Search

Hyperspectral images, having more than hundreds of bands and very high spectral resolution, endeavors a favorable approach for classification of the soil. The accuracy and viability of visible-near infrared (Vis-NIR) hyperspectral imaging proved to be more powerful, as these images have both spatial and spectral information. The purpose of this study is to perform classification on AVIRIS hyperspectral images based on their geographical nature of the soil with endmember selection while comparing various classification models. The classification techniques of these hyperspectral images were analyzed using small fractions among the number of training samples and their spectral features. The study analyzed that use of Constrained Energy Minimization technique yields better results among the various supervised classification techniques. Also, when the hyperspectral data has to be classified using unsupervised learning techniques like K-Means and ISODATA, K-Means performed better than ISODATA with the accuracy of 98.3%.

This research paper suggests to build on the results obtained by Goldin and Reck (2020). It suggests to collect a dataset that can be used to test their method. At the same time, the results from the analysis of this dataset will produce framing-consistent estimates of users' privacy setting preferences. The test of Goldin and Reck (2020)'s method will constitute a methodological contribution to the literature on revealed preferences under framing. The preference estimates will contribute to the literature on privacy preferences and will have implications for policy makers concerned with the security concern on personal data present on the internet. It is proposed to write a similar browser add-on to track people's decision about browser cookie settings. According to the General Data Protection Regulation (GDPR) users, who visit a website from within the European Union or the European Economic Area must be asked for their stated consent on storing browser cookies (General Data Protection Regulation 2020). For the intents of this research proposal, one can divide browser cookies into two groups. First, there are essential cookies that are necessary to guarantee the website's functionality. Second, there are third-party ad-tracking cookies. A website's host still has a monetary incentive to nudge users to allow for the ad-tracking cookies. This can be done by choosing the default cookie settings.

Security is a major concern in a wide range of applications, from cloud storage to messaging via chat. Many different approaches have also been proposed to provide data protection in the cloud, such as AES, DES, and RSA, but Existing systems often fail when only a certain form of encoding is utilised, either AES, OR DES, OR RSA depending on a consumer requirement. However, the major issue with this scheme is that each encryption is done with encryption keys, and if these keys are leaked in some manner, the entire data is destroyed, so we need a solution that can have additional security. As a result, hybrid cryptography is used in this project, in which current encryption techniques are combined with three new methods. When a user uploads data, it is divided into three sections, the first of which is encrypted with AES, the second with DES, and the third with RSA. LSB steganography is used to store the keys in the image, and the three encrypted files are stored in the cloud. Users must first recover the keys from the image before they can import all data from the server. These keys are then used to decrypt the data once more with AES, DES, and RSA. This approach increases the security of records.

Digital image is one of the primary way of communication in the present digital world. During the acquiring process, the images may become noisy. Noise reduction is a demanding task during the image analysis process without dissimilating the important features. It is the procedure of restoring the original image by discarding unwanted noises and known as Image denoising. The main intention of any noise removal technique is to completely eradicate the noise from the image, such that the resulting image is better than the original image. In this digital era, remote sensing images are widely commercial for environmental monitoring. In this study, a correlative analysis of different noise removal methods using various filters in spectral images is performed. Spectral images are introduced with different types of noise and further filters are applied to denoise the image. The performances of the methods are evaluated using benchmarks: Signal-to-Noise Ratio (SNR) and Peak Signal-to-N oise Ratio (PSNR). Experimental results demonstrate that the SNR and PSNR measures were comparatively higher for all the filters when the image is introduced with Poisson noise.

In security information and event management (SIEM), real-time monitoring together with analysis of log data for correlation of events can provide anomaly detection and notification. A centralized log system with big-data databases is required for SIEM in order to store and manage the log data. In this paper, we present dockerized Elastic Stack for security information and event management. The main reasons are because of lightweight, simplicity and supporting features. One of important Elasticsearch features is security information. Elasticsearch can act as Intrusion Detection System (IDS) together with log/event management as SIEM. Our experiments show that dockerized elastic stack can be efficiently used for security information and event management.

A simple passive capacitance model has been optimized to predict breakdown in a stacked SOI FET. Specifically, as the number of FETs in a switch increases, an equivalent increase in breakdown is not seen in hardware; instead, the breakdown performance saturates as the number of stacks in the FET increases. This phenomenon is not predicted by the FET foundry model. This work is focused on FETs for RF switches in flip chip topologies. As a result of this work, the different components that contribute to off-state capacitances were also described which is important for model development and accuracy.

