Reviewerly/exHarmony huggingface dataset:
Revocable IBE combined with CRA to overcome the Inadaptability Problem

Identity based encryption (IBE) is an open key cryptographic system and takes out the requesting of the Public key infrastructure(PKI) and confirmation relationship by and large key settings. Due to the nonappearance in PKI, the cancelation problem has become a primary issue in the IBE settings. Two or three cancellable IBE plans have been already proposed concerning this point. As of late, by embeddings an outsourcing figuring framework into the IBE, Li et al. presented a cancellable IBE scheme with the feature of key-update cloud authority association (KU-CSP). Regardless, their arrangement faces two disadvantages. One demerit is that the costs of figuring, correspondence are more than past cancellable IBE designs. Alternate limitation is nonattendance of adaptability as in KU-CSP should maintain secret regard for individual customer. Here another cancellable IBE plot with cloud cancellation authority (CRA) to understand the two disadvantages in which the execution is by and large upgraded and the CRA has only a system puzzle for each one of their customers.
Interpretation on Breast Cancer Generation in 2D &amp; 3D Images by Skeletonization Algorithm

The present usage and values obtained clinically on breast cancer expansion and assessment techniques are tragically not upto the mark. In this advanced world, 3D mammography algorithm is not used till now for identifying cancer expansion. A specialized algorithm called skeletonization algorithm is used after identifying the cancer in women’s breast and estimating the direction of spreading cancer and its malignancy. For this 2D and 3D breast images are taken for clinical experiment.
EyeBlink - “Smart Surveillance System for Detecting Interpersonal Crime”

Due to exponential increase in crime rate, surveillance systems are being put up in malls, stations, schools, airports etc. With the videos being captured 24x7 from these cameras, it is difficult to manually monitor them to detect suspicious objects. So, there is a great demand for intelligent surveillance system. The proposed work automatically detects multiple anomalous objects in videos. Due to exponential increase in crime rate. Surveillance systems are being put up in malls, stations, schools, Airports etc. With the videos being captured 24x7 from these cameras, it is difficult to manually monitor them to detect suspicious activities. So, there is a great demand for intelligent surveillance system. The proposed work automatically detects multiple anomalous activities in videos.
The soil parade to draw attention to soils and ecology

For the first time the Soil Parade action was introduced by the Soil Museum in 2014 as a form of communication practice.
An enhanced system for augmenting urban search and rescue canines

One of the most critical factors in urban search and rescue is time, as the chances of finding someone alive diminish with time. Emergency responders locate casualties, plan their rescue based on the available information, and then extract them. Measures are taken to do this as safely as possible as the harsh environment may lead to rescuers being injured. Our research demonstrates how emergency responders can obtain more information about the victim and the collapse faster, while potentially increasing their Situational Awareness (SA), and thus decreasing the time to rescue of the casualties. The system described is an enhanced version of Canine Augmentation Technology (CAT) -- a telepresence system for augmenting search canines. CAT integrates different technologies like wireless mesh networks, wearable computing, sensors, and software for recording, streaming, and scrubbing of video. The goal of our research is to reduce the time to rescue of victims by providing more relevant information to rescuers faster.
Design and Implementation of Perceptron Neuron in Machine Learning for Handwritten Character Recognition

Due to the exponential increase of electronic devices that are connected to the Internet, the amount of data that they produce have grown to the same extent. In order to face the processing of these data, the use of some automatic learning algorithms, also known as Machine Learning, has become widespread. The most popular is the one known as neural networks. These algorithms need a great deal of resources to compute all their operations, and because of that, they have been traditionally implemented in application specific integrated circuits. However, recently there have been a boom in implementations in field programmable gate arrays, also known as FPGAs. These allow greater parallelism in the implementation of the algorithms. Field Programmable Gate Arrays (FPGA) implementation based feature extraction method is proposed in this paper. This particular application is handwritten offline digit recognition. The classification depends on simple 2 layer Multi- Layer Perceptron (MLP). The particular feature extraction approach is suitable for execution of FPGA because it is utilized with subtraction and addition operations. From Standard database handwritten digit images of normalized 40×40 pixel the features are extracted by the proposed method. It has been discovered by experiential outcomes that 85% accuracy is achieved by proposed system. Overall, as compared to other systems, it is less complex, more accurate and simple. Further this project explains IEE-754 format single precision floating point MAC unit’s FPGA implementation which is utilized for feeding the neurons weighted inputs in artificial neural networks. Data representation range is improved by floating point numbers utilization to a higher number from smaller number that is highly suggested for Artificial Neuron Network. The code is developed in HDL, simulated and synthesis results are extracted using Xilinx synthesis tools .In order to validate its computational accuracy of the FFT, an MATLAB validation script is used to verify the output of HDL with standard reference model.
The Effect of Big Data on English Teaching on the Application of Big Data in English Teaching

