Reviewerly/exHarmony huggingface dataset:
THE ROLE OF PERCEPTION IN THE ENTRY OF WOULD-BE ENTREPRENEUR INTO AGRIBUSINESS: A CASE STUDY OF BENUE STATE, NIGERIA

The study analyzed perceptions as a determinant of young would-be entrepreneurs’ likelihood to venture into agribusiness in Benue State, Nigeria. The study made use of the ex-post facto research design and the population was made up of registered persons who had been trained or were undergoing agribusiness trainings at business school, university, government agencies or non-governmental organizations within the ages of 15-35 for the 2019 and 2020 cropping season totaling 10320. The sample size of 385 was determined from the population using Taro Yamane formula. Primary data was collected through the use of structured questionnaires. Descriptive and inferential statistics were used to analyze the data collected. Findings revealed that age group of entrepreneurs (mean = 2.83), years of experience in agribusiness (mean = 2.33), their occupation (mean = 2.90) and their level of education (mean = 4.66) are likely socioeconomic indicators of perceptions influencing likelihood to venture among young would-be agribusiness entrepreneurs in the State. The result of the ordered logit regression analysis showed that for 3 categories of perception, years in agribusiness, occupation and level of education are significant influencers viz: personal perception (-0.31**, 0.28**, -0.27**), respectively. social perception (-0.83***, 0.64***, -0.36**) respectively and familial perception (-0.87***, 0.64**, -4.81***) all these results were significant at 1% = *** and 5% = **. The study recommended that, more educational programs for young would-be entrepreneurs needs to be deepened through exposure to more learning tools and capacity building to aid in dispelling negative perceptions about the practice of agribusiness. Promotion of hands-on training, mentorship and campaigns is advocated to enhance experience among young would-be entrepreneurs.
Design of an embedded machine vision system for smart cameras

Abstract With the rapid increase in computer users’ requirements for image information and image processing, and the rapid development of the intelligent process, the ability of the traditional visual system to process image information and data has been difficult to meet the needs of users. Therefore, in this article, we upgrade the vision system of smart cameras by introducing three network algorithm structures: convolutional neural network (CNN), LSTM and CNN-LSTM. We compare the classification performance of the three algorithms and evaluate them with three metrics: accuracy, precision and recall. The experimental results show that using the CNN algorithm, the accuracy of image information processing is 98.2%, the precision can reach 87.5% and the recall rate is 99.8%; the LSTM accuracy is 97.7%, its precision is 89.6% and its recall rate is 87.3%; its precision can be improved to 90.5% and the recall rate to 99.7%.
The Impact of Applying the Role Playing Method on Social Studies Lessons in Fourth Grade Student

This study aimed to determine the effect of the role-playing method on student learning outcomes in social studies. The subjects of this study were fourth-grade students who were grouped into experimental and control groups. Methods of data collection using observation, tests and documentation. The research instrument is the learning outcomes test's validity and the observation sheet's validity. The data analysis technique used is descriptive qualitative, and quantitative. The results showed a significant effect of learning methods on learning outcomes. Students who get the role-playing method get higher learning outcomes than student who takes lessons with various lectures. The results of observations on the affective domain in the experimental group were in the score range of 18.71 (high), and the control group was in the score range of 11.9 (low). The average increase in learning outcomes was 19.1 in the experimental group and 9.35 in the control group.
The Application of Coorperative Script in Economics Lesson to Improve Learning Outcomes

This study aims to improve learning outcomes in economics subjects by applying the cooperative script method. This type of research applies class actions with two cycles. The subjects of the study were 10th grade learners who took economics lessons on the topic of consumer and producer behavior. Learning outcomes are measured using multiple choice tests. After two cycles, learners increased their learning outcomes from an average of 77.14 to 79.04. The percentage of students who met learning completion increased from 80.95% to 100%. These results explain that the cooperative script method has the potential to improve learning outcomes. An aspect that is thought to be a success factor is the convenience of learning with group work.
Organizational principles of the formation the beauty of pedagogical speech in the spiritual educational institutions of Ukraine in the end of the XVII-XVIII centuries

Lavrinenko Oleksandr.Organizational principles of the formation the beauty of pedagogical speech in the spiritual educational institutions of Ukraine in the end of the ХVІІ-ХVІІІ centuries.The article considers organizational and pedagogical principles of the formation of the beauty of pedagogical speech in professional training of future teachers in the spiritual institutions of Ukraine at the end of ХVІІ-ХVІІІ centuries.The existence of the components of pedagogical skill in the system of spiritual education of the marked historical period and awareness of the need to prepare future teachers and educators on the basis of a high level of the beauty of pedagogical action, perfection of thought and language interaction with students is proved.
Supporting the productivity of teachers by forming a socio-psychological climate in the process of personnel management of preschool educational institution

