Reviewerly/exHarmony huggingface dataset:
An Empirical Study of Cybercrime and its Prevention

As Cyber Security is Important factor in day-to-day life.Cyber Crime is also increasing rapidly like a rage of fire.Using the computer as an instrument to further illegal ends, such as committing fraud, stealing identities, violating privacy, hacking, website spoofing in today's world.In addition, Cybercrime have increasing accessibility using the smart technology accessing the multiple users for hacking to exploit.Smart technology allows people to connect with the world within seconds using online shopping websites, daily transactions etc.There are lots of advantages of Internet but there are disadvantages too such as Security issues, privacy fraud.I did a research survey through Google Form about cybercrime cases people faces in day-to-day life.I prepared a Google form with around questions and after that summarized the data to find out a conclusion.
Measuring Attribution in Natural Language Generation Models

Abstract Large neural models have brought a new challenge to natural language generation (NLG): It has become imperative to ensure the safety and reliability of the output of models that generate freely. To this end, we present an evaluation framework, Attributable to Identified Sources (AIS), stipulating that NLG output pertaining to the external world is to be verified against an independent, provided source. We define AIS and a two-stage annotation pipeline for allowing annotators to evaluate model output according to annotation guidelines. We successfully validate this approach on generation datasets spanning three tasks (two conversational QA datasets, a summarization dataset, and a table-to-text dataset). We provide full annotation guidelines in the appendices and publicly release the annotated data at https://github.com/google-research-datasets/AIS.
Evidence from United Arab Emirates universities on effective human resources policies for employee perceived performance

The current research is to ascertain the effect of human resources (HR) policies and procedures on employees. The study is based on the quantitative method. The employees at the United Arab Emirates universities are the selected audience. Google Forms was used to disperse the survey, where 100 responses were collected in this study. The questionnaire adopted a Likert scale of seven points. Tests such as factor loading, internal consistency, Convergent Validity (AVE), Discriminant validity, Coefficient of determination (R2) and adjusted (R2), Path Coefficient (β), and t-test through ADANCO were conducted. This research shows that performance evaluation of all other variables, such as compensation, promotion practices, training and development, and employee involvement in decisions, has a really beneficial impact on PEP. The current research helps universities to plan the practices of HR and increase the PEP of their teachers. This is because it has the potential to provide professors, academic leaders, and supervisors with fresh perspectives that will aid in the spread of knowledge and the efficient operation of the academic workplace. Employee turnover in UAE government agencies is affected by management style and a lack of employee empowerment, according to the study. There were signs that workers' distaste for centralized leadership influenced their desire to remain with their current employers. Many research papers have been done on this topic in developed countries. However, none of these studies has been accomplished.
Input Process Output (IPO) AI Chatbot as Personal Learning Assistant for Programming Coursework

Social network services (SNS), such as Telegram, plays an important role as a platform for the students and teachers as most students in programming courses currently lack support to communicate outside the classroom. Conversational agent or Chatbot is integrated into SNS can be the ideal teacher assistants to answer and propose personalized questions to students. The proposed AI Chatbot application helps students analyze programming related problems using the Input-Process-Output (IPO) analysis was fully utilized, viewed and later documented by ten selected students based on standardized test scores. UTAUT model was used to measure the acceptance of newly introduced Chatbot. The findings demonstrate that the students had a positive perception of performance and effort expectancy, attitude, social influence, facilitating conditions, self-efficacy and behavioral intent while the anxiety constructs are low. The result indicates the need for a fully functioning IPO Chatbot consisting of solutions to programming questions involving other control structures.
Competencia digital docente en Educación Primaria: una investigación narrativa

Information and Communication Technologies make up a key element in today´s society, a fact that means that in the educational sector it is essential to meet and respond to the digital demands of students. The continuous social transformations must be appreciated and worked from the schools, being the teachers the one that has the responsibility of presenting updates in the thoughts and knowledge, offering methodologies, strategies, and resources in the new digital age. Given this approach, the main objective of the research’s is to know and understand what is the technological preparation that Primary Education teachers receive to develop digital teaching competence, pretending to know what reasons are those that incite technological work in the classroom. For this, a qualitative study is carried out that is developed from the narrative methodology, that is, from the voice and experience of an active teacher to make an approach to the reality that encompasses the digital phenomenon in teacher training. The results are offered through content nuclei that structure, in seven epigraphs, the most outstanding points by a teacher who appreciates educational technological preparation as a basis for professional development.
Big Data Optimization Analysis and Calculation of First Pass Rate of Special-shaped Curved Curtain Wall Keel Installation

