The IRS-assist or smart radio environment technique is a widely developing technology that network providers can use to establish sustained connectivity between end-user terminals and central data units for the next- generation wireless standards. This article introduced a simple and more accurate link-switching technique for dual-hop communication: a single link-switching threshold (SLST) algorithm to provide an uninterrupted linkage between the transceiver terminals. Depending on the severity of the communicating channel under a dual-hop system, links can do auto switches between themselves and furnish continuous connectivity between end-user terminals. Due to a discrete number of phase shifts of the IRS elements, phase and quantization errors are induced in the channel; the proposed system can also optimize the phase and quantization errors. Besides, this work investigates improving the physical layer performance of the dual-hop wireless communication system under the combined effect of phase shift and quantization error with the introduction of the SLST method. For this particular, three performance metrics have been encountered: the outage probability (OP), average bit error rate (ABER), and average capacity (bits/s/Hz). A new, more accurate mathematical framework using the Meijer'G function has been constructed to evaluate worthwhile analytical derivation. Under analytical calculation, we have assumed the primary link experienced with common Rayleigh fading and the IRS-assist link (IAL) experienced with Nakagami-m distribution due to a large number of reflecting elements in the system. The proposed dual-hop system furnishes noteworthy benefits for each performance metric rather than individual links. Moreover, the suitable selection of quantization level and a number of reflecting elements confirm the exhibition of satisfactory outcomes and minimize the channel hardness of the system. Additionally, numerical simulation results from MATLAB, using Monte Carlo simulation, have been added to validate the analytical outcomes for every performance measure.

The Smart radio environment or Intelligent Reflecting Surface (IRS) technique is the most arising technology for next-generation wireless standards due to the enriching abilities of the physical layer performance of the communication system. The mathematical framework of various types of channel capacity has been derived depending on the existence of channel state information (CSI) on the transmitter and receiver terminal in the proposed IRS-assist wireless communication system in this article. In this aspect, the Optimal Rate Adaption (ORA), Optimal Power and Rate Adaption (OPRA), Channel Inversion with Fixed Rate (CIFR), and Truncated Channel Inversion with Fixed Rate (TIFR), four various channel capacity policies are introduced here. Next, the combined influence of phase shift and quantization error on the different channel capacities has been observed under the proposed model. We have expressed new and accurate analytical closed-form expressions for every type of channel capacity strategy. Moreover, the accuracy of our analytical derivation has been checked by Monte Carlo simulation results from MATLAB.

Digital watermarking can be used to ensure the authenticity and copyright protection of images. In watermarking balancing the trade-offs between its features is an important issue. To address this issue, in this work an adaptive hybrid domain color image watermarking based on Discrete Wavelet Transform (DWT), Walsh Hadamard Transform (WHT), and Singular Value Decomposition (SVD) is proposed. Here, watermarking is carried on YC_bC_r color space. In this work, the embedding factor is calculated adaptively using the visual entropy and edge entropy. For better robustness the watermark is inserted into the Y component of YC_bC_r color Space. Further, Arnold Transform (AT) is used to secure the watermark. The average PSNR and SSIM of the proposed hybrid domain adaptive watermarking scheme is 40.0876 dB and 0.9883 respectively. The experimental results compared to the recent hybrid domain color watermarking, illustrate the superiority of the suggested approach.

This report presents a pixelated wideband Metamaterial Absorber (MA) that operates in a microwave region. The proposed metamaterial absorber contains two same-shape resonators made-up of splitted squares in the form of pixels that have been obliquely placed opposite to each other. Wideband absorption of 5.67 GHz (52.88%) that ranges from 6.40 to 12.07 GHz with absorptivity above 90% has been achieved, which covers the X (8 to 12 GHz) band. The Full Width Half Maxima (FWHM) of the structure is 6.84 GHz (58.82%) which ranges from 5.96 to 12.80 GHz. The presence of metamaterial properties in the region of interest has been explained by plotting an Electromagnetic (EM) parameter, real and imaginary curves. The high absorption phenomenon is explained using surface current and electric field distribution at three absorption peaks (6.8, 8.5 and 11.9 GHz). The sensitivity of the polarization for the structure has been examined under normal and oblique incident of the wave. The proposed structure has been designed using ANSYS HFSS 19.1. The advantage of the proposed MA is the wideband absorption with an overall dimension of 16.5 $$ \times $$ 16.5 $$ \times $$ 3.2 mm in contrast to that of the other reported microwave MAs.