Clean and environment-friendly energy harvesting are of prime interest today as it is one of the key enablers in achieving the Sustainable Development Goals (SDGs) as well as accelerates social progress and enhances living standards. India, the second-most populous nation with a population of 1.353 billion, is one of the largest consumers of fossil fuels in the world which is responsible for global warming. An ever-increasing population is projected until 2050, and consequently, the energy demand in the upcoming decades will be co-accelerated by the rapid industrial growth. The Ministry of New and Renewable Energy (MNRE) with the support of National Institution for Transforming India (NITI) Aayog is working to achieve the Indian Government's target of attaining 175 GW through renewable energy resources. Many Indian states are currently increasing their renewable energy capacity in an objective to meet future energy demand. The review paper discusses in-depth about the three Indian states, namely Karnataka, Gujarat, Tamil Nadu, which pioneers the renewable energy production in India. The global energy scenario was discussed in detail with Indian contrast. Further, the barriers to the development of renewable energy generation and policies of the Indian government are discussed in detail to promote renewable energy generation throughout India as well as globally since the challenges are similar for other nations. This study analyzed various prospects of the country in renewable energy which has been done in a purpose to help the scholars, researchers, and policymakers of the nation, as it gives an insight into the present renewable energy scenario of the country.

In this paper, parallel plate varactor based phase shifter circuits using Barium Strontium Titanate (BST) thin films are presented. A cascade of 10, 15 and 20 parallel plate varactors were able to produce (150°, 258°, 297°), (218°, 381°,443°) and (227°, 402°, 464°) phase shift at (5, 10, 12 GHz) respectively. The 360° phase shift is achieved with small device size, low bias voltages (0-8 V), low leakage currents, low insertion loss and high figure of merit (FOM). FOM of 40, 33, 24 Degrees/dB is achieved with 10, 15 and 20 shunt varactors at 12 GHz respectively. The proposed circuit is very easy to fabricate which uses a CPW transmission line configuration and can be easily integrated with other circuits on chip.

An Event Triggerred — Fractional Open Circuit Voltage Maximum Power Point Tracking (ET-FOCV MPPT) technique is introduced for irradiance change aware open-circuiting in FOCV systems. The ET-FOCV scheme is implemented using a novel Irradiance Change Detection (ICD) block which is based on gradient based current sensing technique. By avoiding the periodic open circuiting in the absence of irradiance change, this technique extracts more energy than the conventional FOCV systems. The proposed ICD block can operate from 10 Hz to 100 kHz system clock frequencies targeting micro scale energy harvesting systems. With the ICD block and ET-FOCV technique, the proposed solar energy harvesting system harvests energy from input power level of 200 µW to 20 mW and input voltage level of 100 mV to 1.5 V and charges a battery to 3.3 V by boost operation. The entire system is implemented in standard 180 nm CMOS technology and the extracted results validate the system performance.

Randomness plays an important role in cryptography algorithms. Increasing randomness of the seed value increases the security offered by any algorithms in cryptography. In this work a novel random number generator was experimented. True random sources were used for seed value generation. Concept of nesting introduced in the series generation section further increased the efficiency of the generated series. Refining step was also done to ensure uniformity of the generated series. Both statistical and graphical tests were done on the generated series and the system was found to be effective.

An ElectroCardiogram (ECG) inter-patient heartbeat time series classification method by a hierarchical system of based on support vector machine and Decision rule, using full heart-beat time series by alignment of R-peaks of all beats, is proposed. PQRST Time series of heart-beats having converted into equal length series by alignment of R-peaks of all heart-beats based on R-peak of largest length PQRST series in the data and by padding zeroes to the smaller length series on either side, was used in this experimentation. The main objective of this paper is to identify the abnormalities in ECG heart beats based on AAMI Categorization. Experiments were conducted on ECG data of 44 patients obtained from MIT-BIH Arrhythmia database. Results were compared with existing methods such as weighted support vector machine (SVM), hierarchical SVM and weighted linear discriminant analysis (LDA). Comparative analysis confirms the viability and superiority of the proposed approach in terms of Total classification accuracy (TCA). Proposed system achieved Sensitivities of 98.7%, 85.9%, 88.8%, 58.3%, PPV% of 98.53%, 82.2%, 89.9%, 85.6% for N, S, V and F classes respectively and a TCA of 97.3%.

Web content extraction is a popular technique for extracting the main content from web pages and discards the irrelevant content. Extracting only the relevant content is a challenging task since it is difficult to determine which part of the web page is relevant and which part is not. Among the existing web content extraction methods, density based content extraction is one popular method. However density based methods, suffer from poor efficiency, especially when the pages containing less information and long noise. We propose a web content extraction technique build on Entropy based Informative Content Density algorithm (EICD). The proposed EICD algorithm initially analyses higher text density content. Further, the entropy-based analysis is performed for selected features. The key idea of EICD is to utilize the information entropy for representing the knowledge that correlates to the amount of informative content in a page. The proposed method is validated through simulation and the results are promising.