Reviewerly/exHarmony huggingface dataset:
DEVELOPMENT OF TEACHER'S PROFESSIONALISM IN THE CONTEXT OF INNOVATIVE PROCESSESP

The aim of the article is to analyze the development of professional qualities of teachers in the context of innovative changes. The article provides statistical information on the functioning of the general secondary education system in Ukraine. The auth
Based on CiteSpace Artificial Intelligence Application in the Teaching Evaluation were Reviewed

Artificial intelligence is widely used in many fields, including education. Artificial intelligence is an important application field in educational guidance, management, evaluation, etc. Through the systematic review and analysis of artificial intelligence theory, it is applied to the study and life evaluation of college students. Therefore, in the past 5 years (2015-2022), this paper has published literature collection database of Science Network (WOS) and searched relevant literature published on CNKI. Found a total of 2336 papers, with the aid of CiteSpace clustering analysis function, keywords co-occurrence and time zone map system analysis. Can be seen from the analysis in the study, in most studies, artificial intelligence application in the education behavior behind the pedagogy less well, at the same time, discovered the formative assessment AI seems to be the evaluation mainly USES. Artificial intelligence (ai) in the evaluation of teaching is a main function of student to carry on the automatic grading. Using CiteSpace countries, institutions, and artificial intelligence research topic is analyzed, in order to get the research field of artificial intelligence and hot spots, the application of artificial intelligence in education evaluation, in turn, provide reference for subsequent research.
Vocational Students’ Core Competence in a Higher Vocational College in China

This paper first analyzes the background of the research on the cultivation of the core ability of higher vocational students. Outline the main questions that need to be explored in depth in this study. Discuss the statement, scope and definition of the problem and its implications. The study aims to make an assessment of the vocational core competencies of students as regards to their basic professional competence, professional interpersonal relationship and team cooperation ability, rational thinking and decision-making ability, and their personality ability. Based on the findings, the study will propose an output to enhance the instruction program for vocational training of students.
Practical Exploration of Project Teaching

Project teaching is a brand-new concept and way in undergraduate English education and teaching activities, and project teaching is equally important in undergraduate English teaching activities. This kind of education teaching way requires teachers to change the original concept of the form of education, get rid of teaching teaching form, to let the student maximum to participate in the classroom teaching, to let students in their own actual participation and participate to master the content of the classroom, their induction and summary need to master the content of each section. Teachers in the classroom only play the role of guidance and supervision, grasp the teaching progress, classroom atmosphere, the direction of the subject, finally let the students can under the guidance of the teacher, to find the results, to practice the results, to show themselves and self-evaluation, and in the process of exercise ability.
Evaluating the importance of nodes in the urban logistics UAV distribution network based on complex network theory

With the rapid development of unmanned aerial vehicles (UAVs) in urban logistics distribution in recent years, it demonstrates that the use of UAVs in this field will realize network operation in the future. However, identifying sites with high importance in the urban logistics UAV distribution networks is a crucial problem in developing this field. To address this, we construct a directional weighted network model of urban logistics drone distribution using basic knowledge of complex networks, with cargo flow between sites as the side weights. Classical statistical characteristic quantities of urban logistics UAV distribution networks are extracted as the evaluation indexes for key node identification in the network. The TOPSIS comprehensive evaluation method is applied to construct the evaluation system of network node importance. Using Chengdu Gaoxin South District as an example, the importance ranking of sites in this zone's urban logistics UAV distribution network is obtained, and suggestions are given on the order of site opening. The identification of key areas is of great reference value for the future development of urban logistics UAV distribution networks.
MillenniumDB: An Open-Source Graph Database System

Abstract In this systems paper, we present MillenniumDB: a novel graph database engine that is modular, persistent, and open source. MillenniumDB is based on a graph data model, which we call domain graphs, that provides a simple abstraction upon which a variety of popular graph models can be supported, thus providing a flexible data management engine for diverse types of knowledge graph. The engine itself is founded on a combination of tried and tested techniques from relational data management, state-of-the-art algorithms for worst-case-optimal joins, as well as graph-specific algorithms for evaluating path queries. In this paper, we present the main design principles underlying MillenniumDB, describing the abstract graph model and query semantics supported, the concrete data model and query syntax implemented, as well as the storage, indexing, query planning and query evaluation techniques used. We evaluate MillenniumDB over real-world data and queries from the Wikidata knowledge graph, where we find that it outperforms other popular persistent graph database engines (including both enterprise and open source alternatives) that support similar query features.
Near Real-Time Crime Detection Using Intelligent Drone Capture and CNN’s

