Reviewerly/exHarmony huggingface dataset:
The Evolution of Information Security Strategies: A Comprehensive Investigation of INFOSEC Risk Assessment in the Contemporary Information Era

In the contemporary era marked by the extensive utilization of data, information systems have been extensively embraced by global organizations and also hold a pivotal position in national defense and various other domains. The growing interconnectedness between individuals and diverse information systems has resulted in an intensified emphasis on the evaluation of potential risks. The mitigation of these dangers extends beyond simple technological solutions and includes established standards, legal structures, and policies, adopting a complete approach based on safety engineering concepts. This study aims to develop a robust framework for the harmonization of Information Technology Security Standards. It will explore prevalent techniques for conducting risk assessments and differentiate between quantitative and qualitative approaches to evaluation. Moreover, this study illustrates the combination of quantitative and qualitative evaluation methodologies, providing a comprehensive framework for the analysis and design of risk assessment. In addition, this study advances our understanding of INFOSEC risk assessment and contributes to the advancement of more efficient information security strategies by sharing global perspectives, addressing challenges in classification, clarifying the incorporation of Information Security Management Systems (ISMS), and highlighting the significance of Artificial Intelligence in the domain of Information Security (INFOSEC).
A Multi Document Summarization of Learning Materials using Bigram Embedding Technique and Integer Linear Programming

In the present era of the Internet, teachers and learners are heavily inclined to use e-learning systems for an efficient learning process. Due to the proliferation of educational text contents in these e-learning systems, the need for incorporating advanced text analysis tools and techniques are becoming inevitable. Multi Document Summarization (MDS) is a technique for producing concise summaries from a collection of related text documents. The usage of MDS in the context of e-learning is more promising for providing summaries for learning materials which helps students and teachers to focus on key concepts of the learning materials. In this paper a semantic approach towards the learning material summarization is proposed based on bigram embedding and ILP technique. This approach considers bigram as the basic meaningful semantic unit of the sentences to understand and summarize documents. Embedding techniques are employed to learn the vector representation of phrases to semantically identify similar phrases to reduce the redundancy and improving coherence. Using ILP technique, the summaries were generated by selecting important sentences while reducing the redundancy using phrase vectors. Experimental results on newly created educational dataset (EduSumm) shows better performance compared to the baseline systems.
Linear Optics Quantum Information

This chapter is an introduction of quantum information processing in the linear optics platform. I describe the mainstream methods to encode quantum information with different degrees of freedom of photons and generate photonic entanglement. I then introduce how to induce on-demand evolutions of photonic-encoded qubits and quantum information, with a stress on the imaginary-time evolution method widely used in this thesis. I conclude this chapter by presenting the techniques of implementing effective readout of quantum information from different degrees of freedom of photons. In an accompanying Appendix, I use a case study to exemplify how to combine the techniques into a proof-of-concept quantum information experiment.
Explore the role and emphasis of K-Means, Decision Tree and Distance Based algorithms in data exception detection

Abstract K-Means, Decision Tree and Distance-Based algorithms are 3 important ways of classifying data. These three algorithms have different methods and focus on data classification. Therefore, they are always applied into different scenarios. K-Means algorithm is to divide three-dimensional data or two-dimensional data into several clusters to facilitate subsequent data processing and analysis. Decision Tree is based on the “tree” structure to make decisions. It is an important classification and regression method in data mining technology. It is a prediction analysis model expressed in the form of tree structure (including binary tree and multi tree). When it comes to the Distance-Based algorithm, it is a common anomaly detection method applicable to various data domains. It defines outliers based on the nearest neighbor distance. The purpose of this paper is to explore the kernel of three anomaly detection algorithms through an example of data anomaly detection. Therefore, in this paper, all three algorithms’ commonalities and differences will be discussed and illustrated through a case of data exception handling.
Enhancing Autonomous Drones With Self- Designed Payload Dropping Mechanism

