Reviewerly/exHarmony huggingface dataset:
Поэтика мертвой плоти: Дэвид Кроненберг как читатель Нормана Брауна

In the present article the philosophical consistence of David Cronenberg’s cinema.is considered His statements and theoretical investigations, devoted to his work, show that for Cronenberg cinema is aesthetical medium, which let him interpret antiessencialistic ontology of life in the contemporary social-historic perspective (1960s – to the present). It becomes possible only in the conversation with the icon figures of XXth century: among others it is Sigmund Freud, Marshall McLuhan and Norman Brown. In the frame of this conversation, science-fiction and psycho-physiological grotesque, which Cronenberg uses in his movies, gets investigative significance, making us to look in a new way on such actual phenomena, like technological and sexual revolutions, mutations, psychic deviations, appearance of internet and virtual reality. This article analyze early movie of Canadian director, called ‘Shivers’(1975), which grounds a foundations of Cronenberg’s creation process, developing in his further films. Author shows, that in ‘Shivers’ Cronenberg works with the image of ‘polymorphous sexuality’, which he takes from philosophy of Norman O. Brown, famous American Freudian and pupil of Herbert Marcuse. For Brown the former is mean of conceptualizing of reunion man with his body and bounded with it eschatological emancipation project. Cronenberg shows that in conditions of hypertechnological milieu this will be seemed like realisation of feminine (maternal) archetype through the physical invasion of ambiguous oral\anal erotic, expressed in new collective body, structured by aggressive sexuality. As well Croneberg disproves Brownian revolutionary pathos, supposing that this collective body can by integrated in middle class society.
The Realistic Bottleneck in the Construction of the Bridging Curriculum System in Middle and Higher Vocational Education and Its Solution Path

The connection of middle and higher vocational education has established an “overpass” for students to diversify their choices and become a useful person via multiple paths, but many bottlenecks exist in the specific practice process. Taking curriculum system construction as a breakthrough, this paper analyzes problems from the three levels of government, inter-school and school. Based on one’s own practical management experience, the author proposes serialized solutions from four aspects: construction principles, construction ideas, construction strategies and implementation guarantees, aiming to improve the practical effectiveness in the connection of middle and higher vocational education.
Revamp the game: evolution of Russian media eco-system and blockchain technology

A protocol for enabling smart, social currency for publishers and content businesses across the internet 1 Delegated Proof of Stake Position Paper.Grigg, 2017.https://steemit
Field Test for Immersive and Interactive Audio Production with the Gewandhausorchester Leipzig using MPEG-H

Next Generation Audio (NGA) codecs offer new features for consumers such as advanced user interactivity, immersive sound and optimized reproduction across different classes of playback devices. Yet, ‘real world’ experience in the application of NGA workflows in classical music production is limited: The realistic depiction of the original concert hall sound and the treatment of elevated sound sources impose challenges when recording and mixing. Besides producing for immersive reproduction systems, sound engineers face new tasks like the integration of user interactivity, ensuring downmix compatibility and loudness consistency. This paper expounds our field test for an NGA production workflow found suitable for complex orchestral music. Using MPEG-H 3D Audio as an example, we recorded three full-length concerts with Gewandhausorchester Leipzig. Among them is the prestigious new year's concert with Beethoven’s 9th symphony conducted by Gewandhauskapellmeister Andris Nelsons. We developed a microphone setup for the immersive recording of classical music in Gewandhaus and achieved convincing results with the recording and mixing strategies presented in this paper. The perceived reverberance in the mixes was found to be realistically relatable to the excellent room sound in the original concert hall. Elevated sources, like the choir and soloists, were clearly depicted as such. For metadata authoring and mastering, MPEG-H production tools were used to regulate loudness, dynamic range and downmix compatibility, targeting playback over loudspeakers and 3D audio soundbars. Additionally, we tested two different approaches for interactivity that are suitable for classical music listeners.
Students' Perceptions of Peer Teaching in a Coding Course

Mobile learning in education has evolved over the last decade and a half. Associated with this evolution is the increased popularity of teaching how to code using mobile technologies. Then again, finding alternative methods to teach coding, such as peer teaching, might affect learning. Peer teaching is a reciprocal learning relationship between peers. This mixed method case study aimed to explore students’ perceptions of peer teaching in an mLearning coding course. Twentysix participant learners, and three peer teachers, voluntarily participated in the study for six weeks. 77% of participants found that learning from their peers was fun, satisfying and more informative than they expected. However, 42% of participants highlighted that they did not have enough confidence to peer-teach the material they learned during the peer teaching process. Thus, it is important to design a teaching process which considers culture, students' expectations, and students' needs, because those factors affect the learning process.
Sign to speech converter for speech impaired people

