Reviewerly/exHarmony huggingface dataset:
Realization of a New Robust and Secure Watermarking Technique Using DC Coefficient Modification in Pixel Domain and Chaotic Encryption

The proliferation of information and communication technology has made exchange of information easier than ever. Security, Duplication and manipulation of information in such a scenario has become a major challenge to the research community round the globe. Digital watermarking has been found to be a potent tool to deal with such issues. A secure and robust image watermarking scheme based on DC coefficient modification in pixel domain and chaotic encryption has been presented in this paper. The cover image has been divided into 8×8 sub-blocks and instead of computing DC coefficient using Discrete Cosine Transform (DCTI, the authors compute DC coefficient of each block in spatial domain. Watermark bits are embedded by modifying DC coefficients of various blocks in spatial domain. The quantum of change to be brought in various pixels of a block for embedding watermark bit depends upon DC coefficient of respective blocks, nature of watermark bit (0 or 1) to be embedded and the adjustment factor. The security of embedded watermark has been taken care of by using chaotic encryption. Experimental investigations show that besides being highly secure the proposed technique is robust to both signal processing and geometric attacks. Further, the proposed scheme is computationally efficient as DC coefficient which holds the watermark information has been computed in pixel domain instead of using DCT on an image block.
Error tolerant global search incorporated with deep learning algorithm to automatic Hindi text summarisation

There is an exponential growth in the available electronic information in the last two decades. It causes a huge necessity to quickly understand high volume text data. This paper describes an efficient algorithm and it works by assigning scores to sentences in the document which is to be summarised. It also focuses on document extracts; a particular kind of computed document summary. The proposed approach uses fuzzy classifier and deep learning algorithm. Fuzzy classifier produces score for each sentence and the deep learning (DL) also produces score for each sentence. The combination of score from both fuzzy classifier and DL produces the hybrid score. Finally, the summarised text can be generated based on this hybrid score. In our proposed approach, we have achieved an average precision rate of 0.92 and average recall rate of 0.88 and the compression rate is 10% according to the experimental analysis.
Testing Design for Pixel Value Graphical Password Scheme on Image Specimens

In decades, authentication system is relying on username and password as pass-phrase object for authentication process. The longer, wider the variety of symbol choices, and randomly arranged phrase considered as a strong password. A strong password is hard to memorize and make it less preferred by most of the users in most of the cases. To make pixel value graphical password scheme a test-able subject, a coded prototype was developed and deployed. The coded prototype was called as Pixel Value Access Control (PVAC). The study is focused on the testing design and result of experimental testing on different scenario using 24 specimens are used to test the functionality of PVAC pixel value extraction process to produce an accurate pixel value
Synapse Spark

Azure Synapse Analytics provides three compute engine options to choose from. There are two Synapse SQL engines, namely Serverless Synapse SQL and Provisioned Synapse SQL; the third option is Synapse Spark, which is based on Apache Spark. We discussed Synapse SQL in detail in the previous chapter. Now, let us discuss Apache Spark, or Synapse Spark, in detail in this chapter.
Neutrino Oscillations: Atmospheric

The Standard Model of particle physics is an amazingly successful theory describing the fundamental particles and forces of nature. This text, written for a two-semester graduate course on the Standard Model, develops a practical understanding of the theoretical concepts it's built upon, to prepare students to enter research. The author takes a historical approach to demonstrate to students the process of discovery which is often overlooked in other textbooks, presenting quantum field theory and symmetries as the necessary tools for describing and understanding the Standard Model. He develops these tools using a basic understanding of quantum mechanics and classical field theory, such as Maxwell's electrodynamics, before discussing the important role that Noether's theorem and conserved charges play in the theory. Worked examples feature throughout the text, while homework exercises are included for the first five parts, with solutions available online for instructors. Inspired by the author's own teaching experience, suggestions for independent research topics have been provided for the second-half of the course, which students can then present to the rest of the class.
Data Summarization based on Multiple Attributes in Unreliable Categorical Data

Data summarization in preposterous or doubtful front page new streams is an integral production in relational story sources. For prosperous announcement summarization on between rock and hard place story cat and dog weather evaluation by all of the jumps of story streams environments. Traditionally one-class learning work summarization act was approved to translate the indistinguishable illustration and then constitute Undefined One Class Classifier (UOCC) by utilizing such class summarization effectively. This framework substance density based rule of thumb to inspire possible did a bang-up job to garner each chides mutually pragmatic front page new maintenance; UOCC furthermore provides support vector (SV) cross-section to summarization theory centered on user’s likings and article in the stored data source. It was produced potential database on data illustrations. It is unsuccessful to sponsor data distribution based on data characteristics to use data illustrations with cluster-based data sets. We proposed and implemented Enhanced Categorical Cluster Ensemble Approach (ECCEA) to handle data relations between different attributes to explore data from uncertain data. This approach consists of matrix to describe anonymous records into groups in indeterminate dependable data streams with attribute splitting and feature selection. Investigational outcomes of proposed approach give better and efficient cluster ensemble results with multi attributes in real time data sets.
Widget Classes

