Reviewerly/exHarmony huggingface dataset:
Leveraging Blockchain Technology for Decentralized Domain Name Broker Service

The internet community is striving to move towards decentralized architecture, where users can have real control over their data. Attempts are being made to remove the brokers and centralized entities present in various case studies. One such use-case, which has not been given much attention in recent years but is worthwhile examining, is the secondary market of domain names. A meaningful and appropriate domain name can increase the website’s traffic by improving the Search Engine Optimization ranking. The exponential growth of the secondary market of the domain that motivates us to work on this idea is: With the exponential growth of internet users, domain ownership has also grown exponentially, thereby creating a massive demand for domain names. The chapter discusses the theoretical background needed to understand the proposed work. Domain names are essentially a combination of letters, digits, and hyphens that are generally chosen so as to convey some meaning, acronyms, or even brand names.
Infraestrutura de Investigação para a Ciência e Tecnologia da Linguagem - PORTULAN CLARIN

This paper presents the PORTULAN CLARIN Research Infrastructure for the Science and Technology of Language, which is part of the European research infrastructure CLARIN ERIC as its Portuguese national node, and belongs to the Portuguese National Roadmap of Research Infrastructures of Strategic Relevance. The PORTULAN CLARIN includes a helpdesk, a repository, where resources, such as corpora, lexicons and processing tools are deposited for long-term archiving and can be searched and retrieved, and a workbench, where Language Technology tools and applications are made readily available online and can be used in different types of interfaces. Its goal is to contribute to the technological development of natural languages and for their preparation for the digital age, with a special focus on the Portuguese language in all its varieties and modalities.
Library: Data Visualization: Visualization on Campus

Resources and information about data visualization at the University of Calgary and beyond.
Pengalaman pemanfaatan cloud storage mahasiswa Teknik Komputer Universitas Diponegoro (Undip) dalam pengelolaan arsip digital

The use of cloud storage every student is certainly different, different behaviors also affect how individuals manage and use the digital archives they have stored in cloud storage. The purpose of this study is to find out how cloud storage behavior emerges when managing digital archives that students have in their educational activities. This study is done qualitatively with phenomenological methods through interviews to active computer engineering students Undip and observation as techniques in obtaining data. The data analysismethod used in this study is thematic analysis method, which is used to find patterns or themes by analyzing the data obtained then associated with the phenomenon found through the researchers' glasses. The results of this study obtained two themes, namely student knowledge regarding the management of digital archives owned using cloud storage and the behavior of using cloud storage that was raised by computer engineering students. While managing digital archives owned by students, it tends to be done simply in accordance with their knowledge and abilities. The management stage is carried out starting from the selection stage, the structuring and grouping stage, the evaluation stage and the meeting again. All stages of management that are carried out are of course related to one another. The utilization behavior shown by students has different goals in various ways to help with their lecture activities. The behavior of using cloud storage that is carried out is adjusted to the needs and interests of students to be able to meet information needs to support their academic activities.
Research on the Architecture of Cloud Host Autonomous Backup System in a Cloud Data Center

In order to realiaze data central control, improve resource utilization and reduce the operation and maintenance cost of information system, enterprises often use private cloud data center to provide virtual cloud host services for users. Therefore, data backup for cloud host usres is particulary important. In this paper, an appropriate technical solution is proposed according to the actual requirements of enterprise cloud host data backup. First according to the performance requirements of data backup recovery for an enterprise cloud host, the three basic elements of data backup are briefly analyzed. Then the logical architecture of the cloud host's autonomous backup system is built. Finally, the current mainstream backup networking mode, backup strategy and snapshot strategy are analyzed in detail. This architecture research can provide effective technical support for an enterprise to build a cloud host autonomous backup system.
Speech Recognition: Transcription and Transformation of Human Speech

The specified subfield of computational linguistics and computer science can said to be linked with speech recognition. Speech recognition can develop new variation technologies as well as methodologies generated as interdisciplinary concept. It can be considered to translate and recognize and satisfy the capability towards understanding and translating the words that are already spoken. It is more preciously said that in the most recent times this field has secured positive feedback by intense learning of voice recognition. Such evidences shows the proof that it has more market demand for implementing the application of specific data as voice recognition. Deployment of speech recognition systems can be utilized as the evidence shown to its analyzing methods that is helpful for designing each and every individual's future. It is said that the computer plays an important role for this process as by this all the translated words can be acknowledged by the texts also.
A Study on Applying Proxemics to Camera Position in VR Animation

