Reviewerly/exHarmony huggingface dataset:
Yoga Scale Intervention Study Based On Sikh Thoughts

Background&#x0D; Sri Guru Granth Sahib is the main Sikh scripture. The SGGS promote principles of liberty and impartiality to pursue the way to the Guru following the path of peace and prosperity. The Sikh code of conduct is known as Sikh Rehat Maryada. The code is an outline of the mandates of daily routine followed by every Sikh. It stipulates philosophy and mandates, according to the teachings of Sikhism’s 10 gurus. The primary goal of SGGS is to achieve union with God by constantly remembering God’s name.&#x0D; Methodology&#x0D; The concept of oneness of God for all humanity based on Guru Nanak Dev Ji’s teachings. Based on this concept, we formulated 30 questions like “I wake up before dawn”, “I meditate in silent location “etc. Meditation is a part of overall spiritual practices discussed with a sample size of 200 participants in the age group of 18-50 years. The generalized Linear Model (GLM) is used to find the significance. RMANOVA (SPSS -25) software is used to find the calculated p-value 3 different tests viz; unpaired t-test, Chi-square test, and F statistics.&#x0D; Discussion&#x0D; The effects of the values and SGGS yogic practices of the present studies reasonably matches well with the historical examples, contemporary data, and some semi-structured interviews conducted by Nirvikar, 2022.&#x0D; Conclusion&#x0D; It is concluded from the present studies that a significant effect of SGGS yogic teachings may be seen in human life.
The Use of Social Media and Its Effects on Students' Academic Performance

The rapid development of technology, especially social media, has enabled people to live increasingly comfortable, convenient, and uncomplicated lives in the modern era. Numerous individuals now consider social media an indispensable component of their daily lives as its use becomes increasingly widespread. The primary objective of this study is to determine whether or not the use of social media influences students' academic performance. In this study, descriptive analysis was used as the methodology. This study's necessary data was collected using a technique known as "simple random sampling." After collecting the data, they were analyzed with the Statistical Package for the Social Sciences (SPSS), and the resulting frequencies and percentages were displayed in tables. According to the study's findings, students' use of social media has no adverse effect on their overall academic performance. Social media platforms are potent tools that can significantly enhance academic performance. However, students should rely on something other than it as their sole source of information.
Impact of Digital Communication in Human Resources: A Comprehensive Review

Modern businesses increasingly recognize the value of digital communication within their HR departments. This study seeks to gain a deeper understanding of how organizations utilize digital communication and its impact. The prevalence of social media in recent years has made it a ubiquitous presence across various digital platforms. Both Indian and international businesses employ digital communication platforms for purposes such as marketing their products, engaging with customers and employees, advertising job openings, and connecting with the public. One notable advantage is its significant simplification of the hiring process for HR managers. Furthermore, digital communication empowers HR departments to monitor employee activities and reinforce the company's brand. This research aims to explore digital communication's role as a medium in HR departments. It underscores the importance of the topic through a review of relevant literature, drawing upon reputable sources like Wiley, Emerald, and Sage to highlight the extensive adoption of digital platforms for internet-based communication. The study also establishes the contextual framework for the use of internet technology in digital HR communication. Notably, it identifies the need for further research due to the rapid advancements in internet technology. This research examines the function of digital communication within HR departments, potentially revealing new dynamics in the determination of formal and informal communication activities within organizations.
Enhancing Oral Reading Skills to Improve Reading Comprehension

Reading is a pleasurable activity. Reading skills contain several objectives and methods. An overall discussion on the identification of the problems that students may face in their schooling is an important aspect. The main objective of this study is to analyze and process the link between students' reading skills and their potential to make out the texts they read. The steps of using certain methods portrayed by secondary sources in the study based on the proper approaches and individual communication approaches. The process of using the steps of certain methods in this study have been portrayed in a manner that helps the students not only in their academic career but also their daily scheme of communication. The proper advancement of reading skills is the crucial topics of accuracy, reading speed, and other activities. This paper will enlighten the strategies while highlighting oral reading activities.
An Algorithm to Increase the Attached Complexity and Time Consumption for Iot Healthcare Applications Based on the Truncated Quantum Hashed Method

