Reviewerly/exHarmony huggingface dataset:
Lower Bounds on Circuit Depth of the Quantum Approximate Optimization Algorithm

The quantum approximate optimization algorithm (QAOA) is a method of approximately solving combinatorial optimization problems. While QAOA is developed to solve a broad class of combinatorial optimization problems, it is not clear which classes of problems are best suited for it. One factor in demonstrating quantum advantage is the relationship between a problem instance and the circuit depth required to implement the QAOA method. As errors in NISQ devices increases exponentially with circuit depth, identifying lower bounds on circuit depth can provide insights into when quantum advantage could be feasible. Here, we identify how the structure of problem instances can be used to identify lower bounds for circuit depth for each iteration of QAOA and examine the relationship between problem structure and the circuit depth for a variety of combinatorial optimization problems including MaxCut and MaxIndSet. Specifically, we show how to derive a graph, $G$, that describes a general combinatorial optimization problem and show that the depth of circuit is at least the chromatic index of $G$. By looking at the scaling of circuit depth, we argue that MaxCut, MaxIndSet, and some instances of Vertex Covering and Boolean satisifiability problems are suitable for QAOA approaches while Knapsack and Traveling Sales Person problems are not.
Research Guides: Creative Commons Licenses: Why Creative Commons Licensing?

This guide provides information on licensing your materials using Creative Commons Licenses and using items that are so licensed.
Fractal, chaos and neural networks in path generation of mobile robot

This paper is an attempt to solve problems involved in the path planning for the mobile robot with obstacle avoidance. Therefore, we propose three approaches for control using a fractal process system, neural networks and a combination between the chaos and the fractal process. Firstly, we present the fractal process system and its impact on the trajectory of robot. Secondly, a new variable structure model of neurons is utilised to control the robot trajectory in the presence of obstacles with different positions. Thirdly, we design as well a controller by combining the chaotic system and the fractal process inspired from the Julia set. Thus, we give several examples of trajectory control for the mobile robot for such an approach with simulation.
A CASE-STUDY ON WECHAT-BASED COLLEGE ENGLISH WRITING AND ITS RELATIONSHIP TO MOTIVATIONAL ORIENTATION FOR COLLEGE ENGLISH LEARNERS

WeChat, characterized by interactivity and real-time communication, is one of the most prevalentsocial networking applications in Mainland China. Previous studies have rarely emphasized the impact ofWeChat-based English writing. Is the WeChat platform effective in improvingcollege English writingperformances? Is its impact related to motivational orientation? This small scale study aims to form someunderstandings upon the effectiveness of WeChat-based college English writing and look into its link to learningmotivation among undergraduates in Mainland China. Both quantitative and qualitative methodology wereemployed. The participants were 10 sophomore students preparing for CET4 (College English Test Band-4) inMainland China.They were administered a questionnaire to investigate their learning motivation before and afterthe three-week WeChat-based English writing class. Each week they had a weekly writing test and all theassignments were reviewed and analyzed on WeChat. Before and after the three-week course, their Englishwriting performance was evaluated and they were interviewed. The results indicate that 1) ideal L2 self motivatedand amotivated learners benefit most from WeChat-based English writing, 2) Motivational orientation can‟t beaffected by WeChat-based English writing but can influence writing performances, 3) WeChat-based Englishwriting in this study is effective in improving writing performance concerning text and substance, and 4) collegeEnglish learners indicates positive attitude towards improving English writing on WeChat.
LibGuides: ENG101 Library Research Strategy: #Refining: E-Journals

ENG101 Library Research Strategy Find links to all the library online journal articles, ebooks, ereference, and video information.
SISTEM PENDUKUNG KEPUTUSAN PENERIMA BANTUAN PROGRAM KELUARGA HARAPAN (PKH) MENGGUNAKAN METODE TECHNIQUE FOR ORDER OF PREFERENCE BY SIMILARITY TO IDEAL SOLUTION (TOPSIS)

The poverty that hit Indonesian people became a problem faced by the government, so to overcome poverty since 2007 the Government of Indonesia has implemented the Program Keluarga Harapan (PKH). This Social Protection Program has proven to be quite successful in reducing poverty in Indonesia. In choosing residents in PKH recipients, problems often occur because the data used by PKH from BPS are not up to date, where the data used to determine the PKH recipients in 2019 used data in 2014 which caused new poor families not to receive the Program Keluarga Harapan (PKH). The problem that often occurs is that manual selection requires a lot of time and the selection of participants can be influenced by the objective assessment of PKH companions, the criteria of citizens surveyed are not in accordance with government regulations, and the government determines the number of PKH recipient quotas, so that there are still communities did not accept PKH. To deal with the problem a decision support system is needed to help the Village Government determine PKH recipient residents, one of the decision support system methods is the TOPSIS method. The system is built based on Desktop Applications which can improve data quality and effectiveness of PKH participant selection so that PKH assistance can be received right on target
Pearl Fernandez: anti-kvinnan: En studie om konstruktioner av den kvinnliga mördarens femininitet, moderskap och aktörskap

