Reviewerly/exHarmony huggingface dataset:
Repeated-root bidimensional (&lt;i&gt;μ&lt;/i&gt;, &lt;i&gt;ν&lt;/i&gt;)-constacyclic codes of length 4&lt;i&gt;p&lt;/i&gt;&lt;SUP align="right"&gt;&lt;i&gt;t&lt;/i&gt;&lt;/SUP&gt;.2&lt;SUP align="right"&gt;&lt;i&gt;r&lt;/i&gt;&lt;/SUP&gt;

No AccessRepeated-root bidimensional (μ, ν)-constacyclic codes of length 4pt.2rShikha Patel and Om PrakashShikha PatelDepartment of Mathematics, Indian Institute of Technology Patna, Patna-801106, India and Om PrakashDepartment of Mathematics, Indian Institute of Technology Patna, Patna-801106, IndiaPublished Online:October 13, 2020pp 266-289https://doi.org/10.1504/IJICOT.2020.110738PDF ToolsAdd to FavouritesDownload CitationsTrack Citations Share this article on social mediaShareShare onFacebookTwitterLinkedInReddit AboutAbstractLet p be an odd prime. The main concern of this article is to study all the repeated-root bidimensional (μ, ν)-constacyclic codes of length 4pt.2r over the finite field 𝔽pm. Here, we provide all the self-dual repeated-root bidimensional (1, 1)-constacyclic and (−1, 1)-constacyclic codes of length 4pt.2r over 𝔽pm. We also discuss the repeated-root bidimensional (η, 1)-constacyclic codes of length 4pt.2r over 𝔽pm. Moreover, it has been shown that these structures are useful in the construction of linear complementary dual (LCD) codes and self-dual codes. As an example, we are listed all the repeated-root bidimensional (μ, ν)-constacyclic codes of length 72 over the finite field 𝔽27.Keywordscyclic codes, constacyclic codes, two-dimensional constacyclic codes, dual codes, LCD codes, repeated-root codes Previous article Next article FiguresReferencesRelatedDetails Volume 5Issue 3-42020 ISSN: 1753-7703eISSN: 1753-7711 HistoryPublished onlineOctober 13, 2020 Copyright © 2020 Inderscience Enterprises Ltd.Keywordscyclic codesconstacyclic codestwo-dimensional constacyclic codesdual codesLCD codesrepeated-root codesAuthors and AffiliationsShikha Patel1 Om Prakash2 1. Department of Mathematics, Indian Institute of Technology Patna, Patna-801106, India2. Department of Mathematics, Indian Institute of Technology Patna, Patna-801106, IndiaPDF download
An importance of Primary Health Care in combating the COVID-19 pandemic in Brazil: A systematic review of the literature

INTRODUCTION: In February 2020, the Ministry of Health in Brazil declared the emergency situation facing the COVID-19 From this, the importance of Primary Health Care is confirmed as a strategy to combat the pandemic in Brazilian states, especially in municipalities. Currently, the Unified Health System is responsible for serving 210 million people, with Primary Care being the gateway to the public health service. In this context, the health education actions carried out by the Family Health Strategy Teams (FHS) in conjunction with the other support networks of the Unified Health System are extremely important for mitigating the growing number of COVID-19 cases. all over the country. AIM: To search the literature for academic productions that confirm the importance of Primary Health Care in combating the COVID-19 pandemic in Brazil. MATERIALS AND METHODS: This is a systematic review of the literature carried out on a database of the Virtual Health Library, whose Health Sciences Descriptors (DeCS) were: “primary health care” AND “Corona Virus infections” AND “ pandemic. They were adopted with inclusion criteria: articles published in full, with the delimitation of the last 5 years, in English, Portuguese and Spanish, and articles that were not focused on the theme were excluded.  RESULTS: Eighty-two articles were found on the theme. In light of this, research was able to identify that about 80.9% of people should have mild symptoms of the new Corona Virus, with primary health care as a priority as of the appearance of symptoms. Furthermore, it is the responsibility of the Basic Health Unit to submit the patient to reception with a risk classification. Nevertheless, health education actions carried out by primary health care professionals during the pandemic are responsible for containment and awareness in the fight against the COVID-19 pandemic.  CONCLUSION: In this way, Primary Health Care is extremely important in combating the pandemic of the new Corona Virus, considering its fundamental role in carrying out health education activities in Brazilian municipalities.
Scientific-methodological and scientific study of postgraduate and doctoral students

This publication is a reviewon textbook of I.V. Ponkin and A.I. Redkina “Methodology of Scientific Research and Practical Analytics” (Moscow: Buki Vedi, 2020, 365 p.).
Exploiting Code Generation and Belief Propagation to Infer Identity of Polluters in Cloud Environment

