Reviewerly/exHarmony huggingface dataset:
Seismic window: Artificial intelligence finds faults

In recent years it has taken some effort for me to get my head around Machine Learning (ML). I even bought a book (“The Master Algorithm” by Pedro Domingos) that was recommended to me by a Canadian...
CREATIVE WORK AS A METHOD OF CORRECTION OF THE PSYCHOEMOTIONAL STATE IN PUPILS OF HIGH SCHOOL

A preliminary report is given on the comparative study of the level of psycho-emotional state of students studying at the “Quant” gymnasium and the State College of Fine Arts in different educational environments. The comparative analysis of the obtained data shows that creative work has a relaxing effect on mental tension, allows the individual to better adapt to life, allows for self-knowledge.
Assessment of hazardous soils contamination and remediation actions in Burgan oil field-Kuwait

The environment in Kuwait had suffered a massive damage by the Iraqi tropes during the 1990 - 1991 military invasion. 734 oil wells were damages and burned causing huge amount of oil spill on the soil surface and sub-surface. The majority of the soil around the oil fields were effected by hazardous contamination. This study was conducted to measure the extent of contaminated soil and to determine the contaminant composition, then choose a suitable remediation action for rehabilitation of Kuwait’s desert environment and ecosystem. Site soil samples taken from five well heads located in Burgan’s field were investigated to measure the depth level and compositions of the contaminated soil. The results showed that the contaminated soil was identified, and well head number three had the deepest contamination of 4.3 meter and the lowest depth was in the well head pit number one of 1.2 meter. The amount of the petroleum hydrocarbons resided in the soil can cause a series health risk. The necessary remediation actions were made using different quantities and mixing of nutrients. Furthermore Epidemiology studies are needed to monitor the long term positive impacts of remediation actions of the pollutants on the ecology, environment and human health.
LibGuides: Library Workshop 2020: Home

Resources and services covered in Staley Library's What's new at the library? workshop on August 19, 2020.
Management of The Formation of The Experience of Information Activities in Students Based on Work with Educational Texts

The purpose of the research is to identify the influence of an educational text on the organisation of information activities of schoolchildren. Methods: content analysis, structural and semantic analysis of educational texts and the results of their interpretation. Research results: identification of features of the educational text as an information structure (the integrity of multi-layer content, reproducibility, presence of system connections with the thematic information field), description of the information activity of a complex of educational texts united by the function of updating the value attitude to knowledge, which can be represented in three main types: impersonal, authorised and personal. Each of these types is correlated with the level of perception of information by the student-reader, which can be a. detached and impersonal, b. in conscious collaboration with the author, c. to their own cognitive experience. As a result of the research, the basic information-significant structural components of educational texts are also identified: the title and the beginning correlated with the key meaning of the text, the means of axiological field and dialogisation.
Semantic Tagging-Based Document Retrieval Using Non-Negative Matrix Factorization

Many document retrieval methods focusing on unstructured text to deliver more meaningful information on the user.Tag-based document retrieval aims to address a challenge to searching relevant text-documents given a set of tags.Tag-based approaches received a wide attention as a possible solution to the big-content related IR, showing a high performance through a combination of its effectiveness and efficiency.This paper use word sense disambiguation with non-negative matrix factorization to generate topic model based semantic.
MENINGKATKAN KEMAMPUAN KOSAKATA BAHASA INGGRIS ANAK USIA DINI MELALUI METODE BERNYANYI DI TKQ YAA BUNAYYA

Language is one aspect of development that must be improved in early childhood. English is also commonly called the second language is part of aspects of language development can be improved through the singing method. The purpose of this study is to improve children's English vocabulary through singing methods. This research is motivated by the problems that exist in TKQ Yaa Bunayya due to obstacles in mastering and memorizing English vocabulary, as well as any errors or inaccuracies pronunciation in using English. In this research, the method used is a descriptive qualitative method that is an approach that serves to give a picture of a symptom or event of a problem that occurs, where researchers directly examine the learning process of children in improving children's English vocabulary by the singing method. Data collection in this research in using observation, interview, and documentation techniques. In research data analysis techniques using qualitative analysis techniques using data reduction, data display, and concluding. The study was conducted in 5 meetings in group A with 8 children. Through singing, methods children are not easily bored in following the stages of the learning process.
LibGuides: Campus Study Spaces: Cushing- Martin Hall

Find places to study or to take a class remotely in one of the many spaces available on campus.
Adaptively Innovative Pedagogical Technologies In The System Of General Education