In recent years, the application of big data technology in various fields has also attracted very close attention from many scholars and experts. Some experts proficient in big data technology connect English teaching with big data technology, which also helps to further develop the application and development of English teaching in big data technology. This article will also study through the analysis of the significance and function of big data technology, and also explores more new development ideas and points out the difficulties of English teaching in big data technology. At the same time, this article also points out the specific implementation measures, paths and methods of computer big data technology in English teaching. This also helps to enrich computer big data technology to conduct English teaching, and also lay a very good foundation for the quality of English teaching.
Implementation of Efficient Architecture of Fine Grain Pipelined Lifting Scheme Based Two Dimensional Discrete Wavelet Transform

Many Discrete Wavelet Transform (DWT) based VLSI architectures have been projected to meet the necessities of the synchronized signal processing. It includes image processing, speech processing, signal and video processing, etc. The practical implementation of DWT has fewer hitches in terms of hardware complexity and memory requirement since it needs to process huge volume of data. The traditional convolution based system needs more multipliers and larger memory and is also not suitable to provide speed or power efficient image or video processing designs. The lifting scheme involves very few mathematical computations compared to the convolution-based DWT. In this paper, we propose an architecture that performs Discrete Wavelet Transform (DWT) using a lifting-based scheme with fine grained pipelined architecture. The basic DWT filters used in image compression are 5/3(lossless) and 9/7(lossy) filters. In fine grain pipelining, multiplier is split into two units by placing the latches on the horizontal cutset across the multiplier. Thus the critical path is reduced to half of the multiplier delay. As a result, it is a speed efficient architecture and is symmetrical with a lower hardware complexity. The architecture is designed using verilog HDL and implemented on Xilinx Spartan 3E FPGA.
Searchable Encryption

Searchable encryption (SE) is an encryption technique that allows outsourcing the encrypted data to possible untrustworthy third-party service providers, while at the same time allowing the users to apply searching operations directly over the encrypted data safely and securely. Searchable encryption can be considered a type of homomorphic encryption, which will be discussed in Chapter 12 .
Table of Contents and Foreword

In this issue of JICS some of the papers have been selected from the presented at SBMicro2012 (27th Symposium on Microelectronics Technology and Devices), which has been held in Brasília, Brazil, in 2012. Among the contributions presented at the s ymposium, only a few best rated were selected by the JICS Editorial Board and have been invited to submit an extended version to the Journal. These extended papers have passed through the usual reviewing process before acceptance. In addition to the best papers presented at the conference, spontaneous submissions passed through the usual reviewing process and have been accepted as regular papers. We would like to thank the authors for their effort in preparing these high quality papers, as well as the reviewers for their valuable contribution on paper evaluation and selection, which guarantees the scientific level of this issue. We sincerely hope that JICS readers will enjoy these contributions. We also would like to thank the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) for the financial support for this JICS Issue.Marcelo Antonio Pavanello - JICS Editor-in-chiefFernando Gehm Moraes - JICS Co-Editor
Case translation: China

Hangzhou Huatai Yimei Culture Media Co., Ltd. v. Shenzhen Daotong Technology Development Co., Ltd. (2018) Zhe 0192 Civil Case, First Court No. 81, Hangzhou Internet Court of the People’s Republic of China, 27 June 2018&#x0D; China; intellectual property infringement; authenticity of electronic evidence; screenshot of webpage; SHA256 hash value; blockchain related evidence; Bitcoin block chain; integrity of evidence; law of electronic signatures
Data Transmission between Computers via Mobile as a Medium

This paper presents information regarding One-Way data transmission or parallel way data transmission between two computers and computer to mobile/tablet or vice-versa with an inter – mediate medium as mobile for transmission within ‘N’ number of computers and mobiles/tablets connected together with a key feature of unlimited data transmission without third party involvement.
Fraud investigations, records should be in law enforcement unit

Case name : Letter to: Liberty University (SPPO 12/05/17).
VIRTUAL REALITY VIDEO IN DIGITAL CULTURAL HERITAGE APPLICATIONS

