Reviewerly/exHarmony huggingface dataset:
Research on Countermeasures for the Employment of Chinese University Students in the Context of the Development of Digital Economy

After agricultural and industrial economies, the digital economy is the third economic structure that utilizes data resources as a fundamental component. The major carrier is modern information networks, and the integration and application of information and communication technology, as well as the digital transformation of all elements, are significant driving forces. This promotes greater coherence between equity and efficiency. The rapid growth of the digital economy has increasingly affected employment in three main areas: scale, structure and quality.The Chinese government attaches great importance to the employment of college students, which still faces greater challenges under the impact of weak global economic growth and multiple international and domestic factors exceeding expectations. In this context, researching the influence of the digital economy’s development on employment and offering positive and effective countermeasures will assist to promote full employment and improve the quality of employment for Chinese university students.
Small Object Detection Algorithm in Drone Aerial Images Based on Improved YOLOv5

In response to the low accuracy of conventional object detection algorithms in small object detection during drone aerial missions, this paper proposes an improved YOLOv5 algorithm for small object detection. Firstly, we introduced a 160x160 small object detection head and removed the 20x20 large object detection head, adopting a strategy of fusing feature maps of P2, P3, and P4 scales to enhance small object detection performance. Secondly, by eliminating the P5 scale network layers in the backbone network, we strengthened the high-order semantic information of the P4 layer. Finally, we utilized adaptive spatial feature fusion technology to replace the direct concatenation method in the Neck network for merging different scale feature maps, optimizing the fusion effect of feature maps of different scales. The experimental results on the VisDrone2019 small object dataset show that, compared to the original YOLOv5, the proposed algorithm in this paper achieved significant improvements of 7.3%, 7.1%, and 9.2% in Precision, Recall, and mAP@0.5, respectively. Furthermore, the model's parameter quantity was reduced by 40%, indicating that the improved model presented in this paper has superior performance in drone small object detection tasks and is highly practical.
Research on College Student Development Planning Platform Based on Intelligent Q&amp;A Mechanism

This paper proposed that education, science and technology, talents are the basic and strategic support for the comprehensive construction of a modern socialist country, and emphasized the organic connection between the three to jointly shape the new momentum and new advantages of development. However, many college students, as the reserve force of the country, do useless work, take detours, blindly involve, and are deeply troubled by academic life pressure, emotional crisis, career development planning and other problems due to lack of clear planning for the future, and do not give full play to their talents and values. Therefore, based on the analysis of the current situation of intelligent question answering platform, this paper will use Java, Python and other technologies to study a platform similar to campus assistant, optimize management on the basis of the original model, and provide planning consulting for more college students.
Video Sequence Anomaly Detection with Multi-Layer Memory-Augmented Autoencoder

In order to enhance the model's ability to learn normal pattern features in the video anomaly detection task, this paper proposes an end-to-end video anomaly detection method that combines reconstruction and prediction. The method consists of two modules: (1) multi-layer memory-enhanced auto-encoder module: reconstructs RGB frames using a multi-layer auto-encoder with skip connection to compensate for the information loss due to memory; (2) conditional variational auto-encoder module: the reconstructed RGB frames from the previous step are taken as inputs, and predicts future frames using the current optical flow as a condition to capture the correlation between the optical flow and the video frames. Comparative experiments are conducted on Avenue, Ped2, and SHTech datasets, and the experimental results show that the hybrid model achieves relatively strong anomaly detection capability.
FORMATION OF RESEARCH COMPETENCIES IN TEACHERS-UNDERGRADUATES

The article analyzes the formation of research competencies in future teachers, who get education at the master's level. For this purpose, the views of Azerbaijani educators, as well as foreign educators on the formation of scientific and research skills in the laws of the Republic of Azerbaijan are investigated. In our country, the “special educational program of the magistracy" has been approved. Among the professional competencies that a graduate needs to form according this program, a special place is occupied by competence in the research field.It is from this point of view that we found it necessary to analyze the formation of research skills among future teachers getting a master's degree. The modern level of development of society requires serious and important intellectual searches, and s since these searches should serve a person that provide a complex human activity in unity and connection.
DEVELOPMENT OF FUNCTIONAL LITERACY IN MATHEMATICS LESSONS

