Reviewerly/exHarmony huggingface dataset:
Tailored for Real-World: A Whole Slide Image Classification System Validated on Uncurated Multi-Site Data Emulating the Prospective Pathology Workload

Standard of care diagnostic procedure for suspected skin cancer is microscopic examination of hematoxylin & eosin stained tissue by a pathologist. Areas of high inter-pathologist discordance and rising biopsy rates necessitate higher efficiency and diagnostic reproducibility. We present and validate a deep learning system which classifies digitized dermatopathology slides into 4 categories. The system is developed using 5,070 images from a single lab, and tested on an uncurated set of 13,537 images from 3 test labs, using whole slide scanners manufactured by 3 different vendors. The system's use of deep-learning-based confidence scoring as a criterion to consider the result as accurate yields an accuracy of up to 98%, and makes it adoptable in a real-world setting. Without confidence scoring, the system achieved an accuracy of 78%. We anticipate that our deep learning system will serve as a foundation enabling faster diagnosis of skin cancer, identification of cases for specialist review, and targeted diagnostic classifications.
Machine learning for patient risk stratification: standing on, or looking over, the shoulders of clinicians?

Abstract Machine learning can help clinicians to make individualized patient predictions only if researchers demonstrate models that contribute novel insights, rather than learning the most likely next step in a set of actions a clinician will take. We trained deep learning models using only clinician-initiated, administrative data for 42.9 million admissions using three subsets of data: demographic data only, demographic data and information available at admission, and the previous data plus charges recorded during the first day of admission. Models trained on charges during the first day of admission achieve performance close to published full EMR-based benchmarks for inpatient outcomes: inhospital mortality (0.89 AUC), prolonged length of stay (0.82 AUC), and 30-day readmission rate (0.71 AUC). Similar performance between models trained with only clinician-initiated data and those trained with full EMR data purporting to include information about patient state and physiology should raise concern in the deployment of these models. Furthermore, these models exhibited significant declines in performance when evaluated over only myocardial infarction (MI) patients relative to models trained over MI patients alone, highlighting the importance of physician diagnosis in the prognostic performance of these models. These results provide a benchmark for predictive accuracy trained only on prior clinical actions and indicate that models with similar performance may derive their signal by looking over clinician’s shoulders—using clinical behavior as the expression of preexisting intuition and suspicion to generate a prediction. For models to guide clinicians in individual decisions, performance exceeding these benchmarks is necessary.
Deconstructing Scatter/Gather I/O

Bayesian algorithms and access points have garnered profound interest from both cyberneticists. Indeed, couple of programmers worldwide would oppose this idea with the improvement of vacuum tubes, which embodies the robust principles of steganography. We argue that while e-commerce and e-commerce can cooperate to accomplish this goal, synthesis of the location-identity split [13]. The notion that information theorists collude with collaborative modalities is often considered intuitive. To what extent can public-private key pairs be harnessed to achieve this ambition? [1],[ 3],[5]
Cloud Based Teacher’s Assessment Data in Educational Data Mining

Questionnaire of teacher 's assessment survey in higher education al system is very impo rtant and especially cost effective method which is one of survey type from three such as face -to-face interviews and telephone interviews.Teacher assessment survey for educational system is very important in developing countries to improve the education system can be well mot ivated fro m evaluation of teacher assessment survey data by analyzing knowledge discovery data mining process.Teacher assessment survey data can be collected fro m mobile phone android application and which data stored on cloud storage database.In this system the real data is collected for teachers fro m the University of Co mputer Studies, Yangon, Myan mar.Association rule mining is one of the approaches to extract h idden frequent pattern and association rules between the items of dataset with varying levels of strength.The proposed system also used simp le k means clustering to organize the levels of groups of data set.In this paper presents the relevant studies in the EDM field and KDD process steps.
Creating an Angular App, Part 1

In this chapter, I start the process of creating an Angular web application that has the same set of features as the example in Chapters 15 and 16. Unlike other frameworks, where using TypeScript is an option, Angular puts TypeScript at the heart of web application development and relies on its features, especially decorators. For quick reference, Table 17-1 lists the TypeScript compiler options used in this chapter.
Cryptanalysis of the existing integrated PKE and PEKS schemes

