Reviewerly/exHarmony huggingface dataset:
Bodies Now and Otherwise: Theology of the Cross and Trans Experience

Martin Luther’s theologia crucis can be seen through a postmodern lens as an articulation of the limits of bodies as signifiers, as Jesus’ body simultaneously reveals and hides divine identity. Likewise, transgender embodiment is often experienced as somehow contradictory, the site of both euphoria and dysphoria; a failed, contested, or ambiguous signification. This paper reads Luther’s theological claims together with contemporary trans theory and narratives toward a theological conception of the polyvalent and dynamic character of embodiment, which recognizes the deep personal and social significance of the body and its shapes while insisting that identity, value, and personhood cannot be straightforwardly read off a body but can only be perceived by an orientation of the heart. In this way, Luther’s articulation of a God revealed in the body of God’s “opposite” can provide an epistemological opening to see all bodies differently.
"Integrado en el mundo de los seres humanos": Narraciones nacionales en relatos actuales de inmigrantes clandestinos senegaleses en Italia

Current nationalist discourses in Europe are accumulating force and blaming mainly undesired immigrants, especially from Africa. Meanwhile, the latter continue to arrive in boats, often simply hoping for a better future. These two tendencies–the strengthening of nationalist discourse on the one hand, and a growing internationalization on the other hand–are observed by Homi Bhabha in his introduction to Nation and Narration (1990). However, how do these undocumented African immigrants take part in constructing the narration of the nation? Se Dio vuole (2011) by Papa Ngady Faye and Il mio viaggio della speranza (2011) by Bay Mademba relate such a situation. Without an official residency permit, the immigrants represent a double national absence: in Italy an administrative absence, and in Senegal a physical one. Nonetheless, both migrated narrating subjects obtain a narrative and social presence.The present paper examines how the narrations of the Senegalese immigrants in Italy represent a national construction from below and how these narrations address the ambivalence mentioned. We will observe how the subjects present themselves as mediators between the two nations, which corresponds to a former-colony and a former-colonizer dynamics, and how they underline the conceptualization of nation as mainly human.
Sosiologi Sastra dan Pratiknya dalam Kehidupan Bermasyarakat

Sociology of literature has the fact that reality is not only built from a series of actions and interactions that are physical and behave but also awakened from discourse practice. This fact is very pronounced even in Indonesia where words or language are always used with great care because they are aware of the power of their social impact. Oral literature was born and developed in a society and is preserved through stories from time to time by one generation to the next. The ancestors inherited the oral literary tradition considered that oral literature was a way to pass on the world's truth to future generations. For the ancestors, fantasy, science and technology have something in common and become one unit. Oral literature contains many cultural messages to provide knowledge for the next generation. Just as adult humans have the right to language and also enjoy literary works, children also need information about the world, about everything that exists and happens around them that their mind can reach. Fulfilling children's rights is an adult's duty and it is a form of appreciation for children. Fulfilling children's needs for this information can be done and provided, among others, by telling stories through literature.
Research on Textual Emotion Recognition based on Deep Learning Methods

Textual emotion recognition (TER) is the process of automatically identifying emotional states in textual expressions. It is a more in-depth analysis than sentiment analysis. Owing to its significant academic and commercial potential, TER has become an essential topic in the field of NLP. Over the past few years, although considerable progress has been conducted in TER, there are still some difficulties and challenges because of the nature of human emotion complexity. This thesis explores emotional information by incorporating external knowledge, learning emotion correlation, and building effective TER architectures. The main contributions of this thesis are summarized as follows:(1) To make up for the limitation of imbalanced training data, this thesis proposes a multi-stream neural network that incorporates background knowledge for text classification. To better fuse background knowledge into the basal network, different fusion strategies are employed among multi-streams. The experimental results demonstrate that, as the knowledge supplement, the background knowledge-based features can make up for the information neglected or absented in basal text classification network, especially for imbalance corpus.(2) To realize contextual emotion learning, this thesis proposes a hierarchical network with label embedding. This network hierarchically encodes the given sentence based on its contextual information. Besides, an auxiliary label embedding matrix is trained for emotion correlation learning with an assembled training objective, contributing to final emotion correlation-based prediction. The experimental results show that the proposed method contributes to emotional feature learning and contextual emotion recognition.(3) To realize multi-label emotion recognition and emotion correlation learning, this thesis proposed a Multiple-label Emotion Detection Architecture (MEDA). MEDA comprises two modules: Multi-Channel Emotion-Specified Feature Extractor (MC-ESFE) and Emotion Correlation Learner (ECorL). MEDA captures underlying emotion-specified features with MC-ESFE module in advance. With underlying features, emotion correlation learning is implemented through an emotion sequence predicter in ECorL module. Furthermore, to incorporate emotion correlation information into model training, multi-label focal loss is proposed for multi-label learning. The proposed model achieved satisfactory performance and outperformed state-of-the-art models on both RenCECps and NLPCC2018 datasets, demonstrating the effectiveness of the proposed method for multi-label emotion detection.
Cycle-GAN for removing structured foreground objects in images

