Reviewerly/exHarmony huggingface dataset:
PSEUDO RANDOM KEY GENERATOR USING FRACTAL BASED TRELLIS CODED GENETIC ALGORITHM FOR IMAGE ENCRYPTION

Cryptographic applications such as online banking, and securing medical and military data require the usage of random keys, which should remain unpredictable by adversaries. This paper focuses on the strengths and limitations of the techniques and algorithms that are used in the generation of random keys and a new method to generate random keys is proposed using fractals. Fractals are generated using the Sierpinski triangle and fed as input for Non-Deterministic Finite Automata (NDFA) to generate an Initial Vector (IV). Trellis Coded Genetic Algorithm (TCGA) code generator generates seed value using IV as input. Pseudo-Random Key Generator (PRKG) generates a Session Key matrix (SKM) using a seed value. Images are encrypted using SKM to generate cipher images. The randomness of the TCGA code is tested using entropy measure and efficiency based on NIST Tests. SKM with high entropy value is used for image encryption. The Number of Pixel Change Rate (NPCR) and Unified Average Changing Intensity (UACI) values are used for calculating the randomness of cipher images.
Comprehensive Evaluation of Online Experimental Teaching Quality in Colleges and Universities Based on Support Vector Machine

Affected by the global COVID-19 epidemic, many universities in China have to carry out online experimental teaching. Online experimental teaching can fully realize retention of experimental teaching data, the maximum sharing of experimental teaching, and improve teachers’ ability to complete experimental teaching by mobile means through good network storage devices. Scientific and systematic evaluation of online experimental teaching quality can promote continuous improvement of online teaching activities, give full play to teachers’ teaching enthusiasm, improve comprehensive training quality of college students, and make online experimental teaching a new trend of experimental teaching reform. Based on existing literature, this study analyzes the factors affecting the quality of online experimental teaching, puts forward evaluation indicators of online experimental teaching quality, and uses support vector machine training evaluation system to establish evaluation model of online experimental teaching quality in colleges and universities. Experimental results show that evaluation indicator of online experimental teaching quality proposed is relatively perfect, and has good applicability and popularization. The method based on the support vector machine has improved evaluation effect of online experimental teaching quality in colleges and universities. Output evaluation results are highly consistent with actual evaluation results. Online experimental teaching quality evaluation results are very objective and comprehensive. Conclusions have important reference value for online experimental teaching behavior analysis, improvement of online experimental teaching quality evaluation indicators, reduction of online teaching quality evaluation errors, and improvement of online teaching quality evaluation effect.
ADVANCEMENTS IN CROWD-MONITORING SYSTEM: A COMPREHENSIVE ANALYSIS OF SYSTEMATIC APPROACHES AND AUTOMATION ALGORITHMS: STATE-OF-THE-ART

Growing apprehensions surrounding public safety have captured the attention of numerous governments and security agencies across the globe. These entities are increasingly acknowledging the imperative need for reliable and secure crowd-monitoring systems to address these concerns. Effectively managing human gatherings necessitates proactive measures to prevent unforeseen events or complications, ensuring a safe and well-coordinated environment. The scarcity of research focusing on crowd monitoring systems and their security implications has given rise to a burgeoning area of investigation, exploring potential approaches to safeguard human congregations effectively. Crowd monitoring systems depend on a bifurcated approach, encompassing vision-based and non-vision-based technologies. An in-depth analysis of these two methodologies will be conducted in this research. The efficacy of these approaches is contingent upon the specific environment and temporal context in which they are deployed, as they each offer distinct advantages. This paper endeavors to present an in-depth analysis of the recent incorporation of artificial intelligence (AI) algorithms and models into automated systems, emphasizing their contemporary applications and effectiveness in various contexts.
THE RELATIONSHIP BETWEEN THE CHARACTERISTICS OF SOFTWARE DEVELOPERS AND SECURITY BEHAVIOR INTENTION

Software security is integral to information security, requiring software developers to be aware of software security as implementers and information security as employees. Little is known about the impact of software developers’ characteristics on their information security behaviors. This study examined the relationship between software developer characteristics such as their application security awareness (AW), training, and self-efficacy (SE) and their information security behavior intention (SeBI). Data from a survey of 200 software developers in the United States were analyzed using correlational statistical methods. AW and SE positively correlated with SeBI, while application security training did not correlate. Developers’ AW and SeBI mean score was found to be poor. Information security managers should aim to improve software developers’ application security awareness and self-efficacy to help improve their information security behavior. Application security training infused with information security awareness and conducted by application security experts is recommended.
Manajemen Anestesi pada Kraniotomi Pengangkatan Tumor Meningioma dengan Riwayat Operasi Kliping Aneurisma: Studi Kasus

