JOURNAL OF MULTIMEDIA TECHNOLOGY & RECENT ADVANCEMENTS
ISSN: 2349-9028 Scientific Journal Impact Factor (SJIF): 6.099 Journal DOI no.: 10.37591/JoMTRA
STM JOURNALS ( Consortium eLearning Network Pvt Ltd)
Prospective Research Fields and Difficulties in Digital Forensic Evidence Analysis
As technology becomes increasingly prevalent in modern life, digital gadgets are more likely to be relevant to a criminal investigation or civil case. Law enforcement organisations around the world are currently dealing with enormous backlogs of digital evidence due to the sheer volume of investigations requiring digital forensic expertise. Anticipated future trends suggest a significant rise in the volume of incidents necessitating digital forensic analysis. A growing variety of devices, such as PCs, smartphones, tablets, cloud-based services, Internet of Things gadgets, wearable technology, etc., will probably need to be analysed for each case.The diversity of new digital evidence sources presents the digital investigator with novel and difficult identification, acquisition, storage, and analysis issues. The technical issues causing the backlog in digital forensics are examined in this study, along with a number of potential future research areas that could considerably improve the effectiveness of the digital forensic process.
Copyright (c) 2023 JOURNAL OF MULTIMEDIA TECHNOLOGY & RECENT ADVANCEMENTS
The Impact of Influencer Marketing on Consumer Purchase Intentions: A Social Media Perspective
In recent years, influencer marketing has emerged as a dynamic and influential strategy within the realm of digital marketing, particularly on various social media platforms. This research delves into "The Impact of Influencer Marketing on Consumer Purchase Intentions: A Social Media Perspective". The study aims to comprehensively examine the relationship between influencer marketing activities on social media platforms and consumers' intentions to make a purchase. The study has been conducted in Bhavnagar city and total 68 responses have been duly recorded which contains majorly young audience. The findings of the study suggest that influencer’s quality, overall shopping improvement, and product related decision are heavily influenced by the age group, level of education and level of income.
The Digital Frontier in Mental Health for Modern Schools
In the dawn of the 21st century, educational landscapes are evolving rapidly, moving beyond traditional brick-and-mortar confines and integrating deeply with the digital realm. This study delves into an emerging facet of this digital integration, using web development tools and platforms to address and bolster student mental well-being in contemporary schools. As mental health becomes a paramount concern, with its profound impact on academic performance, peer interactions, and holistic development, there is a discernible void in effectual and wide-reaching interventions. This study posits that digital tools offer unparalleled flexibility, immediacy, and adaptability, providing potentially transformative solutions.Modern students, inherently digital natives, find solace and support in online realms. Through web-based platforms, schools can craft proactive, personalized, and comprehensive support systems, addressing everything from immediate crises to long-term well-being. Furthermore, the potential of emergent technologies, such as AI and predictive analytics, promise even more refined, real-time interventions.However, the journey towards effective digital mental health integration is not without challenges. Concerns surrounding data privacy, the impersonality of digital interactions, and ensuring sustained engagement demand attention. By analyzing pioneering endeavors globally, the research uncovers best practices, successful frameworks, and potential pitfalls. In essence, as schools stand on the precipice of this digital mental health frontier, this study offers both a beacon and a guide, illuminating the potential pathways and ensuring the journey is both impactful and ethically sound.
An Analysis of Effects of Digital Marketing by Looking at and Comprehending How It Affects Social Marketing
This review work aims to assess the influence of digital marketing and examine its significance for both consumers and marketers. It begins with an exploration of the concept of digital marketing, followed by an elucidation of the various platforms utilized in digital marketing. Furthermore, it draws attention to the distinctions between traditional and digital marketing, outlining the advantages, disadvantages, and the crucial role of digital marketing in contemporary times.The global landscape is undergoing a paradigm shift from analog to digital, and the field of marketing is embracing this transformation. The increasing pace of technological progress is driving a growing adoption of digital marketing strategies, encompassing social media marketing and search engine marketing. Notably, the escalation in the number of internet users has significantly contributed to the success of digital marketing, as it heavily relies on online platforms. Additionally, there is a discernible change in consumer buying behavior, marked by an increasing inclination towards digital marketing as opposed to conventional marketing approaches.