Our aim for this project was to create a communication system between speech impaired people and other, and we came up with an idea for making a glove through which the speech-impaired people can send any type of simple signs like raising a finger and for each sign there would be different command or signal associated with it which could be then converted and given out as sound output through the speakers. We believe this project could be used in a wide area of application of not just for speech impaired people but also for elderly people who are bedridden or semi-paralyzed people.
re3data COREF - Community Driven Open Reference for Research Data Repositories

Use unique identification in machine-to-machine (M2M) communication to foster the usage of re3data as an open reference for repositories.Import and export of metadata fragments, controlled vocabularies and database entries of external sources.Adress funding bodies and publishers to recommend re3data in their respective policies to foster the usage of trustworthy repositories complying with the FAIR-principles.
Distributed Black-Box optimization via Error Correcting Codes

We introduce a novel distributed derivative-free optimization framework that is resilient to stragglers. The proposed method employs coded search directions at which the objective function is evaluated, and a decoding step to find the next iterate. Our framework can be seen as an extension of evolution strategies and structured exploration methods where structured search directions were utilized. As an application, we consider black-box adversarial attacks on deep convolutional neural networks. Our numerical experiments demonstrate a significant improvement in the computation times.
Digital Workplace Security Framework

Security is an important success factor for the digital workplace. As the EXP manages a lot of confidential employee information, it is imperative to ensure that the proper security standards are adopted. A comprehensive security framework covers all aspects of security such as logical security, functionality security, application security, security event tracking, and such.
PERBANDINGAN METODE MD2 DAN MD4 UNTUK MENDETEKSI KEASLIAN CITRA DIGITAL

Cryptography is used to protect the contents of information from anyone except those who have the authority or secret key to open information that has been encoded. Along with the development of technology and computers, the increase in computer crime has also increased, especially in image manipulation. There are many ways that people use to manipulate images that have a detrimental effect on others.The originality of a digital image is the authenticity of the image in terms of colors, shapes, objects and information without the slightest change from the other party. Nowadays many digital images circulating on the internet have been manipulated and even images have been used for material fraud in the competition, so we need a method that can detect the image is genuine or fake. In this study, the authors used the MD2 and MD4 methods to detect the originality of digital images, by using this method an image that is still doubtful of its authenticity can be found out that the image is authentic or fake. Keywords: Authenticity, Image, MD2 and MD4
A Random Vector Functional Link Network Based Content Based Image Retrieval

Image Retrieval (IR) framework enables the user to search query images in order to retrieve images stored in the database according to their advantage. Content Based Image Retrieval (CBIR) is a technique which uses visual features of an image such as color, shape and texture feature to retrieve images of user interest. The major issue that exists in any CBIR system is semantic gap and computational time. Hence this work aims to provide an exchange off between computational time and accuracy. To extract the color, texture and shape feature, the RGB color histogram from the three independent color channels, Local Binary Pattern (LBP) from the gray scale image Histogram of oriented gradients are derived respectively. These three features are concatenated to obtain the feature vector of the images in the database. The dimensionality of the feature vector is reduced by Linear Discriminant Analysis (LDA). The compact feature vector set is trained using Random Vector Functional Link (RVFL) network to create the knowledge base. In the testing phase, once the user rises a query, the query feature vector is derived for the corresponding query image and tested against the knowledge base using RVFL classifier. Using the class code obtained by RVFL classifier, the images are retrieved using Minkowski distance. The performance of the proposed algorithm is validated by evaluating it on a Corel Image database using metrics like precision, Recall and F-score. The proposed feature combination along with LDA and RVFL provides better results in retrieving the query image.
Organic Waste Chopper Tool Design Using Autodesk Inventor 2015 Software

In the program of mechanical engineering, the software used to draw is Autodesk Inventor. Autodesk inventor is a CAD program in the program of engineering that is applied to the design of mechanics in 3D. In designing a tool, of course, it is preceded by a planned design concept. In making a design a tool requires a process or steps for making the design. These steps include the size, dimensions, and materials used in making organic waste chopper tool. The drawing process uses the 2015 Autodesk Inventor program, the first is the making of sketches, components on the machine, followed by assembly of each component, then rendering images, animation as the final stages of drawing design input into "IDW" complete with size, scale, material. Image projection to make it easier for designers to make tools. Drawings of plan and complete details covering the scale dimensions will be able to simplify the manufacturing process (production) of the components of the tool and can reduce the risk of errors in the process of making tools.
internet of things (IOT): alleviation for indian farmers