The co-existence of brain tumors with cerebral aneurysms is extremely rare, with an estimated incidence of 0,5-4,5%. The priority for surgical treatment of these two pathologies is not clear, where surgery on a cerebral aneurysm is sometimes performed initially before surgical removal of brain tumor. Treatment of brain tumors in patients with a history of clipping aneurysm has its own challenges in the field of anesthesia, where anesthetic action has the goal of reducing the risk of aneurysm rupture, preventing cerebral ischemia, and optimizing systemic function while facilitating surgical procedures. This case study reports on a 58-year-old woman who underwent surgical removal of a meningioma tumor with a history of aneurysm clipping. Aneurysm clipping surgery was performed 3 months before brain tumor removal. Patient with clinical headache and blurred vision in the right eye, without other neurological deficits. Anesthetic management is carried out with the target of preventing further increase in intracranial pressure, with adequate analgesia, proper brain relaxation techniques, and prevention of hypercapnia, hypocapnia, and hypoxia. In addition, blood pressure must be maintained by preventing hypotension or hypertension. At the end of the operation, the patient was extubated and transffered to the intensive care unit. On postoperative examination the patient was conscious, without seizures, and without neurological deficits.
NEAR ULTRASONIC ATTACK AND DEFENSIVE COUNTERMEASURES

The practical implications of issuing inaudible voice commands. The research mapped each attack vector to a tactic or technique from the MITRE ATT&amp;CK matrix, covering enterprise, mobile, and Industrial Control System (ICS) frameworks. The experiment involved generating and surveying fifty near-ultrasonic audios to assess the attacks' effectiveness. Unprocessed commands achieved a 100% success rate, while processed commands achieved an 86% acknowledgment rate and a 58% overall executed (successful) rate. The research systematically stimulated previously unaddressed attack surfaces, aiming for comprehensive detection and attack design. Each ATT&amp;CK identifier was paired with a tested defensive method, providing attack and defense tactics. The research findings revealed that the attack method employed Single Upper Sideband Amplitude Modulation (SUSBAM) to generate near-ultrasonic audio from audible sources. By eliminating the lower sideband, the design achieved a 6 kHz minimum from 16-22 kHz while remaining inaudible after transformation. The research also investigated the one-to-many attack surface, exploring scenarios where a single device triggers multiple actions or devices. Furthermore, the study demonstrated the reversibility or demodulation of the inaudible signal, suggesting potential alerting methods and the possibility of embedding secret messages like audio steganography. A critical methodological advance included tapping into the postprocessed audio signal when the server demodulates the signal for comparison to both the audible and inaudible input signals to improve the actionable success rates.
ANALYSIS OF THE USE OF NETWORK PARLANCE FROM THE PERSPECTIVE OF WORD FORMATION

Network parlance refers to the language that first became popular on the Internet and has a certain deviation from the conventional language. Under the birth of the network environment, today’s network parlance has developed into a new dialect. The characteristics of the network information age determine that the network parlance is not only very active in life but also can reflect social and cultural phenomena to a certain extent. From the perspective of sociolinguistics, this paper studies its origin and analyzes its characteristics from the perspective of word formation. The results show that the most frequently used word formation methods are functional shift and burrowing. From the perspective of the use trend in the past five years, the formation of network terms also shows the characteristics of diversification. Specifically, the frequency of using coinage and clipping is increased. This study holds that the word-formation of network parlance reflects the characteristics of the contemporary new language formation. That is, from the beginning of 2017, the expansion of the meaning of existing words and the absorption of other cultures gradually changed into the creation of new words and the use of short words simplified by existing words.
Data Security Concerns in Approaches to Overcome Cold Start Problem in Recommender Systems - A Survey

In the subject of recommendation engines, the cold start problem is a significant research topic.Due to a lack of knowledge about the user and/or services, the recommendation system is unable to predict the user's preferences or interested products, resulting in a cold start.Many people have sought to overcome the cold start problem in recommending generic domains such as music, movies, E-Commerce, and travel websites using different types of machine learning models.This work provides a survey of the most recent to the traditional methods used for solving the cold start problem and also provides a holistic view of the adversarial attacks that are possible on the machine learning models used while trying to solve the cold start problem using the machine learning models.
Harnessing Flask for Web Scraping and Sentiment Analysis: A Comprehensive Application for News and E-Commerce Reviews