This project focuses on connection visualising with the help of a social network. The digital age has exponentially expanded professional networks, making it imperative for individuals to harness platforms like LinkedIn efficiently. Our project introduces the "Profile Resonance Recommendation Algorithm (PRRA)", a unique approach to navigatethis intricate web. PRRA refines the traditional Content-Based Filtering mechanism to provide LinkedIn users with recommendations that resonate closely with their professional profiles. By analysing individual user attributes and correlating them with broader network data, PRRA offers nuanced connection suggestions, facilitating more strategic and fruitful networking endeavours. This studydelves into the development, implementation, and promising outcomes of PRRA within the professional networking ecosystem. In the digital age, the significance of professional networking has grown exponentially, with platforms like LinkedIn serving as crucial tools for individuals seeking to expand their connections. This project introduces the innovative "Profile Resonance Recommendation Algorithm (PRRA)", a sophisticated approach aimed at navigating and optimizing the complex landscape of professional networking. PRRA represents an evolution of the traditional Content-Based Filtering mechanism, refining it to provide LinkedIn users with recommendations that align closely with their professional profiles.The PRRA algorithm operates by analysing individual user attributes and correlating them with broader network data. This in-depth analysis allows PRRA to offer nuanced connection suggestions, thereby facilitating more strategic and fruitful networking endeavours. The development and implementation of PRRA involved a meticulous process, combining data science methodologies, machine learning techniques, and user behaviour analysis to ensure its effectiveness within the professional networking ecosystem.
Profile Resonance Recommendation Algorithm (PRRA)
Offline Distribution Application with Salesman Tracking System
In today’s highly competitive business environment, where customer demands are constantly changing, organizations are actively exploring methods to streamline their sales procedures and enhance their overall effectiveness. Sales force automation software emerges as a transformative solution, offering a suite of tools designed to streamline, automate, and enhance sales activities, ultimately leading to improved efficiency, effectiveness, and customer satisfaction. This abstract delves into the fundamental aspects of sales force automation software, exploring its significance, key features, benefits, and potential impact on businesses of all sizes. Sales force automation software offers relief to sales teams by automating mundane responsibilities like data input, lead tracking, order handling, and client correspondence. This empowers them to dedicate their time and effort to more valuable tasks such as cultivating relationships, comprehending customer requirements, and finalizing transactions.
A Massive Production to the Era of Technology by Social Bots Combating Fake News on Digital Platforms
Social networks have revolutionized communication, enabling individuals to connect with a broader audience and express their opinions freely. However, this unprecedented accessibility also opens doors to potential challenges, such as the unintentional spread of misinformation. In this study, we delve into the mechanisms behind the generation of false information and present a thought-provoking vision of a future where social bots autonomously evolve into semantic webs, inundating media platforms with fabricated content. The study begins by acknowledging the power of social networks as a valuable tool for expanding overall exposure. It emphasizes how anyone can utilize these platforms to share their ideas, but also highlights the lurking presence of social bots. These automated entities, often driven by hidden agendas, can exploit the open nature of social media to disseminate misinformation on a large scale. Ultimately, this study serves as a call to action for researchers, policymakers, and technology companies to address the evolving challenges posed by the spread of misinformation on social media. By understanding the methods employed by social bots in generating false information, we can strive to develop robust countermeasures that protect the public’s right to accurate and reliable information, fostering a healthier and more informed digital society.
Cloud System Performance and Security Improvements with Multi-tenancy Integration
Cloud computing has emerged as a popular paradigm for delivering scalable and flexible computing resources to businesses and individuals. However, ensuring the performance and security of cloud systems continues to be a significant concern. Multiple users or tenants can share the same cloud infrastructure thanks to multi-tenancy, a crucial notion in cloud computing. This dissertation explores the integration of multi-tenancy as a means to enhance the security and performance of cloud systems. The comprehensive review of the existing literature on cloud computing, multi-tenancy, and the associated security and performance challenges. It analyses the benefits and drawbacks of multi-tenancy and identifies the key research gaps that need to be addressed. To address the security concerns, the dissertation investigates various security mechanisms and techniques that can be employed within a multi-tenant cloud environment. It explores access control models, encryption techniques, and secure data isolation methods to ensure the privacy and integrity of tenant data. The dissertation also explores auditing and monitoring mechanisms to detect and mitigate potential security breaches.