Crime has grown to become a preeminent issue in today’s society, creating a problem for the common man and governments. There are instances where the felon cannot be convicted due to insufficient evidence and sometimes the incident is not even reported. The current law enforcement agencies lack the manpower and technology to combat this. Here lies the incentive to create a system which once automated, can survey a crime-ridden area to capture footage and on the occurrence of a crime, notify the concerned authorities. The proposed model in this paper contains a drone or UAV which is programmed to monitor a locality or town. The camera on the drone captures the frames in which a crime has occurred and sends selected frames to the server (backend) or the CNN. Post training and testing the CNN model, its core competency is to detect whether a crime has occurred in the frames or images received in near real-time. The images from the UAV are also processed within the drone via the facial recognition module using OpenCV. This framework introduces the integration of a Tello Py DJI drone with a facial recognition module and a Dense-Net 121 convolutional neural network.
THE USE OF CROSSWORD PUZZLES TO INCREASE STUDENTS' VOCABULARY MASTERY

This research aims to determine whether the use of Crossword Puzzles can increase Vocabulary of SMP Alkhairaat Tandaigi. This is research using a quasi-experimental research design. In selecting the sample, the researcher used a purposive sampling technique. The research samples were class VIII A as an experimental group and class VIII B as a control group. The instrument of data collection was divided into a pretest and a posttest. The data gathered were analyzed statistically. The results of the data analysis show that the mean score of both tests where the mean score of the experimental group improved from 63.93 to 73.33, and the control group's mean score improved from 63.17 to 68.56. The result showed that the value of t-counted (2.176) was greater than the value of the t-table (1.683) by applying a 0.05 level of significance and the degree of freedom (df) 22+21-2= 41. It could be concluded that the research hypothesis is accepted. In other words, Crossword Puzzles could increase vocabulary of grade VIII students at SMP Alkhairaat Tandaigi.
Issues of Metaphoric Competence Formation at ESP Classes

This work deals with the problem of metaphorical competence formation for students majoring in economics at ESP classes. The author describes the specifics of metaphoric competence and functions of metaphor within economic discourse. The analysis of the obtained competence in using metaphorical units as well as the types of mistakes that cause difficulties in professional communication is carried out, approaches and exercises are proposed to overcome the difficulties of forming metaphorical competence not only through classical exercises, but also with the involvement of automatic translation systems and ChatGPT.
Classification of Mask Use during a Pandemic using the CNN Algorithm with Voice Notifications

Various technologies were created to prevent the threat of the Covid-19 virus, which has spread in many countries including Indonesia. One of them is the use of masks in public places. With this in mind, this study aims to detect facial objects. Based on the Kaggle website, the object used for research is a human face in 2D form. This research consists of two stages, namely creating and testing a model. The model is a system that detects and classifies faces with masks, inappropriate masks and without masks. Then the model is tested for its accuracy. The result of thirty trials, the model has an accuracy of 99% which is tested using a webcam in real time. This model has a sound indicator which is a notification to faces using the Convolutional Neural Network (CNN) algorithm method.
Transfer Learning-Based Machine Learning Approach to Solve Problems of E-commerce: Image Search

The online fashion market is growing all the time, and a method that can recognize clothes can help companies in the clothing sales industry understand the profile of potential buyers, focus on sales that target specific niches, create campaigns based on customer tastes, and make the user experience better. Artificial intelligence systems that can read and label people's clothes are needed, and they could be used to boost sales or learn more about customers. Convolutional neural network models have been shown to be effective in picture c1assification. In this study, we offer a novel approach for classifying fashion article photos. To categorize photos in the Fashion-MNIST dataset, we used transfer learning using convolutional neural network-based VGG-16 architectures. We suggested several convolutional neural network topologies and employed batch normalization and residual skip connections to make the learning process easier and faster. On the Fashion-MNIST benchmark dataset, our model performs well. Comparisons demonstrate that our suggested model outperforms current state-of-the-art systems by around 3%. The end result is a revolutionary picture recognition and feature extraction method with a high classification accuracy of 90% that is stable and robust enough to be employed by a Fashion-MNIST data set.
The Effect of Using Storytelling On Student’ Speaking Skill at the Eight Grades of SMPN 28 Muaro Jambi

