Reviewerly/exHarmony huggingface dataset:
Changes in Financial Performance of Traditional Intermediatries for Financial Innovation

The purpose of this thesis is to examine the impact of digital bank deposit, asset and loan growth on selected traditional bank performance measures. In order to estimate whether a causal relationship between digital bank measures and traditional bank performance exists, Granger causality method is selected as the main empirical model. In addition, to determine the direction and strength of said relationship, OLS regressions are performed. Research results lead to the conclusion that digital bank deposit and loan growth have a causal relationship to traditional bank performance ratios. Deposit growth has a negative impact on traditional bank performance ratios and loan growth shows both positive and negative impact on different ratios. This research demonstrates some of the challenges that traditional banks are facing in the age of innovation.
HIGH AVAILABILITY IN SERVER CLUSTERS BY USING BACKPROPAGATION NEURAL NETWORK METHOD

Server is a host device applications to serve every request in finding information needs. The server must fully support the services used for the organization's digital needs 24 hours in a day, 7 days in a week, and 365 days in a year. The concept of High Availability is needed to maintain the quality of server services. The algorithm used to build HA can use both classical and modern algorithms. The algorithm used in this research is using backpropagation neural network. In this study, the parameter values to obtain optimal accuracy are learning rate 0.1, training data 80 and test data 20, the number of nodes in hidden layer 4, minimum error 0.0001, and the number of iterations 2500.The best accuracy value using these parameters is 93.79% .
Aurora Retrive – An Augmented Reality Game using Real World Maps

The game developed uses real world map data to generate real world 3D environment in Augmented Reality (AR). This Real world Game developed represents a way of technology implemented in augmented reality which is used to play Multi player Role Play Game (RPG). The game can be played on two different modes like role playing or multi-player mode. This game system is made as multiplayer game on a role playing environment for specific player, in which every player has their own role playing in it. The entire real world game environment is loaded in AR on any of the object that acts as the marker in the real world environment. This game system is developed using the UNITY game engine for creating game environment and the environment itself is created using real world data obtained using Map box. Vuforia studio frame work is used for implementation of game environment in AR. C# programming language is used to program game play actions and environment generations and modifications in runtime.
Hologic, Inc. v. Minerva Surgical, Inc. United States Court of Appeals of the Federal Circuit, 2020 957 F.3d 1256

Biotechnology Law ReportVol. 39, No. 4 As presented by Chris HolmanHologic, Inc. v. Minerva Surgical, Inc. United States Court of Appeals of the Federal Circuit, 2020 957 F.3d 1256Edited for Biotechnology Law Report by CHRISTOPHER M. HOLMAN*Published Online:17 Aug 2020https://doi.org/10.1089/blr.2020.29189.cmhAboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View articleFiguresReferencesRelatedDetails Volume 39Issue 4Aug 2020 InformationCopyright 2020, Mary Ann Liebert, Inc., publishersTo cite this article:Hologic, Inc. v. Minerva Surgical, Inc. United States Court of Appeals of the Federal Circuit, 2020 957 F.3d 1256.Biotechnology Law Report.Aug 2020.332-336.http://doi.org/10.1089/blr.2020.29189.cmhPublished in Volume: 39 Issue 4: August 17, 2020Online Ahead of Print:July 8, 2020PDF download
The Application of Probing Prompting Learning Model to Increase Activity and Mathematics Learning Outcomes

Learning is a key activity of the educational process. Researchers conducted observations in class VII-A MTs As-sunniyah Ranuyoso virgin and approximately 80% of the data obtained shows student scores ≤ 70. This study aimed to determine Increased Activity dan Student Result in studying the math the subject is social arithmetic with probing prompting learning model. Type of research is a classroom action research (CAR). The procedure used is the model cycle based on these result, the percentage of student learning in the first cycle of 60,3%, and a second cycle 0f 92,8%. While the result of daily tests of student in the first cycle obtained average value 31,5, while on the second cycle of 79,95. It is proved that the activity and student learning outcomes can be improved with the implementation of probing prompting learning model. For a particular subject, type probing prompting learning model is used to avoid boredom in learning actifity. Keywords: probing prompting, learning activity, learning outcomes.
Automatic Lung Cancer Detection using Sobel &amp; Morphological Operations

