Reviewerly/exHarmony huggingface dataset:
Pengaruh Wabah Penyakit Covid-19 Terhadap Minat Belajar Siswa Kelas X MAN 1 Langkat

The type of research used is quantitative research with a correlational approach. The population studied were all class X MAN 1 Langkat. The samples studied were two classes totaling 72 students. Data collection techniques using a questionnaire. The technique used to analyze the data is correlation test and simple linear regression test. The results of the study show that the trend of the covid-19 disease outbreak in some (61.1%) is high, and (38.9%) is in the medium category. So it can be concluded that the covid-19 disease outbreak variable is in the high category (61.1%). And the tendency of students' interest in learning in some (66.7%) is high, and (33.3%) is in the medium category. So it can be concluded that the variable of student interest in learning is in the high category (66.7%). The results of the simple linear regression test show that the correlation coefficient rxy is positive (0.213). From the t-test, the results of the t-count calculation are 1.971 with t-table (db = 70 ) which is 1.9944 with a significant level of 5%. So tcount &lt; ttable then Ha is rejected and H0 is accepted. In other words, reject the alternative hypothesis (Ha) and accept the null hypothesis (H0) for testing both variables. So it can be concluded that the variable X has no effect on the variable Y.
The Ising model as a discovery tool in cognitive sciences

In this contribution we will explore how the Ising model can connect different physical phenomena with the cognitive sciences.
Industrial Sector and Development of Iraqi Economy by Kaldor's Approach For Years (2017-2030)

The study aims to clarify the impact of growth in the industrial sector on economic growth in the Iraqi economics according to the methodology of Kaldor for (2017-2030) , taking into consideration the effect of the accumulation of capital in the calculation of growth rates in the economy through productivity estimate of Total Factor Productivity (TFP) to growth in the economy, which is why the study assumes a formula to comply with the laws of Kaldor growth models developed requirements. This study is the most important to find out the development of the laws of Kaldor among Arabic studies, especially the first and third, so that the relationship between the growth of industrial production and economic growth as represented by the overall productivity of factors of production , while employment relationship is in the non-manufacturing sector with total production of inputs (TFI).&#x0D; The study has concluded from the developed formulation to calculate degree of increasing in returning any production stage that the increasing degree of return comparable size when estimating the laws formats as there is a strong impact between the growth rates in industrial production and growth rates in gross domestic product
DMA‐Net: Dual multi‐instance attention network for X‐ray image classification

Security inspection has been playing a critical role in protecting public space from safety threats. As object detection is a fundamental and mature research filed, it still suffers from numerous challenges such as scale, viewpoint and intra-class variance of X-ray images. The main reasons are, mis-modeling of actual security inspection as well as insufficient effective X-ray samples. To this end, the X-ray inspection task is reconsidered by predicting the dangerous attributes without boxes and categories, a Dual Multi-instance Attention network (DMA-Net) is proposed in this paper to mine the key-instance from both patch and proposal branch. In patch-level multi-instance attention pooling, Recursive Attention Pyramid (RAP) and Spatial-Channel Attention (SCA) are proposed to effectively learn discriminative representation from hierarchical features. Meanwhile, the proposal-level multi-instance attention pooling selectively emphasizes interdependent of crucial regions. The features of dual pooling layers are fused to predict dangerous attributes of X-ray inspection images directly. Further, this paper contributes a large-scale and high-quality X-ray image dataset from railway stations, named Railway Station X-ray (RSXray). Enormous experiments on RSXray, GDXray and SIXray demonstrate that the proposed DMA-Net achieves surprising performance with dual multi instance learning diagrams and attention mechanism. The superiority of the employed framework for applications in real world scenarios are also verified.
Collaborative Learning Environment in the Professional Training of Future Teachers

The importance of this study is linked to the topic of increasing the quality of future teacher professional training by creating a collaborative learning environment. The purpose of this research is to conduct a theoretical analysis of the effectiveness of creating a collaborative learning environment in university and demonstrate its impact on the successful professional activity of future teachers. The paper presents the data of the experimental research in the form of Action Research, conducted among 1st and 2nd year students of pedagogical specialties in the natural sciences (chemistry, biology, physics, computer science). The core requirements of the personality-oriented, activity-based, systemic, environmental, axiological and competence-based approaches form the methodological foundation for building a collaborative learning environment. Students who are immersed in a collaborative learning environment have the opportunity to reflect on the level of formation of their own professional skills, the success of achieving educational goals, and the processes of self-realization, self-development, and self-actualization on a regular basis. This study examines the impact of collaborative learning on students’ communication skills, knowledge quality, assessment of educational achievements, and study time savings. The research findings are linked to the use of Action Research in the educational process, involving students in the process of professional self-improvement. The novelty of the research is characterized by the identification of developmental effect of a collaborative learning environment based on the concept of a zone of actual student professional growth. The practical significance of the research is the development of positive experience in structuring the educational process, with the prospect of applying this experience in future professional activities, such as working with students.
Efficient incremental hash chain with probabilistic filter-based method to update blockchain light nodes