The TRACAB Image Tracking System is used by ChyronHego for the tracking of ball and players on football fields. It requires the calibration of the cameras around the arena which is disrupted by fen ...
LibGuides: Science - Year 8 - First Hand Investigation: Physical Activities & Heart Rate

A selection of resources to support Year 8 Science students to complete their assessment task.
Pengolahan Air Limbah Sablon Mengunakan Metode Kombinasi Bak Berjenjang Dengan Tanaman Eceng Gondok

Processing waste printing using a combination of a level tub with water hyacinth plant aims to improve the welfare of society will be clean AI in industrial activities. Pollution caused by the industry due to the existence of waste from the factory and contain toxic materials and waste is the disposal of its presence at a time and certain places are not required by the environment because it does not have Economic value. Such waste can be either solid waste, liquid waste, and gas waste. The purpose of this research is to test water hyacinth efffectivity to liquid waste printing to absorb various substances contained in screen printing wastewater and test the content of BOD, COD, pH which is the benchmark of pollution of substances – organic substances. The methods of research used are experimental methods and sampling waste water in Jagan, RT 02 RW XII, Brackets, Ceper, Klaten. The study took place in December – January 2020. The results of this study resulted in percent processing efficiency with BOD, COD and pH parameters consecutively at 73%, 31%, 5% with the test result then compared to Sukoharjo regional regulation on the raw quality of liquid waste Printing industry in Sukoharjo. The results of a comparison of test parameters show that all waste before processing and after processing has a value above the quality standards. The smell change from this research is quite successful because on the 2nd day the smell of the waste printing is lost. In Figure 3.8.1 and pictures 4.1 can be seen smell changes every day. If not processed, the liquid waste screen printing the longer the time of the bait will be more smell. Odor arising from liquid waste printing caused by the breakdown of chemical substances contained in the Dilimbah that produces ammonia and H2S by natural microorganisms.
Early Size Estimation using Machine Learning

The process of size estimation of a project is one of the key activities that forms the indispensable part of any project development process. This broadly involves the evaluation of the number of codes and packages that can only be analyzed once the project is completed. The presented paper aims at the size estimation through predictive analysis using Machine Learning (ML) architecture to offer best possible size and effort estimation to complete a project. The article also evaluates the existing research in the field of size estimation discussing the research trends inspired with the ML techniques as size prediction models. Finally, it presents comprehensive survey of the possible prospective of ML approaches for size estimation along with the detailed information in terms of strengths, limitations, evaluation metrics implemented for evaluation along with the datasets involved in the studies.
LibGuides: Artificial Intelligence and Careers after Coronavirus Articles.: Home

These articles are food for thought. These are to let students know what is being said; HBU does NOT ACCLAIM these to be the truth or our future.
Female Saudi University Students’ Perceptions of Online Education Amid COVID-19 Pandemic

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한국어 시간관계 연결어미의 중국어 대응 양상 고찰

In order to teach the Chinese Korean learners more effectively, this study analyzed the concepts and categories of Korean temporal conjunctive morpheme at first. Then through the Korean-Chinese parallel corpus, it analyzed the Chinese cor-respondence patterns with Korean temporal conjunctive, such as ‘-myeo’, ‘-myeonseo’, ‘-ja’, ‘-jamaja’, ‘-go’, ‘-eoseo’, which are frequently used. On this basis, this study analyzes the characteristics of Chinese correspondence patterns to the Korean temporal conjunctive.
Focused Web Crawler For Retrieving Relevant Contents