Cultural heritage now can be experienced. Digital technologies recreate original appearances of cultural monuments and life inside them. Interactive digital storytelling (Rizvić et al. 2017a) introduces the viewers to historical information through short interconnected stories resolving the problem of short attention span of the audience and their reluctance to read. Virtual, Augmented and Mixed Reality technologies transfer the users in the past. An important part of digital cultural heritage applications is VR video.
Analysis and modeling of the learning process for digital competencies

The article presents the results of a study of the level of digital literacy of the population and student satisfaction when using digital distance educational forms. The authors consider the features of organizing educational environment and present the use of the club system for teaching the population to digital competencies. The article proposes a model for forming digital competencies, taking into account the minimization of training time to achieve an individual set of required competencies. The results of approbation of he club format and model for teaching digital competencies to the population are presented on the example of the work of the "Digital Family".
Feature Selection for Machine Learning in Big Data

We are in the information age there by collecting very huge volume of data from diverse sources in structured, unstructured and semi structured form ranging to petabytes to exabytes of data. Data is an asset as valuable knowledge and information is hidden in such massive volumes of data. Data analytics is required to have a deeper insights and identify fine grained patterns so as to make accurate predictions enabling the improvement of decision making. Extracting knowledge from data is done by data analytics, Machine learning forms the core of it. The increase in the dimensionality of data both in terms of number of tuples and also in terms of number of features poses several challenges to the machine learning algorithms . Preprocessing of data is done as a prior step to machine learning, so feature selection is done as a preprocessing step to have the dimensionality reduction of the data and thereby removing the irrelevant features and improving the efficiency and accuracy of a machine learning algorithm. In this paper we are studying various feature selection mechanisms and analyze them whether they can be adopted to sentiment analysis of big data.
Comparing Automated and Manual Techniques in the Assessment of Blood Parameters at the Kenyatta National Hospital Hematology Laboratory, Kenya

The KNH hematology laboratory has used validation reports done by laboratories in other countries for its operations.This is in contravention of good clinical laboratory practice (GCLP) and the international organization of standards (ISO) 15189-2012 guidelines on laboratory accreditation.There is need for agreeability between both manual and automated CBC results produced
Elliptic-Curve Cryptography

Elliptic-curve cryptography (ECC) represents a public-key cryptography approach. It is based on the algebraic structure of elliptic curves over finite fields. ECC can be used in cryptography applications and primitives, such as key agreement, digital signature, and pseudo-random generators. It can also be used for operations such as encryption through a combination between key agreements with a symmetric encryption scheme. Some other interesting usages can be seen in several types of integer factorization algorithms that are based on elliptic curves (EC), with applications in cryptography, such as Lenstra Elliptic-Curve Factorization (L-ECC) [1]. Elliptic curves appeared for the first time in Diophantus’ works [3], a subject that has remained close to Diophantine geometry [2].
Denoising Images by Dual–Tree Complex Wavelet Transform Combined With Meta Heuristic Optimization Algorithms

Denoising is a prime objective technique for processing images. Image denoising techniques removes the noises present in an image without interrupting its features and contents. The image gets interrupted by channel or processing noise depending on the applications. Thus, the contaminated noises produce degradable image qualities with respect to subjective and objective approach. To overcome this, image denoising approaches were suggested. In the present research, Dual–Tree Complex Wavelet transform (DTCWT) is utilized to achieve image denoising since they perform multi resolution decomposition by two DWT trees. Soft and hard thresholding methods are used to threshold wavelet coefficients. The present research proposes a novel technique to denoise images which gives image information clearly by thresholding and optimization technique. The optimization is carried through different Meta-heuristic optimization Algorithms Genetic Algorithm (GA) and Grey-wolf optimization (GWO) algorithm. Optimization of threshold value is performed after Bayesian method and the observed output produces better results when compared to other techniques involving Visu shrink, Sure shrink and Bayes shrinkbased on peak signal to noise ratio (PSNR) and visual qualities.
Final report on the assessment of the U.S. Geological Survey’s bureauwide Research Grade Evaluation (RGE) process

Graphs comparing the probability of evaluation above grade (odds
Perceived Importance of and Equipment Used for Home Vision Therapy Activities

Home vision therapy activities can be prescribed as part of an in-office optometric vision therapy treatment program. Home training between in-office sessions can be prescribed anywhere from intensive activities to sporadic assignments during a week. Anteo and Emergent ran independent surveys, prior to their partnership and previous to the COVID-19 lockdown, to gather information from vision therapy providers in 2019 and 2015 respectively. Emergent is a vision therapy equipment company whose services also include online vision therapy training and practice management consulting. Anteo is a vision therapy platform for in-office and remote vision therapy. The Anteo survey aimed to (1) identify the perceived importance of vision therapy home activities during a weekly in-office vision therapy regimen (2) assess home activity compliance. The Emergent survey aimed to (1) determine what equipment providers were using when assigning home vision therapy (2) the cost and price charged for that equipment.
Windows 10 IoT Development with C++