In blockchain, ensuring integrity of data when updating distributed ledgers is a challenging and very fundamental process.Most of blockchain networks use Merkle tree to verify the authenticity of data received from other peers on the network.However, creating Merkle tree for each block in the network and composing Merkle branch for every transaction verification request are time-consuming process requiring heavy computations.Moreover, sending these data through the network generates a lot of traffic.Therefore, we proposed an updated mechanism that uses incremental hash chain with probabilistic filter to verify block data, provide a proof of data integrity and efficiently update blockchain light nodes.In this article, we prove that our model provides better performance and less required computations than Merkle tree while maintaining the same security level.
The Effect of Learning Tenses Using Abbreviated Formulas on Students’ Grammar Mastery at the Takhasus grade of Mazro’atul Lughoh Islamic Boarding School Pare Kediri

The aim of this study is to investigate the effect of learning tenses using abbreviated formulas on students’ grammar mastery at the Takhasus grade of Mazro’atul Lughoh Islamic Boarding School Pare Kediri. The method of this study is quantitative by taking 20 students of the population, and using saturated sampling. This study was pre experimental research design conducted with one group. Before giving treatment, the writer gave pre-test. After four meetings, the writer gave the post-test. The scores of pre-test and post-test were collected from twenty essay questions, then, it was analyzed by using t-test. The findings of this study shows that learning tenses using abbreviated formulas on students’ grammar mastery was effective. It is proved by the result of the calculation of paired sample t-test with the sig (2 tailed) with the result was .000, and it was &lt; 0.05. It is considered that the null hypothesis (Ho) in this study is rejected and the alternative hypothesis (Ha) is accepted, which states that there is a significant difference between students learning tenses before and after using abbreviated formulas. It means that learning tenses using abbreviated formulas affects students’ grammar mastery.&#x0D; &#x0D; Keywords : Grammar Mastery, Abbreviated Formulas, Tenses.
ICT for Sustainable Development: Evidence from Nguruman Community Knowledge Centre, Kajiado County, Kenya

For over a decade, development partners have advocated the application of ICTs as tools for poverty alleviation especially targeting the agricultural sector. To provide an in-depth analysis of the impact of the CKC on the Nguruman community, the participatory ethnographic research methodology, combining participatory techniques and ethnographic approaches, was used. The use of this approach with the potential to feed into action research. I selected certain elements of the Ethnographic Action Research (EAR) developed by Tacchi and others. This research was undertaken in Nguruman, a rural Sub-location situated in arid and semi-arid land within the Olkiramatian Group ranch about 40 kilometers from Magadi town at the foot of the Nguruman escarpment in Kenya. The findings show a general view of Nguruman as being relatively developed. Participants originally from Nguruman compared its current state of development to earlier years and said it is developed. However, participants who are not originally from Nguruman say the area has considerable development when they compare it with other communities in Kenya. Like the participants from the focus groups, those from the interviews described development in terms of infrastructure such as roads, communication services, community institutions, and socio-economic conditions such as an increase in population, cultural issues, and education. Most of the participants, especially those originally from Nguruman, mentioned that the infrastructure of Nguruman has improved when compared to its former state some years back. For all the participants, the perceiving influencers of the development of Nguruman were commonalities in the emerging issues such as gender and cultural issues, illiteracy, and the value of education. A comparison of the participants’ communicative ecologies reveals different communication and information patterns and activities unique to each individual. Each individual uses different ICTs and links these ICTs to his/her social network to enhance communication and information patterns. Based on the findings, it is recommended that development communication that emerges from successful rural development calls for the conscious and active participation of the intended recipients at each phase of the development process. Rural development cannot occur without changes in the attitudes and behaviors of the people concerned. Emphasis should be on the planning of communication initiatives, focusing on dialogue rather than one-way communication as support to development initiatives.
Comparing Some of Robust the Non-Parametric Methods for Semi-Parametric Regression Models Estimation

