Reviewerly/exHarmony huggingface dataset:
Where have Foreign Banks in Nigeria Gone? Market Structure, Competitive Intensity and the Capabilities of Nigeria Banks

Privately-owned Nigerian banks hold 94% of Nigeria banking assets, the world's second largest share of local ownership. Theoretical explanations for the dominance of local firms related to liabilities of foreignness do not explain this phenomenon, suggesting that foreign banks do not experience additional costs compared to local Nigerian banks. In search for explanation for this puzzle, we focus on market structure and competitive intensity and their impact on capability development. In-depth exploratory study of Nigeria banking industry, based on interviews with industry experts and practitioners and supplemented by secondary data, suggests that the regulatory approach towards both foreign and Nigerian banks instilled market structure and competitive dynamics that were conducive for the development of competitive capabilities by Nigeria banks, whose strength arrested foreign entry. The study throws light on a regulatory approach that incentivizes capability development via discipline imposed by markets rather than by direct government intervention in the form of protectionism or favorable resource provision. It highlights the merits of studying phenomena that are inconsistent with existing theories for theory extension and development.
UTILIZING DUOLINGO IN LEARNING VOCABULARY

Using technology is a solution to answer the difficulties of learning English in the current global pandemic era. One of the technologies that can help in learning English is Duolingo. Duolingo is an application that can help students to increase their vocabulary mastery. This study sought to find out the implementation of Duolingo in learning vocabulary, the effect of using Duolingo in enhancing students’ vocabulary mastery, and students’ perception toward the use of Duolingo. A qualitative research was employed on this research to reach the aims mentioned. The instruments were test, questionnaire, and observation. The observation was used to find out the answer of the first question. Meanwhile, the questionnaire was used to find out the answer to third question, and the test was used to find out the answer of the second question. To analyze the data collection, this study followed Miles and Huberman model. Based on the data, the study reveals that there was a significant effect of the students’ vocabulary mastery after they were taught through Duolingo application since the test value was higher. This indicates that Duolingo facilitates the learners to enhance their vocabulary mastery
Varieties of autocracy and human development

The idea of a connection between a country’s political institutions and its human development record is not new, but attention has mostly focused on comparing democratic and non-democratic regimes, whereas the institutional differences characterizing the non-democratic universe have remained largely disregarded. This chapter examines how different institutional environments could shape the importance that autocrats attach to improving citizens’ living conditions. The discussion highlights autocratic survival strategies and time-horizon as two key dimensions of variance. Autocrats that rely on regime performance to hold on to power, and that face a longer time horizon, should pay more attention to citizens’ living conditions. Accordingly, using data on school enrolment and child mortality for the 1971-2015 period, a time-series cross-sectional analysis compares the human development performance of different forms of autocracy, using data on school enrolment and child mortality. Overall, the empirical test shows that elected autocrats in competitive autocracies and monarchs achieve better human development results.
Supervised Topic Compositional Neural Language Model for Clinical Narrative Understanding

Clinical narratives that describe complex medical events are often accompanied by meta-information such as a patient’s demographics, diagnoses and medications. This structured information implicitly relates to the logical and semantic structure of the entire narrative, and thus affects vocabulary choices for the narrative composition. To leverage this meta-information, we propose a supervised topic compositional neural language model, called MeTRNN, that integrates the strength of supervised topic modeling in capturing global semantics with the capacity of contextual recurrent neural networks (RNN) in modeling local word dependencies. MeTRNN generates interpretable topics from global meta-information and uses them to facilitate contextual RNNs in modeling local dependencies of text. For efficient training of MeTRNN, we develop an autoencoding variational Bayes inference method. We evaluate MeTRNN on the word prediction tasks using public text datasets. MeTRNN consistently outperforms all baselines across all datasets in perplexity ranging from 5% to 40%. Our case studies on real world electronic health records (EHR) data show that MeTRNN can learn and benefit from meaningful topics.
APPLYING TREE DIAGRAM PROGRAMS IN TEACHING SYNTAX DURING ONLINE LEARNING

During pandemic, teachers and lecturers were trying to make learning process effective through online platforms and programs. Thanks to the technology that it offers a lot of platforms supporting educators in performing the learning process.  Technology also helps in teaching syntax which needs a lot practice including creating tree diagrams of sentences to parse each contituent that requires a platform or program that can lead the students to diagramming. Therefore, this study focused on the effectiveness of applying tree diagram programs in teaching syntax, specifically tree diagrams editor, during online learning. The study used observation and assessment to see whether the use of this program worked to students’ comprehension and motivation. Through lectures, quizzes, and practices, the study found that the use of tree diagram editor was effective to teach syntax during online as it offers practical use, editable sections, and export tool that ease the students to submit their quizzes and examination
Analysis of Variety of Learning Difficulties to Indonesian Language Education Students On English Language Courses at University of Ma'arif NU Kebumen

