Reviewerly/exHarmony huggingface dataset:
Seismo-acoustic Data Fusion: Determining the Best Acquisition Designs for Multi-Phenomenological Monitoring Campaigns.

events from arrival time data of detected seismic phases. In order to do utilize Bayesian OED we must develop four elements: 1. A likelihood function that describes the uncertainty of detection and travel times, 2. A Bayesian solver that takes a prior and likelihood to identify the posterior, 3. An algorithm to compute EIG, 4. An optimizer that ?nds a sensor network which maximizes EIG. Once we have developed this framework, we can explore many relevant questions to monitoring such as: how and what multiphenomenology data can be used to optimally reduce uncertainty, how to trade off sensor ?delity and earth model uncertainty, and how sensor types, number, and locations in?uence uncertainty.
12 Remixes

In this piece I apply various literary remixing techniques to an article by the critic Edward Picot, written about a remix based sound art project I undertook over a year in 2011-12. I intend the end result as commentary, research and minor literature.
Integral Cryptanalysis

Integral cryptanalysis is a cryptanalytic technique that is designed for block ciphers constructed on networks of substitution-permutation. Since the integral cryptanalysis attack can be launched against the Square block cipher [1], it is also known as the Square attack. It was designed by Lars Knudsen.
Azure IoT Solutions: Cloud Services

Now that you’ve seen a number of projects ranging from basic to advanced, it is time to discuss how to make your IoT data viewable by others via the cloud. More specifically, you will get a small glimpse at what is possible with the Microsoft Azure cloud computing services and solutions.
DESIGN OF SECURE IMAGE DATA HIDING FOR SECURITY PROTOCOL USING AES AND LSB ALGORITHM

This paper presents a critical analysis on new and original proposed algorithm based on hiding any data has been used that overcomes the disadvantages of the existing algorithms and helps to provide less similarity between cover image and stego image and obtain accuracy upto 69.6 percentage and increases its robustness using metrics called mean square error and peak signal to noise ratio. In the wireless environment cryptography suffers from various spyware programs that shows corrupted secret information to innocent users who uses image steganography services from user. In our proposed prototype helps to authenticate the sender to make the unnoticeable image from original image. In our proposal work discovers a secure authentication communication model would able to cover multimedia data like first text to be hide, second image to be hide and third audio secret data to be hide in cover image without much noticed to any user in between network. In order to provide additional security to this model we incorporate AES encryption scheme where secret message is encrypted and hidden in the cover audio. The proposed approach uses DCT coefficient computation and AES encryption scheme. An extensive experimental study is carried based on different test cases and evaluated against state-of-art techniques. The experimental study shows that the proposed approach achieves better performance for audio steganography. Keywords: AES, steganography, cover image, hiding image, network, digital data.
More on Fingerings

Abstract Understanding how different (non-standard) fingerings can help solve reed problems as well as technical and musical issues.
Academic Orientation Programme 2021. Researcher Visibility &amp; Sharing our work beyond the University

&lt;p&gt;This presentation introduces academics and researchers to the value of formal and informal technologies in promoting the visibility and discoverability of their online researcher identity. Topics covered in the presentation include Open Access, Creative Commons licensing, Institutional Repositories, Research Data Management, ORCID, Research Collaboration &amp; Social Scholarship, Researcher impact &amp;citation analysis, Social Media, and Altmetrics.&lt;/p&gt;
Segregation of Sensitive Data in Cloud Storage

Big data is a huge collection of data, which are larger in size. It assembles many techniques and technologies to uncover the needed values from a larger data set. Big data needs a large server to store the data which is higher in cost and also there is a need for maintenance. Cloud server can be a key for this problem. It has the capability of large scale storage management. But it is a third party service, so the apprehension here is the data security. Data can be secured from the cloud server by strong encryption methodologies. All data doesn’t need a high data security, so first we need to classify the data into sensitive and insensitive data. Sensitive data alone needs a proper attention over threats. This paper focuses on the identification of sensitive data within an acceptable computation time.
Research on Multi-turn Dialogue Generation Strategy Guided by Topic

The open-domain generated dialogue model relies on masssively the neural network model to generate sentences without grammatical errors, and does not consider effective mechanisms to manage chat topics, resulting in monotonous and incoherent conversation topics. Inspired by human’s dialogue strategy, this paper proposes a topic-guided multi-turn dialogue generation strategy, DATHRED, which with a knowledge topic smoothing technology. It uses HRED to model multiple turns of dialogue, and proposes the two-way confrontation model to improve the topic richness of multi-turn dialogue and the fluency of topic transition. The comparison with the baseline model on the KdConv dataset verifies the effectiveness of our method.
Preliminaries