In today’s, digital world the usage of new technology has increased tremendously. Nowadays, the confidentiality of our data which we send or store for our privacy purpose is not completely secured and protected. It’s because of digitalized thefts like Brute Force attack, corruption of data, cloud storage data thereafter etc. In order to overcome these thefts and secure our data, I have proposed a web application security using RKG and Belief Propagation algorithm. Here, we can able to secure the data even in cloud storage system. Using these algorithms, detection of corrupt data, password thereafter has been done and the data is secured and protected in this web application security.
Design and Implementation of Secure Cloud Storage System Based on Elliptic Encryption

Background/Objectives: With the rapid development of Internet technology, more and more Internet users tend to store their data and information in the cloud, and the security of the existing cloud storage system has been criticized by people, which is not conducive to protecting the data and information security of users. Therefore, how to effectively guarantee the security of cloud user data becomes more and more important. Security cloud storage system is the key to solve this problem. Methods/Statistical analysis: A secure cloud storage system is implemented for the user’s cloud data security. Its main function is: in the user login phase, the strict user identity authentication method is adopted to control the user’s access rights and prevent illegal users from logging in. Firstly, the identify authentication scheme based on zero knowledge proof is proposed. Secondly, in the user data upload stage, the user data is split. Finally, the encryption algorithm based on elliptic curve is proposed to encrypt the user’s file splitting table. Findings: The experimental results show that, in the user identify authentication stage, compared with the traditional user authentication method, the security of user identify authentication can be greatly improved by using the identify authentication method based on zero-knowledge proof. Improvements/Applications: The secure cloud storage system based on ellipse encryption developed in this thesis can realize the security of user's data by encryption while considering the efficiency of data upload and download, and has a broad application prospect.
Fault Prediction System With Face And Biometric Using Convolutional Neural Networks

In our everyday lives, everybody is utilizing vehicles.In request to begin thevehicle, the vehicle key is the best way to begin the vehicle or to give start to the engine.TheMulti model based vehicle starter framework actually replaces the vehicle start bysupplanting the key with explicit client face. This savvy vehicle framework is controlled by aRaspberry pi circuit.Here we utilize a two way verification framework for making sureabout the vehicles.The techniques utilized here are Face acknowledgment and BiometricMethod.It contains LCD show, engine, signal, camera and a Fingerprint scanner. Here, theMultiple validation framework takes numerous photographs of the individual and storesthis information into the database and simultaneously it takes a lot of fingerprints andstores them in the database.when the driver goes into the vehicle, his face will be examinedby the camera and it should coordinate with the unique mark that is put away in thedatabase. On the off chance that both face and unique mark is coordinated, at that point thevehicle starts.If an unapproved client attempts to gain admittance to the vehicle,the get togets denied,so that the engine doesn't turn over and empower signaling sound.Hence,itencourages us to make sure about such wise vehicles in a more intelligent manner.
Artificial Intelligence and Access to the Patent System

How likely is it that the average American will become an inventor? With a novel idea and hard work, it should be a possibility for all Americans. The data suggests otherwise. Most patents are obtained by inventors that work for large corporations. Small businesses, solo inventors, women, and minorities lag behind their counterparts in patenting. A common explanation for this phenomenon is that it is a “pipeline” issue. However, evidence suggests that the patent system is not accessible to underrepresented innovators for more problematic reasons.At almost the same time as information about the concentration of patenting activity has garnered attention, the U.S. Patent and Trademark Office (“USPTO”) has become more vocal about its interest in Artificial Intelligence (“AI”). AI will transform how the USPTO examines patent applications. It may also transform how people invent. What has been absent from the conversation about AI and patenting is the negative effect AI has had when introduced in other social systems. For example, AI models can exhibit bias that concentrates power around incumbents. In addition, leaders overestimate the ability of AI models to solve human issues. This article refers to these problems collectively as “AI enthusiasm.”This Article argues that AI enthusiasm threatens to make the patent system less accessible for underrepresented innovators. In response, this article presents a framework for improving access to the patent system given the emergence of AU. First, limits must be placed on AI-assisted examination informed by best practices that combat AI bias. Second, the USPTO should grant patents to inventions that are created with the assistance of AI only if the AI involved adheres to a set of best practices that reduce the chance of biased outcomes. Finally, true access involves removing obstacles to the innovation culture that has historically been closed to underrepresented inventors. Thus, AI tools should be deployed to assist underrepresented innovators in the patenting process. Collectively, these measures may provide U.S. innovators from all walks of life the opportunity to call themselves an inventor.
Translating Transitivity of Indonesian Tourism Texts and Its English Translation : A Case in Madura