With the popularity and growing availability of opinion rich sources such as reviews from e-commerce sites, choosing the right product from huge product brands is difficult for the user.In order to enhance the sales and customer satisfaction, most of the sites provide opportunity for the users to write review aspects about the product.These reviews are in text format and increase day by day.It is difficult for the user and manufacturers to understand the likes and dislikes of a customer with regard to the product.In this situation sentiment analysis helps the people to analyse the reviews and come to conclusion whether it is good or bad.Sentiment Analysis which is also known as opinion mining is one of the subsection in Natural Language processing in which it learns about sentiment or subjectivity from reviews.The main purpose of the project is to develop a system to extract the reviews from e-commerce site, extract aspect from the reviews and categorize reviews into positive and negative.In this project, the application developed will accept the URL from the user and then ask for the option to be selected.The user can then select whether he/she wants to scrape the news article or the reviews from the blogs or the ecommerce sites.Then the sentiment analysis can be done to get the sentiment of the
Factors Influencing the Probability of Dropout in a Romanian Higher Education Institution, Incorporating the Impact of the COVID-19 Pandemic

Dropout rate is an important indicator of the quality of higher education systems, especially in the case of mass education. When the Bologna reform in higher education was introduced, it was hoped that more people would graduate from short-cycle undergraduate courses, but the transition from a more traditional educational model to the Bologna system did not reduce the dropout rates. In Romania, a recent study carried out by UEFISCDI indicates that almost half of the students enrolled in undergraduate programmes in 2015 had not completed their studies by 2021, while Herțeliu et al. (2022) show that 43.8% of students drop out of university while being enrolled in the first year of a bachelor’s degree programme. The current study focuses on two surverys carried out at a Romanian higher education institution (Babeș-Bolyai University), with the aim of identifying individual, socio-demographic and institutional risk factors for university dropout, as well as factors that protect against it. Using factorial analysis, the study reveals that the factors associated with university dropout have a multi-causal character, and are related to both institutional, economic and external factors.
Problems of High School Students in Interpersonal Relationships

The article presents the current situation of problems faced by high school students in interpersonal relationships. The research sample includes 790 students in grades 10, 11 and 12 at 6 high schools in Hanoi. Research results show that the majority of high school students rate themselves as having few problems (difficulties) in interpersonal relationships. The most common interpersonal problems students face are related to lack of social skills, teamwork, and adapting to new (changing) social environments. Students also rarely have interpersonal problems with teachers. The survey results also found a number of factors that significantly affect the expression level of interpersonal problems of students. This result contributes to providing useful information in early recognition of problems in interpersonal relationships, and as a reliable database when developing educational solutions to improve students’ problem solving capacity in the interpersonal interactions.
The Effectiveness of Quizlet.com in Arabic Vocabulary Learning; Students’ Perception and Acceptance of Technology

The increasingly massive development of technology makes language learning no longer limited to only being in the classroom, but can be done anywhere using digital devices. Vocabulary is one of the important parts of language acquisition because vocabulary is the initial stage of mastering the four language skills. This study aims to determine the influence of the use of Quizlet in mastering the Arabic vocabulary of Arabic Language and Literature students, student perceptions of the use of the application in learning Arabic vocabulary, and acceptance of the technology used in quizlet.com. This study used an experimental design and was conducted on 25 Arabic Language and Literature students. This study used several data collection techniques, including pretest-posttest, perception questionnaires, and Technology Acceptance Model (TAM) questionnaires. The results of this study explained that the value of the posttest was greater than the pretests and the results of the T-Test showed a significant difference. These results are supported by a perception questionnaire that shows that students consider the use of the quizlet.com application to be effectively used in learning Arabic vocabulary. As well as the results of the TAM questionnaire showed that students were satisfied with the use of quizlet.com in learning Arabic vocabulary. The results of this study can be a recommendation for Arabic teachers, that quizlet.com can be used as a medium for learning Arabic vocabulary both in the classroom and outside the classroom.
Gesture Recognition for Interpretation of Bengali Sign Language using Hyper Parameter Tuning Convolution Neural Network

In recent years, the proportion of deaf and dumb persons has increased dramatically all across the world.Physically challenged persons have found it challenging to communicate with normal others.Via the movement of gestures like the face, hand, and body, communication takes place.The goal of this research is to develop a hand gesture recognition method that can understand sign language for deaf and hard of hearing persons.We collected our hand sign data from a well-known source called Ishara-Lipi.Because of the low amount of gestures, we augment this data set from 1009 images to 9360 images for our recognition purposes.This augmented dataset is divided into the following sections: training and testing.We develop the Convolutional Neural Network (CNN) model that uses multilayer CNN, followed by pooling layers and dropout layers and also adding multiple hidden layers, or simply called dense layers afterward.We experiment with our CNN model with the tuning of hyper parameters in all possible combinations.Our model provides 98.78 percent and 97.45 percent accuracy in training and validation respectively.We evaluate our trained CNN model through the test dataset that also has provided both 98 percent for accuracy and f1 score.
Organizational culture and its relationship to job commitment among employees of the General Directorate of Education in Muscat Governorate, Sultanate of Oman