This article reveals the concept of functional literacy, describes some of its types, substantiates the need for its development. In addition, various examples of tasks aimed at developing functional literacy in mathematics lessons are given. It also presents the results of diagnostic methods that prove the development of functional literacy among students by solving the tasks given as an example in the article. The relevance of the issue considered in the article lies in the fact that the concept under consideration contributes to the development of students' ability to adapt the acquired knowledge and acquired skills to life. This work is significant in that, in addition to the theoretical justification of functional literacy and its types, it contains a variety of examples that contribute to the formation of the skill of applying knowledge by students in life. Methods used in this study: observation; analysis of theoretical sources on the research topic; questioning students; comparison of students' results based on the results of various tests, etc. The results obtained in the course of the study can be applied in the process of teaching students: to prepare students for the Pisa study, to prepare students for other exams containing practice-oriented tasks.
Research on robot path planning based on artificial potential field method

With the arrival of the new era, computer technology has also developed rapidly on the basis of electronic technology. The development of these technologies usually also supports the development and application of artificial intelligence technology. For example, applying artificial intelligence technology to the field of robot action path planning. In order to solve the problems of low efficiency and path errors encountered in robot path planning, this paper proposes a research method for robot path planning based on artificial potential field method. This method first constructs an environment map on a two-dimensional plane based on the motion environment of the robot, which includes all obstacle points and free points; Then, based on the principle of artificial potential field algorithm, the MATLAB software environment is used for programming to implement the artificial potential field algorithm model; Then set the relevant program running parameters to make the algorithm model run; Finally, two-dimensional and three-dimensional visualization charts are used to display the combined forces, midway search process, costs, and paths during the planning process. After 749 iterative searches, the system has planned a reasonable red path that meets the expected requirements and can be promoted for use.
English reading comprehension data classification based on random forest bidirectional voting mechanism

The rapid development of information technology has made the application of artificial intelligence more and more widespread, and English reading data classification is an important research branch, which has gradually been recognized and deeply explored by many researchers. At present, traditional English reading data classification methods face the dilemma of inaccuracy, long inference time, and inability to be applied in real-time. With the development of artificial intelligence related technologies, significant progress has been made in English reading data classification, but there is still great room to fully solve the problem. This article proposes a data classification method based on random forest bidirectional voting mechanism to address the problems faced by English reading data classification. This method first analyses the ensemble learning method of random forest and discusses the advantages that can be widely applied in data classification and non-parametric regression; Secondly, the importance of random forest convergence theorem, generalized error bound, and out of bag estimation was analysed; Finally, specific steps for improving the random forest improvement algorithm are provided. The experiment shows that the algorithm proposed in this paper performs significantly better than traditional methods on English reading corpora, improving testing efficiency and effectively improving the classification performance of English reading data without reducing the accuracy of the test set.
A digital health solution for parasitological surveillance at Anti-Malaria Campaign, Sri Lanka

The Anti Malaria Campaign in Sri Lanka is a public health initiative aimed at preventing and controlling the spread of malaria in the country. The outcome of the malaria control program is improved by effective surveillance. The National Malaria Strategic Plan highlights the lack of a web-based surveillance system for malaria as a weakness in the central-level availability of malaria parasitological surveillance data. DHIS2 (District Health Information Software 2) is a global-good, health management information system recommended by WHO. Creating a malaria information system based on DHIS2 and incorporating an interactive dashboard are employed to enhance the prompt accessibility of data at the national level.
Cooperative Target Recognition System Threat Assessment Based on Network Model

In threat assessment method, the relationships among indicators considering insufficiency and weights set unreasonable, the threat assessment method via network model put forward, used for coordinate target recognition system based on secondary radar. Firstly, the indicators were given by hierarchical structure, thinking of the relationships among indexes, then giving the indicators by network model. Then making standardization of indicators, solving the indicators weights by Analytic Network Process (ANP). Getting the systems' threat degree through threat degree assessment model, then made sequencing. Finally an example is used to verify the method, shows it is reasonable and effective. And the result is helping for allocation of interfere resources and operational deployment in later.
Detecting Hoax News Regarding the Covid-19 Vaccine using Levenshtein Distance

The internet is a communication tool that we often use. The internet itself has brought many benefits. However, some people misuse it, for example, individuals or a group of people who spread hoaxes or fake news to incite and lead the publics’ opinions to their desired side. When COVID-19 spread in Indonesia and the government implemented mandatory vaccine obligations, the total of hoaxes on vaccination increased rapidly. Due to a large number of hoaxes on the Internet on COVID-19 vaccinations, As for several studies on the creation of a hoax detection system with various methods to try to overcome this problem, one of the studies with a system that detects hoax news and uses several methods, one of these methods is Levenshtein, getting a fairly low-performance result of 40% compared to other methods used. Therefore. Researchers are motivated to develop a hoax detection system with a similar method by adding Feature Extraction which aims to improve system performance from the previous research. In this study, 2 main experiments were conducted using Levenshtein distance as the main classification method, the results showed the best results in experiment-2 with an f1-score of 70.2% which was an increase compared to previous studies due to adding feature extraction using tf-idf.
FORMATION OF VALUE ORIENTATIONS AS A COMPONENT OF THE FUTURE TEACHER'S PERSONALITY