The installation of special-shaped curved keel should not only be reliably connected with the main structure, but also meet the requirements of panel installation in the later stage of the curtain wall.Different professions have different construction precision, and there are inevitable errors in the construction process.Therefore, strict control of the first-pass rate of installation of special-shaped curved curtain keel is the key of curtain wall construction.In this paper, by making full use of BIM technology to optimize analysis and model program installation and construction, the first-pass rate of installation of special-shaped curved curtain wall keel is greatly increased from 76% to 92%.The successful application of this process provides reference for similar projects.
Features of the Policy of Branding Leading Russian Economic Universities

This article is devoted to the assessment of the development of communications of leading economic universities with all targeted audiences and the development of their brands, in order to increase noticeability in the global space, attracting a well -known professor, talented applications, organizing collaborations in the broadest sense of understanding the term. The authors conclude that it is impossible to rest on the laurels of historical fame and the established reputation, and the university brand, although it has a funded component in time, requires constant work on maintaining and improving.
Avaliação de Algoritmos de Aprendizado de Máquina para Predição de QoE em Redes 6G

This paper evaluates the performance of Machine Learning (ML) algorithms to provide Quality of Experience (QoE) user decisions in multimedia services. A specialized dataset was built for mapping network Quality of Service (QoS) Key Performance Indicators (KPIs) with video quality metrics to perform QoE predictions. An evaluation is then carried out considering the main regression models to support the development of QoE-aware systems and meet the critical requirements of applications characteristic of 6G scenarios.
Fast adaptive up scaling of low structured images using a hierarchical filling strategy

Due to the explosion of online and multimedia content, there is now an overwhelming quantity of information available in the form of still photographs, moving pictures, and sound recordings.As a result, there is a need for efficient and effective methods of storing and retrieving multimedia data like photos.Visual content is used to guide the search, navigation, and retrieval processes in Content Based Image Retrieval (CBIR).Images include information about the items they portray, such as their colours, textures, shapes, and locations.Colour, texture, and form are all examples of low-level qualities that can only tell you so much about an image's content.As a result, a semantic gap emerges between how pictures are understood visually and how they are represented using simple attributes.newline Using low-level traits and their combinations, researchers from all across the globe are attempting to bridge this semantic divide.We identify a number of issues with current low-level features and retrieval methods, and we offer some potential fixes.newline As the volume and diversity of photos in a Content Based Image Retrieval system's database grows, the system's accuracy tends to decline.This may lead to the retrieval of pictures that seem similar but convey distinct semantic notions.In addition, precise picture segmentation is necessary for form feature extraction.However, since segmenting images remains an open problem, extracting shape features is not very trustworthy.To address these issues, this article proposes a CBIR that employs a multistage retrieval technique.newline A picture's low-level details might be either regional or worldwide.Both global and local characteristics may be retrieved from a picture, with the former relying on the whole frame and the latter on only a small section of it.CBIR systems that rely on regional traits are known as RBIRs.In most cases, an RBIR system's accuracy exceeds that of its comparable global CBIR.There is a need for precision in question formulation and a longer response time in conventional RBIR systems.
Support as a training tool: philosophical and methodological aspects

Introduction . The work of the school in the context of distance learning is complicated by the virtualization of subject-introductory activities, the decrease in the effect of the teacher's guiding, orienting influences of the educator, and the increased dependence of learning outcomes on self-organization and self-control. Purpose setting . Based on the experience of developing visual logical-semantic models and using them as visual didactic regulators, the task was to determine the regulatory framework for the actions of these didactic tools. Methodology and methods of the study . The study applied: the method of "reverse engineering" – the construction of a theoretical description of the real result; visualization method of logical-semantic modeling of knowledge; the fundamental principle of visualization and the principle of improving educational cognitive activity with the help of supports and regulators. Results . The function of supports and regulators to aid the regulatory component of educational cognitive activity is substantiated. Provisions are formulated that link the law, the theoretical principle and the practical function of visualization with the empirical law of educational cognitive activity, which implies the dominance of subject-introductory actions in the formation of an image-representation of the object or process being studied. Conclusions . A theoretical and methodological substantiation of the regulative foundations of actions and the regulative component of educational cognitive activity is proposed. The use of supports and regulators of a logical-semantic type in classroom-distance learning is shown.
Examining the Role of Breadth and Depth of Vocabulary Knowledge in Reading Comprehension of English Language Learners