Now that you have a basic understanding of how to use Visual Studio 2019, you can learn more about some of the languages you may encounter when developing your IoT solutions. One of those languages is C++—a very robust and powerful language that you can use to write very powerful applications. Mastering C++ is not a trivial task and indeed could take someone several years to be fully knowledgeable of all of its features. However, you do not need to achieve a Zen-like harmony with C++ to be able to write applications for Windows 10 IoT Core. You saw this in action in the last chapter. In fact, if you are just getting started programming or know little about C++, all you need to get going is knowledge of the fundamentals of the language and how to use it in Visual Studio.
Invited Associate Editors for This Special Issue

Reading Research QuarterlyVolume 55, Issue S1 p. S17-S17 Invited Associate Editors for This Special Issue Invited Associate Editors for This Special Issue First published: 16 September 2020 https://doi.org/10.1002/rrq.369Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume55, IssueS1Special Issue: The Science of Reading: Supports, Critiques, and QuestionsSeptember 2020Pages S17-S17 RelatedInformation
Predicting the Network Traffic flow using Long Short-Term Memory (LSTM)

With the information pace of fast connections expanding, the effect of nonlinear variables turns out to be increasingly noticeable, which bring incredible sign uprightness difficulties to the examination and plan of rapid connections. Notwithstanding, there are two holes in the investigation of the nonlinear practices of the rapid connections. One is that there is no recreation stage which can deftly manage various types of nonlinear practices. An elective fast connection demonstrating and examination technique is recommended dependent on the framework ID approach, rather than utilizing industry standard models. This methodology is particularly advantageous for the framework structure/investigation in that the means are basic and the philosophy is entrenched in other control. The other is that there is no metric which can measure the degree of the nonlinearity of the connections. Focusing on these two issues, this paper first models a nonlinear rapid connection dependent on Simulink, which can deftly change the nonlinear practices and investigate the effect of nonlinear practices on the presentation of the fast connections. At that point a measurement is exhibited base on the chief segment examination (PCA) to evaluate the degree of the nonlinearity of the fast connections. Re-enactment results show that the measurement can viably catch the nonlinear seriousness of the connections.
Kob: A Methodology for the Visualization of Boolean Logic

Moore’s Law must work. In this work, we validate the study of spreadsheets. In our research we verify not only that Scheme can be made psychoacoustic, homogeneous, and mobile, but that the similar is right for hash tables. [1],[ 3],[5]
MOBILE LEARNING :

Mobile learning is one of the learning models using mobile technology devices that can support learning (Marinakou &amp; Giousmpasoglou, 2015). Laptops, tablets, smartphones, and other are technology devices that can support mobile learning such as (GÃ¶ksu &amp; Atici, 2013). From these devices, smartphones are the most widely used devices (Ken Nee Chee, Noraffandy Yahaya, Nor Hasniza Ibrahim, &amp; Mohamed Noor Hasan, 2017). Mobile learning uses a very flexible approach, which allows students to learn wherever and whenever (Your et al., 2014), (Kim, Lee, &amp; Rha, 2017). In its application, lecturers are only as facilitators to excel and hone student skills (Hamdani, 2013). This study was research and development (R&amp;D) (Sugiyono, 2016). Data collection techniques used in this study used questionnaires, walkthroughs, Interviews, and tests of student learning outcomes. The development model used is the adoption of the Lee &amp; Owens development model consisting of 5 (five) phase: assessment/analysis, design, development, implementation, and evaluation. (Lee, William W &amp; Owns &amp; Diana L, 2004) At the phase of assessment/analysis, a needs analysis was carried out from the study. Phase Design carried out several steps in the design of the mobile learning model which consists of the preparation of flowcharts, storyboards, and scripts that will be implemented in making applications and implementing mobile learning models. The development phase is the implementation of the design phase. The app that will be used in building products is Moodle mobile app. At this phase, there will be a presentation of media experts, material experts, learning design experts, and linguists experts. The next step is the implementation, which is the implementation of the mobile learning model. The last phase is the evacuation, which is a field trial involving 26 students. The effectiveness test of the mobile learning model done by giving pretest and posttest to assess the increase in student learning outcomes.