Evolution of 6G Networks: Novel Perspective, Current Trends, and Future Directions
The advent of 6G technologies promises a revolutionary leap in the realm of wireless communications, bringing forth a new era of hyper-connectivity and empowering an unprecedented array of applications. This article presents a concise overview of the pivotal role that 6G technologies are expected to play in shaping the future of telecommunications and beyond. It highlights the key features that differentiate 6G from its predecessors, such as higher data rates, ultra-low latency, massive connectivity, and enhanced energy efficiency. By harnessing advanced technologies such as terahertz frequencies, artificial intelligence-driven network optimization, and quantum cryptography, 6G is set to create a robust infrastructure capable of supporting emerging technologies like holographic communications, advanced augmented reality, and autonomous systems. While exploring the potential challenges and opportunities, these abstracts underscore the transformative potential of 6G technologies in driving societal progress, enabling novel applications, and laying the foundation for a truly interconnected and intelligent world.
Multimedia Abstraction in E-learning via LexRank and Latent Semantic Analysis
In today’s era of abundant online information, it is essential to offer an efficient and precise solution for accessing information. With the growing usage of the Internet and smartphones, there has been a consistent rise in online education, entertainment, and various other activities. However, there are instances when we lack the time to delve into lengthy content like videos or podcasts. Hence, there is a need for a method to condense lengthy materials into brief statements while retaining the original meaning. Automatic summarization comes into play here. Its primary goal is to extract concise summaries from vast amounts of digital data accurately and efficiently. To achieve this, we employ natural language processing techniques, utilizing algorithms like LexRank and latent semantic analysis.
Vehicle Insurance Fraud Detection Using Supervised Neural Network Model
Vehicle insurance fraud is a serious problem that causes huge financial losses to insurance companies. In recent years, developing fraud detection models using machine-learning techniques has been of great interest. This study proposes a novel approach for vehicle insurance fraud detection using Supervised Neural network model on the Kaggle Vehicle Insurance Fraud Detection dataset. The initial step in this study involves performing data pre-processing and feature extraction on the dataset, which consists of information such as ages of those insured, the gender of the policyholders, and the make and model of the vehicles. As traditional rule-based techniques are not adequate for detecting fraudulent claims, there are ongoing investigations on machine learning-based methods. Our research proposes a supervised learning method using a neural network model for vehicle insurance fraud detection. The proposed model is trained on a large, publicly available dataset and assessed using standard evaluation metrics such as F1 score, recall and precision. Moreover, we compare the model’s performance with other well-known machine learning algorithms such as decision trees and logistic regression. Our exploratory results show that the proposed approach gains increased accuracy in detecting fraud cases. The proposed learning algorithm outperforms other traditional supervised learning algorithms in terms of classification performance, demonstrating the effectiveness of the proposed approach. Overall, our suggested approach shows a promising solution for vehicle insurance fraud detection, with the potential to reduce financial losses significantly for insurance companies.
Security Monitoring Intelligence System Using IoT
The main objective of the Security Monitoring Intelligence System (SMIS) is to provide security for human beings and to people under dangerous circumstances wherever immediate help is required. CCTV surveillance is provided everywhere, but its disadvantage is that we do not have night vision cameras so we cannot get a hold of what is really happening there and so we cannot judge. We are providing a night vision camera which will help to get a clear picture of the entire situation happening around the person in danger. We are also making use of suspicious activities for training the model, with the use of which the model will identify all the suspicious activities and send the message on the owner's mailbox.
A fascinating skill in computer vision under Artificial intelligence is the technique of automatically changing monochrome photos into colour ones without human assistance. When a substantial annotated dataset is not readily accessible, transfer learning is commonly employed as the preferred approach. Typically, this involves utilizing pre-trained models with extensive general knowledge gained from training on ImageNet, which are subsequently fine-tuned to cater to specific tasks. From the utility point of view, it is useful in the restoration of movies to the augmentation of photos to increase their readability, re-colorization of pictures, improvement of grayscale drawings, and the restoration of black-and- white photographs. It is believed that automated colorization, in the case of black-and-white movies, has the potential to improve the viewing experiences of viewers. It is possible to utilize it in the sphere of security as well since it can transform the black-and-white photos collected by CCTV cameras into colour ones. In this study, we suggest a method for colouring grayscale images using a Generative Adversarial Network (GAN).