Cancer is the most dangerous disease that may cause death and lung cancer is one of them which is more common among all. There are various imaging techniques through which organs can be scanned for diagnosis. Lung cancer is a disease that may be caused by unrestrained cell growth in lung. Lung cancer is the most common and most dangerous cancer. CT scan can obtain the lung images, but still it has been recognized manually. Manual lung cancer detection is a challenging task because false error rate may lead you to compromise with human’s life. There are lots of researches that has been done in this field but still failed to obtain high precision with minimal error rate. Here the system proposes automatic lung cancer detection using Sobel &amp; Morphological operations that can acquire good precision along with cancer area detection. Sobel is a gradient edge detection technique through which absolute gradient magnitude is computed in the reference of 2D input lung image that is later dilated with morphological operator. The obtained result is liable to attain high precision with less false alarm rate.
Visualization of Formal Semantics - Possibilities of Attracting Formal Methods in Teaching

The goal of formal semantics of languages is to reveal the nature of a language beneath its syntactic surface.One of the popular and frequently used methods is operational semantics.Its categorical representation using coalgebras is a new approach to semantics.Current trends show that software visualization of various calculations contributes to clarity and easier understanding.To support students' interest in semantic methods, we designed and prepared a software tool whose task is to visualize computations in coalgebraic operational semantics.
Survey Paper on Applications of Generative Adversarial Networks in the Field of Social Media

Social Media today is one of the most widely known terms.If the internet is the window to the world, social media is what actually has brought people from all over the world together.Today one can easily sit in the comfort of their homes and actively engage in an impactful political movement, taking place on the other end of the world.Social Media has enabled and impacted a myriad of fields.It has been a big aggressor in political movements, where candidates direct a major investment both in terms of time and money towards spreading the popularity of their campaign on social media websites.It has impacted major movements in recent times and brought out path-breaking societal changes.Social Media has provided companies with a new route of targeting their advertisements and has brought them closer to their customers and shareholders.Social Media has also opened up a new path of careers for many.Amongst all these positives, social media possess multiple challenges as well which include but are not limited to cyberbullying, privacy attacks and peer pressure which results in alarming rates of mental health detrition.The Generative Adversarial Nets is an extremely nascent but fastgrowing network architecture in Deep Learning.This paper explores different forms of GANs and their applications in Social Media.
On Time Document Retrieval using Speech Conversation and Diverse Keyword Clustering During Presentations

In this paper we present the idea of extracting keywords from discussions, with the point of using these words to recuperate, for each small piece of conversation and generating reports to individuals. Regardless, even a smaller piece contains a blend of words, which can be effortlessly interrelated to a couple of subjects; additionally, using a customized talk affirmation (ASR) system presents slips among them. Thus it is hard to sum up effectively the data needs of the conversation individuals. We initially propose a count to kill significant words from the yield of an ASR system which makes usage of topic showing strategies and of a sub particular prize limit which supports varying characteristics in the word set, to organize the potential contrasting characteristics of subjects and diminish ASR disturbance. By then, we set forward a strategy to surmise different topically detached requests from this definitive word set, remembering the ultimate objective is to build the potential outcomes of making at any rate one appropriate proposition while using these inquiries to investigate the English Wikipedia. The readings depict that our pronouncement continue ahead over past procedures that watch simply word recurrence or idea commonality, and states the good response for a report recommended framework to be used as a piece of conversations.
A Comprehensive review of Transfer Learning on Deep Convolutional Neural Network Models

In deep learning the most significant break though in the field of image recognition, language processing was done by Convolutional Neural Network (CNN).The CNN is a powerful algorithm which is capable of using features extraction at multiple levels and this is done based on the distribution of data automatically.The rapid growth in Big Data and the high-performance architectures have made it possible for the growth of CNN.Transfer Learning is the method for performance improvement in the specific problem with the transferring of knowledge learned from other domains.Transfer learning have a wide range of applications and it is widely used in deep learning algorithms There is rapid growth in the use of transfer learning in the pre trained models in CNN.The transfer learning helps to improve the performance of the models and it helps in saving time by acting as an optimization technique.This survey attempts to provide a comprehensive review in understanding the mechanisms of transfer learning and the pretrained models in CNN.
Review - ISO/IEC 24760-2:2015 IT Security and Privacy - A framework for identity management - Part 2: Reference architecture and requirements

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Smishing Detection: Using Artificial Intelligence