In this research, some robust non-parametric methods were used to estimate the semi-parametric regression model, and then these methods were compared using the MSE comparison criterion, different sample sizes, levels of variance, pollution rates, and three different models were used. These methods are S-LLS S-Estimation -local smoothing, (M-LLS)M- Estimation -local smoothing, (S-NW) S-Estimation-NadaryaWatson Smoothing, and (M-NW) M-Estimation-Nadarya-Watson Smoothing.&#x0D; The results in the first model proved that the (S-LLS) method was the best in the case of large sample sizes, and small sample sizes showed that the (M-LLS) method was the best, while the second model showed in general that the S-LLS method was the best in addition to the method M-LLS was the best in some cases of sample sizes and at different levels of variance. As for the third model, it was shown through the results that in most cases the S-LLS method was the best in addition to the M-LLS method which was better in some cases of sample sizes and at different levels of variance.&#x0D;
Smarat tag for social distance and face mask detection

Today the biggest problem the world is facing above all the natural disasters is the Covid-19. It's been more than a year but the solution to the issue is still at a far fetch. However, still have few ways to control the outbreak as instructed by the WHO (World Health Organization). A few among them are wearing a mask and maintaining social distance. The objective of the project is to detect face masks in a public gathering or an event. The algorithm used in the project to achieve the objective is MobileNet V2. An image of a few people wearing a mask and without wearing a mask is used as an input dataset. There are few processes involved in achieving the objective of the project that include pre-processing, data augmentation, training, testing and image segmentation. After the processes, with the help of the Mask R-CNN algorithm, will get a segmented image of the input dataset of people wearing a mask and people not wearing a mask. Then, the model is implemented using a webcam where get result of people wearing a mask and not wearing a mask along with the accuracy in percentage.
Improving The Students’ Vocabulary Mastery Through TPR Method At SMP Negeri 29 Medan Tahun Ajaran 2020-2021

Vocabulary is one of the essential language components in studying English. Without a propotional amount of vocabulary anyone will get trouble in speaking, reading, listening and writing. In other words, the first that to be master for language learner in learning language especially English is vocabulary. It means that learning vocabulary is very important, especially for students in junior high school. They must master English vocabulary and its grammatical rules to make communicate to another people. A good teaching technique makes students understand and master the lesson like the 2 other lessons which need a suitable technique and methods, teaching language also needs a suitable techniques and methods. In reality learning English especially to memorize vocabulary is boring for some students. One of the method will can improve the students mastery is use TPR (total physical response) in the class. That is way I want to conduct the research with title “Improving the Students’ Vocabulary Mastery Through TPR Method at SMP Negeri 29 Medan Tahun Ajaran 2020-2021’’. This research was conducted at SMP NEGERI 29 MEDAN to be exact in class VIII with a total of 12 students. by using the Classroom action research techniques to get student scores. The results of this study are sought to support the creativity of teachers in teaching and increase knowledge to students about the ease of memorizing vocabulary
A Review on Hand Gesture Recognition

Abstract: User Interface (UI) and Human Computer Interaction (HCI) have come a long way from the time computers went personal. The constant work and research done to explore HCI allows for new ways and improvements. Hand gesture recognition is part of HCI that quickly picked up after the advancements in computer hardware and machine learning, particularly computer vision. Hand gesture recognition is a natural alternative to interact with computer as compared to mechanical devices(mouse, keyboard, etc),just as we interact with other humans through hand gestures. We review the existing tools and techniques that make hand gesture possible today, along with some common pitfalls and potential fixes.
A Survival Status Classification Model for Osteosarcoma Patients Based on E-CNN-SVM and Multisource Data Fusion

Traditional algorithms have the following drawbacks: (1) they only focus on a certain aspect of genetic data or local feature data of osteosarcoma patients, and the extracted feature information is not considered as a whole; (2) they do not equalize the sample data between categories; (3) the generalization ability of the model is weak, and it is difficult to perform the task of classifying the survival status of osteosarcoma patients better. In this context, this paper designs a survival status prediction model for osteosarcoma patients based on E-CNN-SVM and multisource data fusion, taking into full consideration the characteristics of the small number of samples, high dimensionality, and interclass imbalance of osteosarcoma patients' genetic data. The model fuses four gene sequencing data highly correlated with bone tumors using the random forest algorithm in a dimensionality reduction and then equalizes the data using a hybrid sampling method combining the SMOTE algorithm and the TomekLink algorithm; secondly, the CNN model with the incentive module is used to further extract features from the data for more accurate extraction of characteristic information; finally, the data are passed to the SVM model to further improve the stability and classification performance of the model. The model has been demonstrated to be more effective in improving the accuracy of the classification of patients with osteosarcoma.
Is Ethereum's Price Return Determined by COVID-19, Macro-financial, and Crypto Market Factors?