In this chapter, we’ll review the UI widget classes of the MmgBase API. These are advanced classes similar to those we’ve reviewed before, but they are designed to work as part of a game menu, a settings screen, or other types of configuration screen. These classes greatly simplify the work needed to get a game screen that takes user input up and running. They also provide solid support for scroll panes and large text blocks:
Agrobot: NLP based Image and Text Query Chatbot

Technology is getting advanced day by day in almost every fields. But farming is a field in which the advancement in technology is still lacking in many of the rural areas. Farmers in the rural area still follow the traditional method of collecting information that is talking to each other but the information they obtain through this might not be accurate. So the proposed system aims to solve all the farming related queries within a short instant. The proposed system is named as Agrobot and is an intelligent system which can recognize misprinted words, avoids grammatical mistakes and gives output even if the sentence is inadequate. Agrobot is built using natural language processing techniques which takes the sentence does several processing on it and then the most suited result is displayed. To get the accurate output classification algorithms are used. Agrobot produces an output in text as well as in voice form. Agrobot is able to solve query in English as well as in Hindi language.
Suckling Pig

Other| April 01 2019 Suckling Pig A. L. Snijders; A. L. Snijders Search for other works by this author on: This Site Google Lydia Davis Lydia Davis Search for other works by this author on: This Site Google Common Knowledge (2019) 25 (1-3): 484. https://doi.org/10.1215/0961754X-7299594 Cite Icon Cite Share Icon Share Facebook Twitter LinkedIn MailTo Permissions Search Site Citation A. L. Snijders, Lydia Davis; Suckling Pig. Common Knowledge 1 April 2019; 25 (1-3): 484. doi: https://doi.org/10.1215/0961754X-7299594 Download citation file: Zotero Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search Books & JournalsAll JournalsCommon Knowledge Search Advanced Search The text of this article is only available as a PDF. Copyright © 2016 A.L. Snijders2016 Article PDF first page preview Close Modal You do not currently have access to this content.
Multi Labeled Imbalanced Data Classification Based on Advanced Min-Max Machine Learning

Some true applications, for example, content arrangement and sub-cell confinement of protein successions, include multi-mark grouping with imbalanced information. Different types of traditional approaches are introduced to describe the relation of hubristic and undertaking formations, classification of different attributes with imbalanced for different uncertain data sets. Here this addresses the issues by utilizing the min-max particular system. The min-max measured system can break down a multi-mark issue into a progression of little two-class sub-issues, which would then be able to be consolidated by two straightforward standards. Additionally present a few decay procedures to improve the presentation of min-max particular systems. Trial results on sub-cellular restriction demonstrate that our strategy has preferable speculation execution over customary SVMs in settling the multi-name and imbalanced information issues. In addition, it is additionally a lot quicker than customary SVMs
Recognizing Facial Expression in Video Processing

Theoretical, the Micro-expressions convey explicit nonverbal data, for instance the facial development caused by agony. In any case, as a result of their neighborhood and short nature, it is hard to distinguish MEs. This paper displays a novel recognition technique by perceiving a nearby and worldly example of facial development. In our framework, with the reason of improving the discovery precision, fleeting neighborhood highlights are created from the video in a sliding window of 300ms (mean span of a ME). These highlights are separated from a projection in PCA space and structure a particular example amid ME which is the equivalent for all MEs. Utilizing a traditional characterization calculation (SVM), MEs are then recognized from other facial developments. At long last, a worldwide combination examination is connected on the entire face to dispose of false positives. Trials are performed on MATLAB. The discovery results demonstrate that the proposed technique beats the most prevalent discovery technique by the investigation of different measurements.
Google Charts JSON Data Tables directly from ERDDAP