Abstract. This research aims at investigating the translation of the transitivity system of Madura tourism texts from Indonesian as the Source Text (ST) into English as the Target Text (TT). Besides, this also purposes to study how the transitivity as the representation of experiential meaning in tourism texts is realized and translated. The method used in this research is qualitative descriptive, while the data were taken from tourism texts of promotional media in Madura. Accordingly, Systemic Functional Linguistics (SFL) is pondered as a tool to identify the transitivity system and its translation of tourism promotion media in Madura. This study shows that the transitivity in tourism texts is translated differently which results in the realization of experiential meaning expression between ST and TT. Most of the experiential meaning in ST are realized with the relational process and as well as in the TT. Transposition and modulation in terms of translation technique also influence the differences of the understanding of readers (tourists) to the object promoted in Madura. Therefore, the process and participant in the transitivity system found ST and TT also generates the dissimilarities interpretation of experiential meaning and point of view in Indonesian tourism texts and its English translation. Keywords: transitivity; translation; tourism texts
Fairness and Explanation in Clustering and Outlier Detection

As machines move towards replacing humans in decision making the need to make intelligent systems transparent (explainable and fair) becomes paramount. However, fairness and explanation remain understudied problems for unsupervised learning with a recent survey on explanation not covering the topicand the seminal papers on fairness appearing only in 2017. The work in outlier detection is even more recent appearing only in the last year. The need for transparency in unsu- pervised learning is greater than in supervised learning as the lack of supervision means there is no extrinsic measure why a given model was chosen. Hence there is more room to be unfair and a greater demand for explanation. In this tutorial we will consider fairness and explanation for classic unsupervised learning methods that are used extensively in data-mining. The majority of published work is for clustering but we will also cover newer work on unsupervised outlier detection. We will cover both explanation and fairness from multiple perspectives. We begin with the philosophical, legal and ethical motivations of what we are trying to achieve with fairness and explanation. Then we move onto rigorous formal definitions of these problems, algorithmic solutions along with their limitations. We then overview example applications and future work.
The Implementation Analysis Of Lamport Scheme With Sha-256 On Mobile E-Office

Electronic administration system is one of the best solutions in the current digital era, electronic-based systems are considered to make it easier for an organization to process data and can reduce the possibility of data loss due to human error or natural disasters. The current administrative data management application is called the Electronic Office (E-Office). The E-Office handles data for incoming mail, outgoing mail and mail disposition. There are frequent delays in receiving information and validating letter files that are still carried out using physical files, so the mobile e-office is a solution that can be used by an agency to make it easier for workers to access information more quickly and can be done anywhere. Data security is an important thing that needs to be considered in an electronic transaction, so this research will add data security to the mobile e-office using sha-256 and lamport schemes. We present data on the results of this mobile e-office test on mobile devices and virtual private servers (vps), the data is in the form of functional application performance testing results and records of processing time performed by mobile and vps devices. From this data an analysis will be carried out to determine the appropriateness of the devices that can be used in running a mobile e-office.
PLP 2021: Workshop on Programming Language Processing

The first international Workshop on Programming Language Processing presents interdisciplinary contributions that address programming language procession problems with machine learning and data mining techniques. Recently, there are lots of successful natural language processing methods. But the mining of programming languages could not exactly follow the manner of natural language processing. The difference between natural language and programming language brings in new research challenges and opportunities. The workshop will bring together researchers from machine learning, data mining and software engineering to discuss and debate the path forward for mining the value of programming languages.
Research on the Teaching Practice of English Linguistics in the Internet Era

As a compulsory course, English linguistics is very important for English majors in colleges and universities. The rapid development of Internet technology not only provides advanced technical support for English linguistics teaching, but also brings new challenges and opportunities to traditional English linguistics teaching. This paper first introduces the main content of English linguistics course, through the analysis of the current situation of English linguistics teaching, explores the new teaching ideas of English Linguistics course under the background of Internet era, hoping to enrich the content of English linguistics course and promote students to have a better learning and mastering of English linguistics course.
Application of Multimedia Technology in College English Teaching Practice

Abstract In the context of global economic integration, English teaching practice is an important part of college teaching curriculum. Improving the quality of college English teaching is conducive to promoting students’ all-round development and improving their comprehensive ability. This paper first analyzes the application of multimedia technology in college English teaching practice, and discusses the specific measures and paths of English teaching mode innovation for readers’ reference.
A Novel All-In-One Grid Network for Video Frame Interpolation