With the development of science and technology, virtual reality (VR) has become increasingly popular, being widely used in various fields such as aviation, education, medical science, culture, art, and entertainment. This technology with great potential has changed the way of human-computer interaction and the way people live and entertain. In the field of animation, virtual reality also brings a new viewing form and immersive experience. The paper demonstrates the production of VR animation and then discusses camera’s position in VR animation. Where to place the VR camera to bring a comfortable viewing experience. The paper, with the proxemics as its theoretical framework, proposes the hypothesis about the camera position. Then the hypothesis is verified by a series of experiments in animation to discuss the correlation between camera position and proxemics theory.
Simultaneous image deblurring and inpainting via convolutional sparse coding

Image deblurring and inpainting are traditional image processing problems, and the effects achieved for high-resolution images are not satisfactory. In recent years, Convolutional Sparse coding (CSC) has been received more attention and introduced into image processing, such as blind deblurring. However, none of the works address the issue containing both blur and inpainting. In this work, we propose a novel framework of CSC for simultaneous image deblurring and inpainting. First, we learn a dictionary instead of applying a given dictionary for better image representation. Second, we use the learned dictionary with the &ell;<sup>1</sup> norm to regularize images. In addition, we apply a total anisotropic variation to enhance the edges of the image. Usually, we use the alternating direction method of multipliers (ADMM) formulation in the Fourier domain for the dictionary. We demonstrate the proposed training scheme for simultaneous image deblurring and inpainting, achieving state-of-the-art results.
Label dependent lambda calculus and gradual typing

Dependently-typed programming languages are gaining importance, because they can guarantee a wide range of properties at compile time. Their use in practice is often hampered because programmers have to provide very precise types. Gradual typing is a means to vary the level of typing precision between program fragments and to transition smoothly towards more precisely typed programs. The combination of gradual typing and dependent types seems promising to promote the widespread use of dependent types. We investigate a gradual version of a minimalist value-dependent lambda calculus. Compile-time calculations and thus dependencies are restricted to labels, drawn from a generic enumeration type. The calculus supports the usual Pi and Sigma types as well as singleton types and subtyping. It is sufficiently powerful to provide flexible encodings of variant and record types with first-class labels. We provide type checking algorithms for the underlying label-dependent lambda calculus and its gradual extension. The gradual type checker drives the translation into a cast calculus, which extends the original language. The cast calculus comes with several innovations: refined typing for casts in the presence of singletons, type reduction in casts, and fully dependent Sigma types. Besides standard metatheoretical results, we establish the gradual guarantee for the gradual language.
PERENCANAAN PEMBANGKIT LISTRIK TENAGA SURYA OFF-GRID DI GEDUNG GIS 150 KV PANTAI INDAH KAPUK SEBAGAI PASOKAN UTAMA

Designing a Solar Power Plant in GIS PIK is necessary as a back-up system or a substitute to reduce conventional electricity usage. The Off-Grid System is an unconnected Solar Power Generation system to the PLN electricity network. This Off-Grid system is also called the Stand Alone system because Solar Power Plant only relies on solar energy as the main source by using solar modules to produce electrical energy according to the demand. The design of Solar Power Plants 58,792 m2 Off-Grid system with 147 modules solar power plant components installed with 400 Wp solar panels, 12 inverters with 5 kW capacity, 19 SCCs with 5 kW capacity, and 77 units of batteries with 1000 Ah capacity. The lowest solar radiation occurred in December, which is 3.86. Meanwhile, the highest was in February, at 5.18. The energy cost of GIS PIK Solar Power Plant 58,792 m2 is Rp. 4,450.58 / kWh. According to economic calculations, the total investment cost in this plan is Rp. 993,696,825.6
Studi Komparatif Literasi Sains Siswa Berdasarkan Gender dan Tempat Tinggal di MTs NU Jogoloyo

This study aims to determine the achievement of scientific literacy skills in aspects of knowledge based on gender and place of residence. This study uses a quantitative descriptive method. The sample of this study was 60 seventh grade students at MTs NU Jogoloyo for the 2020/2021 academic year. The research instrument used was a test. Data analysis using total sampling technique. The results showed that the students' scientific literacy ability had an average in the low category, there was a significant difference in the average score based on gender and there was no significant difference in the average score based on place of residence.
Attacks on Deep Learning and Their Countermeasures

This chapter categorizes the types of the adversarial model on privacy-preserving deep learning based on its behavior, define the major security goals of privacy-preserving deep learning for machine learning as a service, discuss the possible attacks on privacy-preserving deep learning for machine learning as a service, and provide detailed explanations about the protection against the attacks.
Incostituzionalità prospettata e causa di giustificazione dell’aiuto al suicidio: novità nella continuità