Purpose of the study: Storytelling can help the learners becomes more confident to express their ideas spontaneously and creatively. So, the researcher thought that may be this technique could help the researcher to solve the students’ speaking problems. The researcher gave a story and asked the students to retell the story with their own expression and language.&#x0D; Methodology: This research used quantitative design. This research was to find out the effect of using storytelling on students’ speaking skill. It was experimental research. The best type of testing hypotheses about cause effect is experimental research. It used quasi experimental design with were chosen two classes as two groups.&#x0D; Main Findings: Storytelling have positive effect toward students’ speaking ability. The result of the data analysis indicated that the students’ speaking skill in terms of pronunciation, grammar, fluency, and vocabulary have increased from the pretest to posttest. The result of posttest in experimental class is higher than in control class.&#x0D; Novelty/Originality of this study: The result of this research was expected to provide some significance and contributions in teaching and learning speaking English that had useful information. For students, storytelling could get input to develop students’ ability in speaking. Students also learned how to speak English well by storytelling.
Unlocking the Power of Schema Theory based Pre-Reading Activities: Enhancing Reading Comprehension at the Intermediate Level

The study evaluated the efficacy of schema theory-based pre-reading activities in enhancing intermediate-level reading comprehension. The study was conducted solely on first-year English students at GHSS Togh Bala Kohat. The study involved 60 first-year students, divided into two groups of 30 participants each. The study employed two groups, a control group and an experimental group. The experimental group underwent five English lessons utilizing schema theory-based brainstorming activities while the control group received traditional instruction. Pre- and post-tests were administered to students to evaluate their performance and assess the outcomes of schema theory-based pre-reading exercises. The collected data were analyzed through SPSS. The study revealed that incorporating schema theory-based pre-reading exercises in teaching resulted in superior academic performance of students compared to those who were not exposed to such activities. After a period of four months, retention tests were conducted once more. The findings indicated that Schema-based pre-reading exercises improved students’ performance.
Rapid Onsite Evaluation for Specimen Adequacy and Triage of Breast Masses in a Low-Resource Setting

Rapid onsite evaluation (ROSE) is critical in determining sample adequacy and triaging cytology samples. Although fine-needle aspiration biopsy (FNAB) is the primary method of initial tissue sampling in Tanzania, ROSE is not practiced.To investigate the performance of ROSE in determining cellular adequacy and providing preliminary diagnoses in breast FNAB in a low-resource setting.Patients with breast masses were recruited prospectively from the FNAB clinic at Muhimbili National Hospital. Each FNAB was evaluated by ROSE for overall specimen adequacy, cellularity, and preliminary diagnosis. The preliminary interpretation was compared to the final cytologic diagnosis and histologic diagnosis, when available.Fifty FNAB cases were evaluated, and all were adequate for diagnosis on ROSE and final interpretation. Overall percentage of agreement (OPA) between preliminary and final cytologic diagnosis was 84%, positive percentage of agreement (PPA) was 33%, and negative percentage of agreement (NPA) was 100% (κ = 0.4, P < .001). Twenty-one cases had correlating surgical resections. OPA between preliminary cytologic and histologic diagnoses was 67%, PPA was 22%, and NPA was 100% (κ = 0.2, P = .09). OPA between final cytologic and histologic diagnoses was 95%, PPA was 89%, and NPA was 100% (κ = 0.9, P = <.001).False-positive rates of ROSE diagnoses for breast FNAB are low. While preliminary cytologic diagnoses had a high false-negative rate, final cytologic diagnoses had overall high concordance with histologic diagnoses. Therefore, the role of ROSE for preliminary diagnosis should be considered carefully in low-resource settings, and it may need to be paired with additional interventions to improve pathologic diagnosis.
Utilizing Longitudinal Chest X-Rays and Reports to Pre-fill Radiology Reports

Despite the reduction in turn-around times in radiology reporting with the use of speech recognition software, persistent communication errors can significantly impact the interpretation of radiology reports. Pre-filling a radiology report holds promise in mitigating reporting errors, and despite multiple efforts in literature to generate comprehensive medical reports, there lacks approaches that exploit the longitudinal nature of patient visit records in the MIMIC-CXR dataset. To address this gap, we propose to use longitudinal multi-modal data, i.e., previous patient visit CXR, current visit CXR, and the previous visit report, to pre-fill the "findings" section of the patient's current visit. We first gathered the longitudinal visit information for 26,625 patients from the MIMIC-CXR dataset, and created a new dataset called Longitudinal-MIMIC. With this new dataset, a transformer-based model was trained to capture the multi-modal longitudinal information from patient visit records (CXR images + reports) via a cross-attention-based multi-modal fusion module and a hierarchical memory-driven decoder. In contrast to previous works that only uses current visit data as input to train a model, our work exploits the longitudinal information available to pre-fill the "findings" section of radiology reports. Experiments show that our approach outperforms several recent approaches. Code will be published at https://github.com/CelestialShine/Longitudinal-Chest-X-Ray.
Digitalisation of Revenue Laws in Pakistan