Torubara Victoria.Supporting the productivity of teachers by forming a socio-psychological climate in the process of personnel management of preschool educational institution.The article examines the concept of «socio-psychological climate» and the factors influencing the socio-psychological climate in the team.The influence of positive and negative socio-psychological climate on the productivity of teachers is determined.It is invented ways to form and maintain the socio-psychological climate in the teaching staff in the process of personnel management of preschool educational institution.The author pays attention to interpersonal and collective interaction of teachers and the head of preschool educational institution in the process of collective solution of educational tasks and analyses leadership styles, their implementation in different teams and their impact on the socio-psychological climate in the teaching staff of preschool educational institutions.
Application of Web Data Mining Technology in Computer Information Management

We used the Web mining algorithm to carry out experiments on the computer information management system. By comparing the traditional algorithm with the improved algorithm, we obtained the following experimental results in the computer information management system. The improved algorithm eliminates the influence of outliers, has higher accuracy and better clustering results. The improved PageRank algorithm can sort the pages according to the user’s preferences in the computer information management system, which greatly improves the user’s experience and reduces the time for users to filter useful pages themselves. Different users will get different sorting results. Since this improved algorithm calculates the PR value based on the similarity of topic links, this algorithm can improve the phenomenon of topic drift to a certain extent. Thus, the feasibility of the improved algorithm is proved.
Deep Learning Based Cancer Detection in Bone Marrow using Histopathological Images

The cancerous proliferation of abnormal white blood cells (WBC) in the bone marrow and blood is characteristic of leukemia, which has its origins in these blood-forming tissues. Blasts are immature aberrant cells that inhibit the creation of new, lineage-normal blood cells. Acute Lymphoblastic Leukemia (ALL), Acute Myeloid Leukemia (AML), Chronic Lymphocytic Leukemia (CLL), and Chronic Myelomonocytic Leukemia (CML) are the four Chronic Lymphocytic Leukemia (CLL), Chronic myeloid leukemia (CML), and Acute myeloid leukemia (AML) (CML). Patients with leukemia are often diagnosed after their symptoms have been evaluated, a complete blood count (CBC) has been run, and a peripheral blood smear has been examined under a microscope by a pathologist. As part of the process to confirm and classify leukemia, a bone marrow examination and other sophisticated laboratory testing are performed. Traditional blood and bone marrow smear examination using light microscopy is plagued by intra- and inter-observer variability. Overcoming these individual biases of doctors is possible with the use of image processing-based approaches that can automatically analyse pictures of blood and bone marrow smears to detect abnormal cells. Using an American Society of Hematology dataset, the researchers classified cases of ALL into B-cell and T-cell subtypes, as defined by the World Health Organization (ASH). The research improves classification accuracy to 94.12% and compares the effectiveness of three distinct training strategies. The research also includes subtyping AML into M3, M4, and M5 using a ResNet-50 pretrained network and traditional machine learning based classifiers based on the CNN's characteristics. Using the features of ResNet-50, we were able to get a classification accuracy of 96.43 percent, and we were able to get a hundred percent accuracy using just a small number of traditional classifiers. Using the properties of Element and an ASH dataset, the researchers also sought to classify cases of chronic leukemia into CLL and CML. Classification using the Element yields an accuracy of 92.59%, while classification using the SVM with the Lucent's deep features yields an accuracy of 98.15%. The study's classifications are based on a straightforward framework that doesn't need sophisticated picture segmentation or feature extraction. The research has various limitations, one of which is that the dataset utilized in some of the classifications is not particularly big, which leads to a loss in classification accuracy. To address this, the research used data augmentation methods.
Natural Language Processing and Naïve Bayes Classifier Algorithm to Automate the Detection of Cyberbullying

Abstract: The impact of social media on contemporary culture has been unprecedented, making it the most significant medium of our times. While it has had a positive effect on people's worldview, social media has also been linked to a rise in undesirable phenomena such as cyberbullying, cyberstalking, and cybercrime. Cyberbullying, in particular, can have a negative impact on individuals' mental health and has even been identified as the root cause of mental health issues in some cases. The proliferation of sexually explicit comments and the spread of rumors by multiple individuals are some of the negative influences that have been observed in the social media ecosystem. In recent years, academics have been increasingly concerned about the indicators of online harassment. Our goal is to develop a system that can detect instances of online abuse using Natural Language Processing (NLP) and Naïve Bayes, among other techniques. The cultural norms have shifted dramatically due to the rapid transmission of the COVID-19 virus, resulting in a rise in cyberbullying, especially among adolescents. The younger generation is more likely to engage in this practice, which has become more widespread with the stratospheric rise in popularity of various online engagement-promoting platforms. The COVID-19 pandemic has changed the way people interact online and has contributed to an increase in cyberbullying. As more people began working from home, bullying became a more significant concern. Our proposed system includes modules for data cleansing, text mining, word embedding, and regression analysis, among others. We utilize the Lemmatization technique for text mining, which enhances the model's precision. We also utilize the Vader emotion for feature extraction, which generates word vectors that are scattered numerical representations of word attributes. Additionally, Naive Bayes is used for data categorization to prevent overfitting in the proposed model. This would help in creating vectors that connect words with similar meanings
The case of the Pseudo-hypercorrection

