Reviewerly/exHarmony huggingface dataset:
A Visualization Tool for Analyzing the Suitability of Software Libraries via Their Code Repositories

Code repositories are a common way to archive software source code files. Understanding code repository content and his- tory is important but can be difficult due to the complexity of code repositories. Most available tools are designed for users who are actively maintaining a code repository. In contrast, external developers need to assess the suitability of using a software library, e.g. whether its code repository has a healthy level of maintenance, and how much risk the external developers face if they depend on that code in their own project. In this paper, we identify six risks associated with using a software library, we derive seven requirements for tools to assess these risks, and we con- tribute two dashboard designs derived from these requirements. The first dashboard is designed to asses a software library's usage suitability via its code repository, and the second dashboard visually compares usage suitability information about multiple soft- ware libraries’ code repositories. Using four popular libraries code repositories, we show that these dashboards are effective for understanding and comparing key aspects of software library us- age suitability. We further compare our dashboard to a typical code repository user interface and show that our dashboard is more succinct and requires less work.
Subdural Electrodes and Skull Anchor Bolts

Biomedical Safety & Standards: November 15, 2019 - Volume 49 - Issue 20 - p 155 doi: 10.1097/01.BMSAS.0000605416.30982.f9
Learning Effective Video Features for Facial Expression Recognition via Hybrid Deep Learning

Facial Expression Recognition is one of the recent trends to detect human expression in streaming video sequences. To identify emotions of video like sad, happy or angry. In this paper, the proposed method employs two individual deep convolution neural networks (CNNs), including a permanent CNN processing of static facial images and a temporary CN network processing of optical flow images, to separately learn high-level spatial and temporal characteristics on the separated video segments. Such two CNNs are fine tuned from a pre-trained CNN model to target video facial expression datasets. The spatial and temporal characteristics obtained at the segment level are then incorporated into a deep fusion network built with a model of deep belief network (DBN). This deep fusion network is used to learn spatiotemporal discriminative features together
Managing a Secure JSON Web Token Implementation By Handling Cryptographic Key Management for JWT Signature in REST API: : A survey

JSON Web Token (JWT) is a compact and self-contained mechanism, digitally authenticated and trusted, for transmitting data between various parties. They are mainly used for implementing stateless authentication mechanisms. The Open Authorization (OAuth 2.0) implementations are using JWTs for their access tokens. OAuth 2.0 and JWT are used token frameworks or standards for authorizing access to REST APIs because of their statelessness and the signature implementation. The most important cryptographic algorithms were tested namely a symmetric algorithm HS256 (HMAC with SHA-256) and an asymmetric algorithm RS256 (RSA Signature with SHA-256) used to construct JWT for signing token based on several parameters of the speed of generating tokens, the size of tokens, time data transfer tokens and security of tokens against attacks.In this research,we propose an approach used for handling cryptographic key management for signing RS256 tokens to ensure the security of the application's architecture. JWT offer a variety of options to manage keys, the server always needs to verify the validity of the key before trusting it for verify that a JWT implementation is secure.The experimental results show It's better to use the RS256 signature method for handling cryptographic key management for signing tokens to manage a secure JWT Implementation
Load Balancing Applying Resources Based on Runtime Conditions in Cloud Computing

With the fast advancement of the Internet, numerous sellers have begun to give cloud administrations. An everincreasing number of administrations can be gotten in the cloud, and clients don't need to do activities on a nearby PC. All activities are figured on the cloud. At the point when an enormous number of clients endeavor to access cloud benefits, this frequently makes the server neglect to react. Deciding a technique by which to give clients auspicious and exact reactions is a subject deserving of cutting edge examine. A few examinations have been proposed to assess and to create calculations and load adjusting approaches for cloud-based applications. It is hard for a server to manage the progression of data created by the majority of the different endeavors endeavoring to get to it. Unreasonable stream causes server over-load with a resulting loss of data. So the primary target of this examination is to investigate the outstanding task at hand among every single virtual machine and execute upgraded load adjusting the calculation to increase the allotment of VM to cloudlet and limit the make span time.
Explaining probabilistic Artificial Intelligence (AI) models by discretizing Deep Neural Networks

Artificial Intelligence (AI) models can learn from data and make decisions without any human intervention. However, the deployment of such models is challenging and risky because we do not know how the internal decision- making is happening in these models. Especially, the high-risk decisions such as medical diagnosis or automated navigation demand explainability and verification of the decision making process in AI algorithms. This research paper aims to explain Artificial Intelligence (AI) models by discretizing the black-box process model of deep neural networks using partial differential equations. The PDEs based deterministic models would minimize the time and computational cost of the decision-making process and reduce the chances of uncertainty that make the prediction more trustworthy.
Chapter 20: A Lightweight Java Clustering Framework