This paper explores the job of Internet of Things(IoT) in Agricultural Sector. Today farming is installed with development benefit like GPS, sensors that empower to convey to one another break down the information and furthermore trade information among them. IT gives benefit as cloud to farming. Horticulture cloud and IT benefit gives an exceptional aptitude administration to ranchers in regards to development of harvests, estimating, composts ,infections detail strategy for fix to be utilized Scientist taking a shot at farming will give their revelations, recommendations with respect to present day methods for development ,use of manures can acquire the historical backdrop of the locale. the investigation depended on applying a cloud put together application with respect to farming. This depends on agri-cloud that improve rural creation and accessibility of information identified with research extends in the fizzled, the effect of doing this will spare the expense and time make the correspondence less demanding and quicker. This paper would advance a great deal of research in the territory of utilization of IoT in agribusiness.
DEVELOPMENT OF AUTOMATED WORKPLACE OF ADMINISTRATOR TO WORK WITH CUSTOMERS

The article discusses the experience of developing software for automatization of the activities of an administrator in working with clients in organizations of service sector. The project will be used as a practical part when working on final qualifying work.
Certificateless Digital Signature Technology for e-Governance Solutions

. In spite of the fact that digital signing is an essential requirement for implementation of e-governance solutions in any organization, its use in large scale Government ICT implementation is negligible in India. In order to understand the reasons for low-level acceptance of the technology, authors performed a detailed study of a famous e-governance initiative of India. The outcome of the study revealed that the reasons are related to the challenges concerning the use of cryptographic devices carrying private key and the complicated process of generation, maintenance and disposal of Digital Signature Certificates (DSC).The solution, for the challenges understood from the case study, required implementation of a certificateless technology where private keys should be generated as and when required rather than storing them on cryptographic devices. Although many solutions which provide certificateless technology exist, to date there have been no practical implementation for using biometrics for implementing the solution. This paper presents the first realistic architecture to implement Identity Based Cryptography with biometrics using RSA algorithm. The solution presented in the paper is capable of providing a certificateless digital signature technology to the users, where public and private keys are generated on-the-fly.
NACOSTI Portal Demo and Discussion

NACOSTI Portal Demo and Discussion waspresented at the 2019 Kenya ORCID Workshop on November 14, 2019.
A New Model to Detect 2D Hand based on Multi-feature Skin Model

Recognition of hand gesture is one of Human PCs most growing interfaces.In most vision-based signal recognition system, the initial phase is hand detection and separation.Because the hands are linked to a variety of day by day, local work experiences both extraordinary changes in the illumination and the innate unbroken appearance of the hand.In order to address these issues, we suggest another 2D hand position software that can be seen as a combination of multi-feature hand proposal generation and cascading neural system network characterization (CCNN).When considering various luminances we select color, Gabor, Hoard and Filter to separate the skin and produce a hand proposal.Therefore, we are selling a cascaded CNN that holds the deep setting information between the proposals.A mix of some datasets, including a few Oxford Hands Datasets, VIVA Hand Recognition, and Egohands Datasets, is tested as the positive example and image patch Net 2012, FDDEB dataset as a bad example; the proposed Multi-Feature Directed Cascaded CNN (MFS-CCNN) strategy.Aggressive results are achieved by the technique proposed.Our average sample dataset accuracy is considerably inferior to DPM.With an average of 43.55 and 51.78 percent accuracy, our CCNN and MFS-CCNN model perform DPM.Average accuracy of the CCNN model in a combined test set is 9.16% higher than the SSD model.Still, our model is faster than a DPM based on the statistical performance.
Your Honor, on Social Media: The Judicial Ethics of Bots and Bubbles

Many judges sitting in county, state, and federal courts in the United States have joined the ranks of social media users. Judges post on social media. They engage followers on Twitter and friends on Facebook. Like other humans using social media, judges may unwittingly encounter bots simulating human behavior or “bubbles” created by algorithms. This article is the first to examine at length the potential threat to judicial impartiality arising from judges interacting with bots and bubbles—both present, known phenomena on social media. While much scholarly literature has delved into ethical issues implicated by judges’ social media contacts, very little attention has been focused on the impact of automated bots and algorithmic bubbles on judges’ impartiality.Judges are expected to be impartial. Impartiality has long been a cornerstone of the judicial role. With social media bots and bubbles that put social media users at greater risk of believing falsehoods and of seeing only what confirms their own beliefs, judicial impartiality, a central feature of the judicial system, may be under threat at a level not encountered in the past. In this article, I argue for increased precautions and awareness to help maintain judicial impartiality in light of the potential unfortunate impact of social media bots and bubbles.
P1_5 Martian muon decay