WSN has been exhilarated in many application areas such as military, medical, environment, etc. Due to the rapid increase in applications, it causes proportionality to security threats. Mostly, nodes used, are independent of human reach and dependent on their limited resources, the major challenges can be framed as energy consumption and resource reliability. Due to the limitation of resources in the sensor nodes, the traditionally intensive security mechanism is not feasible for WSNs. This limitation brought the concept of Digital watermarking in existence. The intent of this paper is to investigate the security related issues and role of watermarking in wireless sensor networks. Watermarking is an effective way to provide security, integrity, data aggregation and robustness in WSN. Digital watermarking is essential in WSN since it provides security in various forms such as confidentiality, service availability and data freshness. We have briefly discussed the various security requirements in the wireless sensor networks. Several issues and challenges, as well as the various threats of WMSN, is also considered. The related work, suggests that lots of research work are required to improve the security and authentication issues of WMSN by digital watermarking. This survey contribution will be helpful for researcher to accomplish effective watermarking scheme for WSN. WSN is the collection of sensors that are spread in the environment. They measure and monitor physical conditions like temperature, sound, pressure, humidity, etc. and organize the collected data at the main location. The base station then forwards the data to end-users who analyze and make strategic decisions. Nowadays the modern network is bi-directional i.e. we can control the activity of the sensor. The central stations, unlike another sensor network, have infinite power, plenty of memory, powerful processors and a high bandwidth link. Whereas sensors are small in size, have fewer computation abilities, transfer wirelessly and are power-driven by small batteries Watermarking is an effective way to provide security, integrity, data aggregation and robustness in WSN. Digital watermarking is essential in WSN since it provides security in various forms such as confidentiality, data integrity, service availability and data freshness. In this paper, we have briefly discussed the various security requirements in the wireless sensor networks. We have also discussed work done by several authors in WSN with watermarking techniques Wireless network faces more challenges as compared to wired network. In WSN, maximum amount of data and information can be stealed and effortlessly accessed during transmission. The nodes in a wireless sensor network (WSN) are resources constrained. Due to which WSNs have certain challenges i.e. processing power, storage and computational capacity and high bandwidth demand. Security schemes are not easy to design since the network tends to be large and ad-hoc. The analysis for privacy and security have been explored by some authors like J. Zhu et al. In recent years, a cryptography-based security designs have been proposed for WSNs. Cryptography is the process of concealing the information into the cipher text by encrypting it.

Text classification and Topic Modelling is the backbone for the text analysis of huge amount of corpus of data. With an increase in unstructured data around us, it is very difficult to analyse the data very easily. There is a need for some methods that can be applied to the data to get the sensitive and semantic information from the corpus. Text classification is categorization of text in organised way for the interpretation of sensitive information from the text, while Topic modelling is finding the abstract topic for the collection of text or document. Topic modelling is used frequently to find semantic information from the textual data. In this paper we applied Parsing techniques on various websites to extract the HTML and XML data which includes the textual data and also applied Preprocessing techniques to clean the data. For the text classification purpose some of the Machine learning based classifiers that we have used in our experiment are Naive Bayes and also Logistic Regression Classifier. The models of the document are built using three different topic modelling methods which are Latent Semantic Analysis, Probabilistic Latent Semantic Analysis and Latent Dirichlet Allocation. In the further experiment we have done analysis and also comparison based upon the performance of the models and classifiers on the processed textual data.

This paper proposes a robust and secure watermarking method for a color image in YCbCr color space. In this study, watermarking is performed using Lifting Wavelet Transform (LWT). Here, edge entropy and information entropy is used to find the block to embed watermark. In this work alpha blending scheme is used for embedding and extraction of watermarks in the LWT domain. The use of LWT makes the proposed scheme faster and more efficient. The Arnold Cat Map (ACM) is used to enhance watermark security. Numerous tests are presented to illustrate the feasibility of the proposed scheme. The experimental results obtained are compared to state-of-the-art schemes, which demonstrate the superiority of the proposed scheme.

This paper presents a new and mathematical method for online signature validation based on machine learning. In this way, the average values of the factors are taken into account to ensure validity. Here, seven different types of features used are x coordinates, y coordinates, time stamp, pen up and down, azimuth, height and pressure. Three new features are extracted from it, i.e., (displacement, velocity and acceleration) using the correlated extraction process to obtain dynamic feature of signature. These features are extracted from the popular dataset SVC2004. The extracted feature is then passed to various classifiers named as Naive Bayes, random forest, J48, MLP, logistic regression and PART. The result of genuine and forge signatures is obtained in terms of precision, true positive rate, false positive rate, F -score, etc. The obtained result is then compared with the existing method with respect to false acceptance rate and false rejection rate.