In the previous chapter, we introduced some open-source software that can be used for data clustering. In addition to being used for data clustering, these software can be used for other machine learning tasks, such as classification and regression. As a result, these software are large and complicated. In this chapter, we implement a lightweight Java framework specifically for data clustering. This framework can be used by researchers to develop and test new clustering algorithms.
Search

Recurring application of Gestalt operations to a set of primitives extracted from an image in an attempt to search for hierarchically organized patterns can cause considerable computational loads. It turns out important to bound the amount of computation and storage requirements so that the practical application of such Gestalt recognition becomes robust and feasible. This chapter gives several possibilities: Stratified enumeration implements a breadth-first search. Pruning is achieved by the use of an assessment threshold.
Administrasi Layanan Khusus

This article was created to fulfill the tasks of education administration as well as to increase understanding of special service administration. This article was made based on reliable sources, namely books and articles. Special service administration is the management, planning of services that indirectly support the educational process in schools. Where without these services can be a learning process in schools can not take place smoothly. Special services available at schools include dormitories, cafeterias, UKS, cooperatives, and so on.
Penyuntingan Sebagai Kompetensi Dasar Menulis dan Eksistensinya di Penerbit Gadjah Mada University Press

ABSTRACTEditing at a publisher is one of the conditions that must be taken by 5th-semester students of the Indonesian Language Education program at Sebelas Maret University. This activity is one of the conditions that must be taken by students who take editing courses. Manuscript editing activities are needed by a publisher so that when a book is printed it can be well received by the reader. A text is edited by an editor to correct an article from the elements of spelling, word choice, punctuation, and sentence effectiveness. Editing is one of the basic competencies of writing. Basically editing activities are one of the basic competencies of writing that are interesting to study. Editing activities are not easily obtained by an editor, but through the stages of understanding the writing structure according to spelling, mastering good grammar, having extensive knowledge and having thoroughness and patience. Editing activities will also improve one's writing skills. Because by editing someone will gain knowledge about the use of punctuation, good grammar, and the effectiveness of a sentence.Keywords: editing, script, writing
Designing Popular Classes on Viewboard Public Assessment of Lectures Based on YII Framework

The lecture support system in Higher Education has information about student identity in each system, such as profile photos, names, NIM (Student Registration Number) and according to system requirements. An assessment on the public viewboard is an Online Assessment System aimed at improving services at Raharja University. However, in the multiplication flow system still has 3 disadvantages, namely, students do not yet have the facility to see the allocation value between friends in one class in one course to be able to improve the results of lecture grades with classmates and also between classes. In class design Popular writers also do five methods, namely the method of analysis, method of literature review, observation method, design method, and then implemented. With the existence of this study, there are 3 Benefits, namely, students can see the value determined by classmates, can improve the value, and lecturers can ensure the value given must be recognized by students.&#x0D; &#x0D;
CITATION METRIC AN APPLICATION TO h / i-10 INDEXES

In Research level statistics level like number of CITTATIONS will improve Researcher’s Credibility. But mathematically Citation = f ( h , i-10 index ) . h-index is generally equal to numberof CITATIONS ie h - with a total number of Research Publications i with a restriction that the maximum value of h &amp;lt; = i . The i-10 index = Number of CITATIONS &amp;gt;= 10 .
Diffraktive Optiken

No AccessHandbuch Bauelemente der OptikJan 2020Diffraktive OptikenSteffen ReichelSteffen ReichelSearch for more papers by this authorhttps://doi.org/10.3139/9783446461260.015SectionsAboutPDF ToolsAdd to FavoritesDownload CitationTrack CitationsCopy LTI LinkPDF key 'share (en)' returned an object instead of string.FacebookTwitterEmailLinkedIn previous chapternext chapter FiguresReferencesRelatedDetails 2020Pages: 469-488Print ISBN: 978-3-446-46032-4eISBN: 978-3-446-46126-0 Copyright & Permissions© 2020 Carl Hanser Verlag GmbH & Co. KGPDF downloadLoading ...
Conceptualising the modern proactive internal auditor amidst the 4th Industrial Revolution: a literature review