Internet of Things (IoT) implementations have been used in numerous healthcare domains. The majority of smart devices are connected, including the automatic environment in which such systems operate. Security and privacy have emerged as major challenges for IoT management. Recently published research has revealed the effectiveness of Elliptic Curve Cryptography (ECC) techniques are very useful for undertaking security research and evaluation of IoT applications and have numerous advantages over further techniques. The objective of this research paper is to suggest options for where to improve the encryption system in the ECC technique, with numerous optimization techniques to prepare the best enhancement of the light-weight algorithm. Our primary focus is on enhancing the Truncated Quantum Hashed Signature (TQHS) methods to increase the complexity of the adaptation and reduce the time utilization of the ECC encryption model. A hybrid data encryption architecture model integrating an ECC model with a TQHS-based architecture design to develop a lightweight encryption technology and the proposed Truncated Quantum Hashed Signature method integrates a random Hashed Signature methodology with a key generation model to improve security complexity. Second, from the standpoint of IoT security systems, Comparison and estimation of memory consumption and time complexity analyses to increase privacy and security. Lastly, we enhance the encryption system parameters in the ECC method. In the proposed work, we present a novel model of random key formation for the ECC to improve the model as a lightweight architecture.
A Bibliometric Analysis of Blockchain Research in Supply Chain Management

Blockchain technology has garnered increasing research attention because of its potential to transform supply chain management (SCM) through enhanced transparency, security, and efficiency. This study performed a bibliometric analysis of the emerging body of literature on the intersection of blockchain technology and SCM to elucidate the intellectual structure, knowledge diffusion patterns, and research trajectories within this field. A dataset of 2,500 English-language articles published between 2020-2023 was retrieved from Dimensions and analyzed using VOSviewer and Bibliometrix. The findings revealed that the research landscape focused predominantly on technical topics grounded in computer science, with an emerging interest in supply chain applications. Bibliographic coupling revealed clusters of literature on core blockchain development, implementation challenges, and healthcare use cases. The citation analysis identified influential contributors and geographic concentrations of research productivity in China and East Asia. While currently anchored in technical disciplines, blockchain-SCM research displays a burgeoning interdisciplinarity. This study provides a multidimensional perspective on the topography and evolution of this rapidly developing domain. These insights will orient scholars and practitioners to high-impact contributions and productive directions for future blockchain integration in SCM contexts.
The Impact of Augmented and Virtual Reality Technologies on Customer Happiness in Immersive Shopping Experiences

This study investigates the impact of augmented and virtual reality (AR/VR) technologies on customer happiness in immersive shopping experiences in the Bahraini clothing market. A purposive sample of 500 respondents was used to collect data. The results demonstrate the significance of incorporating AR/VR technologies as a modern marketing strategy to enhance customer happiness and brand loyalty. The study also validated four hypotheses of the conceptual model, indicating that usability, functionality, customer involvement, and personalization directly influence customer happiness and satisfaction with the brand and shopping experience. Additionally, preferred techniques for implementing AR/VR technologies in shopping experiences were identified, including QR code scanning for virtual try-ons, 360-degree product views, AR/VR product showcases, AR filters on social media, virtual fitting rooms, and gamified shopping experiences. The findings suggest that international brands are leveraging AR/VR technologies as modern marketing tools in the era of artificial intelligence to gain a competitive advantage, and to encourage informed purchasing decisions.
Modified Algorithm for Privacy Preservation of Gathered Data

The extensive prevalence of computing technologies in our daily lives and physical landscapes has led to the generation of vast datasets for analysis. Although, there is a growing uncertaintyregarding potential privacy breaches, as sensitive data could be exposed if not adequately protected during analysis. Many existing privacy-preserving methods encounter challenges such as inefficiency, scalability limitations, and the delicate balance between data utility and privacy conservation.&#x0D; In this study, we introduce an algorithm known as PABIDOT. PABIDOT employs optimal geometric transformations to safeguard privacy within the realm of big data. We assess the efficacy of PABIDOT through a series of experiments involving nine distinct datasets and five classification algorithms. Our results highlight PABIDOT's exceptional execution speed, scalability, resilience against potential attacks,andits accuracy in large-scale datasets.In addition, we delve into the practical implications of PABIDOT in real-world scenarios, emphasizing its adaptability across diverse industries and applications. The algorithm's robustness in safeguarding sensitive information while maintaining data integrity sets a new standard in privacy preservation. Moreover, the study sheds light on potential avenues for further advancements in the field of secure data analytics, paving the way for more comprehensive and effective privacy solutions in the era of burgeoning data generation and utilization.
Virtual Worlds, Real Skills: Is the Metaverse the Future of Accounting Education?

