Reviewerly/exHarmony huggingface dataset:
Neural Approaches to Relational Aspect-Based Sentiment Analysis. Exploring generalizations across words and languages

Everyday, vast amounts of unstructured, textual data are shared online in digital form.Websites such as forums, social media sites, review sites, blogs, and comment sections offer platforms to express and discuss opinions and experiences. Understanding the opinions in these resources is valuable for e.g. businesses to support market research and customer service but also individuals, who can benefit from the experiences and expertise of others. In this thesis, we approach the topic of opinion extraction and classification with neural network models. We regard this area of sentiment analysis as a relation extraction problem in which the sentiment of some opinion holder towards a certain aspect of a product, theme, or event needs to be extracted. In accordance with this framework, our main contributions are the following: 1. We propose a full system addressing all subtasks of relational sentiment analysis.2. We investigate how semantic web resources can be leveraged in a neural-network-based model for the extraction of opinion targets and the classification of sentiment labels. Specifically, we experiment with enhancing pretrained word embeddings using the lexical resource WordNet. Furthermore, we enrich a purely text-based model with SenticNet concepts and observe an improvement for sentiment classification.3. We examine how opinion targets can be automatically identified in noisy texts. Customer reviews, for instance, are prone to contain misspelled words and are difficult to process due to their domain-specific language. We integrate information about the character structure of a word into a sequence labeling system using character-level word embeddings and show their positive impact on the system's performance. We reveal encoded character patterns of the learned embeddings and give a nuanced view of the obtained performance differences.4. Opinion target extraction usually relies on supervised learning approaches. We address the lack of available annotated data for specific languages by proposing a zero-shot cross-lingual approach for the extraction of opinion target expressions. We leverage multilingual word embeddings that share a common vector space across various languages and incorporate these into a convolutional neural network architecture. Our experiments with 5 languages give promising results: We can successfully train a model on annotated data of a source language and perform accurate prediction on a target language without ever using any annotated samples in that target language.
Problem of Inner Competitiveness in the Process of Additional Educational Programs Introduction at the University

The system of additional professional education is one of the most topical problems in the strategic planning of the university. Currently, the questions of stimulating attraction to the population, financial state of the university, introduction of the system of long-life learning are connected with additional professional education. In the process of additional professional education programs the administration faces the competitiveness between the university’s offices due to the crossing of thematic fields of professional programs. To overcome the problems, the strategy of monopoly in the regulation of the system of additional education in the frame of the university functioning is offered. There is presented a suggestion to form a number of departments in the Center of additional professional education while realizing the given strategy including the following functions aimed at stimulating the teachers’ work and avoiding the similarities between the professional programs: department of additional professional education (is an owner of the programs); coordinating center (including expert analytical center, financial department); office of programs’ construction and promotion (including the department of programs’ “design”, marketing and advertisement department). When cooperating during the departments’ professional activities the following tasks can be solved: the right to initiate the program, to distribute finances, legislative support, methodological basis, search for clients, development and programs combining, development of requirements to the teachers’ competence, digital assistance with the Bot. The solution of the problems is a way to create the conditions to build the system of additional professional education at the university in the context of themes crossing in professional programs and it results in decreasing the competitiveness between the university’s department.
CampusGuides: BIOL 102 -- General Biology -- Gago / Kretzmann: Citing in MLA style

This guide supports students in BIOL 102 on their labs for Spring '21 regarding the chaparral ecosystem in Los Angeles County, and conservation efforts for zoo animals..
Challenges In Using WhatsApp as An Online Arabic Learning Center

This study aims to examine the challenges and obstacles faced in using WhatsApp as an online Arabic learning center and efforts to overcome them. The data from this qualitative study were obtained from observations of 71 students and 2 Arabic language teachers. The data was then validated and strengthened by interviews with 5 students and 2 Arabic language teachers. The results of this study show that the challenges and obstacles in using WhatsApp as an online Arabic learning center do not only come from students, student guardians, and teachers but can also come from the limitations of the WhatsApp application itself such as the maximum file size limit that can be sent and the record button prone to be canceled. In overcoming the existing obstacles, the teacher converts the files to be sent first, lowers the level of questions in assignments, pays attention to the accuracy of students' answers in doing assignments, and collaborates the use of WhatsApp with Google Drive and Instagram. Finally, by looking at the role of the WhatsApp application in the current learning process, the researcher hopes that the WhatsApp application developer will consider to provide WhatsApp for Education like WhatsApp for Business which has existed for a long time.
Working with noun phrases through ImaColab as a tool for m-learning