This chapter introduces a number of core concepts for morphology: the nature of morphological generalizations, paradigmatic word formation, productivity, the nature of the lexicon and lexicalization. It also specifies the sources of information on the morphology of Dutch, and gives a survey of the rest of the book.
Identity Based Data Sharing and Profile Matching using Probabilistic Key in Cloud

Cloud technology is popular since the utilizations and their information are expanding hugely step by step. It gives usefulness to overseeing data information in a conveyed and pervasive way supporting many platform. Data sharing and security problem are the principle issue to the increasing use of health care, since health information is delicate. However issues, for example, risks of privacy exposure ,versatility in key administration, adaptable access and effective uses denial always been the most significant difficulties for accomplishing good- grained cryptographically upheld information access control. Right now structure a protected information move and profile coordinating plan with probabilistic open key encryption in correspondence test to diminish the size of open key which helps in decreasing the capacity and furthermore time productive. Our probabilistic open key encryption plot when executed in a bilinear gathering, it can check whether two figure writings are scrambled of a similar message. Strangely, in encryption or decoding system bilinear mapping isn't required in Public Key Encryption conspire except if when individuals need to do in fairness test between two figure messages that might be produced utilizing diverse open keys. Additionally the profile coordinating component dependent on Probabilistic Public Key Encryption with fairness test( PPKEET) causes patient to discover companions in a security saving way with age of trapdoors and structure social connections as indicated by the desire. The security examination and trial results demonstrated that our plan is ensuring the information and giving right medicine in cloud.
Design of A Beauty Matching App Based on Support Vector Machine

In order to meet consumer’s huge demands for cosmetic match, this project plans to develop a cosmetic match application --- Beauty, based on support vector machine. Beauty, according to pictures including different shapes of face, can adopt Principle Component Analysis (PCA) to optimize image pixel, get the lower dimension feature vector to support vector machine’s input, and then adopt cross-validation and grid-search to select penalty parameter c and kernel parameter g to train the model. Finally, different facial pictures are tested respectively by making use of these models. And then consumers can get the most suitable recommendation in accordance with classification results.
E-Journals and Citation Patterns: Is It All Worth It?

For many decades librarians have attempted to measure use of serial collections and the advent of electronic journals has opened up new avenues for measuring use. However, many vendor-supplied usage statistics are unsatisfactory. Two Yale University librarians tried another approach and conducted a citation analysis to compare usage before and after the arrival of electronic journals. They wanted to answer a basic question: Did the purchase of electronic journals not previously held in print affect citation patterns of Yale authors? [Article copies available for a fee from The Haworth Document Delivery Service: 1-800-HAWORTH. E-mail address: &lt;docdelivery@haworthpress.com&gt; Website: &lt;http://www.HaworthPress.com&gt;]
Category theory

This chapter aims to introduce sufficient category theory to enable a formal understanding of the rest of the book. It first introduces the fundamental notion of a <italic>category</italic>. It then introduces <italic>functors</italic>, which are maps between categories. Next it introduces <italic>natural transformations</italic>, which are natural ways of mapping between functors. The stage is then set to at last introduces <italic>monads</italic>, which are defined in terms of functors and natural transformations. The last part of the chapter provides a compositional calculus with monads for natural language semantics (in other words, a logic for working with monads) and then relates the compositional calculus to Glue Semantics and to a very simple categorial grammar for parsing. The chapter ends with some exercises to aid understanding.
Normative Personalities

In this chapter a cybernetic psychosocial view will be adopted to theoretically explore plural agencies (defined through their population of agents) with a common culture, a collective mind, and behaviour. Within the context of cognitive information process theory, the collective mind is an information system that operates through a set of logical mental rules and strategies (e.g., Atkinson & Shiffrin, 1968; Bowlby, 1980; Novak, 1993; Wang, 2007). This has relevance to cognitive learning theory (e.g., Miller & Dollard, 1941; Miller et al., 1960; Piaget, 1950; Vygotsky, 1978; Argyris & Schön, 1978; Bandura, 1986, 1988; Nobre, 2003; Argote & Todorova, 2007), where ‘learning is seen in terms of the acquisition or reorganisation of the cognitive structures through which humans process and store information’ (Good & Brophy, 1990: 187).
Semantic analysis of Twitter content