The article reveals aspects of the formation of professional value orientations of future teachers; value orientations of the teacher as a system of personally realized humanistic values, which serve as guidelines for his social and professional activity, determining his life position; the problem of forming sustainable professional orientations in the process of professional training of future teachers is outlined; the concept of "professional and value orientations". Theoretical approaches (axiological, personal-activity and reflexive) solving the problem of formation of professional and value orientations of future teachers in the process of their professional training in a higher education institution are considered; and the mechanisms of formation of professional value orientations through the implementation of three interrelated stages: 1) informing ↔ search → evaluation; 2) dynamism → choice → assignment; 3) design → projection. The teacher's professional and value orientations are outlined as the most important elements of successful professional activity: they stimulate professional and personal development, activating the internal mechanisms of the individual (needs, interests, motives, attitudes, attitudes); play a strategic role in behavior and activity, determine directions of professional activity; adjust the student's activity with the help of assessments, orientations and attitudes, ensuring the relationship of personal and subject aspects of activity based on personal orientation. The content of the teacher's professional value orientations is characterized: values-goals (goals of professional activity: mastering the profession of a teacher, forming the image of "I" as a teacher, "I" as a professional); values-knowledge (orientation on the assimilation of professional and pedagogical knowledge: general, special, pedagogical, methodical); values-skills (focus on mastering prognostic, analytical, communicative and organizational skills); values-qualities (orientation on the development of personal (characteristic) and professional and pedagogical qualities). Pedagogical conditions, formation of value orientations by future teachers are singled out: 1) organization and stimulation of reflexive activity of students to focus on professional values; 2) development and implementation in the process of teaching social and humanitarian disciplines of a special course of knowledge that informs about professional values and is based on the basic concepts of pedagogical science; 3) use of dialogue technologies during the formation of value orientations.
STUDI EFISIENSI REAKTOR RAPID SAND FILTER DALAM PENURUNAN COD PADA AIR LIMBAH PENCUCIAN IKAN DI PASAR IKAN SIDOARJO

The existence of many fisheries products is directly proportional to the number of existing fish markets, including the Sidoarjo Fish Market in the eastern ring area. The many activities in this fish market produce wastewater that must be considered for its management so as not to pollute the surrounding environment. These activities forexample from fish washing activities. The parameters of water used for washing fish are organic, with organic pollutants high enough, namely COD. The purpose of this study was to determine the reduction in levels of BOD (5,20) treatment of wastewater from fish washing from the Sidoarjo Fish Market using sedimentation tub reactors and Rapid Sand Filters (RSF). The research phase will be carried out using a laboratory scale using a Precipitating Body as a pretreatment and RSF as a secondary treatment. The research began with a preliminary test to determine the influent quality of fish washing water effluents, then pretreatment was conducted. RSF uses buffer media in the form of: zeolith and gravel Influent discharge effluents are varied in two variables 10 liters / dayand 15 liters / day. The processing results from the RSF were then analyzed by BOD parameters (5.20) for 4 consecutive days using the standard EPHA method. The results showed that treating fish washing wastewater using sedimentation tanks and RSF can reduce the content of organic pollutants through BOD parameters (5.20) with an effectiveness reaching an average of 90% with gravel media and 95% with zeolith media. So it can be concluded that the fish washing wastewater from the Sidoarjo fish market can be treated before being discharged into the river so that the BOD pollutant can be reduced up to 95% using RSF technology with zeolith media.&#x0D; Keywords: Fish Washing Liquid Waste, BOD, Rapid Sand Filter, Zeolith.
MEMBANDINGKAN REGRESI 4PL DAN LINIER FIT UNTUK VERIFIKASI HORMON 17β-ESTRADIOL MENGGUNAKAN METODE ELISA

One solution for infertile couples to get offspring is IVF, one of the stages is a HOT procedure. On the stage there is an increasing in steroid hormone levels (estrogen) as a result of ovarian follicles development. The 17β-estradiol hormone was chosen to be verified because it can be used as a marker or marker to show the maturity follicle. Linear and logistic regression are the two most commonly used in curve making models for ELISA sandwich immunoassays. Although linear regression may be useful when analyzing samples included in the linear part of the analyte response curve, logistic regression is the preferred for multiplex immunoassays. Verification of 17β estradiol hormone regression results using linear fit obtained the value of r=0.952 while the regression value used 4PL obtained result r=0.998. But the results shown in the verification of the 17β estradiol hormone good, this were evidenced by using of SPSS software. The value of F obtained was 78.712, where the value was greater than the value of F table (6.61) which means that the value of independent variable (concentration) on value of the dependent variable (optical density value). The linearity values ​​obtained through verification using the 4PL model indicates that the linearity of this method was better based on linear regression.
Real Estate Image Classification For E-commerce Website