Mobile learning is an approach in higher education that can be incorporated into face-to-face education continuum and online education modalities. This article presents an m-learning practice through ImaColab designed for Sociology and Social Work programmes at UNSE taking Technical English. The objective was to assess the usefulness of ImaColab through students and teachers' perspectives and to reinforce noun phrases. A mixed-methods approach was applied and the data obtained from students’ scores was contrasted with surveys and an informal interview with the teacher. In conclusion, ImaColab helped to consolidate noun phrases learning and motivated students to work collaboratively. Thus, results indicate the efficacy of ImaColab as a tool for m-learning.
Improvising Touch

In this chapter I examine the role touch plays in musical improvisation. First, I discuss which methods I hold to be productive when conducting artistic research into musical improvisation. Next, by using these methods I analyze an improvisatory performance of my trio Molloy. The results of this analysis are used in the construction of an account of the function of touch in musical performance in general, and in musical improvisation in particular. In this construction theories about touch as developed by Erin Manning and Matthew Fulkerson are incorporated, as well as David Borgo’s ideas regarding improvisation and Mine Doğantan-Dack’s interpretation of gesture. I conclude that touch is exploratory and that it depends on improvisation, on in-the-moment actions and reactions, a process that is exemplified in musical improvisation. Improvisation thus may be considered an articulation of the manners in which we communicate and create identities through touch in our daily lives, how we use touch to express ourselves, to communicate who we are and connect with others. Touch is improvised, just as improvisation is grounded in touch, and by investigating the function of touch in musical improvisation we may learn about the role of touch in our everyday lives as well.
Pengembangan Pembelajaran Daring Melalui Media Interaktif Simulasi Elektronik (MISE) pada Mata Kuliah Ekonomi Makro

There are two objectives achieved in this research, including: 1) developing tools for developing online learning through electronic simulation interactive media in macroeconomics courses; and 2) measuring or knowing the level of accuracy of Online Learning Development Through Electronic Simulation Interactive Media in Economics Courses. The research method used is a Design Based Research (DBR) approach and 22 students of the Faculty of Education and Science of the Economic Education Study Program at Universitas Batanghari as research subjects. There are four stages in the Design Based Research (DBR) used, namely 1) stage I Analysis of Problems in the field; 2) Phase II Development of Online Learning Device Design and Prototype Through MISE; 3) stage III. Testing and Completing Prototypes of Online Learning Tools Through MISE; and 4) stage IV Reflection on Learning Device Products. Data collection techniques are through observation, in-depth interviews, and Focus Group Discussion (FGD). Analysis of the data used in processing the results of this research data using qualitative, quantitative, and mix method analysis. This research produces an Electronic Simulation Interactive Media (MISE) learning product that is packaged in the form of the Adobe Flash Professional CS6 Software application for macroeconomics courses with an accuracy level using the validation test of material experts and interactive learning media experts which can be seen that the results of material expert validation are 4 .5 or good and the result of media expert validation is 4.44 or good.
Utilizing Active Machine Learning for Quality Assurance: A Case Study of Virtual Car Renderings in the Automotive Industry

Computer-generated imagery of car models has become an indispensable part of car manufacturers' advertisement concepts. They are for instance used in car configurators to offer customers the possibility to configure their car online according to their personal preferences. However, human-led quality assurance faces the challenge to keep up with high-volume visual inspections due to the car models' increasing complexity. Even though the application of machine learning to many visual inspection tasks has demonstrated great success, its need for large labeled data sets remains a central barrier to using such systems in practice. In this paper, we propose an active machine learning-based quality assurance system that requires significantly fewer labeled instances to identify defective virtual car renderings without compromising performance. By employing our system at a German automotive manufacturer, start-up difficulties can be overcome, the inspection process efficiency can be increased, and thus economic advantages can be realized.
Enhancing Automated FaaS with Cost-aware Provisioning of Cloud Resources.