Mastery of English as an international language is a necessity at this time. Indonesia as a member of the AEC (ASEAN Economic Community) should properly prepare for this challenge by preparing a capable and skilled generation of the nation. English is an international language that is very important for communication and connecting people with the world in various aspects including education. The government shows its seriousness in improving English language skills to the nation's generation, namely by requiring English at the educational level. In reality, there are various difficulties faced by students when learning English, especially in learners / students who are not from the English department called ESP (English for Specific Purposes) Learners. This study aims to dig deeper into the variety of difficulties faced by students in learning English in students of Indonesian Language Education Study Program at FKIP Ma'arif University NU Kebumen. This study uses a qualitative approach with questionnaire instruments, observation and indepth interview. Analysis of research data was carried out through three stages, namely data reduction, data presentation and conclusion drawing. The results of this study indicate that research subjects face a variety of difficulties learning English, namely: 1) lack of student confidence, 2) students rarely use English in daily life and, 3) lack of vocabulary mastery.
Democracy and growth in Africa

Countries in sub-Saharan Africa have experienced a growth revival and substantial democratization. This raises the question, has democracy increased growth in Africa? We test this hypothesis with four different measures of democracy and do not find any strong and robust empirical support for a democracy causes growth story in Africa, but it has not slowed growth either.
PEMANFAATAN TEKNOLOGI UNTUK DESA: E-Village Berbasis Web Menggunakan Framework CodeIgniter di Kantor Desa Pesisir Besuki

The 3M protocol (washing hands, wearing masks and keeping a distance) makes community services that interact directly with the community must be limited. The creation of a Web-based E-village is intended to assist in improving village community services, namely services related to writing letters and information about villages, especially during the Covid-19 pandemic. E-viilage is a web-based application developed using an open source application, namely the Codeigniter framework with the MVC model (Model View and Control). The method of research and system development in this study uses the Waterfall model which includes needs analysis, system design, writing program code, program testing, program implementation and maintenance. This application was built using Visual Studio Code with PHP programming language and Codeigniter Framework and supported by MySQL Database. The conculsion of this study are: (1) Web-based E-village application has been produced at the Pesisir Besuki Village Office. (2) This application can help and facilitate community service, namely writing services at the Pesisir Besuki Village Office, from external test results with proper status an 79.2%
Automated Generation of Optimized Code Implementing SVM models on GPUs

Deploying Support Vector Machine (SVM) models is challenging, since these contain complex math and logic, and also can be composed of a large number of real-valued coefficients; therefore, when performed by humans, the deployment is a slow and error-prone process. From the premise that the process of translating a machine learned predictive model into source code is deterministic and, hence, automatable, this paper's main contribution is demonstrating that it is possible to automate the generation of source code able to efficiently implement SVM models on Graphic Processing Units (GPU), and thus facilitate their operationalization. This research presents: guidelines for the automatic source code generation and efficient execution of SVM models, including code generation for specialized architectures such as GPUs using the Computed Unified Device Architecture (CUDA) platform/language; experimental evidence showing that the resulting source code implements these models efficiently; and a detailed description of the generated source code from sequential up to an optimized version of parallel code. Experiments with a large data set sized up to 9 GB were conducted to show the proposal's feasibility and scalability; such experiments showed an average speed-up of 112.71 times over the sequential, CPU-based, execution of SVMs; additionally, demonstrated a speed-up of 6.2 with respect to other SVM modeling tools running on GPU.
Optical non-classicality as a Quantum Resource in Continuous-Variable Quantum Information

In this thesis we address the problem of building a Quantum Resource Theory in infinite dimension. In particular, we study bosonic non-classicality as a Quantum Resource in continuous-variable Quantum Information. After reviewing the formalism of open quantum systems and Quantum Optics, we introduce the framework of Quantum Resource Theories and we discuss the case of non-classicality, and its applications in Quantum Optics and Quantum Technologies. Finally, we study a Resource Theory of non-classicality based on the standard and measured relative entropies of non-classicality as resource monotones and we prove, for the first time in an infinite-dimensional Resource Theory, a bound for asymptotic conversion rates.
Library Guides: Using One Search: Simple Search

Using the library's search tool, One Search, to find journal articles, books, book chapters and much, much more. This is the way you will search with One Search most often
ANALISIS FAKTOR MENGUASAI ILMU MENDIDIK DALAM MENINGKAT EFEKTIVITAS PEMBELAJARAN PAK OLEH GURU PADA SISWA KELAS VIII SMP NEGERI 2 DOLOKSANGGUL KABUPATEN HUMBANG HASUNDUTAN TAHUN PEMBELAJARAN 2017/2018