XML Query Optimization for Improvement of Data Warehouses Information Processing
XML data warehouses give decision-support systems a chance to use complicated data by giving them a place to start. But native-XML database management systems are slow right now, so it is important to look into ways to make them faster. This study presents two strategies to think about. To start, we suggest using a link index that was made with the fact that XML warehouses have a lot of dimensions in mind. The join procedures are taken out, but the data from the first warehouse stays the same. Second, we show how to choose XML materialized views by grouping the query load to show how this can be done. To prove that these ideas work, we built a set of decision support XQuery tools and ran them against an XML data warehouse. We compared the results obtained with and without our optimization methods. Our tests show that it works, even though the queries themselves are a little hard to understand and the datasets themselves are very big. XML has emerged as the widely accepted standard for transmitting data over mobile wireless networks. In these kinds of networks, mobile clients can use a wireless broadcast channel to send queries to get the XML data they need. Because mobile devices are so small and have so little storage space and a short battery life, it may be hard for customers to download the whole XML data set on one of these devices. To solve this problem, you need to index XML data so that mobile clients only have to download the parts of the file they need. Users who want to access only certain parts of the XML content in an XML stream could use one of several indexing methods. Still, the indexing methods that are used now add more data to an XML stream that is already very large. This research comes up with a new XML stream structure for broadcasting XML data by compressing and summarizing the information about how XML nodes are put together. This study was conducted in the United Kingdom. When data is summed up before being sent, the time it takes to get it in XML format over a wireless broadcast channel can be cut down. The recommended XML stream structure also has indexes that will help you skip over any data that is not important. So, it could make it less likely that XML query results will drain the batteries of mobile devices when they are being processed. We also found that our suggested XML stream design was better than its predecessors in terms of access and tuning times for processing XML queries over the XML data stream. So, our architecture can be used to answer a wide range of XML questions.
Food Fair: Quick Homemade Food Delivery Website
Food Fair is a quick home-made food delivery website designed to cater to the needs of hostel students who crave home-made, delicious food. The website is built using the latest web development technologies, including HTML, CSS, JavaScript, PHP, and MySQL. Food Fair offers a wide range of home-made food options that are prepared using fresh ingredients and traditional recipes, ensuring that the food is not only tasty but also healthy. The website has a user-friendly interface, which makes it easy for customers to place their orders quickly and conveniently. One of the key features of the website is its fast delivery service, which ensures that the food reaches the customers in the shortest possible time. Additionally, the Food Fair ensures that the food is of the best quality, thereby guaranteeing customer satisfaction.
Open-Source Learning Management Systems: Positive and Negative Aspects
The paradigm of education has changed due to the usage of information and communication technology, from traditional learning to online learning. It offers the chance to learn at anytime, anyplace. E-learning also makes it possible to exchange and manage professional knowledge and abilities, as well as to deliver the appropriate information to the appropriate individuals whenever they need it. There are numerous software programmes that offer a setting for distance learning. Moodle is one of the open-source tools that has been gaining popularity in e-learning systems all over the world. The numerous well-known open-source learning management systems for online learning are discussed in this study.
Copyright (c) 2022 JOURNAL OF MULTIMEDIA TECHNOLOGY & RECENT ADVANCEMENTS
Massive Data Capturing and Transmission using Big Data Analytics Model with Machine Learning Prediction
Deep learning techniques are widely used in many branches of research and engineering, including language processing, image classification, and speech recognition. Similar to this, processing vast amounts of data is restricted by a number of classical data processing approaches. To deal with information progressively with incredible exactness and effectiveness, huge information investigation requests spic and span, complex calculations in light of machine and profound learning methods. Recent research has, however, combined a variety of deep learning algorithms with hybrid learning and training processes to analyse data quickly. Bigdata investigation offers incredible opportunities to estimate future wellbeing status in light of wellbeing boundaries and to convey the best outcomes. To foresee diabetes, we utilized and differentiated Machine Learning methods (Direct Relapse, Guileless Bayes, Choice Tree). Also, we ran investigation on flight delays. This study's essential commitment is an outline of machine learning models and large information advancements. We feature a couple of measurements that let us select a model that is more exact. We utilized three machine learning models to foresee the improvement of diabetes, and afterward we assessed how well they performed. What is more, we saw flight delays and made a dashboard that might help flight organization the executives in getting a 360° viewpoint on their flights and going with vital choices.