The current study aimed to determine the level of organizational culture availability and the level of job commitment among employees in the General Directorate of Education in the Governorate of Muscat in the Sultanate of Oman. And to identify whether there are statistically significant differences at the level of significance (05≥ α) between the arithmetic averages due to the study variables (gender, educational qualification, and years of experience). To achieve the aims of the study, the study used the correlative descriptive approach, in order to answer its questions, a study scales was developed; the first measures the level of organizational culture, while the second measures job commitment. The results were as follows: The level of organizational culture in the General Directorate of Education in the Governorate of Muscat in the Sultanate of Oman was "high and the level of job commitment were high. There are no statistically significant differences at the level of significance (05≥ α) in the responses of the study sample members to the level of organizational culture, and the level of job commitment due to the variables: gender, and years of experience, And there were statistically significant differences at the significance level (α ≥ 05) due to the educational qualification variable in favor of a bachelor's degree or less and There is a positive, statistically significant relationship between organizational culture and job commitment in all its dimensions, except for the relationship between continuity commitment and all of the beliefs, norms, expectations, and organizational culture as a whole. Keywords: Organizational Culture, Job Commitment, Directorate General of Education, Governorate of Muscat, Sultanate of Oman.
A Framework to Investigate Cybergrooming Crimes

Grooming is when an adult builds an emotional connection with a child with the intention of exploiting the child's trust by using them for their own sexual gratification.Groomers will first gain the trust of the child so that the child is less likely going to question their intentions.Groomers can do this by offering to buy gifts for the child, giving the child attention or pretending to be a child themselves therefore deceiving the child who may not know they are being groomed.Thus leading to sexual abuse, and as the groomer would find ways to convince the child to meet up with them to then take sexual advantage of the child.After review, it was found that a method or framework was missing.To address that gap, in this paper, we propose a theoretical framework to investigate child cybergrooming offences in the jurisdiction of England and Wales.The data was gathered through interviews, and grounded theory was applied to create the framework which could then be applied at the operational or managerial level.Future work would also focus on applying digital policing skills to investigate how cybergrooming could be reduced and tackled in this day and age of the cyberworld.
THE EVOLVING THREAT LANDSCAPE: AN OVERVIEW OF ATTACKS AND RESPONSE STRATEGIES AGAINST CYBERCRIME IN SAUDI ARABIA

Saudi Arabia has been a victim of cyberattacks over the years, with an increasing number of attacks being reported since 2020. These cyberattacks significantly threaten the country's national security, economic stability, and personal privacy. In this article, we will explore the types of cyberattacks that have been observed in Saudi Arabia after 2020, the impact they have had on the country, and the measures taken by the Saudi government to counter these attacks. This article is aimed at providing a comprehensive understanding of the current state of cyberattacks in Saudi Arabia and the measures taken to address them.
Comparative Analysis of Face Detection Algorithms using Images

Facial recognition plays a vital role in computer vision applications.Several face detection algorithms have been developed over time to accurately detect human faces in images and videos.This research paper presents a comparative analysis of popular face detection algorithms, including Viola-Jones, Haar Cascade, LBP (local binary patterns), SIFT (scaleinvariant feature transform), and ORB (Oriented FAST and Rotated BRIEF), using precision, recall, F1-score, accuracy, and execution time as evaluation metrics.The objective is to assess the performance of these algorithms in detecting faces accurately and efficiently.The experiments were conducted on a dataset of images, and the results indicate varying levels of performance across the algorithms.Viola-Jones and Haar cascade classifier algorithms offer high accuracy and fast performance but may struggle in low-light conditions and with complex backgrounds.LBP, SIFT, and ORB algorithms showed trade-offs between accuracy and execution time but performed well under challenging conditions, such as low light, obstacles, and non-face objects.The findings of this analysis can aid researchers and practitioners in selecting the most suitable face detection algorithm based on their specific requirements and constraints.Further research can focus on hybrid approaches that combine the strengths of these algorithms or explore the potential of deep learning-based methods for improved face detection accuracy.
A Comparative Analysis for Energy Efficiency in Cloud Computing using CSO

Now a day, many organizations and independent consumers are heavily utilizing cloud services for their scalability, reliability, and low expenses.Developing management techniques used to minimize energy consumption, boost profitability, and decrease environmental impact is a key aspect of cloud data centers.Every consumer's usage of service can generate a huge amount of data.Therefore, it will be very expensive to transfer data between two dependent resources.This paper suggests a meta heuristic-based optimization process called the Cat swarm optimization algorithm to improve the performance and energy efficiency in cloud resource allocation.Also, its performance is compared with gray wolf optimization and Whale Optimization Algorithms with a variation in of population sizes and iterations.Also, energy efficiency and throughput are calculated.