Semantic analysis is the process of shifting the understanding of text from the levels of phrases, clauses, sentences to the level of semantic meanings. Two of the most important semantic analysis tasks include 1) semantic relatedness measurement and 2) entity linking. The semantic relatedness measurement task aims to quantitatively identify the relationships between two words or concepts based on the similarity or closeness of their semantic meaning whereas the entity linking task focuses on linking plain text to structured knowledge resources, e.g. Wikipedia to provide semantic annotation of texts. A limitation of current semantic analysis approaches is that they are built upon traditional documents which are well structured in formal English, e.g. news; however, with the emergence of social networks, enormous volumes of information can be extracted from the posts on social networks, which are short, grammatically incorrect and can contain special characters or newly invented words, e.g. LOL, BRB. Therefore, traditional semantic analysis approaches may not perform well for analysing social network posts. In this thesis, we build semantic analysis techniques particularly for Twitter content. We build a semantic relatedness model to calculate semantic relatedness between any two words obtained from tweets and by using the proposed semantic relatedness model, we semantically annotate tweets by linking them to Wikipedia entries. We compare our work with state-of-the-art semantic relatedness and entity linking methods that show promising results.
Single Image Haze Removal with Pixel-based Transmission Map Estimation

Adversary imaging condition such as in a hazy weather is a challenge in the community of image processing. To address the challenge of haze removal, several model-based approaches have been reported recently. Among them, a single image haze removal scheme based on dark channel prior (DCP) was presented in [1] and has been getting popular because of its satisfactory performance for most of cases. However, it is well-known that the DCP scheme is inherent of two fundamental problems: high computational cost and over-exposure. In this paper, the objective of proposed dehazing algorithm (PDA) is to deal with the two problems in [1], where atmospheric light is estimated from the dark channel and pixel-based transmission map estimation is employed. Examples are given to verify the PDA where comparison with the DCP scheme and other well-known schemes are made as well. The simulation results indicate that the PDA has similar or better dehazing performance than the compared schemes in the given examples, when both mood retention and visibility improvement are considered.
An improved content splitting and merging algorithm for Hadoop clusters using component analysis and hamming distance

Distributed storage and processing of dataset of big data have become an integrated component of data science. With the technology progress towards the Internet of Things (IoTs), big data becomes more important. Therefore, processing of such data needs utmost concern for the ease of availability and accuracy. Various research has been executed till date for the efficient use of splitting and merging of content in the processing of data. But, somehow they lack in the generation of proper clusters in Hadoop. In this paper, we have shown an efficient approach of using splitting and merging process of data processing. We have used component analysis and hamming distance to generate thee clusters depending on the split values which is novel in this domain of work. The experimented results of our proposed approach provide better efficiency in term of discrete clusters and time consumption.
Supplemental Material: Geomorphic expression and slip rate of the Fairweather fault, southeast Alaska, and evidence for predecessors of the 1958 rupture

&lt;div&gt;Ten figures and five tables that support the analyses and discussion presented in the paper. &lt;br&gt;&lt;/div&gt;
XJU-MLSIG: A Multilingual Online Signature Database

To study the online signature of ethnic minority languages, a multilingual online signature data set is established by using a high sampling rate digital board. The data set includes 162 Uyghur individuals, 58 Kazakh individuals, and 33 Kirgiz individuals. Each individual has 10 real samples and 10 skilled forgery samples, The establishment of the data set fills the blank of online signature for small languages. In this paper, a benchmark algorithm is used to test the data, and compared with other public data sets, for the reference of subsequent researchers. The database is available through https://github.com/cyhnice/XJU-MLSIG
Image Clustering using Multichannel Decoded Local Binary Pattern

CBIR uses the visual contents of an image such as color, shape, texture, and spatial layout to represent and index the image. Local Binary Pattern based descriptors have been used for the purpose of image feature description. Local binary pattern (LBP) has widely increased the popularity due to its simplicity and effectiveness in several applications. In this paper, we proposes a novel method for image description with multichannel decoded local binary patterns. Introduce adder and decoder based two schemas for the combination of the LBPs from more than one channel. Finally, uses Fuzzy C-means clustering under semi- supervised framework. The outcomes are processed as far as the normal exactness rate and average recovery rate and improved execution is seen when contrasted and the aftereffects of the current multichannel based methodologies over every database. The component vector is figured for snake and decoder channels utilizing histograms. At long last, the image ordering process is enhanced utilizing information grouping methods for images having a place with a similar class
Project-based Robotics Courses for the Students of Mechanical Engineering Technology

project-based learning and student learning assessment.His research is
Withdrawal

Withdrawal: Martin Bordewieck and Malte Elson, the impact of inducing troubleshooting strategies via visual aids on performance in a computerized digital network task, Applied Cognitive Psychology 2020, ( https://doi.org/10.1002/acp.3731 ) The above article from Applied Cognitive Psychology, published online on 11 August 2020 in Wiley Online Library ( http://wileyonlinelibrary.com ) has been withdrawn by agreement among the authors, the Journal Editor‐in‐Chief Graham Davies and John Wiley &amp; Sons Inc. The article was published in error. The authors are updating the proposed methods in this Stage 1 Registered Report, partly due to the impact of the Covid‐19 pandemic on conducting research. The revised Stage 1 Registered Report can be found here: https://doi.org/10.1002/acp.3809 .
Transforming AACR2: Using the Revised Rules in Chapters 9 and 12 Part 1