Compute resources are becoming more diverse, more specialized, and more physically distributed every day. To properly use these resources, the new paradigm of serverless computing aims to abstract away the complexity associated with resource configuration and workload deployment. Building on this serverless architecture are efforts for automated resource selection and automated task distribution and coordination. As computing resources advance, so too does application-specific optimizations, as is the case of deep learning on GPUs or even the more specialized TPUs. To better navigate the efficient and effective use of these diverse resources, we present the addition of automated, cost-aware provisioning of cloud resources to a state-of-the-art automated serverless framework. By automating the selection, provisioning, and configuration of cloud resources, our framework, which we call DELTA+, will enable truly cost-aware usage of the cloud by navigating complex computational tradeoffs. In this proposal, we will outline how we plan to introduce burstable cloud computing to automated serverless infrastructure and to present our initial findings with respect to system design and performance.
Simulating $\phi^4$ scalar field on quantum computers

computers can provide advantages in systems with fermions which are difficult to simulate on classical computers. In this study, we first employed classical computational methods to analyze a Friedmann-Robertson-Walker mini-superspace with a scalar field and visualize the calculated wavefunction of the universe for a variety of different values of the curvature of the universe and the cosmological constant. We then used IBM’s Quantum Information Science Kit Python library and the variational quantum eigensolver algorithm to study the same systems on a quantum computer. The framework was extended to the world line approach to quantum field theory.
GPU based Image Compression with Scaling-Hard-Threshold Using HWT (Haar-Wavelet-Transform) + RL (Run-Length) Pair Encoding

In 5G MASSIVE MIMO the main problem for better video communication is of transmission bandwidth issues which in turn reflects in video conferencing, Mobile-learning, gaming, graphics applications etc. However, in regard to a versatile framework i.e. a computerized camera with web and correspondence office, at that point the transmission capacity for correspondence and additionally stockpiling are of genuine concern. Tremendous valuable data must be put away and recovered proficiently for down to earth purposes. This is the novel methodology that scaling technique has proposed for 2D Haar wavelet transform based compression of picture utilizing parameter CR- ratio of Compression with PSNR improvement, with maintaining picture quality, less bandwidth usage with better compression ratio which increase by increasing speed with the help of NVIDIA GPU.
An Analytical Study of Users of Telegram Supergroups

Several features like channels, bots, supergroups, end-to-end encryption, and personalization available in Telegram, has made the instant messenger popular among rivals. The possibility of creating public channels and supergroups has changed Telegram application to a social network rather than an instant messenger. Although Telegram has more than 200 million active worldwide users and 40 million active Iranian users, there is little research based on Telegram. In this paper we have studied Iranian supergroups. More than 300,000 Persian supergroups have been analyzed in our study. The results will give a deep insight of Telegram environment to the reader. We have defined some measures to detect high-quality supergroups, too. In our view, a high-quality supergroup is a supergroup whose members are more engaged with its content.
Completely positive completely positive maps (and a resource theory for non-negativity of quantum amplitudes)

In this work we examine quantum states which have non-negative amplitudes (in a fixed basis) and the channels which preserve them. These states include the ground states of stoquastic Hamiltonians and they are of interest since they avoid the Sign Problem and can thus be efficiently simulated. In optimization theory, the convex cone generated by such states is called the set of completely positive (CP) matrices (not be confused with completely positive superoperators). We introduce quantum channels which preserve these states and call them completely positive completely positive. To study these states and channels, we use the framework of resource theories and investigate how to measure and quantify this resource.
Optimal convex approximation of qubit states and geometry of completely represented states

We investigate the problem of optimally approximating a desired state by the convex mixing of a set of available states. The problem is recasted as finding the optimal state with the minimum distance from target state in a convex set of usable states. Based on the fidelity, we define the optimal convex approximation of an expected state and present the complete exact solutions with respect to an arbitrary qubit state. We find that the optimal state based on fidelity is closer to the target state than the optimal state based on trace norm in many ranges. Finally, we analyze the geometrical properties of the target states which can be completely represented by a set of practicable states. Using the feature of convex combination, we express this class of target states in terms of three available states.
THE ANALYSIS OF STUDENT’S GRAMMATICAL ERROR IN WRITING SKILL OF RECOUNT TEXT AT THE ELEVENTH GRADE OF SMK NEGERI 17 WEST JAKARTA

The article investigated about Grammatical error in writing skill of recount text at the eleventh grade of SMK Negeri 17 West Jakarta. The purpose of this study was to know the grammatical error of the students in part of speech and tense in recount text writing. The indicators are: (a) error in sentence pattern, (b) error in tense, (c) error in omission. From these indicators, the researcher would know the kinds of error that students made in their writings. To achieve this goal, this research uses descriptive qualitative methods. The population was class XI in SMK Negeri 17 West Jakarta. The samples were 10 students majoring in management. The researcher used total sampling to take the samples. The Instrument was writing test. Keywords : Grammatical Writing Error, Recount Text
Analysing Documents About Colombian Indigenous Peoples Through Text Mining