This study explored the effect of English language learners’ breadth and depth of vocabulary knowledge on their understanding and grades of reading English texts. Sixty-one Jordanian EFL undergraduates were assigned three tests, which were the Vocabulary Levels Test Version 2 (VLT), the Word Associates Test (WAT), and Academic International English Language Testing System (IELTS). The collected data was analysed utilizing Pearson correlation analysis and multiple linear regression. According to the empirical outcomes, breadth and depth of vocabulary knowledge correlated positively with each other and with reading comprehension. Further, the significant predictor of the overall variance of reading comprehension was vocabulary depth, while the breadth of vocabulary knowledge was the less significant one. The results demonstrate the importance of expanding and deepening EFL learners’ vocabulary knowledge in classrooms. Keywords: Vocabulary Depth, Vocabulary Breadth, Depth of Vocabulary Knowledge, Vocabulary Levels Test, Reading Comprehension.
Perpustakaan Sebagai Pilar Merdeka Belajar-Kampus Merdeka: Telaah Kepuasan Pengguna Perpustakaan Perguruan Tinggi Dengan Structural Equation Modelling

&lt;p&gt;This study examines the impact of university library performance, service quality, and leadership support on user satisfaction at the Muhammadiyah University of North Sumatra. This study employs a sample of 380 students from nine faculties with data analysis techniques using SmartPLS. The study results prove that library performance, service quality, and leadership support significantly influence library user satisfaction. Service quality is an essential predictor of library user satisfaction. The leadership support becomes a quasi-moderation that strengthens library performance, service quality, and library user satisfaction. Consequently, users are satisfied with the services provided by the UMSU library and will help decision-makers to provide more support for library management in the future. The authenticity of this study provides knowledge about UMSU library's strategies in comprehensively using library performance indicators and service quality to increase user satisfaction and support the implementation of MBKM.&lt;/p&gt;
Inovasi Taman Bacaan Masyarakat (TBM) Pena Ananda Dalam Memberikan Layanan Informasi Kepada Masyarakat di Tengah Pandemi Covid-19

The government's policy to respect and avoid crowds in the form of killing the spread of the corona virus that occurred throughout 2020, had an impact on system changes in various aspects of public services and information to the public. Likewise, the service at the community reading park (TBM) has the main function as a means of independent learning for the community and as a support for informal education programs. This study aims to determine the innovation of TBM Pena Ananda in providing information services to the public through various innovative activities and services that are online. This research method uses descriptive qualitative methods with data collection techniques through observation, interviews and documentation. The results showed that the innovation of information services to the community at Pena Ananda TBM was carried out through system changes from offline to online such as exclusive writing training activities, poetry day echo talk shows, online reading rally, garbage magic from home, group talk, children's song creation workshops, writing creative, happy home learning August, 21st century children's talk room, vibrant pandemic with children's songs, children's films in the industrial revolution, thought process together, discussion together, junior writing class online, educational article writing competition, volunteer talk through applications zoom.
Unit middleware for implementation of human–machine interconnection intelligent ecology construction

Abstract General speech recognition models require large capacity and strong computing power. Based on small capacity and low computing power to realize speech analysis and semantic recognition is a research area with great challenges for constructing intelligent ecology of the Internet of Things. For this purpose, we set up the unit middleware for the implementation of human–machine interconnection, namely human–machine interaction based on phonetics and semantics control for constructing intelligent ecology of the Internet of Things. First, through calculation, theoretical derivation and verification we present a kind of novel deep hybrid intelligent algorithm, which has realized speech analysis and semantic recognition. Second, it is to establish unit middleware using the embedded chip as the core on the motherboard. Third, it is to develop the important auxiliary tools writer-burner and cross-compiler. Fourth, it is to prune procedures and system, download, burn and write the algorithms and codes into the unit middleware and cross-compile. Fifth, it is to expand the functions of the motherboard, provide more components and interfaces, for example including RFID(Radio Frequency Identification, RFID), ZigBee, Wi-Fi, GPRS(General Packet Radio Services, GPRS), RS-232 serial port, USB(Universal Serial Bus, USB) interfaces and so on. Sixth, we take advantage of algorithms, software and hardware to make machines "understand" human speech and "think" and "comprehend" human intentions so as to implement human–machine interconnection, which further structure the intelligent ecology of the Internet of Things. At last, the experimental results denote that the unit middleware have very good effect, fast recognition speed, high accuracy and good stability, consequently realizing the intelligent ecology construction of the Internet of Things.
Analysis of Sobel and Laplacian Edge Detection Algorithms for Blue Plasma Lymphocytes in the Blood Smear of Dengue Fever Patients