Currently, the image is the most important part of e-commerce websites and has a very significant impact on the real estate industry. In this work, we represent a novel approach for image classification in real estate. This problem can be applied to resolve some automated functions in operating the website when using machine learning algorithms in data-driven approaches. We can find some datasets about real estate images, such as REI and SUN, for this classification problem. However, they do not have images related to ecommerce websites such as TopReal in the Vietnam market. Therefore, we propose a new dataset called REID that is based on real requirements from the TopReal website and the others. This dataset has a hierarchy with 4 generics and 8 specific classes. To this end, we propose two model-based ConvNets for classification problems. In the first model, we design based on the LeNet architecture as in the baseline model to investigate and analyze the dataset for deep understanding. In the second model, we propose a transfer learning-based approach with ResNet as the feature extraction module and SVM as the classifier. The experimental results show that we obtain 97.6% and 87.3% accuracy for classes 4 and 8, respectively, on the REID dataset. These results show that our proposed methods achieve high accuracy on a real estate image dataset that adapts the websites in the Vietnam market and can extend easily to the others. Furthermore, the REID dataset can be extended to resolve many problems in real estate images for the Ecommerce Website.
Implementasi Augmented Reality Pada Pembelajaran IPA Siswa SMP

In the learning process at the inclusive junior high school SMP Muhammadiyah 5 in the city of Cimahi, conventional methods are still employed, utilizing limited book resources, and students remain passive, merely listening to what the teacher imparts. Augmented Reality is a technology that combines the real world with digital or virtual elements, creating an engaging and interactive user experience. The purpose of this research is to develop a learning media using Augmented Reality technology that is engaging and interactive in the field of Science, thus facilitating both teachers and students in comprehending the material. The stages in this research employ the Multimedia Life Cycle method, which includes concept, design, data collection, creation, testing, and distribution. The research has successfully developed an Android-based application that has undergone black box testing. Survey results also indicate a 90% satisfaction rate, demonstrating that the application is easy to use, interactive, and engaging.
Implementasi Sistem Pakar Android untuk Deteksi Penyakit Tanaman Coklat dengan Metode Certainty Factor

This research focuses on issues within the agricultural sector, specifically in cocoa farming. The associated problem is the lack of agricultural extension workers, which results in farmers' limited understanding of cocoa plant diseases and their management. As a consequence, disease identification in cocoa plants has traditionally relied on mere estimates, often proving inaccurate and inefficient in taking appropriate actions. The primary objective of this research is to design and develop an Android-based application utilizing the Certainty Factor method for diagnosing diseases in cocoa plants. The application is envisioned to function as an intelligent consultant for providing disease diagnoses in cocoa plants. The research employs the Research and Development methodology, gathering data from both primary and secondary sources through observations and interviews. The application is tested using both whitebox and blackbox methodologies. Whitebox testing results demonstrate that the system can operate effectively, as indicated by calculations of V(G) and Cyclomatic Complexity (CC). Blackbox testing, conducted with sample tests, also indicates that the system functions as expected and efficiently. In conclusion, the system developed in this research can significantly assist users, particularly farmers, in diagnosing diseases in cocoa plants. The expert system for diagnosing cocoa plant diseases can be relied upon and operates effectively.
Analisis Komparasi Algoritma Data Mining Naive Bayes, K-Nearest Neighbors dan Regresi Linier Dalam Prediksi Harga Emas

The results of implementing Orange Data Mining for forecasting the value of the Gold Price are displayed on the Test and Score widget. RMSE and MAE values were obtained from each model from the test. The RMSE and MAE values for the K-Nearest Neighbor (K-NN) method are 0.007 and 0.006, respectively, while for the Support Vector Machine (SVM) method are 0.006 and 0.005. The RMSE and MAE values for the Linear Regression method are 0.004 and 0.003, respectively. Compared to the K-Nearest Neighbor and SVM methods, the Linear Regression method is the best at predicting changes in Gold prices based on the RMSE and MAE data mentioned above. For future research, this best practice method needs to be studied more deeply. It is recommended for future research to compare the Linear Regression method with alternative approaches using the Orange tool set or other related tools.