The onset of the COVID-19 pandemic radically altered the landscape of education, particularly affecting primary and secondary school students. Traditional classroom environments, characterized by physical interaction and social learning, were suddenly swapped out for remote learning platforms during the first two academic years of the pandemic. While educational institutions quickly pivoted to online learning to maintain some semblance of normalcy, research indicates that these years represented a low point in educational quality for teachers and students alike. A plethora of educational models have emerged in response to the challenges introduced by the pandemic-induced shift to digital learning. Among these, three-dimensional virtual learning environments have attracted considerable attention. These platforms aim to elevate the student experience by enhancing readiness levels and promoting interpersonal interaction. In the context of these sweeping changes, the study focuses on the Metaverse—a concept that has garnered significant buzz in contemporary discussions on digital transformation.&#x0D; The study's primary objective is to explore the feasibility of using the Metaverse as an educational tool, particularly in the realm of accounting education. The paper delves into various facets of the Metaverse, reviewing the existing literature to understand its potential benefits and limitations. Specifically, the study scrutinizes its application in accounting education, outlining a series of recommendations based on evaluations of previous educational endeavors within Metaverse settings. The study brings to light various critical points concerning the adaptability and efficacy of the Metaverse as a viable model for accounting education. It raises essential questions: Can the Metaverse bridge the gap left by traditional classroom settings in fostering engagement and facilitating high-quality learning experiences? Or are the complexities and limitations of this novel platform too great to make it a practical solution for accounting education? By investigating these queries and cross-referencing them with empirical evidence, the study provides a nuanced understanding of the Metaverse's potential role in shaping the future of accounting education. The pandemic has been a catalyst for innovation in education but has also highlighted the limitations of hastily adopted digital models. The study ventures into the realm of possible solutions, examining the Metaverse as a prospective alternative that could potentially revolutionize accounting education. Through an in-depth review of the literature and a critical evaluation of existing Metaverse educational models, the paper offers valuable insights that could inform future educational strategies in the accounting domain.
A Novel Technique for Restoration of Images Subjected to Variable Noise Distribution

Image restoration plays a pivotal role in numerous applications across diverse fields due to its profound significance in enhancing the quality and interpretability of images. Whether in medical diagnostics, scientific research, surveillance, or historical preservation, the importance of image restoration cannot be overstated. By addressing issues such as noise, blur, and other forms of degradation, this process contributes to the preservation of vital information within images. This research focuses on enhancing image-denoising techniques by employing the Ladner-Fischer Adder (LFA) method. The study explores the effectiveness of LFA in mitigating varying noise distributions, particularly Salt and Pepper Noise (SPN) and Gaussian noise. Through detailed experimentation and analysis, the paper evaluates the performance of LFA-based Median Filtering (LFA-MF) and Finite Impulse Response (LFA-FIR) filtering methods. The results demonstrate substantial improvements in Peak Signal-to-Noise Ratio (PSNR), Mean Square Error (MSE), and Structural Similarity Index Measure (SSIM) values for both noise types. Notably, LFA-FIR consistently outperforms LFA-MF in terms of denoising efficacy, highlighting its potential for image restoration in the presence of complex noise patterns. Moreover, the research investigates the ASIC synthesis of LFA, examining parameters such as area, power consumption, and delay across different technology nodes. The findings emphasize the potential of LFA for robust image denoising under diverse noise conditions, offering insights into its applicability and performance in real-world scenarios.
Comparative Analysis on Image Compression Algorithm Based on Block Truncation Coding

Block Truncation Coding is a quick and effective method for compressing images, because it employs a non-parametric one-bit or two-bit quantization procedure that adapts to the features of the image. This paper describes and compares the performance of BTC and BTC based techniques such as Enhanced Block Truncation Coding (EBTC), Modified Block Truncation Coding (MBTC), and Adaptive Block Truncation Coding – Edge Quantization (ABTC – EQ). These techniques were applied on the general images and their performance were measured using the metrics such as Peak Signal Noise Ratio (PSNR), Structured Similarity Index Measure (SSIM), Weighted Peak Signal Noise Ratio (WPSNR), Feature Similarity Index Measure (FSIM) and Compression Ratio (CR).
Devanagari CAPTCHA: For the Security in Web