Public key encryption with keyword search (PEKS) is a useful cryptographic primitive which allows one to delegate to an untrusted storage server the capability of searching on publicly encrypted data without impacting the security and privacy of original data. However, due to lack of data encryption/decryption function, a PEKS scheme cannot be used alone but has to be coupled with a standard public key encryption (PKE) scheme. For this reason, a new cryptographic primitive called integrated PKE and PEKS (PKE/PEKS) was introduced by Baek et al. in 2006, which provides the functions of both PKE and PEKS. So far, several PKE/PEKS schemes have been proposed in the literature. However, none of them considers the keyword guessing attack. The first PKE/PEKS scheme proposed by Baek et al. was shown to be insecure under this attack. In this paper, we analyse the security of other PKE/PEKS schemes. We demonstrate that none of these schemes can resist the keyword guessing attack. The presented attacks show that a malicious storage server can successfully guess the keyword encoded in any keyword trapdoor produced by these schemes. Therefore, it is still an unsolved problem to devise a PKE/PEKS scheme withstanding the keyword guessing attack.
Sound

Adding sound to a game will add an additional dimension and can help bring the game come to life. This can be achieved by adding special effect sounds or adding background music to set the mood. You may also use the sound as a key component in the game.
A TPM-Based Secure Multi-Cloud Storage Architecture Grounded on Erasure Codes

In cloud storage systems, data security management is becoming a serious matter. Big data and accessibility power is increasingly high, though the benefits are clear, such a service is also relinquishing users' physical possession of their outsourced data, which inevitably poses new security risks toward the correctness of the data in cloud. As a result, cloud storage security has become one of the driving components in Cloud Computing regarding to data manipulation trust on both hosting center and on-transit. This paper proposes a TPM-Based Security over Multi-Cloud Storage Architecture (MCSA) grounded on Erasure Codes to apply root of trust based on hardware authenticity. An erasure codes such as Reed-Solomon, is capable of assuring stability in storage costs with best practice to guarantee data accessibility failure recovery. A Multi-Cloud Control Node manages other Control Nodes evolved in the cloud; this work introduces TPM-Based Security functions per Control node in the architecture. This concept will resolve a number of storage security issues, hence Cloud Computing adoption.
CAI method in Cloud services for user workload using Cloudsim framework

In sighting the distinct patterns of processing capability in a cloud service is pedantic to enhance the resource management and operable conditions of the servers without compromising the Quality of Service is important. Simulations and models based on practicable parameters are required to understand the impact of the load on new system designs and policies. The proposed scheme and analysis provides a requirement for designing new systems which will be lessaffected by process loads. Classifying, analysis and improving (CAI) is done using real-time data center logs and simulations are done based on user requests and data center configurations. Simulations are created using cloudsim framework. Various simulations are done to provide a comprehensive result to improve the resource allocation for the system.
CodeRibbon: More Efficient Workspace Management and Navigation for Mainstream Development Environments

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.
Influence of Social Media on Reading Habits among Year 5 Pupils

Social media is an online platform which allows individuals and groups, as well as pupils to collaborate with each other. However, studies shown that pupils used them more for leisure than for academic purposes, including cultivating bad reading habits. This study aimed to explore the influence of social media towards reading habits and interest in reading among year 5 pupils in an urban school. The researchers see a need to carry out this study as it provides an insight for educators, especially for primary education teachers, who are longing for different pedagogical approach in language teaching, specifically the teaching of reading. A survey was carried out with 50 year 5 ESL pupils by using a questionnaire comprising 50 close-ended and 1 open-ended items to identify the influence of social media on their reading habits. Besides, unstructured interviews were conducted with 10 of the respondents to examine the influence of social media on interest of reading. The findings showed positive reading habits are able to construct by using social media as it successfully increased the interest of pupils in reading. In conclusion, the use of social media is effective in cultivating positive reading habits. The results of this study may be beneficial to educators in adapting the use of social media in teaching reading. It is suggested that further studies could be done to identify the social media platform that contributes towards pupils’ better reading habits.
New type of learning environment based on a cross-platform learning model: methodology and testing