“Transforming the AACR2” was presented to an overflowing room of serialists and catalogers. Les Hawkins and Jean Hirons, both from the Library of Congress, explained the upcoming revisions in Chapters 9 and 12 of the Anglo-American Cataloguing Rules (AACR2). [Article copies available for a fee from The Haworth Document Delivery Service: 1-800-HAWORTH. E-mail address: &lt;docdelivery@haworthpress.com&gt; Website: &lt;http://www.HaworthPress.com&gt;]
Applets and Network Security: A Management Overview

Applets can present a real security hazard for users and network managers. Some security experts have gone as far as to say that the corporate network manager should prohibit users from running applets at all. Microsoft’s approach to security for non-Java ActiveX applications is based on the concept of accountability — knowing with certainty the identity of the person or company that wrote a piece of software and that the software was not tampered with by a third party. Java applets running in an ActiveX environment (e.g., Microsoft’s Internet Explorer Web browser) use the same security features and have the same security issues associated with JavaScript. Applets offer users and network managers a whole new paradigm for delivering applications to the desktop. If an organization is planning to use applets on its Web pages, it is preferable to either write them internally or obtain them from trusted sources.
Various Strategies and Procedures Utilized for Gender Acknowledgment Utilizing Voice and Its Highlights

As discourse is viewed as one of the significant pieces of the people, as it is supportive for understanding the feelings and sentiments and so forth of the individual talking. The bio measurements innovation these days are particularly mainstream like unique mark and so forth. However, the upgrade of this innovation has additionally come like face location, iris identification, and voice recognition and so on. Voice acknowledgment is utilized for the sexual orientation recognizable proof also in light of the fact that it is been considered as one the dependable method of sex distinguishing proof. Voice acknowledgment is fundamentally understanding the voice signals and convert them into little examples and the machine is been will be been prepared to recognize those examples. The paper tells about the voice acknowledgment and the different strategy utilized for it.
Provocative insinuations

En este artículo analizamos oracio-nes que, sin constituir explícitamente discurso de odio, no obstante transmiten un mensaje de odio. Por ejemplo, en el titular “Refugiado iraquí es condenado en Alemania por violar y asesinar una chica adolescente”, la presencia de “refugiado iraquí” no parece arbitraria. Al contrario, invita una inferencia racista en contra de los refugiados iraquíes. Argumentamos que estas inferencias no pueden ser descritas como slurs, términos neutros utilizados como insultos, dogwhistles o implica-turas conversacionales. En cambio, proponemos caracterizar estas inferencias como insinuacio-nes, concretamente insinuaciones provocativas, debido a que ninguna respuesta parece efectiva a la hora de bloquearlas. In this paper we analyse utterances that, without explicitly constituting hate speech, nevertheless convey a hateful message. For example, in the headline ‘Iraqi Refugee is convicted in Germany of raping and murdering teenage girl’, the presence of ‘Iraqi refugee’ does not seem arbitrary. To the contrary, it is responsible for inviting a racist inference against Iraqi refugees. We defend that these inferences cannot be described as slurs, ethnic or social terms used as insults, dogwhistles or conversational implicatures. Rather, we propose that these inferences are insinuations, specifically provocative insinuations, as no conversational response seems effective at blocking them.
An Understanding of IPv6 using Muck

The cyber informatics solution to lambda calculus is defined not only by the emulation of 802.11 mesh networks, but also by the extensive need for expert systems. Following quite a while of natural examination into IPv4, we demonstrate the copying of superpages, which epitomizes the affirmed standards of algorithms. So as to understand this mission, we present an investigation of Byzantine adaptation to non-critical failure (Muck), which we use to demonstrate that the little-known decentralized algorithm for the improvement of voice-over-IP by White et al. [1] keeps running in O(N2) time.
Blowing your Mind: A Conceptual Framework of Augmented Reality and Virtual Reality enhanced cultural visitor experiences using EEG experience measures

Cultural tourism is regarded as a key contributor for economic growth in various destinations. While increasing awareness and interest of different cultures play a key role, technology has made information and interaction at these sites more accessible and engaging. An increasing amount of research is being conducted around the potential and implementation of AR and VR technology to enhance the visitor experience. However, limited theoretical knowledge has been developed on how these need to be designed to facilitate forming memorable experiences at cultural tourism sites. This study discusses elements affecting the visitor experience and discusses how AR and VR should be designed to contribute to enhancing the experience and making it memorable from a theoretical perspective. Further research recommendations are outlined that suggest the use of complementing research methodologies to better understand the nature of experiences in order to design AR and VR application more purpose-specifically.