This paper discusses a phenomenon I qualify as a pseudo-hypercorrection. A pseudo-hypercorrection has the same basis as a hypercorrection, but the important characteristic of a pseudo-hypercorrection that distinguishes it from a hypercorrection is that the expression is grammatically correct. As a case example I have used a phenomenon in Dutch, from the consideration that it occurs frequently, so that it cannot summarily be dismissed as a chance event.
Assessing Learning Behaviors Using Gaussian Hybrid Fuzzy Clustering (GHFC) in Special Education Classrooms

The article suggests an unsupervised model for featuring student's learning patterns in an openended learning scenario.The article proceeds by generating powerful metrics to characterize the learner's behavior and efficacy through Coherence investigation.Then, the selected features are combined through a Gaussian Hybrid Fuzzy Clustering (GHFC) that categorizes students based on their learning patterns.The proposed system features the essential behaviors of every group and associate the behaviors with ability to develop right models to gauge the learning gains between preand post-test scores.Also, this article explains the deployment of behavior characterization to be developed as a adaptive framework of learning behaviors.
Performance Analysis of Students in Nawalparasi Based on SEE Results in 2078 BS

The primary objective of this study was to examine students' gender-wise performance in different subjects of SEE results, the average grade point of each subject, and the total grade points of all subjects in the SEE exam in 2078 in Nawalparasi district. The data for this study was obtained from the 2078 BS SEE exam results using secondary data collection methods. The data analysis technique of this study was descriptive statistics where correlation analysis, arithmetic mean, Mann-Whitney U test and Chi-square test of independence were used for data analysis. The study included the exam results of 13139 students from both private and public schools in Nawalpur district. There were 6654 male students (50.6%) and 6485 female students (49.4%) in the sample. The results indicated that the majority of the SEE participants students (97.9%) were between 13 to 21, and 34.7% were 16 years which is the maximum observed percentage of students. In 2078 BS, only 1.1% of students over the age of 21 participated in the SEE exam, according to the results.&#x0D; The results importantly show a significant association between the gender of students in Grade Point Average (GPA) of the SEE results in 2078 BS. The majority of the students had poor results in the SEE-2078 exam, as 56.3% of students secured less than 2.39 GPA, whereas no one obtained 4 GPA out of 4. Finally, the results indicate that the total grade point (TGP) of girls (2.53) is higher than boys in compulsory Nepali compared to male (2.59) students in the SEE results of 2078 BS in Nawalparasi district. The implication of this study would be beneficial to the Education Department of Secondary Education Examination (SEE), educators, researchers, policymakers, and parents to improve the overall GPA in SEE results.
Forecasting the Weather and its Visualization using Augmented Reality

-In the recent period, many real-world applications and institutions generates a huge amount of data which is unstructured i.e., in the form of images containing data, receipts, invoices, forms, statements, contracts etc. This rich and detailed information presented in the text is of great significance in computer vision-based applications (driverless cars, assisting blind and visually impaired people, detecting labels and packages, automatic number plate recognition etc.). Recently, there has been a hike in the efforts, This project presents AR Weather, a simulation application, which can simulate three types of precipitation: rain, snow, and hail. We examined a range of weather phenomenon and how they may be simulated in a mobile augmented reality system. AR Weather was developed and deployed on the Tinmith wearable computer system to enable autonomous and free movement for the user. The user can move freely inside the simulated weather without limitation. The result of this work, the AR Weather application, has been evaluated with a user study to determine the user’s acceptance and draw conclusions to the applicability of augmented reality simulated weather Keywords- Mobile augmented reality, environmental sensor networks, mobile visualization
Pedagogical conditions for the implementation of interdisciplinary connections within the framework of the updated educational content