The article discusses modern trends in the development of education and substantiates the need to take into account their impact on the development of pedagogical technologies and their systems. A feature of the authors' approach is the definition and justification of various ways of updating pedagogical technologies by improving their microstructures: adaptive and adaptive-innovative. At the same time, special attention is paid to the adaptively innovative transformation of technological microstructures, which is distinguished by the elements of novelty, “local invention”, aimed at achieving high sustainable results with optimal costs of resource provision. In the process of analyzing theoretical sources and pedagogical experience, the authors identified the “driving forces” of adaptive-innovative evolutionary improvement of pedagogical technologies in the form of mechanisms and methods to achieve the planned results, determined the essential features of adaptive-innovative mechanisms of modification, transformational and combination types, taking into account their functional purpose and structural features of the implementation, on the basis of which criteria-based descriptions were developed that ensure the identification of adaptive-innovative pedagogical technologies and open up prospects for applied work. Adaptation-innovation mechanisms allow to trace the development path of pedagogical technology, identifying it as adaptive-innovative. The article substantiates the methodological feasibility of a new form of popularizing unique experience –TED-conference with international participation, which contributes to the disclosure of the adaptive and innovative potential of pedagogical technologies used in school practice.
Research on Cloud Computing User Privacy Protection Based on Dynamic Adaptive Ant Colony Algorithm

In order to overcome the problems of long encryption time and poor security of traditional cloud computing user privacy protection methods, this paper proposes a cloud computing user privacy protection method based on dynamic adaptive ant colony algorithm. In this method, the dynamic adaptive ant colony algorithm (DAACA) is used to realise highly adaptive encryption transmission of information. Combining identity-based public encryption (IBE) with secret sharing strategy and IBE, we adopt corresponding threshold strategy for untrusted cloud computing service providers to reduce the threat of data leakage brought by a single untrusted service provider, and authorise the identity information of cloud computing users through authorising the identity information of cloud computing users through data providers. The experimental results show that the proposed method can effectively reduce the encryption time and improve the security of the whole system.
Analyses of Life Skills Development Practices in Secondary Schools of Islamabad

The study was designed to make analysis for developing Life Skills practices in the secondary schools of Islamabad. It was descriptive survey study. All 1039 SSTs, all 146 principals of public secondary schools working under FDE at Islamabad were population of the study. Five hundred and seventy (570) SSTs; one hundred and forty (140) principals were selected by using stratified random sampling technique. A questionnaire having 36 items were developed by the researcher on five point Likert scale. Mean, Standard Deviation, and t-test, were applied to analyze the data. There was moderate level of practice of skill development in secondary schools. Male teachers were better performing in developing communication skills and critical thinking while female teachers were better for developing problem solving skills. Development of strategy and proper training of teachers and principals, by the government, for life base skill education was recommended.
3D Pose Estimation

The task of estimating position of objects and human body in three-dimensional space is more challenging than in 2D, but the result is stunning. In this chapter we'll cover basic principles of camera optics and fundamentals of 3D reconstruction with a monocular and multiview camera. We'll also discuss datasets and some of the most advanced methods for 3D pose reconstruction available today, including sparse and dense reconstruction.
Adaptive Ensemble Embedding for Transfer Learning

In this work, we present an approach for transfer learning. Many adversarial transfer learning approaches train merely one domain classifier to differentiate the features as either source domain or target domain and train a feature generator to perplex the discriminator. One problem exists with this family of approaches, where the single discriminator is used to differentiate the features as source or target thus could not mine the hard samples. To solve the above problem, we introduce a new adaptive ensemble embedding scheme for transfer learning (AEETL). We propose to learn multiple adaptive embedding features with considering the hard samples for transfer learning. AEETL mainly contains two components: (1) the weight module is applied to predict the adaptive ensemble weights; (2) the ensemble module is applied to mine the hardness of samples following a coarse-to-fine scheme. Comprehensive experimental results demonstrate the effectiveness and superiority of our approach.
Reasoning with Inconsistent Knowledge using the Epistemic Approach to Probabilistic Argumentation

Structured argumentation involves drawing inferences from knowledge in order to construct arguments and counterarguments. Since knowledge can be uncertain, we can use a probabilistic approach to representing and reasoning with the knowledge. Individual arguments can be constructed from the knowledge, with the belief in each argument determined just from the belief in the formulae appearing in the argument. However, if the original knowledgebase is inconsistent, this does not take into account the counterarguments that can be constructed. We therefore need a wider perspective that revises the belief in individual arguments in order to take into account the counterarguments. To address this need, we present a framework for probabilistic argumentation that uses relaxation methods to give a coherent view on the knowledge, and thereby revises the belief in the arguments that are generated from the knowledge.
Implementasi Algoritma Apriori Pada Penyusunan Menu Makanan Rumah Makan Prasmanan

