Reviewerly/exHarmony huggingface dataset:
Immaterialrättsliga skyddsmöjligheter för objekt med teknisk funktion

This thesis examines the possibility of obtaining intellectual property protection for objects with a technical function, beyond the patent rights. The patent is commonly associated with technical function due to its subject and qualification requirements. The trademark law has a strict approach in terms of including technical function in the scope of protection. Through an absolute ground of refusal, the trademark law prohibits signs that are necessary to obtain a technical result. The exclusion is motivated by the functions of a trademark as well as efforts to prevent monopoly as a trademark registration is not limited to a certain term of years. A similar exclusion for technical function is found within design law. It is not applied with the same strict approach, although new case law from the EU shows a stricter interpretation to prevent market monopoly and unfair competition. Patent specifications are often used as supporting evidence for infringement claims to prove technical function, within both trademark and design disputes. The Swedish copyright law does not include a substantive exclusion ground for technical function within works. Instead the copyright protection for a functional object is determined after an assessment of autonomous concepts of EU law, constituting the originality standard and the notion of work. Recent case law from EU may affect the assessment of functional works, as it states that no specific aesthetic values should be required for copyright protection. (Less)
Interpretability of a Deep Learning Model for Semantic Segmentation : Example of Remote Sensing Application

Understanding a black-box model is a major problem in domains that relies on model predictions in critical tasks. If solved, can help to evaluate the trustworthiness of a model. This thesis propose ...
Evaluating Vector Representations from User's Reviews in a Recommendation Task

The recommendation task is a prominent and challenging area of study in Machine Learning. It aims to recommend items such as products, movies, and services to users according to what they have liked in the past. In general, most of the recommendation systems only consider structured information. For instance, in recommending movies to users they might use features such as genre, actors, and directors. However, unstructured data such as users' reviews may also be considered, since they can aggregate important information to the recommendation process, improving the performance of recommendation systems. Thus, in this work, we evaluate the use of text mining methods to extract and represent relevant information about user reviews, which were used alongside with rating data, as input of a content-based recommendation algorithm. We considered three different strategies for this purpose, which were: Topics, Embeddings and Relevant Embeddings. We hypothesized that using the considered strategies, it is possible to create more meaningful and concise representations than the traditional bag-of-words model, and yet, increase the performance of recommendation systems. In our experimental evaluation, we confirmed such a hypothesis, showing that the considered representations strategies are indeed very promising for representing user reviews in the recommendation process.
Colour key-point detection

A lot of image processing tasks require key-point detection. If grey-level approach are numerous, colour and hyper-spectral ones are scarce. In this paper, we propose a generic key-point detection for colour, multi and hyper-spectral images. A new synthetic database is created to compare key-point detection approaches. Our method improves detection when the image complexity increases.
A Study on the Development of the Education Program for the Training of Talents Customized to the Fourth Industrial Revolution by the Application of ICT to Hotel Enterprises

This study aims to establish the purpose and direction of ICT-related education programs in preparation for the demand of manpower in the job of each part according to the application of ICT in the hotel industry, and to suggest future job utilization plans by suggesting a program verified through the FGI (Focus Group Interview). Specifically, this study will verify the appropriateness of job and technology level that needs ICT introduction in the hotel industry and establish the utilization system to provide the necessary policy support and help reduce mismatch of future hotel industry manpower. As a result of the demand survey and FGI in this study, it was shown that the technology and capability that hotel companies need first was the understanding of S/W related to big data and the utilization of database. Also, as innovative service of hotel company is expanding into the IoT, education and training are needed. Lastly, the educational program(plan) in this study is only basic education and training for the fourth revolution, but in the field, it is necessary to develop the deepening process that can be selectively used according to position, occupation, department and can train ICT experts in personnel, technology, and computer field.
Elections as vehicles for change? Explaining different outcomes of democratic performance and government alternation in Africa

Does having more regular elections improve democratic performance in Africa? And have elections transformed the patterns of alternation in government? To answer these questions, two analyses are conducted drawing on an original dataset of 179 elections in 27 African countries, from the founding multiparty elections until 2019. The first tests the effects of alternation in government on democratic performance and shows that while alternation in government in the founding elections improves democratic performance, opposition victories in subsequent elections do not produce democratic gains. The second examines why alternation in government is more frequent in certain countries than in others; and reveals that the odds of turnover are increased by alternation in government in the founding elections, the level of political competition and the quality of elections. These findings contribute to literature linking elections, democracy and turnover in Africa.
Vicissitudini lessicografiche di <i>cocoggio</i> e di <i>acudia</i>