Completely Automated Public Turing Test to Tell Computers and Humans Apart or CAPTCHA is a solution for cyber-attack. CAPTCHA is a small challenge that an internet user has to pass before accessing any online service. The most common type of CAPTCHA is text-based CAPTCHA, in which a small image (contains a random number of alphabets) is presented before the user. The user has to identify and then type the alphabet in a text box. The textual information in the CAPTCHA must not be identified by a bot (computer code). So, artificial noise and distortion are applied in the image. Earlier text-based schemes use English alphabets, but over time non-English language-based text CAPTCHAs also came into the picture. Native language-based text CAPTCHA is very useful for internet users who do not know the English language. This article is an effort towards the current status of the Devanagari script-based CAPTCHAs. We have analyzed 28 unique Devanagari CAPTCHAs from a security and usability point of view. Total 28000 different samples are collected for this experiment. For the success of a text-based CAPTCHA, it must be very secure from the bot and easy for human beings. Devanagari CAPTCHA can be very beneficial for Indian websites. This paper is written by keeping the importance of Devanagari script-based CAPTCHA.
Impact of Innovation and Technology on Eco System for Inclusive Growth: Special Reference to Digital Marketing and Secured Iot

This essay will show how IOT supports digital marketing and administers a beneficial, safe system for buyers and sellers. In addition to facilitating data transmission, IOT devices also assist in gathering and building a secure consumer database, which is crucial in the current digital era. Data is king, as you have certainly heard.&#x0D; Digital marketers can gain better marketing insights and develop more precise digital marketing plans with the aid of the customer-secured database. This method is specifically fetched with the intention of enabling users to use the database in a secure manner.&#x0D; We will determine the growth percentage of sellers with the assistance of the chosen company and their IOT installation technology. These gadgets gather information from their surroundings and share it with other gadgets through the internet using sensors and actuators.&#x0D; Electronic device sensors are collecting data, transferring it to the internet, and exchanging it with one another. The synchronization and dependency ratio of the IOT and digital marketing samples will be shown in selected graph representations using the T-Test in order to determine the actual statistical result.
A Novel Security Model for Password Encryption Using Aadhaar and Amicable Number

In this day and age, data hacking has become a major source of fear. In order to avoid any further theft of data, we must stop this criminal hacking. Backups, encryption, access control, and other techniques are just a few that may be used to ensure data integrity. We did not combine the existing approaches when we announced our encryption process. The secret to encrypting user passwords is to utilize a mathematical calculation equation that is well-defined and a number conversion mechanism. Users must provide their password and Aadhaar number in order to register. Encrypted password has been recorded in the database. Every industry uses encryption to secure data, and there are many potential applications for it in the future.
A Comparative Study of Evolutionary and Swarm Intelligence Algorithms for Job Scheduling on Identical Parallel Machines

In parallel computing systems, job scheduling plays a crucial role in enhancing system efficiency and minimizing the makespan. In recent years, evolutionary and swarm intelligence algorithms have gained prominence as effective approaches for solving combinatorial optimization problems. In the present work, we have considered genetic algorithm (GA) for evolutionary algorithms and particle swarm optimization (PSO) for swarm intelligence algorithms. Evolutionary algorithms (EA) and swarm intelligence algorithms (SIA) have shown promising results in solving job scheduling challenges. In this study, we collate the performance of EA and SIA approaches for job scheduling on parallel machines. We use different benchmark instances to evaluate the algorithms' makespan and computational time performance. The results show that SIA algorithms outperform EA algorithms regarding makespan and computational time for all benchmark instances. Furthermore, the study provides insights into the strengths and weaknesses of EA and SIA algorithms for job scheduling on parallel machines. Our findings provide useful insights for researchers and practitioners interested in applying optimization techniques to solve job scheduling problems on parallel machines.
A Novel Approach of Deep Learning Using Sentiment Analysis in Python

This paper focused on Sentiment Analysis is the task of categorize the division of a given text. For instance, a text-based tweet can be categorize into either "positive", "negative", or "neutral". Given the text and accompanying labels, a model can be trained to predict the correct sentiment. Sentiment Analysis techniques can be categorized into Deep Learning approaches, lexicon-based approaches, and even hybrid methods. Some subcategories of research in sentiment analysis include: multimodal sentiment analysis, aspect-based sentiment analysis, fine-grained opinion analysis, language specific sentiment analysis. Sentiment analysis (SA) is a process of extensive exploration of data stored on the Web to identify and categorize the views expressed in a part of the text. The intended outcome of this process is to assess the author attitude toward a particular topic, movie, product, etc. The result is positive, negative, or neutral These study illustrated different techniques in SA approach for extracting and analytics sentiments associated with the polarity of positive, negative, or neutral on the topic selected. Social networks SA can be a useful source of information and data. SA acquires important in many areas of business, politics, and thought.. The main aim of this study is to provide full concept about SA techniques and its classification and methods used it. Also, we give a brief overview of big data techniques and its relation and use in SA field. Because the recent period has witnessed a remarkable development in the use of Big Data (Hadoop) in the process collection of data and reviews from social networks for analysis.