ERDDAP is a data server developed at NOAA Southwest Fisheries Science Center that allows users to easily access and download subsets of gridded and tabular data. At the Scientific Data Integration Group at NOAA’s Pacific Marine Environmental Laboratory we have focused on ERDDAP as the primary mechanism by which we serve all of our tabular data. Besides offering data access in a variety of useful formats, ERDDAP takes care of normalizing the data structure so that all tabular data sets have a simple row and column structure. Additionally, time values are normalized to have a consistent units across all data sets on the server. The simplified tabular nature of the discrete data in ERDDAP lends itself nicely to use with the Google Visualization API (Google Charts). Charts is an API which renders nearly all of the graphics in the browser client. The basis of all charts is the Google Charts DataTable which is exactly analogous to a TableDap table in ERDDAP. Charts are interactive, visually pleasing, free and easy to use and so connecting ERDDAP data to Google Charts is a natural fit. Even though ERDDAP has many output formats including several different JSON renderings, none fit exactly into the specified Charts data types. Initially, as a result, it was necessary to create custom code (either in the client or on a server between the client and the ERDDAP server) to manipulate the ERDDAP data stream to match the Charts API requirements. However, since Charts has a well-documented specification for a JSON representation of the required data type and because ERDDAP is an open source project, it was possible to extend ERDDAP to support the Charts DataTable as a new data type. Using this new data type, it’s possible to instantiate a Charts DataTable object directly from the ERDDAP URL using a simple Ajax call in the client which downloads the JSON DataTable representation. Because the newly added data type is now native to ERDDAP, it is possible to use default constraint syntax and ERDDAP RESTful services (using the ERDDAP user interface if desired) to build the URL for the exact data subset which is to be visualized by the desired google chart. In this presentation, we’ll explain what we’ve done to add the JSON data type to ERDDAP and provide many examples of client-side rendering of earth science and engineering data using Google Charts directly from ERDDAP URLs.
Introduction

Dear readers, I introduced the first edition of this book with the words: "It is still a sad reality that many software development projects are in bad condition, and some might even be in a serious crisis." That was a little over three years ago, and I am pretty sure that the general situation has not improved significantly since then.
An effective programming of GCD Algorithms for natural numbers

We study the problem of acceleration of GCD algorithms for natural numbers based on the approximating k-ary algorithm.We suggest a new scheme of the algorithm implementation ensuring the value of the reduction coecient ρ = A i /B i at a stage of the procedure equal or exceeding k where k is a regulating parameter of computation not exceeding the size a computer word.This ensures a signicant advantage of our algorithm against the classical Euclidean algorithm.
Determining Factors Influencing Faculty Feedback using Data Mining Technique

Faculty is a major stakeholder in an education institute. Quality of faculty reflects the quality of youth, the future nation builders. Based on the vision of honorable management, an attempt has been made to gather the feedback of faculty reflecting their current state of work. Data have been collected initially via open-ended questionnaire. Faculties serving renowned institutes in the states of Punjab and Haryana have been approached to gather information. Attributes have been identified from the literature review and using an appropriate measurement scale. Only the willing respondents and their responses have been taken into consideration. The responses gathered using 5-point Likert-Scale was then factor analyzed. The attributes converged mainly on six dimensions- recognition, sense of belongingness, working environment, basic need fulfillment, self-respect, and contribution to society. These dimensions have been discussed keeping in view the current scenario in the education sector. The study also provides insights into future research.
Here to Stay After the Pandemic: Sentiment Analysis of Higher Education Teachers at UNAM

In order to continue teaching during the Covid-19 pandemic, teachers around the world were forced to move their courses online without prior notice, learn digital technologies quickly, and adapt their teaching practices to this new environment. In this research project, we analyzed 244 comments posted in a collaborative wall by teachers at a university regarding the changes that are here to stay. Using four artificial intelligence algorithms, we estimated and classified the sentiments and emotions expressed in the texts; we also identified the themes that were mentioned by teachers with a qualitative methodology, thematic analysis. Findings showed that positive and neutral feelings towards the changes prevailed among teachers, and that comments were centered on facts more than opinions. The predominant emotion was confidence, followed by anticipation, joy and sadness. It was also evident that they envision technological changes in their teaching practice, but that they are also considering an impact on their pedagogy as well as in their attitudes towards education and life, and in their relationships with students.
Interscale adaptive threshold wavelet filter for ultrasound image despeckling

In this paper, a new wavelet shrinkage algorithm in the undecimated wavelet domain is proposed using an interscale adaptive threshold and an exponential thresholding function for the removal of speckle noise in ultrasound images. An improved spatial adaptive threshold is discussed, exploiting the inter and intrascale dependency of the wavelet coefficients. A new exponential thresholding function is proposed in this paper to overcome the smoothing effect produced by the hard and soft thresholding functions. The reconstructed image exhibits an improved noise removal with preservation of fine details. Performance of the filter is measured using various performance metrics like peak-signal to noise ratio (PSNR), mean square error (MSE), structural similarity index measure (SSIM), equivalent number of looks (ENL) and edge preservation index (EPI). A comparison of the results reveals that the proposed filter shows significant improvement in terms of quantitative measures and in terms of visual quality of the images.
SIMULASI PENERAPAN TEKNOLOGI FACE RECOGNITION PADA APLIKASI PENDATAAN KEHADIRAN KARYAWAN / KARYAWATI TERINTEGRASI E-MON SISTEM PENGGAJIAN DENGAN PENDEKATAN EIGENFACE DAN UXD LARAVEL VERSI 5.6 BERBASIS CLOUD SERVICE