The author presents a multi-component practical study of a new type of electronic educational environment on the example of the author’s cross-platform project Langteach-online, aimed at teaching foreign students Russian. A new type of elearning environment will allow you to create online courses without the use of Western learning management systems, such as LMS Moodle, Schoology, and others with the integration of mobile devices that are trained in the learning process in mixed and distance formats. The methodology of this study will allow creating multidisciplinary online courses for teachers without special training in information technology and programming, which is especially relevant in the context of the Covid-19 pandemic. Russian cross-platform project Langteach-online is used in teaching foreign citizens Russian at the bachelor’s and master’s levels in a number of higher educational institutions of the Russian Federation in order to form a creative professional personality of a foreign graduate. The multi-format of organized tasks and materials (text, video, audio, graphics, presentations) allows us to talk about the possibility of using cross-platform projects of this type not only for teaching practical courses in foreign languages and RFL, but also other disciplines that are taught in schools and higher educational institutions. Training based on this model can be carried out both in blended and distant formats. The system of technical and methodological organization of a cross-platform project has the fexibility to use it inside the personal web resource of a teacher or educational institution.
KEMAMPUAN BERKOMUNIKASI SISWA MELALUI PENERAPAN MODEL STUDENT FACILITATOR AND EXPLAINING DI KELAS X SMA

The purpose of this research was to determine the level of communication ability of student in class X SMA PGRI Pekanbaru, through the implementation of the Student Facilitator and Explaining model on the material of momentum and impulses. This research was conducted in class X IPA of SMA PGRI Pekanbaru in 2019, amounting to 29 students, where male students numbered 14 people while female students numbered 15 people. The research design uses a type of pre-experimental design in the form of one shot case study. The research instrument used observation sheets for oral communication ability and assessment sheets for worksheet (LKS) reports for written communication. The results of the research were obtained based on indicators of verbal communication ability which include expressing information and ideas, giving attention when others are talking, responding, and asking questions, students have the communication ability with high categories. Furthermore, students' written communication ability for each meeting have increased with an average of each indicator which includes the accuracy of the answers and the quality of writing is categorized very high. Thus it was concluded that the communication ability of students in oral and written form in class X SMA PGRI Pekanbaru can be trained to be better through the application of cooperative learning models of Student Facilitator and Explaining (SFAE) types on momentum and impulse material.
Significance of Vocoders in Mobile Communication

Signal Processing finds its applications in many fields of engineering like Communications, Multimedia processing like audio, speech, video compression. It is the constant endeavor in compression techniques to retain highest quality of media through lowest bits so that communication band width utilization can be maximized. The most basic form of end user communication in the mobile industry has been voice calls. Speech signals captured at the microphone are sampled at 8 or 16 KHz and using 16 bits per sample presents 128 KHz of information. Transmitting all of it is very inefficient usage of the communication channel. There are multiple ways to encode the speech input at lower bit rates using Source Coding and Waveform coding techniques. This paper is scoped to practically simulate some of the basic and advanced signal processing concepts and apply them to the speech signal processing domain to minimize the vocoders packet exchange bit rate. Existing techniques are studied and a new schema is proposed which reduce the vocoders packet exchange bit rate further.
Sorority and Guild Partner to Host Superhero Dash

Special Events GaloreVolume 20, Issue 5 p. 1-1 Family-Friendly Events Sorority and Guild Partner to Host Superhero Dash First published: 09 April 2020 https://doi.org/10.1002/speg.31340Read 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. Volume20, Issue5May 2020Pages 1-1 RelatedInformation
Multiple polynomial regression for solving atmospheric scattering model

Multiple polynomial regression (MPR) is a novel technique for removing haze from images. Haze removal is a challenging task because not much information is there if the single image haze removal is taken into consideration. MPR is a method that solves the atmospheric scattering model (ASM). In solving the ASM from a single image many unknown variables like depth of the scene, scattering coefficient, transmission of the medium, atmospheric light have to be calculated. If all these variables are calculated with precision then it is possible to obtain a haze free image. The current work has shown improvements over the state of the art methods.
Diagnosis of Malaria from Peripheral Blood Smear Images using Convolutional Neural Networks

Malaria is a deadly disease brought about by Plasmodium parasites which affects the general population through the bites of female mosquitoes, called "malaria vectors." There are about five parasites species that cause malaria in human body, and two of the species namely P. falciparum , P.vivax pose the greatest threat. The most prominent technique to detect malaria is by taking blood smear samples to check if the RBC is affected by parasite under the microscope by qualified experts. It is a complex technique and the diagnosis depends on the experience and inside of the person who performs the examination. Malaria blood smear have been diagnosed earlier using image processing methods based on machine learning. This was not effective so far. Convolutional Neural Network (CNN) is use in this system which helps in classifying the cells present in the blood smear images as infected or uninfected.
A Fuzzy Logic Based Personalized Result Analysis Support for Student Performance Up-Gradation