Abstract This study aims to analysis the Factors Mastering Educational Sciences in Improving the Effectiveness of PAK, with hypothesis Factors Mastering Educational Sciences in Improving the Effectiveness of PAK Learning by teachers in students of Class eigth Junior High School 2 Doloksanggul Year Learning 2017/2018 75% than expected. This research uses descriptive quantitative method, with research population are all students of Class eight Junior which amounted to 261 people and samples taken 20% so that the sample amounted to 52 people. The research instrument is a closed questionnaire. The trial was conducted to 30 students of class eight Junior High School 1 Doloksanggul. Instrument validity test using Pearson Product Correlation Coefficient formula is obtained rcount rtable that is between 0453 s / d 0.740 3.61 thus the instrument is categorized valid. Test Reliability instrument with Formula Alpha formula obtained r11 = 0.95,thus reliable. From the results of data analysis obtained value of Factors Mastering Educational Science in Improving the Effectiveness of PAK = 84.86% is in very good category. Based on t test obtained t count ttable that is 16,578 1.66 thus H0 rejected and Ha accepted that is Factor Mastering Science Educate in Improve Effectiveness of PAK 75% from which is expected to be accepted. Keywords: Factors Mastering Educational Sciences in Improving the Effectiveness
Attentive pooling for group activity recognition

In group activity recognition, the hierarchical framework is widely used to represent the relationships between individuals and their corresponding groups and has achieved promising performance.However, existing methods simply employ the max/average pooling in this framework, overlooking the distinct contributions of different individuals to the group activity recognition.In this paper, we propose a new contextual pooling scheme, named attentive pooling, which enables weighted information transition from individual actions to group activity.Using the attention mechanism, attentive pooling is intrinsically interpretable and can embed the member context in the existing hierarchical model.To verify the effectiveness of the proposed scheme, two specific attentive pooling methods, i.e., global attentive pooling (GAP) and hierarchical attentive pooling (HAP), are designed.GAP rewards individuals significant to the group activity, while HAP further considers the hierarchical division by introducing the subgroup structure.Experimental results on the benchmark dataset demonstrate that the proposed scheme is significantly superior over the baseline and comparable to state-of-the-art methods.
Fusion of part-of-speech vectors and attention mechanisms for cross-domain sentiment analysis

The grand challenge of cross-domain sentiment analysis is that classifiers trained in a specific domain are very sensitive to the discrepancy between domains. A sentiment classifier trained in the source domain usually have a poor performance in the target domain. One of the main strategies to solve this problem is the pivot-based strategy, which regards the feature representation as an important component. However, part-of-speech information was not considered to guide the learning of feature representation and feature mapping in previous pivot-based models. Therefore, we present a fused part-of-speech vectors and attention-based model (FAM). In our model, we fuse part-of-speech vectors and feature word embeddings as the representation of features, giving deep semantics to mapping features. And we adopt Multi-Head attention mechanism to train the cross-domain sentiment classifier to obtain the connection between different features. The results of 12 groups comparative experiments on the Amazon dataset demonstrate that our model outperforms all baseline models in this paper.
Evaluation of Input/Output Interface using Wrinkles on Clothes

Wearable computing has created textile-based interfaces utilizing the interaction between the user and cloth for operation, as well as the touch and the pinch input operation. The user wears and uses the device in various postures, environments, and operating positions that affect the operation speed and accuracy. However, no study has assessed such factors of touching and pinching using the same input interface. One of the textile interfaces has an input interface using wrinkles on clothes. A ridge of cloth produces a wrinkle that forms naturally on clothes, and the shape of these wrinkles can be recognized by their tactile sensations. Additionally, the act touching or pinching wrinkles does not look strange to an onlooker, which reach that wrinkles have the potential suitable for the wearable computing operation. To reveal the potential, this paper evaluates the input performance using wrinkles on clothes. We designed three touch input methods and one pinch input method for the operation using wrinkles. We implemented the input and the output device which use wrinkles and carried out four evaluations. The results indicated that the pinch input reached the highest accuracy of 98\% of four input methods after learning. The narrowing-down selection reached the fastest input time of 1.64 seconds of four methods after learning. The long press touch and the pinch input achieved the accuracy of 90\% or more in all combination of operating environments and device positions. According to the result of the wrinkle recognition, users have a high accuracy of the identification of wrinkles of 89.4\% and recognize their shape in approximately 12 seconds.
La geografia linguistica di Dante : varietà mediane e perimediane