Abstract: Phishing occurs when people's personal information is stolen via email, phone, or text communications. In Smishing Short Message Service (SMS) is used for cyber-attacks, Smishing is a type of theft of sensitive information. People are more likely to give personal information such as account details and passwords when they receive SMS messages. This data could be used to steal money or personal information from a person or a company. As a result, Smishing is a critical issue to consider. The proposed model uses an Artificial Intelligence to detect smishing. Analysing a SMS and successfully detecting Smishing is possible. Finally, we evaluate and analyse our proposed model to show its efficacy. Keywords: Phishing, Smishing, Artificial Intelligence, LSTM, RNN
A novel approach for secured transmission of DICOM images

Digital Imaging and Communications in Medicine (DICOM) communication mainly focuses on the transmission of medical images, storing the information in medical image and also for printing and securing the image. A medical image communication is mainly for secured medical facilities for the physicians and the patient. The medical image is compressed under the JPEG 2000 format. The hash value is found out using additive hash function (AHF) and it is encrypted using RSA to form the digital signature. Combination of digital signature and text will be the watermark. This text consists of patient information, doctor information, disease information, and prescription. Reversible watermarking is a technique in which watermark is embedded and watermarked images passes through the authentication process, the original image is extracted along with the watermark. Strict authentication is provided in order to have high security for accessing the secure medical images by implementing Kerberos technique.
Социокультурные особенности коммуникации в городе

The article deals with the problem of transformation of communication processes in a modern city under the influence of technology dominance. The authors reveal features of communication processes in the information and network space of the city and show the transformation of value attitudes in the communicative space of the city. The authors conclude that it is necessary to use a synergistic methodology in the study of communicative interactions in the urban space.
UKRN Checklist for an Open Research Action Plan

UKRN Checklist for an Open Research Action Plan
Testosterone administration in women increases the size of their peripersonal space

Peripersonal space (PPS) is the space immediately surrounding the body, conceptualised as a sensory-motor interface between body and environment. PPS size differs between individuals and contexts, with intrapersonal traits and states, as well as social factors having a determining role on the size of PPS. Testosterone plays an important role in regulating social-motivational behaviour and is known to enhance dominance motivation in an implicit and unconscious manner. We investigated whether the dominance-enhancing effects of testosterone reflect as changes in the representation of PPS in a within-subjects testosterone administration study in women (N=19). Participants performed a visuo-tactile integration task in a mixed-reality setup. Results indicated that the administration of testosterone caused a significant enlargement of participants’ PPS, suggesting that testosterone caused participants to implicitly appropriate a larger space as their own. These findings suggest that the dominance-enhancing effects of testosterone reflect at the level of sensory-motor processing in PPS.
Magnetic interference mapping of four types of unmanned aircraft systems intended for aeromagnetic surveying

Abstract. Magnetic interference source identification is a critical preparation step for magnetometer-mounted unmanned aircraft systems (UAS) used for high-sensitivity geomagnetic surveying. A magnetic field scanner was built for mapping the interference that is produced by a UAS. It was used to compare four types of electric-powered UAS capable of carrying an alkali-vapour magnetometer: (1) a single-motor fixed-wing, (2) a single-rotor helicopter, (3) a quad-rotor helicopter, and (4) a hexa-rotor helicopter. The scanner’s error was estimated by calculating the root-mean-square deviation of the background total magnetic intensity over the mapping duration; averaged values ranged between 3.1–7.4 nT. Each mapping was performed above the UAS with the motor(s) engaged and with the UAS facing in two orthogonal directions; peak interference intensities ranged between 21.4–574.2 nT. For each system, the interference is a combination of both ferromagnetic and electrical current sources. Major sources of interference were identified such as servo(s) and the cables carrying direct current between the motor battery and the electronic speed controller. Magnetic intensity profiles were measured at various motor current draws for each UAS and a change in intensity was observed for currents as low as 1 A.
Performance Analysis of Combined Discrete Fourier Transformation (DFT) and Successive Division based Image Watermarking Scheme

A combined Discrete Fourier Transformation (DFT) and Successive Division based image watermarking scheme has been proposed in this article. Due to intrinsic parameters: Imperceptibility, Data Embedding Capacity and Time of Execution, many spatial domain approaches are less efficient. Many frequency domain approaches satisfies imperceptibility and data embedding capacity, but utilizes more execution time. The proposed algorithm is a hybrid technique under frequency domain, which embeds watermark into host using Discrete Fourier Transformation (DFT) and successive division. Through DFT better imperceptibility is noticed and the algorithm utilizes very less execution time compared to other existing approaches. Performance analysis is done based on similarity between original and retrieved watermark images. The experimental results are better compared to other existing techniques.
Prevention of Unintended Appearance in Photos Based on Human Behaviors Analysis