Education system conducts various competitive exam and analyze the result but there is no any provision for improvement of result analysis. The proposed research method uses a fuzzy logic based result analysis system which suggest the improvement is possible in performance of result. This method uses Mamdani Fuzzy inference system and Triangular and Trapezoidal membership functions for removing uncertainty and prediction of better results. When marks are analyzed through a classical method it represents two dimensional graphs only. Using this two dimensional graph it is quite difficult to predict range of result. In the proposed method using 36 Fuzzy rules output is categorized in 6 grades namely O, A+, A, B, C, D. and it is represented in 3D surface graph. This graph helps to increase the grade level of number of student by upgrading phase.
Teaching and Development Ideas of Double-row Keyboard Electronic Organ in Colleges and Universities

The double-row keyboard electronic organ is different from other musical instruments.It is a comprehensive and expressive electronic instrument.It not only brings people good enjoyment, but also opens up the field of expression of electronic instruments.Especially the double-row keyboard electronic organ music form of expression can express a variety of music types such as classical symphony, jazz, pop music, so some people call it a person's band.Because of its rich expressive force, it is loved by many music lovers.
The Acceptance Model of QR Code Payment Systems in Thailand: A Proposed Model

Technological developments have been playing an important role in the economic system of countries.In order to further propel the Thailand economic system, the government has a national e-payment master plan to support standardized e-payment systems conforming to existing technology.The QR code payment system is one of the national e-payment master plan which the government is trying to push to take Thailand into a cashless society.QR code payment system for citizens in Thailand is very new technology and yet does not have many users.Thus, the purpose of this research is to develop the conceptual framework on QR code payment system in Thailand to initially identify relevant factors which influence the intention to use it for making payments.The research framework has been developed by integrating the Unified Theory of Acceptance and Use of Technology (UTAUT) with trust, perceived risk (PR) and personal innovativeness in information technology (PIIT).Finally, the contribution of this study provides potential factors that could affect the acceptance of QR code payment systems in Thailand.
Two Web Application Approaches: Rails and Sinatra

In this chapter, we’re going to look at web application (or web app, for short) frameworks—libraries of code that provide an easily reusable structure and design patterns for developing web applications. If you want to develop something useful for the Web, you’ll probably find a web application framework very useful, and Ruby has a wonderful selection of them, of which we’ll look at two: Rails and Sinatra.
Comparative Study on MATLAB based Joint Photographic Experts Group Image Size Reduction Using Shearlet and Wavelet Transform for X-Ray Images with Potential Hospital Data Storage Application

Aim: The aim of this paper is to compress the x-ray images using wavelet and shearlet transform and compare the compression ratios to find a better transform. Materials and Methods: The sample size of each group was 30 and the total sample size was 60. Compression ratios (CR) were generated for images based on the transform used for size reduction. Results: Wavelet based CR was seen to be higher mean (6.61) when compared to shearlet (4.025). Hence wavelet transform seems better transform for compressing X-Ray images. Conclusion: We observed that wavelet transform seems to have a better compression ratio compared to shearlet transform (P=0.28, P&lt;0.05, independent sample t-test).
An Efficient Supervised Method for Fake News Detection using Machine and Deep Learning Classifiers

This paper comes up with the applications of Machine learning and deep learning algorithms for police work the 'fake news', that is, dishonorable news stories that come from the unauthorized article writers. This approach was enforced as software and tested against an information set. Aim is to separate the faux news, among the news spread in the articles. It’s required to create a model which is able to differentiate between “Real” news and “Fake” news. The model was created exploitation numerous deep and machine learning strategies. LSTM technique outperforms different classifiers and achieves the accuracy of 94%.
UIDAI Aadhar Enrollment with P2P Blockchain Technologies

Blockchain technologies are becoming more popular in securing the sensitive data such as government holding citizens’ s wealth, health and personal information. A blockchain is a shared encrypted data of records, consisting of a ledger of transactions. As the data stored in blockchain is tamper proof, it is proposed to implement new Aadhar enrolments with P2P Blockchains and migrate the existing centralized Aadhar personnel’s personal data from the conventional RDBMS / Big data system repositories to distributed ledger technologies by creating private blockchains. In this paper, we will discuss how to provide security for Aadhar card enrolment data using blockchain architectures. A blockchain-based Aadhaar would help UIDAI in truly complying with the data protection and privacy stipulations outlined in the Right to Privacy Act judgment