Abstract The word cocuyo ‘luminous insect originating from central America’ appears in Italian texts of the last few centuries in a variety of forms. In the article, we analyse the historic events that allowed the creation and spread of the ghost-word acudia (from the original word cocuyo ) and how this is present in various Italian dictionaries.
LibGuides at Priddy Library: ECED 360: Early Literacy: Home

Emerging literacy process in children, birth to age five. Examination of strategies, materials, and experiences for literacy development
A Survey of Generative Adversarial Networks Based on Encoder-Decoder Model

The generative model is a very important type of model in the field of artificial intelligence in recent years.Such models can comprehend the data through the neural network, and then create data according to the probability distribution of the input data, predict the results according to the data characteristics.The whole processing process is "intelligent".At present, two typical applications of generative model are Generative Adversarial Networks (GAN) model and Encoder-Decoder model, which have strong ability to generate image data.In the model of GAN, the generator simulates real data, and the discriminator judges the authenticity of the samples.Its goal is to train a generator to fit the real data perfectly, so that the discriminator cannot distinguish.In the Encoding-Decoding model, it can be understood as a process of "Encoding→intermediate vector→Decoding", It is suitable for processing one kind of data to generate another kind of data with the same probability distribution as the original data.Since most of the data features are intermingled, they are encoded in a complex and disorderly way.But if these features are extractable, it shows that these features are interpretable, and it will be easier to use these features for coding.Based on this situation, some research results have been produced by incorporating the Encoder-Decoder into GAN.This paper systematically analyzes and summarizes the basic concepts and theories of GAN and Encoder-Decoder, as well as their respective advantages and disadvantages.On this basis, by combing the related work of the two types of models, the main technical routes of the three types of GAN based on the Encoder Decoder are summarized, the techniques and theories including variational inference, energy function and correlation transformation of different distribution data are summarized.Finally, the GAN based on the Encoder-Decoder is summarized.
Mobile Device Gaze Estimation with Deep Learning : Using Siamese Neural Networks

Gaze tracking has already shown to be a popular technology for desktop devices. When it comes to gaze tracking for mobile devices, however, there is still a lot of progress to be made. There’s stil ...
Facial Expression Recognition using Discrete Cosine Transform & Artificial Neural Network

Every so often Humans utilize non-verbal gestures (e.g. facial expressions) to express certain information or emotions. Moreover, countless face gestures are expressed throughout the day because of the capabilities possessed by humans. However, the channels of these expression/emotions can be through activities, postures, behaviors & facial expressions. Extensive research unveiled that there exists a strong relationship between the channels and emotions which has to be further investigated. An Automatic Facial Expression Recognition (AFER) framework has been proposed in this work that can predict or anticipate seven universal expressions. In order to evaluate the proposed approach, Frontal face Image Database also named as Japanese Female Facial Expression (JAFFE) is opted as input. This database is further processed with a frequency domain technique known as Discrete Cosine transform (DCT) and then classified using Artificial Neural Networks (ANN). So as to check the robustness of this novel strategy, the random trial of K-fold cross validation, leave one out and person independent methods is repeated many times to provide an overview of recognition rates. The experimental results demonstrate a promising performance of this application.
Analysis of The Use of Lecture Facilities in The Department of Mechanical Engineering Education Welcoming the Opening of New Study Program

This research aims to: 1) provide information for policy making related to strategies for meeting the needs of lecture spaces for opening new study programs, 2) making a map of space requirements based on KKN for each study program at the Faculty of Engineering. The research design is a type of ex p
Αυτόνομο ρομποτικό όχημα με χρήση μηχανικής μάθησης και μηχανικής όρασης

In recent years, developments in Artificial Intelligence and Robotics have been rapid and enormous. Nowadays, autonomous vehicles are found on the roads and autonomous robotic vehicles used not only to explore the seabed, but also to explore space. At the same time, robots for home cleaning and cell phones that use Artificial Intelligence to recognize faces and take better photos are available in the market. In this thesis presents the design and implementation of an autonomous robotic vehicle, which navigates its environment to detect and approach a specific object using Machine Learning and Machine Vision. The autonomous robotic vehicle through its Time-of-Flight distance sensor learns to move around its environment using Q-Learning algorithm of Reinforcement Learning. To detect the object it has camera and uses ORB algorithm, FLANN method and Homography. The work of autonomous robotic vehicle was accomplished after multiple experiments which are presented in detail.
An Error Analysis in Translating Indonesian into English at the Eleventh Grade Students at MAN 1 Medan.