With the rapid increase in the use of the Internet, sentiment analysis has become one of the most popular fields of natural language processing (NLP). Using sentiment analysis, the implied emotion in the text can be mined effectively for different occasions. People are using social media to receive and communicate different types of information on a massive scale during COVID-19 outburst. Mining such content to evaluate people's sentiments can play a critical role in making decisions to keep the situation under control. The objective of this study is to mine the sentiments of Indian citizens regarding the nationwide lockdown enforced by the Indian government to reduce the rate of spreading of Coronavirus. In this work, the sentiment analysis of tweets posted by Indian citizens has been performed using NLP and machine learning classifiers. From April 5, 2020 to April 17, 2020, a total of 12 741 tweets having the keywords "Indialockdown" are extracted. Data have been extracted from Twitter using Tweepy API, annotated using TextBlob and VADER lexicons, and preprocessed using the natural language tool kit provided by the Python. Eight different classifiers have been used to classify the data. The experiment achieved the highest accuracy of 84.4% with LinearSVC classifier and unigrams. This study concludes that the majority of Indian citizens are supporting the decision of the lockdown implemented by the Indian government during corona outburst.

Social media has become a vital platform for individuals, organizations, and governments worldwide to communicate and express their views. During the coronavirus disease 2019 (COVID-19) pandemic, social media sites play a crucial role in people communicating, sharing, and expressing their perceptions on various topics. Analyzing such textual data can improve the response time of governments and organizations to act on alarming issues. This study aims to perform sentiment analysis on the subject of COVID-19 vaccination, perform temporal and spatial analyses of the textual data, and find the most frequently discussed topics that may help organizations bring awareness to those topics. In this work, the sentiment analysis of tweets was performed using 14 different machine learning classifiers and natural language processing (NLP). Lexicon-based TextBlob and Vader are used for annotating the data. A natural language toolkit is used for preprocessing of textual data. Our analysis observed that unigram models outperform bigram and trigram models for all four datasets. Models using term frequency-inverse document frequency (TF-IDF) have higher accuracy than models using count vectorizer. In the count vectorizer class, logistic regression has the best average accuracy with 91.925%. In the TF-IDF class, logistic regression has the best average accuracy of 92%; logistic regression has the highest average recall, F1-score, and ten cross-validation scores, and a ridge classifier has the highest average precision. The unigram models show a standard deviation (SD) of less than 1 for all classifiers except for the Gaussian Naïve Bayes showing 1.18. The experimental results reveal the dates and times in which most positive, negative, and neutral tweets are posted.

With high demands for data and processing power, the server industries are proliferating daily. Some hardware can be controlled by servers or Raspberry pi. So, tester and debugger must log in to this server and test and debug this hardware. If these have to be done on 100s of servers, which will be very difficult. So, to overcome this problem we have designed a framework based on SSH with multi-threading though there are various tools, our analytical & experimental studies show that SSH with multi-threading or multiprocessing is far better than these tools. This Framework which designed by us will parallelly login into nearly 100s of server or clusters of servers (created using cluster algorithm designed by us.) at once and can run some automated activity like updating software, running some test cases like stressing processors & memory or performing some activity which can be controlled by Raspberry pi or get logs, etc. This Framework is very useful for hardware controlled by server or Raspberry pi & server industries, especially in the condition like COVID-19.

In today’s digital era, it is very easy to copy, manipulate and distribute multimedia data over an open channel. Copyright protection, content authentication, identity theft, and ownership identification have become challenging issues for content owners/distributors. Off late data hiding methods have gained prominence in areas such as medical/healthcare, e-voting systems, military, communication, remote education, media file archiving, insurance companies, etc. Digital watermarking is one of the burning research areas to address these issues. In this survey, we present various aspects of watermarking. In addition, various classification of watermarking is presented. Here various state-of-the-art of multimedia and database watermarking is discussed. With this survey, researchers will be able to implement efficient watermarking techniques for the security of multimedia and database.