The presence of Blue Plasma Lymphocytes in a patient's blood sample indicates that the person has been infected with dengue fever.Examination of the blue plasma lymphocytes is carried out under a microscope with visual observation.Blue plasma lymphocytes can now be observed using a computer due to an advancement in digital image processing technology.The computer process to find Blue Plasma Lymphocytes in digital images is edge detection3.Edge detection methods in digital images include the Sobel algorithm and the Laplace algorithm.In order to detect blue plasma lymphocytes, the proper algorithm must be chosen between Sobel and Laplace, so that the results obtained are more accurate.
Discussion on Classroom Teaching Reform under EGP+ESP Mode

In the context of globalization, enterprises no longer prefer people who just only are good at English, but more all-round talents.A simple teaching model cannot meet the current development.The EGP+ESP teaching mode has become the focus.This paper summarizes the problems of the existing EGP+ESP teaching mode, such as poor classroom teaching effects, imperfect practical teaching, unreasonable curriculum setting, nonstandard textbook construction, single talent training method, and insufficient teachers.At the same time, it puts forward corresponding countermeasures in curriculum planning, teaching content, teacher construction and practical teaching.
DETR-crowd is all you need

"Crowded pedestrian detection" is a hot topic in the field of pedestrian detection. To address the issue of missed targets and small pedestrians in crowded scenes, an improved DETR object detection algorithm called DETR-crowd is proposed. The attention model DETR is used as the baseline model to complete object detection in the absence of partial features in crowded pedestrian scenes. The deformable attention encoder is introduced to effectively utilize multi-scale feature maps containing a large amount of small target information to improve the detection accuracy of small pedestrians. To enhance the efficiency of important feature extraction and refinement, the improved EfficientNet backbone network fused with a channel spatial attention module is used for feature extraction. To address the issue of low training efficiency of models that use attention detection modules, Smooth-L1 and GIOU are combined as the loss function during training, allowing the model to converge to higher precision. Experimental results on the Wider-Person crowded pedestrian detection dataset show that the proposed algorithm leads YOLO-X by 0.039 in AP50 accuracy and YOLO-V5 by 0.015 in AP50 accuracy. The proposed algorithm can be effectively applied to crowded pedestrian detection tasks.
A Time Series Regression Model via Improved PCA and Bagging Algorithms

Considering the case that the prediction variable is a time series and the response variable is a continuous scalar, we propose a time series regression model based on improved PCA and Bagging Algorithms.Compared with PCA dimension reduction, the proposed method uses distance correlation coefficient matrix instead of Person correlation coefficient matrix, which makes the distribution assumption of original variables more free.Considering that PCA is an unsupervised dimension reduction technique and the connection functions between principal components and response variables are unknown, we propose to use Bagging Algorithmss to capture information of principal components related to response variables.In the actual data analysis, the comparative methods are LASSO and PCAbased linear models, and the empirical results show that the proposed method has certain competitiveness compared with the comparison method.Finally, because the base-model of Bagging Algorithms is model-free, some machine learning methods with higher precision and flexibility can be used as the base-model for data tasks with different complexity.
Research on the Current Situation and Improvement Path of the Industrial Awareness of Applied Talents

The "Guidelines for the Construction of the School of Modern Industry (Trial)" issued by the Ministry of Education and others in 2020 proposes that "Effectively Improve Student Students' Cognitive Awareness and Resolve Complex problems".It is the first time that the Ministry of Education's documents have proposed the concept of "industrial awareness".It shows that the awareness of the industry has a lack of talent training, affecting the growth of talents and industrial development.To this end, this article defines the connotation of the concept of industry cognition, analyzes the role of industrial cognition in talent training and growth.In addition, this article investigates the current situation of industrial cognition and analyses the reasons for the lack of industrial awareness.Finally, this article puts forward countermeasures and suggestions for the problems existing in the current industrial cognitive education from the three aspects of reconstructing the curriculum system, innovating the teaching organisation model, and strengthening industrial practice.
A phishing website detection system based on machine learning methods

In today's Internet age, phishing attacks are a common means of cyberattacks.Most existing URL-based anti-phishing technologies are simple and effective, but lagging, while machine learning and deep learning-based approaches can effectively improve detection efficiency.This study advocates the use of TF-IDF for website data preprocessing followed by a random forest model to achieve phishing website feature classification.The final experimental results show that the model accuracy of the random forest algorithm based on machine learning to judge phishing websites is high and the anti-phishing capability is superior.
Automatic interpretation of structural plane parameters in borehole camera images from drilling engineering using MOORA method

Drilling engineers in general Extraction and production of oil and gas Used by multinational corporations.Existing Safety measures for evaluation and maintenance of wells Design elements to ensure implementation and they are also responsible for estimating the cost of machinery and construction.The main educational qualification for them is Bachelor's degree in Geology or Mechanical but sometimes equivalent