We investigated COVID-19 cases per country, macro-financial, and crypto market factors that might have affected Ethereum's price return in the top three countries of users, which were also affected by COVID-19 (United States, China, and Germany). Feasible Generalized Least Square (FGLS) was used as the methodology and the generalized method of moments (GMM) was tested for a robustness check. The findings revealed that Ethereum price returns were greatly affected by COVID-19 factors. Meanwhile, macro-financial factors (stock indices and gold) had stronger effects on the return of Ethereum price rather than the crypto market.
Research on Innovative Practice of Midi Music Production in Music Class of Primary and Secondary Schools

Under the new curriculum reform, there are higher requirements for music teaching in primary and secondary schools in information technology based teaching, which also provides channels and platforms for the application and practice of Midi and music software in classroom teaching, and thus becoming one of the important content of music classroom reform in primary and secondary schools. In this study, the Midi music based theory knowledge is introduced with probes into the concrete methods for Midi music production. Through the computer music works creation practice, students can understand the Midi music production process so as to independently make a relatively complete works of music, improving primary and secondary school music classroom teaching effect.
Examining the Asymmetric Impacts of Interest and Exchange Rate on Investment in Egypt for the Period 1976-2020: Applying NARDL Model

Most of the studies conducted in the past decades focused on the effect of interest rates and exchange rates on domestic investment under the assumption that the independent variables have the same effect on the dependent variable, but there were limited studies that investigated the unequal effects of changes in interest rates and exchange rates, both positive and negative, on domestic investment. This study used a nonlinear autoregressive distributed lag (NARDL) model to assess the unequal effects of the real interest rate and real exchange rate variables on domestic investment in Egypt for the period 1976 - 2020. The results revealed that positive and negative shocks for both exchange rates have unequal effects on investment in the long and short term. In addition, the stability of the nonlinear model was tested using recursive estimate tests and found to be stable.
EFFECT OF ADDITIONAL TRISODIUM PHOSPHATE 2% AS A RETARDER TO DIMENSIONAL STABILITY TESTS DENTAL MATERIAL ALGINATE AFTER HARDENING

The alginate moulding material is a negative mold of the teeth and oral cavity tissue. The alginate molding material is hydrophilic and is used as a pre-elimination mold to a custom tray for a more accurate second mold. The dimensional stability of the alginate mold is essential for the success of making a precise mold model. Changes in alginate dimensions are related to the contraction during the hardening process of the alginate molding material or the setting time. The addition of Trisodium Phosphate (TSP) is known to prolong the hardening time of alginates by slowing down the reaction of alginate salts and calcium sulfate. The purpose of this study was to compare the dimensional stability test of the alginate molding material with the addition of 2% trisodium phosphate and those without 2% trisodium phosphate after hardening. This research is pure laboratory experimental research. Alginate was divided into two groups: the group according to the manufacturer's provisions and the group added with 2% trisodium phosphate. The results of this study were analyzed using the unpaired T-test, and the results showed a p-value &lt;0.05, namely (0.00 &lt;0.05), so there was a significant difference in the dimensional stability of alginate without TSP 2% with the addition of TSP 2%. This study showed that the addition of 2% TSP improved dimensional stability in the group with the addition of 2% TSP.
understanding of the contents in the achievements of learning in students of basic general education

The objective of the research was to know the level of understanding of the contents in the learning achievements of the students Basic General Education EGB of the Educational Institutions of the area circuit C10B of the canton 24 de Mayo in the period 2021-2022, for this a survey was applied to a selected sample of 80 students, 70 legal representatives and 5 teachers, once the data was analyzed it was obtained that 40% of the students stated that the teacher talks with them before giving a new topic and when asking the second question, 60% indicated that the type of didactic resource most used by the teacher at the time of the development of their classes is the implementation of books and at the moment of evaluating the knowledge acquired is done through written tests. It is concluded that because of the COVID-19 pandemic, the learning achievements of the students were good and one of the reasons was the participation of parents in their academic activities.
Fake face image detection using feature network

In the recent times, the image data in social networks such as Instagram, Whatsapp, Facebook, Snapchat, twitter etc has an exponential growth in terms of volume, variety due to the velocity of the data stream. On the other hand, the advancements in the image and video processing led to increase in the fake images relatively in huge volumes. Due to the involvement in spreading fake news and leading mob incitements fake images became major concern to handle that demands an efficient a fake image detector is of at most concern to entire social networking organizations. In this paper, a deep learning framework is proposed that differentiates fabricated parts of the image from the real image using supervised learning strategies. Also a modified neural network structure called the Fake Feature Network is proposed in this work which consists of advanced convolution networks. In order to make model effective, the proposed methodology has a two major steps in learning which combines a modified neural structure that uses classifier and pairwise learning for the fake image detection.