Many people can take photos with smartphones and easily post photos via SNS (Social Network Services). This has caused a social problem that unintended appearance in photos may threaten the privacy of photographed persons. For this issue, numerous studies have already been introduced to prevent the unintended appearance in photos from the photographer’s side, but only a few methods tackled this from the photographed person's side. Therefore, we considered calling attention to a situation that a photo-taking behavior by a photographer can be automatically detected by using a wearable camera worn by a photographed person. In this paper, we propose an approach to detect photo-taking behaviors in video data taken from the wearable camera, analyzing specific human skeleton information. OpenPose is utilized to obtain the human’s skeleton information and the time-series data are analyzed. In addition, we compare two similar behaviors which are photo-taking behaviors and net-surfing behaviors. These video data are distinguished by DP matching and cross-validation. Finally, it is concluded that the detection accuracy of photo-taking behaviors is about 92.5%, which is satisfactory enough for this research purpose.
Fuzzy PID Controller to control the attitude of Quadrotor UAV

The stable flight attitude movements of the quad-rotor UAV attained by using Fuzzy PID control algorithm in order to minimize the problems related to slow response and poor robustness.Firstly, the mathematical model of the Plus quad-rotor UAV model is established then the controller is designed which consist of inner ring angular velocity Fuzzy PID and outer ring angle P controller.The traditional techniques of the PID controller, cascade Fuzzy PID controller and cascade PID controller were simulated using Matlab/ Simulink to compare the step signal.The Fuzzy PID controller accelerates the results from the simulations show that the performance of the system improved in terms of accuracy of the system.The simulated flight result also shows that the Fuzzy PID controller shows robust behavior.
Modeling of Speech Recognition using Artificial Neural Network

Automatic speech recognition has attained a lot of significance as it can act as easy communication link between machines and humans. This mode of communication is easy for man to use as it is effortless and easy. Many approaches for extraction of the features of the speech and classification of speech have been considered. This paper unveils the importance of neutral network and the way it can be used for recognition of speech. Mel Frequency Cepstrum Coefficients is made use of for extraction of the features from the voice. For pattern matching neural network has been used. MATLAB has been used to show how the speech is recognized. In this paper the speech recognition has been done firstly by multilayer feed forward neural network using Back propagation algorithm. Then the process of speech recognition is shown by using Radial basis function neural network. The paper then analyzes the performance of both the algorithms and experimental result shows that BPNN outperforms the RBFNN.
Automated Detection of Street-Level Tobacco Advertising Displays

Tobacco marketing, restricted almost exclusively to the point-of-sale in recent years, has proven to be effective in getting more people to consume and fewer to quit cigarettes and smokeless tobacco products.The lack of empirical documentation linking product exposure to behavior, however, is a key obstacle to the adoption of additional restrictions on point-of-sale tobacco advertising.The goal of this project is to map point-of-sale tobacco marketing practices across New York City using automated detection of tobacco signage in street-level imaging data.Convolutional neural networks, which are particularly effective at detecting objects in images, were trained to identify and classify outdoor advertisements of cigarettes and smokeless tobacco.Previous analyses of visual data in public health research involving manual image coding are prohibitively costly and time-
Reconsidering Literacy

Literacy, until recently, was defined as the ability to read printed text and to understand the nuances of both the form and content of that printed text. More recently there has been a focus on subsets of literacy – data literacy, numeracy, visual literacy, media literacy, etc. – that recognizes the means of communicating ideas and facts are not limited to the printed text and that there are multiple means which may be more powerful ways of communicating in our world. In recent years, higher education has been redefining what it means to be educated – from a focus on specific bodies of knowledge, or disciplines, to a focus on developing and mastering skills for varying modes of inquiry. Simultaneously, there has been a growing focus on expanding how students and faculty communicate knowledge – what was once strictly the term paper approach is being replaced by the oral presentation, the poster session, or the artistic response. In a world where ideas are more readily communicated via social media such as YouTube, Instagram, Facebook and Twitter, the ability to accurately assess additional modes of communication is critical. This paper will explore different subsets of literacy, describe a method for developing mastery of those literacies in higher education, and advocate for academic library professionals to become specialists focused on literacies as much, if not more, than on content.