Impact of Social Media on Human being During COVID-19
All of us have been experiencing a new normal for almost 2 years now. COVID-19, an irresistible sickness that arose in late December 2019 in Wuhan, China has impacted our lives in every way possible including our professional life as well as our personal life. The reason for the illness was before long affirmed as a novel Covid, and the contamination has since spread to numerous nations worldwide and has turned into a pandemic infection. Web-based media has turned into a wellspring of scattering data to general society. Social media is not always appreciated due to its negative effects on youth, however, very suddenly over a night, the COVID-19 reshaped the idea of social connection all over the planet. Worldwide dread and vulnerability about the infection started an uncommon requirement for regularly updated data, master suggestions, and virtual commitment with family, companions, customers, understudies, and instructors. Online/Social-Media can be a productive wellspring of data and a powerful method for keeping up to date with the huge measure of clinical information. This is what my research is about, impact of social media on us, human beings, during this unexpected pandemic situation that spread all over the world within a few days and continue to affect in our lives till date.
Text Recognition and Detection of Handwritten Reports Through Image Processing
Nowadays, the biggest problem we are facing is text detection from the scene images, handwritten documents, and various other images at different resolutions. To overcome such problems, we are using artificial intelligence tools and techniques which make use of neural networks to detect the text from the images. In this work, we proposed new solutions to this problem by introducing Artificial Neural Network Techniques which have proven best for text recognition from images. Many studies have been done on OCR by making use of different approaches but this technique has been proven as the best one. Implementation of research work is done on various images and handwritten documents on different resolutions and then we came to this conclusion. Using these elements, we are building a highly accurate and tunable text recognizer that can recognize the text with an accuracy of 98%. This review work gives a detailed survey of the Artificial Neural Network Technique in Text Recognition.
Survey on Parts of Speech Tagging for Gujarati
The study describes the survey on Part of Speech tagging using different approaches for various Indian languages. Indian languages have rich morphological effect, so it may create many problems while tagging the sentences. Researchers have done work on POS tagging for various languages like Hindi, Marathi, Panjabi, English etc. With over 60 million users worldwide, Gujarati is an Indian language that currently has numerous initiatives in place for the development of natural language processing (NLP) resources and applications for Indian languages. It has been demonstrated that the efficacy of translation can be enhanced through the utilization of part-of-speech tagging and stemming-assisted transliteration. It has also been noted that a considerable amount of the material in Gujarati undergoes transliteration during the translation process into the Hindi language. They have used different tagging approaches like statistical, rule based etc. POS Tagging is the basic step for NLP; for that, different tagsets are required that are discussed in this survey.
Hybrid Optimum Model Development to Determine the Brake
The hydraulic rubber places stresses on the braking system during quick braking. Pressure is actually created by the friction between the disc brakes and the disc. The discs experience rotational body pressures as a result of its rotation. These pressures&#39; ensuing deformations can cause the material to fail. Therefore, its crucial to make sure the groove pressures are kept as low as possible. The entire method has been coded into MATLAB to enhance operating systems and modules. This involves creating percentile charts for subsystems and operating system enhancements that need in-depth verification and applying optimization techniques like the interior-point approach and the Multi Parametric Genetic Algorithm (MPGA).
Technological Development in Education through Online Learning
Online education has become familiar nowadays in many countries as well as in India also. Training institutes in India are the pioneers of this system. By following their steps many colleges and universities have also adopted this system. Leaning methods constantly keep changing from generation to generation which proves the development of technology in every aspect. Nowadays students for any of their academic work used to refer or take key points from internet which has been their primary resource. This is of course a blessing of technology. Instructors have also started following modern technical methods as their teaching criteria like uploading contents of the course in Google drive, checking the assignments through LMS (Learning Management System) and so on. We can observe that many top-ranking universities throughout the world have become successful and are in fact serving as a role model for the best educational strategies through online education.
Robotics, Machine Learning, AI, IOT, Zoom, Teams, Skype, Learning Management System, Evopry.