The rapid growth of the World-Wide Web creates unusual scaling challenges for the purpose of general crawlers and for search engines also. we delineate a new hypertext resource discovery system which is called as Focused Crawler. The main aim of a focused crawler is to seek out the pages selectively which are very relevant to a previous deﬁned set of topics. The topics are speciﬁed not only by using keywords, but also using prototypical documents. Instead of collecting and indexing all accessible Web documents we should also be able to answer all the possible ad-hoc queries, The main work of focused crawler is to analyze its crawl boundary to ﬁnd out the links that are mostly alike for the crawl, and it avoids the unnecessary and irrelevant regions of the Web. This leads to savings in the hardware resources and network resources also and it helps the crawl for more up-to-date. A classiﬁer that evaluates the suitable hypertext documents with respect to the relevant topics, and a distiller is introduced to ﬁlter the unwanted topic from the whole content. Focused crawling acquires relevant pages while standard crawling quickly loses its way, even though they are very similar. Focused crawling is robust against large troubles for the initial set of URLs. Focused crawling is very eﬀective for building good quality collections of the Web documents on speciﬁc topics, using modest desktop hardware.
DEVELOPMENT OF AN INTELLIGENT WEB BASED DYNAMIC NEWS AGGREGATOR INTEGRATING INFOSPIDER AND INCREMENTAL WEB CRAWLING TECHNOLOGY

The World Wide Web is a rapidly growing and changing information source. This reality is gradually replacing the traditional way users obtain news or information. Traditionally, individuals get their news or information from print media, such as newspapers and magazines. Although, the advent of the internet has made things a lot easier by making this digitalized news accessible from anywhere in the world, either through news websites or dedicated applications. However, the growth and change rates make the task of finding relevant and recent information harder. Users are still faced with the challenges of visiting numerous websites just to get updated or informed on a specific type of news. This creates a problem as users have to always memorize different URLs and visit numerous websites just to view a specific type of news. Therefore, the need to develop an intelligent web based dynamic news aggregator that will provide a digital platform for individuals to easily find news pertaining to a particular topic in real time becomes imperative. It crawls the web, searches for news agencies and return a specific news of interest to the user. To address the shortcomings of existing news aggregators, this work was implemented by integrating the intelligent web based dynamic news aggregator, into an infospider web crawling technology. This is achieved applying a stochastic selector and incremental web crawling technology that crawls the entire seed urls. This system was implemented with the PHP scripting language developed to access the PHP-crawler using Aptana Studio as the Integrated Development Environment (IDE), Bootsrap3 and jQuery were used to provide a set of style sheets and JavaScript libraries to simplify the client-side scripting. The application was deployed and tested using the apache web server and a personal computer.
LibGuides: Using Hull History Centre: Copying & Referencing

Guide to how to use the facilities at HHC Guide to copying and referencing archive material
SIMULATION OF KINETIC CURVES OF THERMO-OXIDATIVE DESTRUCTION OF PROLIMERS USING DIFFERENTIAL EQUATIONS OF FRACTIONAL ORDER

In the paper it is proposed to consider fractal kinetics equations for process of thermo-oxidative destruction of melt polymers in the form of differential equations of fractional order, equaling to fraction of reactant groups of polymer, which are not subjected to destruction, with order of reaction n &gt; 1. Small νd characterize the autoslowed-down type of reaction, and at big νd &lt;1 - the autoaccelerated thermooxidation type with an decreasing speed of oxidation reaction, respectively much more smaller and close to an integer derivative on time of the first order. Comparative analysis of calculation results with corresponding results obtained by differential equations of integer order and degree of their matching with experimental data is given. Keywords: Fractal analysis, thermo-oxidative destruction, auto-slow and auto-accelerated type of thermal oxidation, differential equations of type and fractional orders.
DISASTER MITIGATION AS AN EFFORT TO MINIMIZE THE IMPACT OF FLOODS IN LAMONGAN DISTRICT

Flood is one of the most dominant disasters in Indonesia with an incident that tends to increase. Lamongan District is an area with a fairly high risk of flooding due to the intensity of which it occurs every year. The high risk of flooding is caused by two reasons, the Bengawan Solo flow and the rainfall (the Bengawan Njero flow). Every flood disaster that occurs will certainly cause various impacts from damage to infrastructure, loss of property, and casualties. Disaster management efforts are certainly carried out to minimize the risk and impact of flood disasters in Lamongan District, such as through disaster mitigation. This research aims to determine disaster mitigation carried out in Lamongan District as an effort to minimize the impact of flooding. This research used descriptive qualitative research methods. Disaster mitigation in this research is divided into two according to Perka BNPB Number 4 of 2008, active disaster mitigation and passive disaster mitigation. The results of this research indicated that active mitigation in Lamongan District was carried out through, making flood disaster signs, supervising spatial planning, conducting training and counseling on flood disasters to officials, communities, and students, planning evacuation places and flood disaster evacuation routes and making embankment reinforcement. Meanwhile, passive mitigation in Lamongan District was carried out through, drafting laws and regulations, making flood-prone maps, making guidelines for every disaster management activity, making disaster posters, conducting flood risk studies, conducting disaster education, forming village forums, and prioritizing disaster management in development planning.
Library Guides: Creating a LibGuide: Setting Up Your Guide