A buffet restaurant is a restaurant that provides buffet food that is served directly at the dining table so that customers can order more food according to their needs. This study uses the association rule method which is one of the methods of data mining and a priori algorithms. Data mining is the process of discovering patterns or rules in data, in which the process must be automatic or semi-automatic. Association rules are one of the techniques of data mining that is used to look for relationships between items in a dataset. While the apriori algorithm is a very well-known algorithm for finding high-frequency patterns, this a priori algorithm is a type of association rule in data mining. High- frequency patterns are patterns of items in the database that have frequencies or support. This high-frequency pattern is used to develop rules and also some other data mining techniques. The composition of the food menu in the Asgar restaurant is now arranged randomly without being prepared on the food menu between one another. The result of this research is to support the composition of the food menu at the Asgar restaurant so that it is easier to take food menu with one another.&#x0D;
Research on the Mobile Learning Mode of College English Based on We Learn APP

Mobile terminal based learning is an important part of English teaching. According to the related theories of mobile learning, this study focuses on the We Learn APP and the corresponding teaching mode around the college English audio-visual course. It investigates and analyzes the current situation of the use of We Learn APP, a case practice is carried out to explore how to improve the effectiveness of college English learning through mobile learning.
Deep Discriminative Feature Learning for Domain Adaptation

Recent advancements have been seen in Deep domain adaptation field, which helps transfer knowledge from a source domain to a related but different target domain, greatly reducing the cost of manual annotation and successfully learning domain invariant features. However, most existing deep domain adaptation methods only align source and target domain distributions, neglecting the class structure information in the source domain, and ultimately leading to domain confusion. To address this issue, we propose a new model for deep domain adaptation, which can simultaneously achieve domain alignment and discriminative feature learning. Specifically, apart from performing domain-invariant embeddings with MMD metric, we utilize a center loss to construct class structure, so as to enhance inter-class separability and intra-class compactness. In addition, our model is effective and easy to implement, compared to other methods. Extensive experiments conducted on two benchmark datasets verify that our model has superior performance over state-of-the-art methods.
A Chinese Speech Recognition System Based on Articulatory Features

In this paper, we build a Chinese speech recognition system based on acoustic features and articulatory features (AFs). We modify the original Chinese phonemes and define several language-independent AF groups based on International Phonetic Alphabet (IPA) and linguistic knowledge. To eliminate the need to force alignment information and simplify training, a technique using connectionist temporal classication (CTC) criterion is adopted. The Mandarin speech recognition system is built by the joint features which are concatenated with AFs and MFCC. The results show that using of AFs can improve the performance of ASR task on THCHS-30 30 hours data set.
LibGuides: Online Research, Teaching, and Learning @ Pitt: Resources for Teaching & Learning

This guide provides links to helpful resources for teaching and learning from a distance and will be updated frequently.
On the Approximability of Weighted Model Integration on DNF Structures

Weighted model counting (WMC) consists of computing the weighted sum of all satisfying assignments of a propositional formula. WMC is well-known to be #P-hard for exact solving, but admits a fully polynomial randomised approximation scheme (FPRAS) when restricted to DNF structures. In this work, we study weighted model integration, a generalization of weighted model counting which involves real variables in addition to propositional variables, and pose the following question: Does weighted model integration on DNF structures admit an FPRAS? Building on classical results from approximate volume computation and approximate weighted model counting, we show that weighted model integration on DNF structures can indeed be approximated for a class of weight functions. Our approximation algorithm is based on three subroutines, each of which can be a weak (i.e., approximate), or a strong (i.e., exact) oracle, and in all cases, comes along with accuracy guarantees. We experimentally verify our approach over randomly generated DNF instances of varying sizes, and show that our algorithm scales to large problem instances, involving up to 1K variables, which are currently out of reach for existing, general-purpose weighted model integration solvers.
How to swap instructions midstream

In this work, we propose an encoding/decoding algorithm for program executable steganography. Some salient features of our approach is that unlike previous work it does not require the introduction of new instructions, which may be detectable. Furthermore, our scheme does not require storing the locations of where changes in the program executable are made.
Local Literature Development Through Fable/Legend in Junior High School