Hawk Eye Detection System (Using Python)
Tennis and cricket are gaining popularity. Hawk eye is a modern tool that can be applied to any sport. Now a days there is lots of advancement in the sports technology. Hawk Eye first gained notoriety in television broadcasts of cricket. Broadcasters used Hawk-Cricket Eye's System at the 2006 ICC Champions Trophy in India, the World Cup, and important Test and ODI series all over the world since 2001. A virtual reality device called Hawk-Eye is a line calling system that tracks a ball's trajectory. It has become common due to the plethora of help this technology offers to enhance game quality. Six calibrated high-speed professional vision processing cameras that are distributed throughout the ground are used by Hawk-Eye. Additionally, the system calibrates the two "Mat" broadcast cameras it utilises to ensure that the visual is always superimposed in the proper location. The way in which it operates then allows the game’s officials to understand where the ball has pitched and what its onward trajectory would have been. The Hawk-Eye framework is divided into two sizable components: the Tracking System, which includes a camera and a speed weapon, and the Video Replay System, which records data to aid arbitrators in making decisions and to aid coaches and players in analysing their performance. However, there is very less research available in this area. Examples of Hawk-Eye statistics include: LBWs, Wagon Wheels, De Spin, Pitch Maps, Beehives, RailCam, Reaction Time,Ball Speeds. The purpose of this paper is to discuss the principle behind Hawk Eye, many of its applications, future developments, system precision, and system dependability in the sport of cricket.
Hawk Eye, DRS, LBW, Despin, Cricket, Tennis, Camera Technology.
A technology known as augmented reality (AR) fuses the actual environment with a virtual item, whether it be in two dimensions (2D) or three dimensions (3D), in real time. The advancement of augmented reality (AR) technology has made significant contributions to several sectors, one of which is the use of AR for academic purposes. The proposed system can help students and peoples to explore the different map in real time. In this paper we are building the geographical Atlas i.e. map of our country by using the technology of Markerless Augmented reality. The main function of application is to display 3D map that exists in App and shows the necessary information via audio and text. The proposed system give all information about our country through Three dimensions (3D) Map i.e. physical, political, mountain ranges, rivers, crops, mineral, States etc. Software used for this proposed system is Unity 3D, Vuforia SDK and Android Studio. And these software are open source and do not required any previous knowledge of programming and are easier to use.
3D Objects, Augmented Reality, Markerless, Atlas of India, Maps.
Novel Perspectives in Future of Wi-Fi: Trends, Applications and Research Challenges
Wi-Fi has changed connectivity in America inside and out. Wi-Fi interfaces us to the internet so we can direct business, find loved ones, do schoolwork, get a clinical diagnosis, stream our number one shows, and substantially more. It's likewise a basic tool for factories, clinics, retail locations, and transportation centers the nation over. We are using the wireless transmissions that permit Wi-Fi to travel like never before previously. As our craving for greater connectivity grows, our nation requires a greater amount of the basic contribution to make Wi-Fi run: unlicensed spectrum. More Wi-Fi in urban areas can make networks more bearable by increasing admittance to administrations and decisively improving correspondence. Using sensors empowered by unlicensed frequencies and Wi-Fi organizations, local area pioneers can further develop building management, empower more efficient traffic stream, and foster better approaches to offer fundamental types of assistance like water or waste management. This paper presents the novel perspectives into the evolution of Wi-Fi technology showing its vast application potential and how nations around the globe are trying to equip the technology with various modifications so as to make its reach even wider in future time to come.
Extending the Mind Share Model by Measuring Media Share of Voice
In this study, the author extends Mind Share model construction to use media Share of Voice to measure Mind Share of customer in a particular brand. The logit regression is used to find the impact factors which can predict the media Share of Voice. The empirical data is obtained from the Google search engine, and the cumulative volume of keyword searches is used to make model application. The volume of media voice in competitive brand, target brand and total issue are calculated by using the data from marketing campaign “buy one and get one free” of coffee store brands. The probabilities of media Share of Voice and parameters of the proposed model also be estimated. The results show that the increasing volume of competitive media voice will case low MSV of the target brand. The customers pay more attention or discuss on the issue of competitive brand may probability accelerate lower Mind Share of the target brand during the period of competitive marketing campaign because the number of customers exposed to the media every day is limited and fixed. In the future, some researchers can compare the different measurement of Mind share to Mind Share Voice to combine these various models of Mind Share from different concepts and perceptions.