One of the first pieces of evidence for Einstein's theory of special relativity was the apparent detection of muons at the surface of earth. We consider the same effect but using a Martian atmosphere. We calculate that the time taken to traverse the Troposphere is $t_{actual} = 1.3\times 10^{-5}$ s after allowing for relativity. Lastly, we find that the number of muon's detectable is $\sim0.26\%$ .
A Machine-Learning Based Approach for Data-Driven Identification of Heating Dynamics of Buildings' Living-Spaces

Modeling the heating dynamics of a given living-space of a real building remains a challenging engineering-science problem because of the quite large number of diverse kinds of involved parameters and their usually nonlinear interdependency. However, the need of such living-spaces' heating dynamics modeling appears as a foremost requirement for designing adaptive controllers scheming the complex behaviors of nowadays' smart buildings. In this context and through considering the above-mentioned complex dynamics' modeling within the slant of “Time-Series Prediction” paradigm, in this paper we propose a Machine-Learning-based data-driven approach for overcoming difficulties inherent to the aforementioned challenging engineering-science problem. The proposed approach takes advantage from the nonlinear autoregressive exogenous (NARX) model's capabilities in time-series' forecasting and the Multi-Layer Perceptron's (MLP) learning and generalization skills. The proposed approach has been applied for living-space heating dynamics identification of a fully automated four-floor real building located at Senart Campus of University Paris-Est Créteil (UPEC). The obtained results assessing the accuracy of the investigated Machine-Learning-based approach are reported and discussed.
Feedforward Neural Network Based on Improved Gray Wolf Optimizer

Neural network is one of the greatest inventions in the field of artificial intelligence. It mimics the neural elements of the human brain and is mainly used to solve classification problems and make data prediction, parameter optimization of which remains to be an important problem. Different results are obtained by different algorithms. In the paper, the gray wolf optimizer algorithm based on bionic simulation is studied. By optimizing the non-linear convergence factor and making it more consistent with the actual convergence process of the algorithm, so it can better balance the global search performance with the local search performance, and further enhance the global optimization ability of the algorithm. By increasing the dynamic weight, the gray wolf of the leadership can dynamically guide the gray wolf herd forward, which greatly enhances the adaptability of the algorithm to the environment. The experimental results show that the performance of the optimized feedforward neural network based on Grey Wolf Optimizer(GWO) algorithm performs better than that of the previous ones.
Smart Packet Forwarding in Router using Classification Of System Traffic with Neural System

Router assumes a critical part in arrange directing or organize flows sending, the router carry the packet to one place to other via preeminent way. In traditional method router forward packet to only known predefined path, unaware of importance of packet and packet count total. It diminishes the productivity of router when the way is inaccessible. If router has knowledge on ingress traffic, easy to manage bandwidth allocation when there is heavy traffic. In proposed method Prior knowledge on traffic is determined by neural network traffic classification method. classification methods like port based and signature methods are give less accuracy, comparatively proposed neural network gives more accuracy then the traditional classification methods. Classification result is optimized by fish seminary search algorithm; this classification result is forwarded to router for efficient packet delivery.
At the intersection of open science and the transforming research library: Carnegie Mellon University Libraries Open Science Program

Poster presented at FORCE2019 in Edinburgh in October 2019. The open science movement includes the core pillars of transparency, access, and collaboration as well as the ability to leverage data science technology. The Carnegie Mellon University Libraries strategic plan endeavors to transform the library into the hub of research support for the university. In 2018, the CMU Libraries founded the Libraries Open Science Program to support collaborative, transparent, openly accessible, and reproducible research across all disciplines at Carnegie Mellon University. This program provides services and infrastructure for open research at CMU through digital tools, training opportunities for research tools and practices, special events and advocacy in support of open research, and a team of experts available as research consultants and collaborators. The team includes subject librarians with a research focus, methods specialists in data management and scholarly communication, and post-docs and faculty focused on specific research areas and techniques (e.g. GIS, digital humanities).
Tiny Tweaks: Small Interventions to Help Improve Student Worker Performance

Presentation for Texas Conference on Digital Libraries 2019. This presentation discusses ways to enhance student assistants productivity and shares UNT's experiences, including simplifying workflows and making small changes in training that can go long ways in terms of improving students overall performances.
Keeping the User and User Data in Mind : A Study on Empathy and Personas

One method to create and work with personas is to abstract the user data into a character with a background story and a set of goals. This method has been argued against as the method is argued to ...