SOMMARIO: 1. Premessa - 2. La procedura costituzionale - 3. Il diritto penale - 4. I principi: a) la dignita … - 5. (segue) b) la coscienza … - 6. (segue) c) la separazione (ovvero la laicita).Presented uncostitutionality and justifiable assisted suicide: innovations in continuityABSTRACT: For the first time the Italian Constitutional Court adopted a double ruling (anticipatory the one, deciding the other) in the same judicial review. And for the first time also elaborated the circumstances of a justifiable (doctor-) assisted suicide, that so far was in any case a crime. They are two outstanding jurisprudential innovations, however the aim of the Author is to demonstrate that they are not in break but in continuity with the decision techniques of the Court, on one hand, and the leading cases on the topic of criminal justifications, on the other hand. Particularly the concept of subjective dignity, that according to the Court is the reason behind the decision of the patient, is recurring in the precedents of the Court of Cassation. Generally, moreover, the concepts of conscience, life and death prevail on this matter, neverthless are differently interpreted according to an ethic, specially religious, perspective or a secular, specially state, perspective. The merit of the decision consists precisely of the separatist, secular planning between ethics and law.
Session 1A | Introduction to Fedora 6.0

TCDL 2021 Session 1A, Monday, 5/24/2021, 10:00 am to 11:50 am | Speakers: David Wilcox, Program Leader, LYRASIS | Moderated by Linsey Ford, Interim Scholarly Communications Librarian, University of Houston - Clear Lake | View the recording at https://youtu.be/mW96uqInjQw
SISTEM PENENTUAN KATEGORI PERKARA PADA SUB BIDANG KOMPUTER FORENSIK PUSLABFOR BARESKRIM POLRI MENGGUNAKAN METODE LAPLACE SMOOTHING NAÏVE BAYES

System based of category determination is one part of work intended to complete work processes more efficiently. at the forensic computer subsection of puslabfor bareskrim polri were still using the konventional way to determine the case and causing much of the case file can be scattered. in other case the way to processing the case data were still doing by pile up the hardcopy of inspection data, and in other way they used the flashdisk or hardisk to save the case file where can cause lost of file and input failure because of human error. Along with current technological developments, the authors do the design and manufacture of web-based systems in determining the case categories which this system will facilitate employees in the process of determining the categories when inputting data quickly and accurately. The purpose of this study is to produce an information system for determining the category of web-based cases. The method used in making this application is the Laplace Smoothing Naive Bayes method which classifies each input. The Laplace Smoothing Naive Bayes method can yield 90% of the accuracy value in the case category grading system. The conclusion obtained is a system that facilitates the police in determining categories based on online cases.
DeepMistake: Which Senses are Hard to Distinguish for a Word­in­Context Model

In this paper, we describe our solution of the Lexical Semantic Change Detection (LSCD) problem.It is based on a WordinContext (WiC) model detecting whether two occurrences of a particular word carry the same meaning.We propose and compare several WiC architectures and training schemes, and also different ways to convert WiC predictions into final word scores estimating the degree of semantic change.We participated in the RuShiftEval LSCD competition for the Russian language, where our model achieved 2nd best result during the competition.During postevaluation experiments we improved the WiC model and man aged to outperform the best system.An important part of this paper is detailed error analysis where we study the discrepancies between WiC predictions and human annotations and their effect on the LSCD results.
University Decission Support System for Promotion Strategy Using Topsis Method

Campus or college is a place of education for people to seek knowledge. One of the essential components of campus sustainability is the existence of students. For this reason, each campus must have the right strategy in carrying out promotions, especially during the Covid-19 Pandemic as it is today. Because in a pandemic like this, many people are inevitably aware of the economy and health. So, the campus must have a strategy where the community continues to respond to the campus's promotions. Among the several promotional strategies to be right on target in this pandemic are conducting webinars, television broadcasts, radio broadcasts, advertisements on social media, placing banners, distributing pamphlets, and distributing campus marches. In carrying out promotions, wherever possible, keep prioritizing health by reducing the risk of covid-19 transmission. The promotion strategy in this pandemic must also pay attention to several factors for its implementation including available costs, human resources involved, the location of the activity implementation, the number of activities, and the risks associated with covid-19. From several promotional strategies and factors that support the smooth running of activities, a decision support system can be made that can help determine the campus promotion strategy. Decision Support Systems made using the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method approach.Furthermore, the developing of decision support systems using the waterfall system development method. Based on the results and discussion of this study, it concluded that the TOPSIS method could be used to determine campus promotion strategies during the Covid-19 pandemic by building a decision support system. The results of determining the promotion strategy with a decision support system obtained  the greatest value lies in V4, which means that the strategy for using social media is the most suitable for campus promotion during the Covid-19 pandemic.
Pedestrian detection based on multi-layer feature fusion