This research paper provides a comprehensive exploration of an autonomous drone experiment integrating the Pixhawk 2.4.8 flight controller. The study offers a detailed analysis of a drone system characterized by a 200-gram payload capacity and a maximum flight duration of 13 minutes. The CAD model, meticulously designed using Dassault's SolidWorks Design Tool, incorporates carbon fiber propellers to optimize both durability and flexibility. One noteworthy contribution of this research is the introduction of a self-designed payload deployment mechanism, further extending the drone's capabilities. Additionally, specialized landing equipment is developed to enhance takeoff and landing stability, thereby elevating overall system performance. The study emphasizes the drone's precise control and navigation capabilities, made possible by its robust processing capacity and integrated sensors. Leveraging the computational prowess of the Raspberry Pi 4B, this project efficiently manages complex algorithms crucial for autonomous operations, all while maintaining cost-effectiveness. The Raspberry Pi's high-resolution capabilities and seamless integration prove to be the optimal choice for accurate object detection, environmental recognition, autonomous navigation, and successful payload deployment missions. This research contributes valuable insights into the integration of advanced technologies in autonomous drone systems, with a particular focus on enhancing their capabilities through self-designed payload deployment mechanisms.
Measuring 3D Vibrations Amplitude with a Single Camera and a Model of the Vibrating Structure

We propose a method to measure the vibrations amplitude of normal modes of a 3D mechanical structure with only one camera. Our method requires only a video sequence taken by a single camera and a collection of admissible 3D deflection shapes. The deflection shapes are projected in the image frame of the camera. This is done thanks to a linearization of the perspective projection model. Comparing the motion of targets seen by the camera and the motion of 2D deflection shapes at the same location gives the time evolution of modes amplitude. Finally, the motion of the model is reconstructed in 2D in the image frame and in 3D in the world frame. By following this procedure, vibration amplitude can be magnified applying a scale factor on a modal basis covering a large frequency bandwidth.
Study on the Reading Classroom of Business English Majors in the Mixed Teaching Mode of Online and Offline

The mixed teaching mode combi ning online teaching and offline teaching has been gradually applied to various fields of education in our country. Therefore, based on the mixed teaching mode of online and offline, this paper takes the reading classroom for business English majors as the research object, analyzes the current situation of reading classroom for business English majors in China, and explores the new paradigm, new situation and new path brought to reading classroom for business English majors under the background of mixed teaching. This paper focuses on the importance of combining tradition and modernity, and the unity of teachers and students in the classroom teaching mode of business English major reading, so as to provide a more perfect teaching mode and method for business English reading classroom in China.
Research on the Construction of E-commerce Teaching System in Higher Vocational Colleges from the Perspective of School Enterprise Linkage

In recent years, the development of e-commerce has been rapidly changing, and the application of e-commerce in various industries has also deepened. However, many vocational colleges have not been able to effectively follow the pace of enterprise job demand in cultivating e-commerce talents, resulting in insufficient integration of talent cultivation with enterprise positions. Therefore, this article mainly analyzes the value of constructing the e-commerce teaching system in vocational colleges from the perspective of school enterprise linkage, explores the problems of constructing the e-commerce teaching system in vocational colleges, and proposes problem-solving strategies such as building a teaching system that meets the requirements of enterprise positions, in order to achieve the cultivation of excellent e-commerce talents in vocational colleges.
Privacy-Enhanced Anonymous and Deniable Post-quantum X3DH

End-to-end encryption (E2EE) is widely used in instant messaging applications to protect data privacy. Forward secrecy (FS) and post-compromised security (PCS) are two essential features that aim to protect security when the session keys are compromised. Among E2EE applications, Signal is known for being the first one that guarantees FS and PCS concurrently by implementing the extended triple Diffie-Hellman (X3DH) protocol and double ratchet protocol. However, the original X3DH and double ratchet protocols cannot resist quantum attacks and require post-quantum implementation. While a post-quantum double ratchet protocol has been proposed, the issues of post-quantum X3DH protocols persist. Some post-quantum X3DH protocols are claimed to be anonymous and deniable. However, their anonymity only protects the communication content, not the identity key that can be distinguished. Additionally, their identity certificates must be delivered through a trusted channel during authentication. If these certificates are considered evidence, their deniability will be broken. To address these problems, we propose a solution that leverages ephemeral keys to hide the identity keys for enhancing anonymity. The identity is automatically authenticated without the trusted channel to exclude evidence for deniability.
Leadership Development Interventions, Job Satisfaction, and Leadership Effectiveness as Determinants of Organisational Performance in Saudi Transportation Sector