ABSTRACTThe purpose of this research to find out (1) the types of error in Indonesian to English translation text made by the students of MAN 1 Medan, (2) the process of making errors by the students, and (3) the reason of errors occurs on students' translation from Indonesian into English. This research is qualitative research. The subject of this research is the second year students of MAN 1 Medan. The students consist of 22 students in XI MIA 6 class. The result of this research, the writer found that the students make error in Indonesian to English translation text, the writer find out the kinds of error and the causes of error that made by students in translating a text Indonesian into English. The kinds of error are verb error, pronoun error, possessive adjective error, article error, conjunction error, omission, addition, misordering, lexical error, capitalization, punctuation and spelling error. The causes of error that make students produce errors in translating Indonesian into English are interlingual transfer, intralingual transfer, lack of motivation, developmental error, and interference error.
LibGuides Home: COVID-19: Home

Information about Connecticut library responses to the coronavirus, as well as links to other COVID-19 sites for libraries and Connecticut. Start here!
LibGuides: Getting Started at University: Glossary

If you're new to university or returning to study after a break, this guide includes our top tips and guidance on finding your feet and information on how to develop your core academic skills.
Bayesian Methods in Interaction Design (Tutorial)

This tutorial introduces Bayesian computational approaches to interaction and design. Bayesian methods offer a powerful approach for interactive settings with uncertainty and noise. This course introduces the theory and practice of computational Bayesian interaction, covering inference of user data and design/adaptation of interface features based around probabilistic inference. The tutorial is built around hands-on Python programming with modern computational tools, interleaved with theory and practical examples grounded in problems of wide interest in human-computer interaction.
Some Remarks on Gries’s Criticism on a Tree-based Approach of Multifactorial Data

A tree model that is typically used in data mining and machine learning has been recently adopted to analyze multifactorial data in corpus linguistics. However, Gries (2019) claims that tree-based approaches fail to deal with a data set in which not all input variables are necessary for predicting the target variable accurately. He demonstrates that a tree model reports a three-way interaction even when a two-way interaction can predict the target variable with 100% accuracy because there is another third significant input variable. In this article, I will argue that the result of a conditional inference tree applied to such a data set suggests that a researcher should analyze a two-way interaction effect. In other words, the result allows two different interpretations that are related to the structure of a data set and requires to test whether a two-way interaction is sufficient to explain the data. In doing so, I will show that the presence of the third input variable does not hinder the detection of a perfect two-way interaction that is displayed by a symmetric tree figure.
An Analytical Study on Gesture Recognition Technology

Over the years, mankind has adapted and evolved, opening up new horizons in terms technology. The intellect and inventiveness of human beings have led to the development of many tools, gesture recognition technology being one of them, to help extend the capabilities of our sense, combining natural gestures to operate technology and making the optimum use of our body gestures, decreasing human effort and going beyond human abilities. Devices these days usually have one type of sensor installed in them; however, this paper will be covering the effect of multiple sensors on recognition accuracy. Furthermore, this paper proposes a new tool for communication made by combining the British sign language with gesture-based technology, which can quickly translate sign language into text, with one mobile phone. Principles of generating EOG, methods of sampling EOG signals, basic eye modes, blinking and fixation modes.
LibGuides: Using the Library Remotely: Online Library Resources

This guide will help faculty and students navigate the library resources during full or partial campus closure events.
Privacy Pass: Architectural Framework

This document specifies the architectural framework for constructingsecure and anonymity-preserving instantiations of the Privacy Passprotocol. It provides recommendations on how the protocol ecosystemshould be constructed to ensure the privacy of clients, and thesecurity of all participating entities.
Comparing neighborhood and matrix factorization models in recommendation systems : Saving the user some clicks

This thesis explores how different recommendation models based on machine learning can be implemented using customer activity data from an internet portal. The recommendation models have been evalu ...
Improved density peaks clustering based on firefly algorithm

The cut-off distance of the density peaks clustering (DPC) algorithm need to be set manually; the two local densities of the algorithm have a large difference in the clustering effect on the same dataset. To address the issue, the paper proposes an improved DPC based on firefly algorithm. It combines the cut-off kernel and the Gaussian kernel defined by the DPC algorithm, and balances the effects of the two kernels by the weighting factor. Meanwhile, a cluster-like centre evaluation criterion based on local density and relative distance of preference coefficient is constructed. In order to determine the parameters of the cut-off distance, weighting factor and preference coefficient, the three parameters are optimised by the firefly algorithm with the Rand index as the objective function. The experiment results show that the performance of the proposed method on synthetic datasets and real datasets is better than DPC and its variants.
Free Tech Tools for the Library: Green Screen, QR Codes, and Screencasting