Flow-based approaches for video frame interpolation typically consist of multiple networks that are responsible for feature extraction, optical flow estimation, and image synthesis, respectively. However, they are usually computationally expensive, and can hardly be employed in devices with limited computing resources. In this work, we propose an All-in-one Grid Frame Interpolation Network (AGFIN) to address this problem. AGFIN is a light-weight network with multiple rows and columns. In each row, we estimate the contextual features and optical flows, then the image synthesis module reconstructs the results from the warped frames and features. Each row serves as a coarser or finer auxiliary for the nearest row. In contrast to using multiple networks, our model integrates feature extraction, optical flow estimation, and image synthesis into a compact network. The experimental results show that our approach has better or comparable performance comparing to representative state-of-the-art approaches with less computational cost.
Development of Learning Materials Making Virtual Learning-Based Videos Community Local Wisdom Through Learning Experience for Students

Abstract: The effectiveness of learning through virtual media is increasingly achieving its goals if lecturers and students can develop instructional video media as virtual learning materials. The use of instructional videos in the learning process needs to be systematically designed so that learning media can be used effectively, experience learning-based learning videos so that they are more contextual about the local wisdom of the community. The research objective was to produce a learning model and learning materials for the development of virtual learning video media based on local wisdom of the community through learning experience for students of the Department Non-Formal Education, Faculty of Education, State University of Malang. The research method used is the development (research development) development research model is an attempt to develop and validate educational products. The research design is systematical as follows: (1) the stage of analyzing, (2) the writing stage, (3) the stage of expert assessment and revising, and (4) the stage of the limited trial of the readability of the contents of learning materials related to understanding the content. The conclusion is based on the data analysis of the results of the content assessment on the development of learning materials for making virtual learning video media based on local wisdom of the community through a learning experience in the subject of learning resources and learning media department non-formal educations obtained valid results.
Study of Preference of Stereo Recording Techniques on Kendang Instruments in Jazz Ensembles

Kendang plays an important role in Simak Dialog, a jazz ensemble group that brings jazz and Sundanese music together This study aims to analyze the preferences of the stereo recording technique of kendang in a jazz ensemble. This research was done by conducting a subjective test of 16 audio samples of kendang which were recorded using the stereo technique XY 90o, XY 120o, ORTF, and AB with two variable distances and angles between microphones. 28 respondents consisting of expert and non-expert groups were asked to fill out a questionnaire to determine most prefered audio samples. Furthermore, interviews were conducted to identify aspects that determine the selection of audio samples. This study has identified that the expert group focused on stereo image, subjective frequency characteristics, and the balance between instruments in the ensemble, while the non-expert group more focused on clarity of kendang in terms of spectral characteristics and transients. The two groups focus on two different things. The expert group pays more attention to the the balance between the drums and other instruments. The non-expert group paid more attention to timbre and clarity. This indicates that spatial aspects, timbre, sound quality and defacts are critical aspects to form recording quality of kendang in a jazz ensemble.
Application of a stochastic algorithm for 3D inversion of EM sounding data

Summary Stochastic algorithms belong to methods of global search which are able to find global minimum of discrepancy function in the presence of multiple local minima. Modified cultural algorithm is implemented for 3D inversion of EM sounding data. The algorithm is tested on data of electromagnetic investigations of detecting the gold mineralization zones. The algorithm uses information about the number of candidates for the role of a parent, the number of parents and the probability of mutation as a belief space together with information about global minimum area. Starting from a homogeneous half-space and using no priori information, results obtained by modified cultural algorithm are in good agreement with the data of the 2D inversion.
Detection of Different Tissue Types of Colorectal Cancer Based on Histological Images Using Deep Learning Approach

Objective: Automatic machine learning methods developed by employing deep learning approaches have been the focus of numerous studies nowadays. The objective of the current study is to design a web-based software that is used in the classification of tissue samples in colorectal cancer, based on eight different histopathological tissue types, to support physicians for the clinical diagnosis of colorectal cancer, and thus to enable physicians to make quick and accurate decisions. Material and Methods: An open-access data set (DOI: 10.5281/zenodo.53169) consisting of 5,000 histopathological images, including different histopathological tissue types of colorectal cancer, was used in the present study. Keras-based AutoKeras library was applied to classify the histopathological tissue types of colorectal cancer. Appropriate python language libraries were employed in the development of the web-based software. A deep learning-based model was constructed to predict eight histopathological tissue types of colorectal cancer. Results: The highest metric values among the performance criteria achieved for different tissue types of colorectal cancer were calculated for adipose type, and we found that accuracy was 0.996, sensitivity 0.992, specificity 0.996, precision 0.974, recall 0.992, and F1-score 0.983, respectively. This research differs from other studies in that it includes open access software. Conclusion: The web software based on the model proposed in this study provided promising predictions in classifying different tissue types from histopathological images of colorectal cancer. Thanks to the proposed software, the tissue types of colorectal cancer are easily understood by medical professionals and other healthcare workers. Hence, the workload of medical professionals can be reduced, and a faster consultation system can be formed.