Organisational performance has always been the focus of firms to measure a firm’s progress and development. However, it was reported that the organizational performance in the Saudi transportation sector is still lagging and below expectations. Hence, there is a need for Saudi transportation firms to improve their performance, which raises an important question of how to improve it. It is argued that leadership development interventions (LDI) such as coaching, mentoring and performance appraisal could improve organisational performance through increased leadership effectiveness and enhanced job satisfaction. This research examines the mediating effect of leadership effectiveness and the moderating effect of job satisfaction on the relationships between LDI on the organizational performance of Saudi transportation firms. A survey-based method was used to collect the data from 385 respondents at Saudi transportation firms. Multi-stage cluster sampling technique was employed. This study revealed that leadership development interventions (LDI) significantly influenced organisational performance directly and indirectly through the mediating role of leadership effectiveness. Further, the study found that the relationships between LDI, such as coaching and performance appraisal, are moderated by job satisfaction.
Training in Data Processing using Smart PLS Software

officers' limitations in their analysis of data at the population and civil registry service in Bandung. The majority of these issues are brought on by the apparatus's lack of knowledge and skill as well as the sparse availability of computers. The sub-district office does not have adequate data storage, and data management and display are not supported by technology. Implementation strategy using coaching and training. The instruction offered takes the form of fundamental knowledge on how to show district population data using Smart PLS. Its operations include instruction and support for using the Smart PLS application in the Cipadung Village to present and process data. To determine how well the trainees understood how to use the Smart PLS program, interviews and questionnaires were administered as part of the service. The customer assistance team provides clear and comprehensive explanations of the data display. The use of this Smart PLS software aids Kelurahan staff in comprehending and processing data. It is beneficial to sub-district authorities in their work with the taught apps.
Workshop Strategi Belajar Bahasa Inggris Bagi Mahasiswa di Universitas Islam Riau

The implementation of this service is motivated by the importance of mastering English in this day. Based on the facts in the field that the world of work demands English proficiency for applicants from all educational backgrounds. This is of course a concern for educators how to motivate students to like English from an early age. Therefore, the purpose of this service is to provide information about effective English learning strategies for Riau Islamic University students. The service team chose FKIP students as service participants on the grounds that they could increase their knowledge so they could master English well. It is hoped that FKIP graduates will be able to use their English language skills to get wider job opportunities and open up opportunities for them to be able to teach Indonesian to foreign speakers abroad. This activity was carried out online using a Google meeting which was attended by 29 semester 6 students. The service team divided the activities into 2 sessions, namely the first session was a presentation on English learning strategies and continued with a second session on motivating FKIP graduates with information on the benefits of mastering English for the world Work. The results of the dedication that has been carried out received a positive response from all participants. All service participants said that they gained additional knowledge about English learning strategies, were motivated to master English and increased their knowledge of mastering English vocabulary. So it can be concluded that the service mentioned above has provided benefits and knowledge about English, especially regarding English learning strategies for UIR FKIP students.&#x0D;
A GENERIC COMPUTER VISION TOOL FOR RECOGNISING HUMAN ACTIVITIES

A prominent application area in the domain of computer vision is human activity recognition, which involves automatically detecting people’s actions from video footage. In this paper, a generic decision support tool capable of performing human activity recognition by employing computer vision is developed. The objective of the decision support tool is to facilitate the analysis of video footage by learning to identify human activities from video footage. The decision support tool facilitates the processing of raw data, the training of a computer vision model in respect of the processed data, and the deployment of the trained computer vision model in respect of unseen video footage. This paper details a computerised implementation of the decision support tool in respect of a benchmark data set and real-world data set involving the cash replenishment process of a South African bank.
SECURITY ACCESS CONTROL EFFECTIVENESS DESIGN

South Africa’s infrastructure has faced a barrage of security attacks that has led to the promulgation of the Critical Infrastructure Protection Act (CIPA) No. 8 of 2019. Residual risk (i.e., that which remains after the threats have been mitigated) must be assessed for the critical infrastructure security system as part of the total security system design. One area that requires attention is access control. This paper demonstrates how to approach such a design, with a particular focus on the effectiveness of the access control system and how to choose the biometric or digital key (such as access cards) system. The approach starts by defining access control events that in turn are used to define access control effectiveness in respect of the probability of invalid access and of anomaly detection. The theoretically derived results are validated by a simulation. Based on these models, guidance is provided for the design of access control for critical infrastructure.
Analysis of Policy Applications of Artificial Intelligence in Education

