the hypothesis is the paired sample t test. Based on the results of the data analysis obtained from the average student pretest questionnaire results was 49.125 while the average student posttest questionnaire results were 70.667. Based on the calculation results of the paired sample t test at the significance level ???? = 0.05, the tcount = 8.749 and ttable = 1.714. Based on the results of the calculation th &gt; tt, it means rejecting H0 and accepting H1, meaning that there are differences in students' interest in learning mathematics after using the active knowledge sharing strategy in class VIII students of SMPN 03 2x11 Kayutanam. So that in this study it can be concluded that there is an increase in students' interest in learning mathematics with active knowledge sharing learning strategies in class VIII SMPN 03 2x11 Kayutanam.
Pemanfaatan Media Pembelajaran IPA terhadap Hasil Belajar Siswa Kelas V di SD Negeri 091 Palembang

This study aims to determine the influence of the use of science learning media on the learning outcomes of grade V students at SD Negeri 091 Palembang. In this study, it uses the experimental research method "To experiment is to try, to look for, to confirm". The population in this study was grade V students of SD Negeri 091 Palembang with a total population of 48 students and the number of samples used was 25 students. The data collection techniques used in this study were tests and documentation. This study concluded that the work hypothesis (Ha) in this study was accepted, and there was an increase in learning outcomes of grade V students. those using image media further enhance significant learning outcomes. Proven in the t test analysis, the calculation results were obtained, namely (3.8088 &gt; 1.679). This proves that there is a significant influence on the use of learning media on the learning outcomes of grade V students of SD Negeri 091 Palembang.