Local literature is a culture that is owned by an area or region and reflects the social conditions in the region.The use of local literature in learning in schools is also an effort to empower culture so that is not displaced by western culture brought by globalization.This study aims to describe local literature as empowerment support of regional literature through learning fables or legends in schools.This research is qualitative research with a qualitative descriptive approach.The sample in this study involved two Indonesian Language teachers from different schools.The data obtained through interviews and analysis of documents in the form of syllabus, lesson plans, one main book, and two enrichment books.The results obtained from this study were (1) the application of local literature has not been implemented in the field, (2) there was a mismatch between syllabus, lesson plans, and textbooks.
BUILDING A SMART TREASURY - How Artificial Intelligence can revolutionise Treasury

Since the financial crisis, the role and responsibility of Treasury has grown significantly in terms of scope and strategic importance. There are an ever-increasing number of requirements from Regulators, Senior Management and Shareholders that Treasury needs to deliver on. Regulatory demands are becoming more onerous in terms of granularity and frequency; while the CEO/CFO increasingly requires real-time attestation that the balance sheet is efficiently optimised and protected against risks. To meet these demands Treasury needs to revolutionise its time-consuming operational processes and become more strategically orientated. Leveraging digital technologies associated with the 4th Industrial Revolution, can enable the transition towards a ‘Smart Treasury of the Future’. One technology that shows a lot of promise is Artificial Intelligence (AI).  AI has been around for the last couple of decades. However, recent growth in processing power and explosion of data available to ‘learn from’ mean innovative analytical tools are becoming far more useful and effective. This is very relevant for a Treasury, that needs to analyse large amounts of liquidity, capital and risk data, to inform strategic decisions around the scarce resources of the bank. AI can offer many benefits - improving predictability of Financial Planning and Forecasting; providing a holistic real-time view of Intraday cashflows required for Liquidity Management; and deriving smart hedging decisions for Interest Rate and FX risks.   AI also brings new challenges, but banks that invest in next generation technologies, will be rewarded with improved ability to manage risks, higher operational efficiencies, reduction in operating costs, and ensure a completive advantage.
The Analysis of Form and Meaning of Written Language in Social Media

The objective of this research was to examine the form and meaning of written language used in social media as a means to communicate between users of social media.It was a qualitative research with descriptive qualitative method.The data were collected through observation and document study.The data analysis and interpretation indicates that there are five forms of discourse used by the Facebookers they are descriptive form, narrative form, exposition form, argumentative form, and persuasive form.There are also six styles of meaning they are denotative, connotative, idiom, synonym, antonym, and ambiguity.The finding indicated that the user of Facebook tended to use those form and meaning of written language to express their feeling.
Using Lo-Fi prototyping to envision conversational agents in public settings

Speech interactions are often associated with virtual assistants and smart home devices, designed primarily for private contexts. A less developed domain is speech interfaces in public contexts. In a smart city development project, we explored the potential of distributed conversational speech interfaces in lampposts. Deploying a research-through-design method, we created a lo-fi prototype of the speech interface that test subjects could interact with during experiments in a lab setting. Our first exploratory prototype consisted of a loudspeaker that acted as the interface and preconceived dialogues designed to investigate the boundaries of desirable and acceptable experiences regarding issues such as privacy. Experiencing the interaction with this rudimentary prototype helped people envision potential use cases and reflect on privacy issues: the dialogues revealed subjective limits of what kind of (personal) information people were willing to share with the lamppost. They also elicited thoughts on possible consequences in the social context of citizens. LinkedIn: https://www.linkedin.com/in/atjylha/ https://www.linkedin.com/in/josvanleeuwen/
Automatic Extraction Of Epidemic-Related Sites In Covid-19 Media Reports Of Webpages Based On Conditional Random Field Model

Taking Guangdong province as an example, the identification of named entities and the automatic extraction of epidemic-related sites are carried out. This method will help locate the spread of the epidemic, prevent and control the spread of the epidemic and gain more time for vaccine clinical trials.
Krithi: Cows at the Beach

Intercultural creative practice is a topic that has attracted a lot of recent scholarly attention. As improvising musicians from very different cultures and traditions, we decided to analyse a recent collaborative performance that we were involved in to unpack the ways that we were interacting through music. As performers, we were interested primarily in the ways that such an analysis would help us to work more effectively in intercultural situations, but we also wanted to understand the synergies and dissonances that exist between improvising cultures more broadly. For the essay we adopt the musical form of a krithi, a Carnatic compositional form that allows for joint statements and improvised exchanges. Through this dialogic process, we propose improvisation as a kind of negotiation that occurs between musicians, and between musicians and their culture, highlighting some of the specific challenges and rewards that we faced.