Digital image watermarking technique based on LSB Substitution and Hill Cipher is presented and examined in this paper. For better imperceptibility watermark is inserted in the spatial domain. Further the watermark is implanted in the Cover Image block having the highest entropy value. To improve the security of the watermark hill cipher encryption is used. Both subjective and objective image quality assessment technique has been used to evaluate the imperceptibility of the proposed scheme.Further, the perceptual perfection of the watermarked pictures accomplished in the proposed framework has been contrasted and some state-of-art watermarking strategies. Test results demonstrates that the displayed method is robust against different image processing attacks like Salt and Peppers, Gaussian filter attack, Median filter attacks, etc.

The society is progressing toward the centralization of information, and hence, there is an urgent need to have the information available at any dimension, anywhere, and anytime. To fulfill the need, the radio signals that have high frequency are used to communicate among the PCs or computers including other network devices from last three decades. In this paper, a survey on secure transmission is done to identify the problems faced while transmitting data over wireless network and ensure safe transmission. Further, various types of protocols and issues related to wireless networks are identified.

Grid computing or network computing allows users to increase computational ability within a constrained amount of resources. Grid computing is used to create a mega self-sustaining virtual system, that consists of a huge number of connected heterogeneous systems. Although, unprecedented resource access is provided in the grid, but its underlying characteristics of large scale distribution, heterogeneity, dynamism, autonomy, etc. make it failure prone. Extensive research has been done in finding out the security challenges to achieve the dependability of grid system. In this paper, we attempt to the describe different level of security solution against various security challenges such as resource level, management level, authentication and authorization level and information level.

Cloud computing can be thought of as a emerging model for business computing. It provides an on-demand supply of shared pool of data and resources hosted at providers’ site. In this paper we will discuss primarily about the issues and challenges faced in cloud computing.

During last few years, the electronic medical records can be effortlessly stored with the fast development of healthcare technology. However, the patient's medical information security is current prime concern. Massive volumes of health data are generated in the development of treatment in medical centers such hospitals, clinics, or other institutions. Because of these ever-growing numbers of medical digital images data and the requirement to share them between specialists and hospitals for improved and more precise diagnosis requires that patients’ privacy be protected. For this fact, there is a necessity for medical image watermarking. In this paper several security requirement in healthcare system is presented. We have also discussed the role of watermarking in the healthcare domain. There is also a brief discussion on various watermarking methodologies to protect the secrecy of medical records and data.

This research paper presents path following two wheeled compact portable robot with arduino nano as cental driving functional unit with novel features of wireless control using wifi and bluetooth module with collision detection, avoidance and control features which provides the unique ability of danger avoidance, falling from a hieght with improved stablity and precision control. The extremely sophistcated design provides very good controlled movement on horizantal ground terrain surfaces with data collecting and processing capabilties. The design is integrated with infrared sensors, bluetooth module, wifi module control with dc gear motors which controls the speed of the vehicle of the robotic vehicle and avoid collision with any obstacle detected in the path of the robot. It has the unique abilty of running in maze with path following abilties controlled from any remote location using WiFi for long range control and bluetooth for short range control. In this research article a entire system is designed and implemented in which movement is stably controlled based on feedback from infrared transreciever module. A low cost robust portable design using GUI control has been implemented with advanced features which makes it very unique and attractive for commercial production.

Digital Watermarking enables us to protect ownership rights on digital multimedia, such as audio, image and video data. Digital watermark is a digital signal carrying information of the creator or distributor of the media. Digital watermark is inserted into digital media in such a way that it is imperceptible to the human eye, but it is visible to a computer. A watermarking attack is any processing that may impair watermark detection. There are different types of attacks which can affect the watermarked image which include cropping, noise (salt & pepper, Gaussian), rotation etc. In order to create the copyright issues, these attacks damage the inserted watermark. This paper reviews the performance analysis of the watermarking algorithm based on the combined concept of entropy of block image and LSB Substitution in the presence of different types of attacks to justify the robustness of the algorithm.

During last few years for copyright protection, security and data authentication of digital media, digital watermarking has been raised as the one of the burning research topics due to the rapid expansion of Internet. This paper presents a new technique for image watermarking in the spatial domain where the concept of information theory is utilized with the popular LSB substation technique. Here, the cover image is segregated into a number of blocks and the watermark is embedded into the block(s) with the maximum entropy value. The extraction algorithm is also able to find the watermark correctly. The proposed algorithm was evaluated with the help of various standard performance measures like Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR) and Structural Similarity (SSIM) measure to verify the perceptibility and the robustness of the algorithm. Experimental resultsdemonstrate that the improved algorithm performs reasonably well over a large varied datasets of cover and watermark images.