The indigenous peoples of Colombia have a considerable social, political and cultural wealth. However, issues such as the decades-long armed conflict and drug trafficking have posed a significant threat to their survival. In this work, publicly available documents on the Internet with information about two indigenous communities, the Awá and Inga people from the Cauca region in southern Colombia, are analysed using text analytics approaches. A corpus is constructed comprising general characterisation documents, media articles and rulings from the Constitutional Court. Topic analysis is carried out to identify the relevant themes in the corpus to characterise each community. Sentiment analysis carried out on the media articles indicates that the articles about the Inga tend to be more positive and objective than the Awá. This may be attributed to the significant impact that the armed conflict has had on the Awá in recent years, and the productive projects of the Inga. Furthermore, an approach for summarising long, complex documents by means of timelines is proposed, and illustrated using a ruling issued by the Constitutional Court. It is concluded that such an approach has significant potential to facilitate understanding of documents of this nature.
Persepsi dan pengembangan peta kognitif mahasiswa dalam blended learning

Tujuan dari artikel ini adalah untuk merefleksikan manfaat perkuliahaan perkembangan anak berkebutuhan khusus melalui perkuliahaan blended learning dari aspek persepsi secara kuantitatif dan peningkatan peta kognitif secara kualitatif. Metode penelitian dengan angket dari respon mahasiswa secara kuantitatif, sedangkan peta kognitif diambil secara kualitatif terhadap fakta refleksi mahasiswa dalam mendalami materi kuliah. Respon angket meliputi sangat sesuai, sesuai, dan tidak sesuai terhadap komponen-komponen substansi perkuliahaan. Analisis data menggunakan persentase bagi data kuantitatif dan kategorial peta kognitif pada data kualitatif. Hasil diperoleh bahwa pada waktu kuantitatif persepsi mahasiswa dalam kondisi stabil, namun fakta peta kognitif secara kualitatif terjadi perubahan meningkat secara bervariasi. Dari sebelas mahasiswa peserta kuliah perkembangan anak berkebutuhan khusus ketika respon terhadap kesesuaian materi kuliah dengan capaian pembelajaran sebelum dam sesudah blended learning ternyata stabil. Peningkatan peta kognitif pada refleksi materi perkuliahaan sebelum dan sesudah blended learning bervariasi tergantung minat dan ketertarikan mahasiswa pada masing-masing komponen dari substansi perkuliahaan. Jadi, mata kuliah perkembangan anak berkebutuhan khusus bermanfaat bagi pencapaian profil lulusan.Perception and development of cognitive map's student through blended learningAbstractThe purpose of the article reflects the benefits of lecturing on the development of children with special needs through blended learning from quantitative aspects of perception and improving cognitive maps qualitatively. The research method with a questionnaire from the students' responses quantitatively, while the cognitive map is taken qualitatively to the fact of student reflection in studying lecture material. The questionnaire response includes very suitable, appropriate, and incompatible with the components of the lecture substance. Next, they were asked to reflect descriptively about the contents of the material in each lecture component. Data analysis uses percentages for quantitative and categorical cognitive map data on qualitative data. The results obtained that in quantitative time the perceptions of students are in a stable condition, but the facts of cognitive maps qualitatively change changes vary. Of the 11 (eleven) students participating in the development of children with special needs when the response to the suitability of the course material with learning outcomes before the dam after blended learning turned out to be stable. Increasing cognitive maps on reflection of lecture material before and after blended learning varies depending on student interest and interest in each component of the lecture substance. So, the developmental course of children with special needs is useful for achieving graduate profiles.
Suggestions to Enhance the Scholarly Search Engine: Google Scholar

The scholarly search engine Google Scholar (G.S.) has problems that make it not a 100% trusted search engine. In this research, we discussed a few drawbacks that we noticed in Google Scholar, one of them is related to how does it perform (add articles) option for adding new articles that are related to the registered researchers. Our suggestion is an attempt for making G.S. more efficient by improving the searching method that it uses and finally having trusted statistical results.
Creating and Using jQuery Plugins

jQuery plugins make functions portable and easy to integrate with any number of projects, hence implementing reusability. In this chapter, you learn to create jQuery plugins from scratch and how to use some popular jQuery plugins. You learn how to do the following with the recipes in this chapter.
LibGuides: System Wide Holds - Training Guide: Edit Hold

The purpose of this guide is to provide staff a reference resource for processing Requests and Holds on NLPL materials.