The article considers the introduction of the still insufficiently studied updated content of education in the educational process of secondary schools. The special importance of interdisciplinary connections has been scientifically substantiated for the purpose of effective assimilation by students of one or another content. The scientific and methodological foundations of the updated program are analyzed, the priorities of which are spiritual, cultural and moral values ​​in the education of young people, the development of skills and ideas that give them confidence and success in such a rapidly changing world, the ability to apply the acquired knowledge in all kinds of life situations from the point of view of critical thinking. Within the framework of the article, the necessary pedagogical conditions obtained as a result of the integration of the subjects of primary school subjects are determined. Along with this, guidelines have been prepared not only for primary school teachers, but also for all teachers leading the educational process according to the updated program. According to the results of world studies in the field of education, it is stated that teachers with a high level of professionalism will be able to improve the knowledge of young people in terms of quality. On the topic of the study, analysis, sorting, questioning, interviews, diagnostics, and a pedagogical experiment were carried out. The methods of conducting mathematical and statistical processing on them are comprehensively applied. The developed system of conditions was tested in experimental and pedagogical work, in which 84 schoolchildren took part on the basis of the N5 school-gymnasium named after Zhambyl Zhabaev in Taraz. Keywords: interdisciplinary connections, updated program, pedagogical requirements, conditions, elementary class, teacher, modeling.
Tourism Search Application within the Bima City Locale of West Nusa Tenggara Utilizing the Android-Based Location-Based Benefit Strategy Utilizing Visual Studio Code

Bima is one of the cities in West Nusa Tenggara which has various tourist objects. Apart from nature tourism, there are also many other tours such as modern water tourism that provides water parks, historical tours, religious tours and culinary tours. So far, recommendations for tourist destinations are usually word of mouth, mass media, browsing¸ and social media. This makes not all tourist objects can be visited, due to lack of information and the location of tourist objects that are scattered so that it is difficult to reach by public transportation. This research offers an android application that can provide convenience to tourists who want to visit tourist attractions. This application provides information about existing tourist objects starting from location information, facilities, opening and closing hours as well as guides for reaching locations using the Location Based Service method. Every tourist can download the application and run it on a smartphone. Application users can select tourist objects by category and the system will provide guide facilities to the tourist sites they want to visit. This application is expected to be a solution to the problems above and become a media for tourism promotion in the city of Bima.
The Role of Electronic Customer Trust Building Tools On Excellent Performance An analytical study of the opinions of a sample of individuals in the administrative and leadership positions in the Northern Cement Company

The current study aims to overcome the conflicts facing the company in its way of staying and continuing to maintain its performance excellent in light of the intense competition, which made it seek to find strong ways and links with its customers through electronic communication using electronic platforms, and this put confidence and safety in The place of suspicion and fear of not fulfilling credibility or violating the privacy, so this research comes to answer about the question: “Can the company achieve an excellent performance by relying on the customer's electronic confidence?”.&#x0D; The study followed the descriptive and analytical approaches by providing a virtual model and testing the zero hypotheses, which stipulates that there is no significant effect of the customer's electronic confidence on outstanding performance. A three-point scale questionnaire was used as the study tool. the employers in administrative and leadership positions at Northern Cement Company in Nineveh Governorate were chosen as a study sample. The study concluded that the measurement and compatibility with the sincerity and reliability of the study model. The results showed the existence of a statistically significant relationship between the variables of the study, which indicates the importance of building electronic customer confidence tools in enhancing the performance of excellence in a researched company.&#x0D; &#x0D; Paper type: Research paper
Development of Entrepreneurship Education Program for Elementary School Students' Real Life Problem Solving Competency Development and Implementation Effect

Objectives This study was to develop an entrepreneurship education program for the development of real-life problem-solving competences in elementary school, and to investigate the effects after conducting classes.&#x0D; Methods For the development of an entrepreneurship education program, a draft was devised through literature research and learner's demand analysis. And the final draft was developed through expert evaluation of the draft. Introspection data were collected during the course of class in this program. After class, 25 participating students were divided into 6 groups, and focus group interviews (FGI) were conducted. The data collected in this way were analyzed according to the content analysis method to find out the effectiveness of the educational program.&#x0D; Results Through the classes of the entrepreneurship education program, the students went through the 16 class hour. In this process, students were able to develop application and analysis of knowledge, communication skills, creativity, leadership and execution skills. In addition, in the process of problem-solving, students were able to obtain positive effects such as challenging spirit for difficulties, positive self-awareness, and self-efficacy.&#x0D; Conclusions The point of entrepreneurship education program is to find empathic problems in real life, create solutions, and put them into practice. Entrepreneurship education program is useful as an educational method to develop competencies necessary for the future society. Entrepreneurship education is to discover and define problems from unstructured situations in real life spaces, and to directly practice solutions created while interacting through team activities. Entrepreneurship education is an educational method that internalizes problem-solving capabilities and is an essential method for fostering future social capabilities.