Implementation of Adaptive Image Watermarking System Using Complementary Quantization Method
Blind watermarking installed the watermark by adding or removing a quantized consistent worth from the quantization table. In this study, another versatile and copy quantized blind watermarking framework is proposed to achieve higher straightforwardness. The versatile and correlative quantized table is proposed to propel the vigor as per the properties of the human visual framework and simply observable twisting. Furthermore, the mistake rectifying based watermarking will have the property that amends blunders of the extricated watermark consequently. A multi-goal watermarking in view of the wavelet change is chosen and hence it can oppose the annihilation of picture handling. In our examinations, the outcomes show that the heartiness and straightforwardness of the versatile watermarking is far superior to the customary one. As proposed, adaptive image water marking system gives awareness of human discernment and complementary quantization methods give versatile quantization that keeps a watermarked picture quality from the bending instigated by watermark-inclusion techniques. With the quality of wavelet, the watermark data is situated at the spatial and recurrence space. In this investigation, the observable parameters from the proposed method give versatile and correlative quantized values and give accurate quantization methods and hence useful for various security and crypto applications.
Watermark, Just Noticeable Distortion (JND), Discrete Wavelet Transform (DWT), Quantization Table, Human Visual System (HVS), Wavelet Coefficients.
A Study on Remote Online Notarization and E-signatures
The e-signatures and remote online notarization application allows notary attorneys and anyone else who needs to certify electronic documents to use secure electronic notarization. E-notary software provides first-rate security and convenience method for both businesses and consumers who deal with notarizations on a regular basis. The software also allows for transparent access to documents that are waiting to be countersigned, as well as to those who have been granted access to sensitive documents. E-notary software can be used by any organization and professional that preliminarily needed notarization; a limited case of the documents that e-notary results can legalize includes property deeds, agreements, and affidavits, among others. The advantages of using an e-notary application include saving time and resources that would otherwise be allocated to the notarization process, providing inspection trails, and ensuring the data integrity of sensitive documents. Certain enotary results grease web conferencing functionality to allow for remote notarization.
E-Notary, E-Signatures, Remote Online Notarization, Law, Contract Management Software.
We as humans tend to feel extreme emotions and if these emotions are not treated correctly these emotions can turn in to depression and anxiety. Moreover, pandemic and lockdowns have made us feel isolated from socializing with other people resulting an increase in cases of anxiety and depression. These cases can be felt untreated. This research aims to treat people with anxiety to some extent. We here discuss about psychological topics like CBT which stands for cognitive-behavioral therapy and DBT (dialectical behavior therapy) which are two types of talk therapy or psychotherapy and about their implementation in the world of information technology. We also discuss that can Alexa from Amazon be used as a platform to implement a voice assistant to treat anxiety at a personal level. It is very important to understand that anxiety and depression must be treated by a doctor and the implementation here is only to research the topics on personal level only.
Anxiety, CBT, DBT, Alexa., Voice Assistant
E-learning: A Paradigm Shift from Traditional in-Campus Learning to Multimedia Based Distance Learning in India Post COVID-19
With the onset of novel corona virus pandemic in early 2020, the major hurdle faced by the educational institutions was to provide continuous and uninterrupted tutoring in the absence of physical availability of the students. Initially, the institutions felt tremendous pressure to provide education to the large amount of students due to the temporary closure of schools, colleges, universities, coaching classes etc. Thus, to overcome the difficulty of physical absence of the students in classrooms, an innovative trend of teaching through virtual classroom has begun to rise. With the influx of video conferencing platforms such as zoom, webEX, Microsoft teams etc., E-learning has become more convenient option to continue imparting knowledge. In the present scenario, E-learning is the most suitable, preferable, accessible and acceptable medium of learning. However, education through E-learning for the prolonged period has shown some failures of its own. The problems faced by the students as well as tutors in virtual classrooms are bound to increase if such ways of teaching continue. Problems related to student participation and interactions are the basic problem in Elearning. Thus, the E-learning can be temporary solution for teaching during the times of current pandemic, but it cannot replace the traditional ways of teaching.