The aim of this study has been to examine and deconstruct the normative understandings of femininity, womens agency, and motherhood that characterize stories of women who murder - especially women who murder alongside men. With the guidance of Laclau and Mouffes discoursetheory this study has analyzed the construction of murderer Pearl Fernandez in the 2020 Netflix documentary The Trials of Gabriel Fernandez. The research has revealed that the hegemonic discursive understanding of the murdering woman is that she is unfeminine and unmotherly. Furthermore, the deconstruction of this dominant discourse has shown that the main understanding of femininity is that it entails being passive, chaste, and motherly. In the discourse, the murdering woman's perceived lack of conformity to these norms of femininity is crucial in constructing her as guilty. This study has also shown that in addition to this hegemonic discourse, there is a counter-discourse present in which the murdering woman is constructed as being passive. In this counter-discourse the murdering woman’s perceived lack of agency constructs her as more acceptable in regards to norms of femininity and heterosexuality. The understanding of the murdering woman's femininity, especially in regards to her agency, is therefore twofold and the research has shown that there is ongoing conflict between the discourses. (Less)
COGNITIVE COMPUTING IN BIG DATA MANAGEMENT

Appears in: EDULEARN20 Proceedings Publication year: 2020Pages: 100-102ISBN: 978-84-09-17979-4ISSN: 2340-1117doi: 10.21125/edulearn.2020.0059Conference name: 12th International Conference on Education and New Learning TechnologiesDates: 6-7 July, 2020Location: Online Conference
From totems to web labels. Anthropology and ethnography as tools for studying information architecture

The main aim of article is depict of anthropological theories and tools, that might be useful for information architecture researchers. AI will be treated as a mental structure representation and compared to the other material structures and systems. Examples from fieldworks and author’s practice display anthropological theories. To sum up, practice of participant design will be presented.
Logistic Regression on Hadoop Using PySpark

Training a Machine Learning (ML) model on bigger datasets is a difficult task to accomplish, especially when a high-end configuration is not accessible. A relatively good configuration may also not always produce quick outcomes and depending on the dataset size, the time taken would be anything between seconds to several hours. More often, the tasks we are interested in involve big datasets and complex models. The purpose of our work was to see how effective Hadoop can be in terms of increasing the efficiency of working with Machine Learning for a given problem. Out of many models to choose from, Logistic Regression was chosen, which is relatively simpler to implement. Three Logistic Regression models were implemented and trained on MNIST Handwritten Digits dataset. First one was implemented in Python using NumPy without any ML libraries. The second implementation used LogisticRegression class that comes with the Scikit-learn Python package, and the third implementation was done using PySpark MLlib. Towards the end of the paper, we present the observations and results obtained from the execution of each.
An Improved ANN Model for Prediction of Solar Radiation Using Machine Learning Approach

An accurate forecast of weather is essential for obtaining energy from Renewable sources. The objective of this paper is to present an analysis of weather parameters and comparison among different models of the weather prediction from accessible parameters and finally deriving a new technique for solar prediction in support of photovoltaic output power. Artificial Neural Network model with 5 weather parameters from NASA POWER dataset have been utilized to predict the day-ahead solar radiation and evaluated against real data measured for 4 years at Agartala, India (Latitude 23.83° N and Longitude 91.282° E). Results detailed in this work confirm the best predicting potential of the proposed method. The proposed model has been shown to predict solar radiation with accuracy of 83% shows the robustness of the system.
Harnessing new sources of economic strength to achieving sustainable development goals in Nigeria

There were many failures recorded in the execution of the Millennium Development Goals which elapsed in 2015; a major cause of this was the limited resources in financing the programmes. The Sustainable Development Goals have been rolled out with higher number of goals as well as targets which elapses in 2030. The Nigerian economy is just recovering from recession and is currently faced with high debt profile coupled with oil price fluctuations. Thus, to finance the sustainable development goals, Nigeria must look away from the current production capacity by harnessing other opportunities that awaits her. This study therefore uses exploratory style of investigation to analyse the other sources of economic strength in achieving the sustainable development goals in Nigeria. From the exploratory investigation, the study found that expansion and massive development in Agribusiness through improvement in the agricultural value chain remains a viable new source of economic strength; this is because it has the ability to reduce massive importation of such product thereby reducing the demand gap. More also, there will be rapid export of such products thereby increasing foreign earnings which further creates massive employment opportunities for the people. Additionally, massive investment in tourism and investment in solid minerals are viable sources of economic strength in achieving the sustainable development goals.
COMPARISON OF HIGHER EDUCATION IN QUANTUM COMPUTING ACROSS EUROPE WITH SPECIAL EMPHASIS ON THE CZECH REPUBLIC