This guide will help you design an accessible, user-friendly LibGuide. Lists the basic steps to create, name, and add metadata to your guide.
Research Guides: Learning Tools - English: Learning Commons Chat

The purpose of this learning tool is to help students learn to study for English class. The focus is on learning how to study efficiently using the study cycle and improving reading & note-taking strategies.
LibGuides: Audio Visual Support: Sound Systems

See what the Innovation Commons has available to borrow to support digital learning and teaching.
A Quantum MMAS Based Algorithm for Multicast Routing Problem

Abstract For solving the problem of multicast routing, ant colony algorithm (ACO) has insufficient optimization ability. The paper proposes a routing algorithm which combines quantum computing and max min ACO. The algorithm uses quantum bit probability amplitude to encode the link, and dynamically adjusts quantum revolving gate to update the quantum coding on the link, so as to meet the cost optimization under constraint conditions, combined with the maximum and minimum pheromone decision mechanism to find the optimal link path, effectively control the evolution speed and direction, and enhance the convergence performance of the algorithm. The simulation results show that the algorithm can effectively control the evolution speed and direction, and is better than ant colony algorithm in the optimization ability and convergence performance.
LibGuides: Electronic Resources: Off Campus Access

This is an information guide about the Electronic Resources at NOVA Libraries. For more information, contact LTS@nvcc.edu
TEACHING WORD-FORMATION THROUGH FLIPPED LEARNING: A PROPOSAL FOR UNIVERSITY LECTURES pp. 17-33

In recent years, thanks to the advent of the Internet technology, flipped learning, in which instruction is accessed at home in advance of class, has received considerable attention as an alternative to traditional lecture-based classroom practices, as it leaves class time for developing higher-order competencies such as applying, analyzing and evaluating by offering students more opportunities for problem-solving, discussion and collaborative learning. The purpose of this article is to present a proposal for teaching English word-formation processes, namely compounding, conversion, blending and clipping, in higher education through flipped learning, understood here as a form of blended learning that incorporates elements from traditional face-to-face teaching, online instruction and cooperative group work. This teaching proposal, which combines the so-called “discussion-oriented” and “group-based” flipped classroom models, includes contents, objectives, competencies, activities and assessment. Although originally designed for Spanish students of English morphology, the proposal is easily adaptable to related courses and provides a basis for teaching a range of linguistic subjects through the inverted classroom approach.
Research on Adding Biotech and Bitcoin to Portfolio

Investors are still worried about the variables brought about by COVID-19 and the presidential election because of the recent growth trend of the stock market despite the macroeconomic downturn. This article speculated whether the portfolio of biotech owned stocks and bitcoin can cope with these uncertainties. At the same time, investors need to pay attention to the companies that are studying the COVID-19 vaccine and whether they have state financial support. Also, Python and Excel were used to explore the daily return, annual volatility, and portfolio performance of biotechnology stocks. Besides, a multiple linear regression model on CPI and GDP focusing on whether macroeconomic factors affect bitcoin was established. These results support the conclusion that currently adding biotech supported by the federal government and bitcoin into the portfolio could respond to the risks from COVID-19.
Fuzzy time series [FTS] and artificial neural network [ANN] : forecasting Malaysia’s palm oil exportation / Intan Nur Syazwina Shamsul Nidzar

Forecasting is an estimate of the value of a variable or group of variables and saying what will potentially happen at a future time. Malaysia is the second-largest palm oil producer in the world after Indonesia. Although Indonesia is the world’s largest palm oil producer, Malaysia is the largest exporter of palm oil in the world. In 2018, lower palm prices were traded. However, it caused the gross export volume to decrease drastically (Kushairi et al., 2019). There is a need to forecast the export quantity of palm oil in Malaysia in order to aid those relevant to the industry to make assumptions or appropriate decisions regarding crop production and export matters. The study has two objectives which is to find forecasted value of the actual data of the quantity of palm oil exports in Malaysia by using Fuzzy Time Series and Artificial Neural Network and to determine the best model by comparing Fuzzy Time Series model and Artificial Neural Network model. From the results, the model that gives the smallest value of MSE, RMSE and MAPE is Fuzzy Time Series (FTS). The value of MSE for Fuzzy Time Series (FTS) is 13107002289 while the Artificial Neural Network (ANN) value is 17778810689. The value of RMSE for Fuzzy Time Series (FTS) is 114485.817 while the Artificial Neural Network (ANN) value is 133337.2067. The value of MAPE for Fuzzy Time Series (FTS) is 5.1063 while the Artificial Neural Network (ANN) value is 7.5328.