This paper proposes a goal detection network of end-to-end multi-scale feature fusion because of the tiny pedestrian target and blocking in pedestrian detection.This algorithm is based on the YOLOv3 network, fully integrates multi-scale features, enhances the expression ability of small target features, improves the robustness of pedestrian detection in complex environments, and improves pedestrian detection accuracy based on guaranteeing real-time detection.In the experiment, the current mainstream pedestrian detection algorithm is compared.This algorithm effectively improves the detection accuracy in INRIA and KITTI data sets, and the average accuracy of Yolov3 in two different data sets is improved by 6% and 24.7%, respectively.
Research Library's Role and Place in the Educational Environment of Pedagogical University

The paper provides some results of the library reader survey which allowed establishing the new role and place of the research library of a pedagogical university. The creative role of the research library determines the possible options of interaction between the library and scientific and educational departments of the pedagogical university. In the educational environment, the library becomes a “third place” between home and classroom.
Hybrid metaphotonics for fast and efficient collection of photons from quantum emitters

We propose a hybrid nanophotonic device which enables faster emission and efficient collection of photons from quantum emitters in hexagonal Boron Nitride. Our proposal offers a modular platform for on chip quantum photonics and sensing applications.
Data-Driven Learning of Feedforward Neural Networks with Different Activation Functions

This work contributes to the development of a new data-driven method (D-DM) of feedforward neural networks (FNNs) learning. This method was proposed recently as a way of improving randomized learning of FNNs by adjusting the network parameters to the target function fluctuations. The method employs logistic sigmoid activation functions for hidden nodes. In this study, we introduce other activation functions, such as bipolar sigmoid, sine function, saturating linear functions, reLU, and softplus. We derive formulas for their parameters, i.e. weights and biases. In the simulation study, we evaluate the performance of FNN data-driven learning with different activation functions. The results indicate that the sigmoid activation functions perform much better than others in the approximation of complex, fluctuated target functions.
LibGuides: Intro to Database Research for Elementary Students: Search Techniques

An overview of digital search techniques and an introduction to pertinent databases for upper elementary students
Feasibility study of "Invariant Information Clustering for Unsupervised Image Segmentation"

In this paper we analyze the performance of a novel clustering objective that optimizes a neural network to predict segmentation. We challenge the reported results by replicating the original experiments and conducting additional tests to gain an insight into the algorithm. We analyzed the efficiency of the clustering objective on a different architecture, dataset and hyper-parameters. To our surprise the algorithm demonstrated considerably lower results when running on the new setup. Further, in our work we detail the reasons behind the discrepancy and provide configurations under which the method performs best. We show that the objective is highly sensitive to the type of images it is predicting and the complexity of the architecture that is being used with.
Research & Subject Guides: Agriculture & Natural Resources: OER Textbooks and Resources: OER Collections and Repositories

This Open Education Resource (OER) guide provides access to interdisciplinary textbooks, instructional materials and learning resources for faculty and students
Two Variants of Noncontingency Operator

By slightly adapting two equivalent semantics of noncontingency operator, we obtain two variants, ⊡ and ⊞, with nonequivalent semantics. We show that on the class of models satisfying any of five basic properties (i.e., seriality, reflexivity, transitivity, symmetry, Euclideanness), the logic L(⊡), which has ⊡ as the sole modal primitive, is less expressive than the logic L(⊞), which has ⊞ as the sole modal primitive. We investigate the frame definability of both languages. We then axiomatize L(⊞) and L(⊡) over various classes of bimodal frames. Among other results, a notion of morphisms, called ⊞-morphisms, are provided to show the completeness of axiomatizations of L(⊡) over serial frames and also over symmetric frames.
Using Navies Bayes Algorithm InSentimental Analysis To Improve Business Intelligence

A study of sentimental analysis is opinion mining, feeling, emotions, sentiments mining and sentiments extraction has increased its acceptance some year ago. Now a Days Online survey reviews have become very essential criteria for checking the status of a company. Now In, This research paper we represent a sentimental analysis method to company reviews organization through extensive reviews datasets which are given by Yelp, Yelp Challenging datasets. In the search paper, we represent many techniques for automatic sentimental analysis classification, by using two methods for extraction methods and by using four techniques in machine learning models. It reflects the similar research on the influence of the ensemble techniques for reviewing the sentimental analysis classification.
CoBERL: Contrastive BERT for Reinforcement Learning.

Many reinforcement learning (RL) agents require a large amount of experience to solve tasks. We propose Contrastive BERT for RL (CoBERL), an agent that combines a new contrastive loss and a hybrid LSTM-transformer architecture to tackle the challenge of improving data efficiency. CoBERL enables efficient, robust learning from pixels across a wide range of domains. We use bidirectional masked prediction in combination with a generalization of recent contrastive methods to learn better representations for transformers in RL, without the need of hand engineered data augmentations. We find that CoBERL consistently improves performance across the full Atari suite, a set of control tasks and a challenging 3D environment.