Since its formal recognition, internal auditing has undergone significant changes such as moving from auditing around the computer towards auditing through the computer. Electronic devices have been acknowledged as important audit tools, resulting in internal auditors having to become all-rounders in a business dispensation and possessing an array of skills. With the responsibilities of internal auditors being periodically revised by the Institute of Internal Auditors (IIA), while considering the rapid changes in the business landscape, the primary aim of this study was to conceptualise the modern proactive internal auditor amidst the 4th Industrial Revolution (4IR). This study was both non-empirical and exploratory and constituted qualitative research (literature review). From the research conducted, the modern proactive internal auditor amidst the 4IR was conceptualised as a natural person that is responsible for executing prescribed key tasks, while possessing a multitude of sufficiently developed basic business-skills and basic information technology-skills.
Inducing the Lyndon Array

The Lyndon array is a powerful data structure that generalizes the idea of Lyndon factorization. It has become of interest since Bannai et al. (2017) used it to prove the long-standing conjecture that the number of runs in a string of length n is smaller than n. There are several algorithms to compute the Lyndon array, most of them requiring suffix sorting as a preprocessing step. In this chapter we show how to modify algorithm SACA-K (Nong 2013) to simultaneously compute the Lyndon array and the suffix array in linear time. Experimental results show that this solution is not only space efficient but also fast in practice.
Virtual Education in Chile, An Example of A New Space For Learning

The Virtual Education was born in 2002 from a joint project between the Center for Improvement, Experimentation and Pedagogical Research CPEIP and the Center for Education and Technology Links.&#x0D; &#x0D; CPEIP has developed a line of distance teacher training through the Internet running several courses since 2002, and Links during the last 15 years has dedicated its efforts to provide the access of teachers and students to educational opportunities associated with new technologies of Information and communication. Both institutions decided to combine their efforts and develop a joint project that integrates the CPEIP distance teacher training line, up to now aimed at curriculum updating, different strategies to support the appropriation of ICTs and their curricular integration.
A Smart Bot as an Interactive Medical Assistant with Voice-based System using Natural Language Processing

In this fast-moving world, people are ignorant about their health issues and avoid routine check-ups. It is very difficult for users to spend longer time on-line and explore health information. To solve the problem, voice-based application is provided to the user where user can interact with system and get inference of diseases and their remedies by giving the symptoms as input.For processing the given input, the data is normalized by using noun phrase extraction and medical term identifier. For getting more precise result, the system generates relevant questions to the user and accordingly provide remedy for problem. Question is generated by mapping the user input array with question generation matrix. The project is based on a digital medical aid through a smart bot using machine learning and optical character recognition techniques. The user can just talk to the bot and get to know what the possible causes and effects of the particular symptoms are, determine the illness and take appropriate actions. Basically, the purpose of this bot is to act as a friendly healthcare assistant that helps in all the work that people need to take care of their health.
Alpha Interlock Suspension System Lanyard Body

Biomedical Safety & Standards: August 15, 2021 - Volume 51 - Issue 14 - p 108 doi: 10.1097/01.BMSAS.0000766984.70658.86
Proses Adminsitrasi Keuangan Dan Pemeriksaaan Serta Pelaporan

Financial administration is one of the substance of school administration that will also determine the running of educational activities in schools. As happened in the substance of education administration in general, financial management activities are carried out through the process of planning, organizing, directing, coordinating, controlling or controlling. Some financial administration activities are obtaining and determining sources of funding, utilization of funds, reporting, inspection and accountability. The purpose of this research is to increase the effectiveness and efficiency of school finance use, improve accountability and transparency in school finance, and minimize misuse of school budgets.
DeepQuake — An application of CNN for seismo-acoustic event classification in The Netherlands

Earth and Space Science Open Archive This preprint has been submitted to and is under consideration at Other. ESSOAr is a venue for early communication or feedback before peer review. Data may be preliminary.Learn more about preprints preprintOpen AccessYou are viewing an older version [v2]Go to new versionDeepQuake — An application of CNN for seismo-acoustic event classification in The NetherlandsAuthorsLucaTraniiDGiuliano AndreaPaganiJoão PauloPereira ZanettiiDCamilleChapelandLäslo GerardusEversiDSee all authors Luca TraniiDCorresponding Author• Submitting AuthorKNMIiDhttps://orcid.org/0000-0001-7750-7254view email addressThe email was not providedcopy email addressGiuliano Andrea PaganiKNMIview email addressThe email was not providedcopy email addressJoão Paulo Pereira ZanettiiDKNMIiDhttps://orcid.org/0000-0002-9955-7751view email addressThe email was not providedcopy email addressCamille ChapelandTU Delftview email addressThe email was not providedcopy email addressLäslo Gerardus EversiDKNMITU DelftiDhttps://orcid.org/0000-0003-2825-6211view email addressThe email was not providedcopy email address
Distributed algorithms for improved associative multilabel document classification considering reoccurrence of features and handling minority classes