The central nucleus of the essay examines the observations that Dante makes in De vulgari eloquentia on the vulgaris Ytalie variationes identified by him in the central portion of the Peninsula, within the linguistic domains that today are classified as ‘area mediana’ and ‘area perimediana’. The modern area definition and the one that can be obtained from the ancient vulgaria for these two domains are superimposed on Dante’s linguistic geography defined in the treatise, showing in the partitions proposed here the reflections of actual linguistic data. The extraordinary anticipation of the ‘perimediana’ linguistic area is flanked in De vulgari eloquentia by other brilliant intuitions, from the notion of vulgare latium to that of the principle of variation of languages in space and time, highlighted in the first two paragraphs of the work. Finally, the essay dwells on the analysis of the exemplum of speech proposed by Dante for the Marca Anconitana, highlighting its complex tradition and adding interpretative hypotheses to those proposed so far.
Possíveis associações entre anemia e câncer gástrico

Gastric cancer has been affecting the Brazilian population, especially men and the population aged over 50 years old, and is therefore a relevant topic for promoting quality of life. This neoplasm may present comorbidities, creating obstacles in the patient's prognosis, such as anemia. Thus, herein, the analysis of the possible associations between anemia and gastric cancer, and the categorization tumor staging, histological type, location, gender, age, leukogram and cause of death of patients with gastric cancer treated at the Regional Cancer Hospital (HRC) of Passos- MG, from January 2012 to December 2014, was proposed. This was a cross-sectional observational study with data obtained from documentary sources. The results from the analysis of 78 medical records showed that 69.23% of the patients are men and the predominant age range was between 70 and 80 years (32.04%). The gastric antrum was the most recurrent location of primary tumors (26.92%) and the prevalent histological type was adenocarcinoma (66.67%). Regarding tumor staging, T3, N0, M0 was observed in 23.07% of the cases. Regarding the mortality rate, it was observed that 64.1% of the deaths resulted from cancer. Meanwhile, for the hemogram, 61% anemia was observed, and all presented normal values when the leukogram was analyzed. It is concluded that the majority of gastric cancer patients had anemia, were male, predominantly aged between 70 and 80 years, with adenocarcinoma being the most prevalent type of tumor and gastric antrum being the most affected anatomical region.
Extract of Japanese Text Characteristics of Simpliﬁed Corpora using Non-negative Matrix Factorization

Ways of disseminating(Verbreitungsmedien) information through different media have rapidly changed owing to technological progress, especially in the field of information and communication technologies. Reflecting the changes in terms of conditions of technological progress, communication methods, and abilities have also changed. On the Internet, contents with different expressions of difficulty are mixed even though they have almost the same contents. A user who intends to search for new things or unknown things may get confused and spend a lot of time in selecting contents that are understandable for them because there are large amounts of similar contents with different difficulties. Herein, The characteristics of relevant simplified corpora are critical for everybody. In this research, we propose a method to compare two types of documents with different difficulty, and select a characteristic related to simple of expression from various characteristics related to text. In our proposed method, thousands of text characteristics are compressed and converted by Non-negative Matrix Factorization(NMF), and a basis for characterizing the simplified document is selected. The proposed method combines the characteristics of the most conducted research using the characteristics of 32 types and 2,196 dimensions. We evaluated the text characteristics in the NMF Base of the results using a classifier. As a result of applying the proposed method to two kinds of environment white papers, it became clear that an effective basis can be selected. In Addtionally, We showed estimate of the causation relationships, Optimization of the parameter. Furthermore, We showed flexibility to other media.
The Construction of Next Great Cyber Wall

By first understanding the behavioral consequences of policy changes in cyberspace, we are better able to defend and understand the increasingly connected world in which we live. One of the greatest drivers of human progress in the last couple of decades is the ability to access technology and the internet, but how we enforce cybersecurity is a pressing problem. Cybersecurity requires an interdisciplinary approach to solve the many problems in fields such as fintech, cyber crime, human rights violations, e-commerce, etc. How individual freedoms can be preserved while human progress can be advanced within cyberspace is the focus of the research within this initiative.
Delving into Variance Transmission and Normalization: Shift of Average Gradient Makes the Network Collapse

Normalization operations are essential for state-of-the-art neural networks and enable us to train a network from scratch with a large learning rate (LR). We attempt to explain the real effect of Batch Normalization (BN) from the perspective of variance transmission by investigating the relationship between BN and Weights Normalization (WN). In this work, we demonstrate that the problem of the shift of the average gradient will amplify the variance of every convolutional (conv) layer. We propose Parametric Weights Standardization (PWS), a fast and robust to mini-batch size module used for conv filters, to solve the shift of the average gradient. PWS can provide the speed-up of BN. Besides, it has less computation and does not change the output of a conv layer. PWS enables the network to converge fast without normalizing the outputs. This result enhances the persuasiveness of the shift of the average gradient and explains why BN works from the perspective of variance transmission. The code and appendix will be made available on https://github.com/lyxzzz/PWSConv.