Presentation slides for Free Tech Tools for the Library: Green Screen, QR Codes, and Screencasting by Stephanie Cotnam. Presented at MegaResource 2020.
Towards Informed Exploration for Deep Reinforcement Learning

Author(s): Tang, Haoran | Advisor(s): Sethian, James A; Abbeel, Pieter | Abstract: In this thesis, we discuss various techniques for improving exploration for deep reinforcement learning. We begin with a brief review of reinforcement learning (RL) and the fundamental v.s. exploitation trade-off. Then we review how deep RL has improved upon classical and summarize six categories of the latest exploration methods for deep RL, in the order increasing usage of prior information. We then explore representative works in three categories discuss their strengths and weaknesses. The first category, represented by Soft Q-learning, uses regularization to encourage exploration. The second category, represented by count-based via hashing, maps states to hash codes for counting and assigns higher exploration to less-encountered states. The third category utilizes hierarchy and is represented by modular architecture for RL agents to play StarCraft II. Finally, we conclude that exploration by prior knowledge is a promising research direction and suggest topics of potentially impact.
Indeks Volume 17 Nomor 2, Februari 2020

Indeks Volume 17 Nomor 2, Februari 2020 It is a Complete Index for Volume 17 Number 2, February 2020 (Editorial use only)
Library Guides: How to Archive Tweets using TAGS: Start here.

A guide exploring the use of TAGS via a Google Sheet to capture recent Twitter data, and explore options for text analysis and visualizations.
MySQL Performance Tuning

This chapter introduces you to MySQL performance tuning by talking about the whole stack as well as the importance of monitoring and basing your actions on data. Since this book is mainly about working with queries, the lifecycle of a query is reviewed before concluding the chapter.
LibGuides: Online Library Resources and Services for Faculty: Reference, instruction & citation help available online

Resources created by the Canada Librarians for faculty to provide library instruction online.
Address students’ self‐perception of online invincibility when creating disciplinary code

Advances in technology and changes in risk‐taking behavior have created a sense of online invincibility for today's students who often struggle to differentiate their online actions from the physical world.
Multi-Directional Ternary Pattern for Facial Expression Recognition

Multi-Directional Ternary Pattern (M-DTP) is the face descriptor which reduces the noise and extracts the key expression related characteristics of the input face image to overcome the recent challenges encountered in unconstrained face recognition. In M-DTP, the derivative of the Gaussian operator is utilized to transform the gray scale facial image into the multi-directional gradient image that is vigorous to changes in the illumination. This pre-processing is introduced to minimize the challenges due to the variations in illumination and unconstrained face expression recognition. Further, by making use of directional information and ternary pattern the emotion-related features are extracted from the face. The proposed multi-level histogram features extracted from the ternary face code technique delivers the finer grain description of facial emotions to improve the facial expression performance under various illumination conditions. The features extracted using M-DTP are high-dimensional, therefore to reduce the dimensionality Principal Component Analysis (PCA) is used. The Support Vector Machine (SVM) classifier is utilized to perform and evaluate the classification performance using different datasets.
Scrum in Practice : Multiple case study on three different levels

Scrum is an agile framework which originates in the early 90’s by Ken Schwaber and Jeff Sutherland. They meant that Scrum can be implemented directly in any project and workflow. But as Scrum is im ...
CONDITIONAL IDENTITY BASED BROADCAST PROXY RE-ENCRYPTION OF DATA AND ITS APPLICATION TO CLOUD

Dispersed handling has gotten otherworldly because of its inclination of tremendous putting away and goliath enlisting limits. Guaranteeing an ensured information sharing is basic to cloud applications. Beginning late, extraordinary character based bestows delegate re-encryption plans have been proposed to choose the issue. In any case, the IB-BPRE requires a cloud client who needs to offer information to an assortment of clients to take an interest the get-together shared key reclamation process since Alice's private key is an essential for shared key age. This, regardless, doesn't use the advantage of dispersed figuring and causes the weight for cloud clients. Along these lines, a novel security thought named revocable character based give middle person re-encryption is appeared to address the issue of key renouncing in this work. In a RIB-BPRE conspire, a go-between can deny a lot of specialists, named by the delegator, from the re-encryption key. The presentation appraisal reveals that the proposed arrangement is capable and down to business.