Quantum technology is a growing and promising field of research and industry, and an area of interest for both private and public sector, as exemplified by the European Union’s Quantum Technology Flagship programme launched in 2018. Leaving aside the fact that the achievement of quantum supremacy (practical supremacy of quantum computers over classical computers) claimed in 2019 by Google is still disputed, quantum computing deserves attention of not only researchers but also educators.In this paper, we offer a review of the state of higher education in quantum computing (QC) across Europe with special emphasis on the Czech Republic, the country of the author’s residence. We argue for the inclusion of quantum computing courses in computer science curricula – as abstract quantum Turing machine is available since its proposal by Deutsch in 1985, QC can be taught and studied with little regard to physical implementation of quantum computers, as in the case of classical computing. We review necessary mathematical background for understanding basic quantum algorithms (such as Shor’s algorithm for integer factorization) and propose an outline of a course in QC for undergraduates with no special training in (quantum) physics.We also analyse current demand for graduates with basic knowledge of QC in the job market and try to predict the situation in near future.
A human evaluation of English-Irish statistical and neural machine translation

With official status in both Ireland and the EU, there is a need for high-quality English-Irish (EN-GA) machine translation (MT) systems which are suitable for use in a professional translation environment. While we have seen recent research on improving both statistical MT and neural MT for the EN-GA pair, the results of such systems have always been reported using automatic evaluation metrics. This paper provides the first human evaluation study of EN-GA MT using professional translators and in-domain (public administration) data for a more accurate depiction of the translation quality available via MT.
DEVELOPMENT EDUCATION PROJECT IN UKRAINE TO IMPROVE THE QUALITY OF MEDIA LITERACY: A CASE OF MEDIASCHOOL GRINCHENKO UNIVERSITY

DEVELOPMENT EDUCATION PROJECT IN UKRAINE TO IMPROVE THE QUALITY OF MEDIA LITERACY: A CASE OF MEDIASCHOOL GRINCHENKO UNIVERSITY
Online Teaching Practice and Reflection Based on the Perspective of Learners

Adverse effects of COVID-19, in order to protect the health of the teachers and students, the offline teaching method in the education industry has been transformed into online teaching. To some extent, educators and learners have been forced to adapt to the innovation of educational concepts in the era of“Internet plus”, and adapt the teaching skills and learning methods to a certain extent. As an educator, we need to observe and experience carefully. Through the experience of personal practice, we need to clarify the perspective of learners as the main body, discuss the concept definition and development process of online teaching. On this basis, we need to deeply analyze the advantages and disadvantages of traditional teaching methods and online teaching, and then from the perspective of teachers, teaching platforms and learners, we propose to improve and enhance online teaching. Finally, it points out that the hybrid teaching, which is the integration of traditional teaching methods and online teaching, will become an important trend of school teaching reform in the future.
THE ROLE OF MIXED REALITY IN THE EDUCATION AND PROMOTION OF CULTURAL AND HISTORICAL HERITAGE

Appears in: EDULEARN20 Proceedings Publication year: 2020Pages: 726-732ISBN: 978-84-09-17979-4ISSN: 2340-1117doi: 10.21125/edulearn.2020.0272Conference name: 12th International Conference on Education and New Learning TechnologiesDates: 6-7 July, 2020Location: Online Conference
Hybrid Translation and Language Model for Micro Learning Material Recommendation

As an emerging pedagogy, micro learning aims to make use of people's fragmented spare time and provide personalized online learning service, for example, by pushing fragmented knowledge to specific learners. In the context of big data, the recommender system is the key factor for realizing the online personalization service, which significantly determines what information will be fmally accessed by the target learners. In the education discipline, due to the pedagogical requirements and the domain characteristics, ranking recommended learning materials is essential for maintaining the outcome of the massive learning scenario. However, many widely used recommendation strategies in other domains showed defectiveness in the ability to rank the recommended results. In this paper, we propose a novel recommendation strategy based on the combination of the language model and the translation model. The proposed recommendation strategy aims to filter out unsuitable learning materials and ranks the recommended learning materials more effectively.
Fair Exchange Protocol in Electronic Transactions Revisited