Face recognition is a face-oriented recognition method by comparing patterns that have previously been stored in the database. In general, facial image recognition systems are divided into two types, namely feature based systems and image based systems. To carry out facial image recognition, there are several kinds of approach algorithms that can support the processing of the face image. One approach algorithm that is well known and capable of processing images with a good level of accuracy is the eigenface approach. By using the eigenface approach, the face image will be processed by performing a matrix calculation, which results in an eucludian distance to be able to get the suitability of the face image. so this research produces a result which includes: the results of the test on the FGD Functional says for the accepted percentage is: 73% for not accepted is 27%, for Non-Functional FGD says for the accepted percentage is 82% and not accepted is 18 %, and for the results of testing the adaptation of ISO 9126 in the good category with a percentage result of 79%, and the last test result, namely the Blackbox Testing test to be accepted is 83% and for the results the percentage that is not accepted is 17%
Agro Image De Noising (Aid) for Enhanced Agricultural Images

Several Noises may be present in acquired images. This is an undesired feature for image processing techniques that analyze these images. Image de-noising helps improve efficiency of image processing. Many image de-noising methods have been proposed and exist in literature. Image de-noising methods for agricultural images have been proposed to a lesser extent when compared to the bright medical or photographic images. This paper proposes Agricultural Image De-noising (AID) which uses a discrete wavelet transform (DWT) to eliminate noise in agricultural images. This study uses specific kind of wavelet family spline wavelet transforms with appropriate decomposition level and the wavelet coefficients are analysed with hard and soft threshold methods. The denoised image using various spline wavelets is compared of hard threshold and soft threshold are assessed. The performance of AID is calculated using the peak signal to noise ratio (PSNR) and signal to noise ratio (SNR).
Hand Writing Recognition System using Neural Networks

Handwritten Recognition is a process of pattern recognition which defines ability of a system to identify characters. There are many applications of Handwritten recognition (HWR) system such as reading postal addresses, bank check amounts, mail sorting and many more. HWR systems transcribes human written text into digital text. Plenty of research done in the field of recognizing handwritten characters but lacking in best accuracy is a challenge. In this proposed technique, offline HWR is done using Neural networks(NN) and Tensorflow is proposed. The proposed technique used to build a system which will be able to recognize the hand written characters with highest accuracy. The experiment is performed on proposed technique with accuracy of 85.5% compared to the state-of-the-art.
A promising method, which would deserve bette rpresentation

Review of DINCAE 1.0: a convolutional neural network with error estimates to reconstruct sea surface temperature satellite observations This study presents a novel approach of reconstructing sea surface temperatures from cloudy satellite data by making good use of modern deep learning techniques.While I believe that the study has been carefully designed and executed, I have severe problems with the paper in terms of its presentation and accuracy in writing.This study could become a high-impact publication if it were better structured and methods and outcomes were described clearer.I advise the authors to apply major revisions and seek the help of a native speaker to avoid erroneous or ambiguous statements.Below, C1
An Efficient Image Downsampling Technique Using Genetic Algorithm And Digital Curvelet Transform

Propelled pictures are used everywhere and are definitely not hard to manage and change in view of the availability of various picture getting ready and adjusting programming. Repeat the image to a lesser extent and change the look of the image. This can be useful at times when the original version of the original will give you a slim version of the film. There are several methods of image downsampling. This sheet uses performance capabilities for a collage based on digital curve transfers and generic algorithms. Genetic Algorithm (GA) is attached by the Digital Curvelet Transform (DCT). Originally DCT The length of the map decreases by using. Using this reduced map, gateways and entry worth are coordinated by the utilization of hereditary estimation. From the appraisal of results, it will when all is said in done be picked that the proposed method is quick and exact.
The implementation of memetic algorithm on image: a survey

The growth of information technology is equal to the use of the algorithm. One of the most well-known algorithms is Memetic Algorithm (MA). MA is a part of the evolutionary algorithm and has been implemented on the most complex computational challenges. MA could be implemented in any field of research such as optimization, scheduling, prediction, image processing, image recognition, and many more. However, this research concerns the survey on the implementation of MA in image classification, image processing, and image recognition to find how many works are conducted related to MA and image. In this work, we use the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analysis) method to survey another research about the implementation of MA, specifically on the image. The purpose of this survey is to determine the extent of the implementation of MA in image data. Finally, we found each 1 paper uses MA for image retrieval, 12 papers use MA for image processing and 18 papers use MA for image recognition and 2 papers use MA for image classification.