Existing work in the domain of distributed data mining mainly focuses on achieving the speedup and scaleup properties rather than improving performance measures of the classifier. Improvement in speedup and scaleup is obvious when distributed computing platform is used. But its computing power should also be used for improving performance measures of the classifier. This paper focuses on the same by considering reoccurrence of features and handling minority classes. Since it is very time consuming to run such complex algorithms on large datasets sequentially, distributed versions of the algorithms are designed and tested on the Hadoop cluster. Base associative classifier is designed based on multi-class, multi-label associative classification (MMAC) algorithm. Since no similar distributed algorithms exist, proposed algorithms are compared with the base classifier and have shown improvement in classifier performance measures.
Adaptive algorithm for reducing pulse noise level in images from CCTV cameras

An optical signal is usually converted into an electrical one by using photosensitive matrices with a large number of discrete elements based on charge-coupled device (CCD) technology or CMOS technology. One of the disadvantages of CCD and CMOS technologies is the impulse conversion noise that appears on digitized images, impairing visual perception and significantly reducing the likelihood of correct identification in pattern recognition tasks. Traditionally, impulse noise is removed from images using median filters with a fixed aperture within each iteration of full-format processing. However, such filters reduce the sharpness of the reconstructed image at high noise levels or insufficiently suppress the interference under the same noise conditions. These setbacks call for a need to develop an adaptive median filtering algorithm, which would produce a reconstructed image as a joint result of processing with median filters with different apertures. The essence of this algorithm is to select image areas with different noise levels and process these areas with filters with different apertures. As an objective criterion for assessing the efficiency of the proposed filtering algorithm, the authors used the criterion of the maximum correlation coefficient between noise-free and non-noisy images at various values of the noise variance. The mathematical modeling performed in this study allowed finding that with an increase in the impulse noise variance, the gain of the adaptive median filtering algorithm increases exponentially, in comparison with the algorithms using the filters with a fixed aperture value. The proposed algorithm can be used for pre-preprocessing images intended for recognition by machine vision systems, scanning text, and improving subjective image characteristics, such as sharpness and contrast.
Intensity Propagation

This fully updated, self-contained textbook covering modern optical microscopy equips students with a solid understanding of the theory underlying a range of advanced techniques. Two new chapters cover pump-probe techniques, and imaging in scattering media, and additional material throughout covers light-sheet microscopy, image scanning microscopy, and much more. An array of practical techniques are discussed, from classical phase contrast and confocal microscopy, to holographic, structured illumination, multi-photon, and coherent Raman microscopy, and optical coherence tomography. Fundamental topics are also covered, including Fourier optics, partial coherence, 3D imaging theory, statistical optics, and the physics of scattering and fluorescence. With a wealth of end-of-chapter problems, and a solutions manual for instructors available online, this is an invaluable book for electrical engineering, biomedical engineering, and physics students taking graduate courses on optical microscopy, as well as advanced undergraduates, professionals, and researchers looking for an accessible introduction to the field.
Disambiguating Mentions of API Methods in Stack Overflow via Type Scoping

The International Conference on Software Maintenance and Evolution is the premier international forum for researchers and practitioners from academia, industry, and government to present, discuss, and debate the most recent ideas, experiences, and challenges in software maintenance and evolution.
Virtual Reality based Hologram for Emergency Situation

Virtual reality is seen as an elite way for viewing and it has the potential to target a wide range of applications. Holography is a pictorial method that records the light scattered from an object, presenting it in a way that appears in a 3D form. During mining the miners will be in need of certain essential requirements to make their work more efficient. Existing system only detects if there isany dangers inside the mines and does not provide with the required items to the miners. The proposed system focuses on providing these essential requirements. The items include Hearing protection device, PAPRs, foot protection, clothes, belts and D-rings and self-rescue device. We have conducted a survey based on various algorithms and methods that are used to create a hologram and for analysing holographic image. The survey tells us that methods like Rule based approach which requires large amount of data is used to classify human activities. Multiplexing is used to combine many signals into one and produce an image. These systems have various issues when it comes to time and performance. It provides with some handy data on some of the encouraging milestones that have been attained in hologram acquisition, display and processing.
Image Generation

Did you ever imagine that neural networks could be used for generating complex color images? How about Anime? How about the faces of celebrities? How about a bedroom? Doesn’t it sound interesting? All these are possible with the most interesting idea in neural networks and that is Generative Adversarial Networks (GANs). The idea was introduced and developed by Ian J. Goodfellow in 2014. The images created by GAN look so real that it becomes practically impossible to differentiate between a fake and a real image. Be warned, to generate complex images of this nature, you would require lots of resources to train the network, but it does certainly work as you would see when you study this chapter. So let us look at what is GAN.