Along with the continuous improvement of data processing and application capabilities, artificial intelligence has gradually penetrated into all areas of human production and life, driving human society into the age of artificial intelligence. At present, AI education is the trend of education innovation and development. The rise of artificial intelligence brings hope for the innovation and development of the education field. As an important pillar for the realization of a new country of science and technology and a strong country of talents, the state pays special attention to the requirements for the transformation of high-quality education by artificial intelligence when formulating policies and plans. The birth of artificial intelligence brings more possibilities for the modernization of education, and plays a solid foundation and promotes innovation in the fields of basic education, higher education and vocational education. The purpose of this paper is to analyze the application of the policy of Artificial Intelligence + Education in the field of education. It explains the strategic significance of the rise of AI in education, and explores the necessary means to collaboratively manage the risks of AI in education.This study will rationally analyze the AI educational applications and explore targeted risk avoidance strategies to safeguard the deep integration of AI and education.
Virtual Workplace and Job Satisfaction During Covid-19 Pandemic for Information Technology (IT) SMES in Riyadh, The Kingdom of Saudi Arabia

This research aims to contribute to the current body of knowledge through new findings on the virtual workplace arrangement for information technology in small medium enterprises, IT SMEs concerning job satisfaction during the pandemic Covid-19. Employee job satisfaction is one of the main keys to the success of an organization. However, current literature on the anecdotes and intriguing prescriptions on the relationship between virtual workplace-job satisfaction especially during a pandemic is vague. Therefore, the main objective of this study is to investigate the relationship between virtual workplace work arrangements and employees’ job satisfaction. The respondents are from selected IT SMEs in the manufacturing industry. The data was collected by using an online questionnaire for the employees. The data was analyzed using Statistical Package for the Social Sciences 25 (SPSS25). Results for employees during the Covid-19 pandemic for IT SMEs in Riyadh, The Kingdom of Saudi Arabia indicate that there is a positive relationship between virtual workplace work arrangement and job satisfaction. The novelty of this research is the contribution of the present body of knowledge. It is expected that the findings can be applied in another related study to improve SME employees’ performance and promote a sustainable industry. The results can be used to direct the progress of initiatives and policies that can increase the job satisfaction of employees and promotes The Kingdom of Saudi Arabia’s initiatives in achieving Saudi Vision 2030
Exploring the exhibition trends of IoT-based science experience centers for future education

The Internet of Things (IoT), poised to become a central information and communication technology (ICT) infrastructure in future societies, is increasingly recognized as a key national competency. As such, education is being tailored to nurture the human resources required for this future. This study aims to analyze experiential exhibitions at eight national science experience centers that attract over a million domestic and foreign visitors. The goal is to investigate whether the trend of experiential education using ICT-based IoT and the development of future talent, a national priority, align with the latest technology education. The study found that interactive exhibitions and ICT technologies are partially applied to domestic and international exhibitions, and hands-on education is conducted in line with technological trends. In Korea, various technology trends were found to be applied to exhibitions more rapidly and broadly than in other countries. The Science Experience Center can contribute to nurturing future talent and scientific literacy by sparking motivation and interest in science and technology, in line with government scientific policies and industrial trends.
Content Design for Multi-view Stereoscopic Video in Real Scene

Multi-view stereoscopic videos (MVS) have emerged as a powerful cinematic technique that enables filmmakers to capture scenes with a heightened sense of depth and immersion. This study examines the complexities of designing content for MVS, specifically in real-world environments. By analyzing existing research and practical experiences, this study seeks to contribute to the development of guidelines and recommendations for enhancing the quality and viewer satisfaction of multi-view stereoscopic videos.
A Study of Emotions and Attitudes of Non-English Majors toward Online Writing Assessment System

This paper takes non-English majors as the research participants to explore the characteristics of their emotions and attitudes, the influencing factors, their coping strategies, and the impact of the above aspects on their English writing learning during the online English writing assessment. Through conducting semi-structured interviews, the study found that: first, when non-English majors use online English writing assessment, their emotions and attitudes are affected by multiple subjective and objective factors, and are mainly positive; Second, the strategies used by non-English majors are mostly aimed at the lexical and grammatical errors in the text, and cover the skills of English writing; Third, the above aspects have played a certain role in promoting students’ English learning and improving their English learning and application ability.