At the present time, electronic transactions are developing rapidly and widely. It is a kind of information technology that it has been increasingly popular. People can make electronic transactions from home, at anytime from anywhere. This is to conserve time in travel costs and to assist convenience its use. In electronic transactions, how to make ensure all parties that any party gains any advantage over the other party. Fair exchange is the solution to resolve this the issue. This paper proposes a brief review the field of fair exchange protocols for electronic transactions currently. The study research presents a survey of existing fair exchange protocol. The content in this review of fair exchange protocol consists of the application of fair exchange protocol, types of trusted third party (TTP) for fair exchange protocol, types of the use of TTP for fair exchange protocol. And finally, this paper illustrated that these method types are compared with existing fair exchange protocol and challenge in developing a fair exchange protocol. The conclusion shown that the best sub-type is offline TTP which is not involved in the exchange phase, also it is low load TTP, high efficiency, decreased source of failure and attack.
EdTech in the Wild

Very little of the rich and vibrant history of ed tech is contained in scholarly journals, and what you find there is typically stodgy and manicured: not what you find in classrooms, tech departments, or conversations between professionals. Though peer review and the traditional publishing process are useful for some things, such as ensuring accuracy and uniformity, they are notoriously detrimental to the sharing of novel ideas and practices that shake the status quo.For that reason, one of the best places to find artifacts of the rich history of educational technology is in self-published blog posts where practitioners, scholars, and anyone else can grapple with the issues that really matter to them, share their crazy ideas, and get feedback from the community without going through a rigid process to determine whether their voices actually matter. These are the hidden historical artifacts of educational technology.In this volume, we want to bring these blog posts together for future reading and dialogue. Blogs don't live forever, but their ideas can as we archive them and share them in helpful ways.
Privacy-preserving release of mobility data: a clean-slate approach.

The quantity of mobility data is overwhelming nowadays providing tremendous potential for various value-added services. While the benefits of these mobility datasets are apparent, they also provide significant threat to location privacy. Although a multitude of anonymization schemes have been proposed to release location data, they all suffer from the inherent sparseness and high-dimensionality of location trajectories which render most techniques inapplicable in practice. In this paper, we revisit the problem of releasing location trajectories with strong privacy guarantees. We propose a general approach to synthesize location trajectories meanwhile providing differential privacy. We model the generator distribution of the dataset by first constructing a model to generate the source and destination location of trajectories along with time information, and then compute all transition probabilities between close locations given the destination of the synthetic trajectory. Finally, an optimization algorithm is used to find the most probable trajectory between the given source and destination at a given time using the computed transition probabilities. We exploit several inherent properties of location data to boost the performance of our model, and demonstrate its usability on a public location dataset. We also develop a novel composite of generative neural network to synthesize location trajectories which might be of independent interest.
BUILDING THE CAPACITY OF STUDENTS OF BUSINESS EDUCATION (ACCOUNTING) WITH ACCOUNTING SOFTWARE SKILLS FOR IMPROVED SERVICE DELIVERY IN MODERN OFFICE AND SCHOOL ENVIRONMENTS

Building the capacity of students of business education (accounting) demands that lecturers should possess relevant technological competencies including accounting software skills. The study assessed how students' capacities can be built with accounting software skills for improved service delivery in modern office and school environments. One research question guided the study and two hypotheses were tested at 0.05 level of significance. Descriptive survey design was adopted. A sample of 293 was selected through proportionate stratified random sampling technique from a population of 489. The main instrument for data collection was a four point rating scale questionnaire with 20 items. The data collected were analysed using mean and standard deviation to answer the research question and determine the homogeneity or otherwise of the respondents while the t-test and ANOVA were used to test the hypotheses. Findings showed that business educators and employers of labour agreed that accounting software skills were needed to build the capacities of business education (accounting) students. There was no significant difference in the mean ratings of business educators and employers of labour and in the mean ratings of male and female business educators and employers of labour in Delta State on the accounting software skills needed to build capacities of business education (accounting)students. Keywords : Capacity, competencies, accounting software skills, service delivery
Addressing the Cold-Start Problem in Outfit Recommendation Using Visual Preference Modelling

With the global transformation of the fashion industry and a rise in the demand for fashion items worldwide, the need for an effectual fashion recommendation has never been more. Despite various cutting-edge solutions proposed in the past for personalising fashion recommendation, the technology is still limited by its poor performance on new entities, i.e. the cold-start problem. In this paper, we attempt to address the cold-start problem for new users, by leveraging a novel visual preference modelling approach on a small set of input images. We demonstrate the use of our approach with feature-weighted clustering to personalise occasion-oriented outfit recommendation. Quantitatively, our results show that the proposed visual preference modelling approach outperforms state of the art in terms of clothing attribute prediction. Qualitatively, through a pilot study, we demonstrate the efficacy of our system to provide diverse and personalised recommendations in cold-start scenarios.
Creativity As A Resource Of A Teacher's Personality

This article presents the views of the development of personal creativity, as a balance between individual creativity to create new and preserve the standards of the past, which is one of the main tasks of education. The formation of a new type of cultural and educational ideal in this context determines the need to update the content, forms and methods of professional education of the future teacher, focused on the formation of creativity and professional competence.