Data The computerization of land records and the introduction of new administrative models have greatly improved public access and control over land records in Pakistan. However, an ongoing problem faced by many landlords on a daily basis is the challenge of 'long distance loading', which could be solved by vertically extending the Arazi Records Center to the union council level. Increase. Research findings show that digitizing land registry services is costly and inaccessible to relevant authorities when needed. In addition, informal payments and lengthy procedures remain prevalent. To address these issues, it is recommended that authorities initiate awareness campaigns at the village level and regularly monitor personnel to improve existing systems.
Pickleball Sound 101 - The Statistics of Pickleball Sound and a Recommended Noise Standard for Pickleball Play

Sound from a pickleball game is a random series of impact sounds each time a paddle strikes the ball. The sound level from these impacts varies depending on the paddles and balls used, the skill of each player, and the force of each impact. A simplified measurement method and a common metric were used to measure the time varying nature of pickleball impacts as individual events. The sound measured from pickleball play exhibited a normal distribution that allowed statistical techniques to be applied to these measurements. Estimates were made of the percentage of time that maximum sound levels would be exceeded. Current noise ordinances fail to quantify the annoyance from these short duration random impacts. This results in measured pickleball sound levels that are not a noise violation but remain a source of complaints from nearby residents. Noise limits for pickleball play are proposed using this common metric so that pickleball sound can be effectively quantified and managed.
LocoSpot – Smart Tourist Guide

The idea of creating an Android travel application with a retrieval-based chatbot that can assist users is investigated in this study. Our system provides reliable and accurate information on every tourist site in Pune, together with an online map. The recommended design will also incorporate a retrieval-based chatbot system, which will allow it to assist those in need and make the programme more user-friendly by providing text guidance so that users may communicate with the bot. We discovered that several websites provide various services. Websites provide booking services, but there is no method for travellers to find potential destinations.This bot will only react to questions regarding the programme and point users in the right direction so they can use it without any trouble. Our strategy will encourage all other travellers to use the easy routes and dramatically increase customer satisfaction and retention.The result of the project is an Android application with a chatbot that suggests hidden local tourist spots, providing an engaging and interactive experience for travellers seeking unique destinations. The application improves its responses and features location-based services and user authentication for personalized recommendations.
Attendance System Using Face Detection and Face Recognition in Python Programming Language

The programming language Python is gaining popularity. It has a fairly flat learning curve and is a free, high-level language. It features a large selection of free libraries. The first topic covered in this study is computer vision libraries. The capabilities of the existing libraries for face detection and identification are next examined. The algorithm utilised in the libraries is provided a basic description. An example of the generated image is given for each significant stage. Even though the study only includes two sample photographs, the technique was tested on a large number of images. The investigation proved that Python is the go-to programme for tasks requiring face recognition and detection.
Secure Data Storage System and Data Leakage Detection

Data transmitted across these networks must be secure and private given how large and rapidly expanding they are. Cloud servers are a key resource for data storage. Therefore, cloud servers must be protected and cannot be left open to the prospect of being utilized by hackers for theft or exposure. They require strategic plans for this to guarantee the data's security and privacy. The solution being proposed makes use of three approaches to guarantee data security. The plans involve data encryption, data distribution across several clouds, and granting data sharing authenticity by using a secret key alone. The system is first set up to allow data sharing across a secure channel of encryption using the Lightweight method. After that, data is dispersed among several clusters using the DROP technique, and data is replicated between clouds to prevent any loss. Only a third private key can explicitly grant those with a need for the information access to various data segments. Any unethical request to share data is detected by a trapdoor, which blocks the request and identifies the individual responsible for any data leakage.
Technologies Based on Phototrophic Microorganisms As a Promising Way to Achieve Carbon Neutrality in Urban Agglomerations

Today, a significant part of the world’s population lives in urban agglomerations. A high building density, a large number of vehicles, and industrial enterprises negatively affect both the air quality in the city itself and the climate in general, releasing a significant amount of carbon dioxide. In this regard, there is a need not only to revise the structure of urban developments and strategies for their greening, but also to propose new technologies that radically change the ecological situation. In this paper, solutions using phototrophic microorganisms are considered as such a technology. It is shown that photobioreactors for their cultivation can be successfully integrated into urban systems, while in addition to air purification, the problem of surface wastewater treatment for their further use can also be solved. A wide range of products obtained from the biomass of phototrophic microorganisms significantly increases the economic attractiveness of this approach. Modern technologies in the field of the Internet of Things make it possible to successfully integrate photobioreactors into the urban digital environment.