Reviewerly/exHarmony huggingface dataset:
The controlled SWAP test for determining quantum entanglement

Quantum entanglement is essential to the development of quantum computation, communications, and technology. The controlled SWAP test, widely used for state comparison, can be adapted to an efficient and useful test for entanglement of a pure state. Here we show that the test can evidence the presence of entanglement (and further, genuine n-qubit entanglement), can distinguish entanglement classes, and that the concurrence of a two-qubit state is related to the test's output probabilities. We also propose a multipartite measure of entanglement that acts similarly for n-qubit states. The number of copies required to detect entanglement decreases for larger systems, to four on average for many (n>8) qubits for maximally entangled states. For non-maximally entangled states, the average number of copies of the test state required to detect entanglement increases with decreasing entanglement. Furthermore, the results are robust to second order when typical small errors are introduced to the state under investigation.
CGC-Net: Cell Graph Convolutional Network for Grading of Colorectal Cancer Histology Images

Colorectal cancer (CRC) grading is typically carried out by assessing the degree of gland formation within histology images. To do this, it is important to consider the overall tissue micro-environment by assessing the cell-level information along with the morphology of the gland. However, current automated methods for CRC grading typically utilise small image patches and therefore fail to incorporate the entire tissue micro-architecture for grading purposes. To overcome the challenges of CRC grading, we present a novel cell-graph convolutional neural network (CGC-Net) that converts each large histology image into a graph, where each node is represented by a nucleus within the original image and cellular interactions are denoted as edges between these nodes according to node similarity. The CGC-Net utilises nuclear appearance features in addition to the spatial location of nodes to further boost the performance of the algorithm. To enable nodes to fuse multi-scale information, we introduce Adaptive GraphSage, which is a graph convolution technique that combines multi-level features in a data-driven way. Furthermore, to deal with redundancy in the graph, we propose a sampling technique that removes nodes in areas of dense nuclear activity. We show that modeling the image as a graph enables us to effectively consider a much larger image (around 16$\times$ larger) than traditional patch-based approaches and model the complex structure of the tissue micro-environment. We construct cell graphs with an average of over 3,000 nodes on a large CRC histology image dataset and report state-of-the-art results as compared to recent patch-based as well as contextual patch-based techniques, demonstrating the effectiveness of our method.
Trust, Temperature Fluctuations, and Asylum Applications

This paper studies the relationship between generalized trust, temperature fluctuations during the maize growing season, and international migration by asylum seekers. A priori generalized trust can be expected to have an ambiguous effect on migration. On the one hand, countries with higher trust may exhibit higher adaptive capacity to temperature fluctuations and so lower climate-induced migration. On the other hand, trust may also facilitate migration by increasing the likelihood that communities invest in risk sharing through migration and enjoy reliable networks supporting migrants. Hence, it is an empirical question whether trust mitigates or increases the impact of climate change on migration. Our findings are consistent with an ambivalent effect of trust on migration. We find that for moderate temperature fluctuations, trust mitigates the impact of weather on migration. This effect is driven by the role of trust in increasing adaptive capacity. However, for severe temperature fluctuations, communities with higher trust experience more migration. Overall, the former effect dominates the latter, so that the net effect is that trust mitigates migration. Our findings point to important policy implications concerning the role of trust in fostering adaptation by facilitating collective action, and the need for targeted interventions to support adaptation and increase resilience in low-trust societies in which collective action may be harder to achieve.
Research on Leisure Sports Activities Based on Decision Tree Algorithm

The study of competition pressure of athletes has been in the science circle for many years. However, computer science research as a coping strategy has not been involved in the past. Based on this, data mining was applied to the survey data of sports competition stress in this article. The basic theory of content-based recommendation algorithm was studied, including the idea of algorithm, algorithm description and algorithm implementation. Combining with the characteristics of the stressor data of sports competition, the algorithm was further improved from the perspective of similarity calculation and potential semantic analysis, and then the word frequency of the data was calculated to get the most similar suggestions, and the results obtained were analyzed.
Otomasi dan Optimasi Pengaturan Kerja pada Pondok Pesantren Menggunakan Profile Matching

Islamic boarding schools are religious institutions that provide education and teaching and develop and spread Islam. As an institution, Islamic boarding schools have many activities in them. In each activity requires an organizational structure to manage activities so that they are carried out properly. The process of selecting the person in charge is generally directly chosen by the board but this has both positive and negative sides. The positive side shortens the time in the election because there is no selection in determining the person responsible. The negative side of the direct appointment process is that it cannot see the abilities possessed by the candidates in charge of leadership, organization, and so on. This can only be known with the selection process, what often happens is the selection of the person in charge who does not have the appropriate ability. Under these circumstances, we need a system that can help boarding school administrators in facilitating the selection and appointment of the person in charge. In this study, profile matching is used to calculate the compatibility of the profile of the work and the profile of the person in charge. Each person in charge who is sought has each criterion consisting of core factors and secondary factors. The results obtained from this study are decision support systems that produce responsible recommendations in accordance with the criteria for each activity in the boarding school.
Agile methodologies in teams with highly creative and autonomous members

The Agile manifesto encourages us to value individuals and interactions over processes and tools, while Scrum, the most adopted Agile development methodology, is essentially based on roles, events, artifacts, and the rules that bind them together (i.e., processes). Moreover, it is generally proclaimed that whenever a Scrum project does not succeed, the reason is because Scrum was not implemented correctly and not because Scrum may have its own flaws. This grants irrefutability to the methodology, discouraging deviations to fit the actual needs and peculiarities of the developers. In particular, the members of the NASA ADS team are highly creative and autonomous whose motivation can be affected if their freedom is too strongly constrained. We present our experience following Agile principles, reusing certain Scrum elements and seeking the satisfaction of the team members, while rapidly reacting/keeping the project in line with our stakeholders expectations.
Implementation of Сritical Thinking Development Technology in Higher Education Institutions of the Marine Profile in Studying Physics

The paper analyzes the scientific understanding of the essence of the concept of « critical thinking » . The methodological aspects of the implementation of the technology for the development of critical thinking of students of higher educational institutions of the marine profile in studying physics from the experience of the Kherson Maritime Academy is presented. The forms of work and methods of implementing the intended technology at three stages are given: organizational-motivational, operational-cognitive and the implementation of reflection. Use of the elements of problem-based learning and experimental research tasks for the organization of educational and search activities of students in order to develop their critical thinking is justified. Authors have highlighted the problematic situations during studying physics on topics: « Laws of constant electric current » , « Current in different substances » , « Electromagnetic induction » , « Laws of alternating electric current » . An example of the implementation of creative physical experimental tasks using digital technology in the laboratory work on the « Electrics and Magnetism » section is given. An example of the content of creative physical experimental tasks using digital technologies for laboratory work is carried out: 1) « Determination of the electromotive force of the source of the galvanic cell by the compensation method » , 2) « Determination of the capacity of the air condenser with the help of the Sotti bridge » , 3) « Determination of the self-induction coefficient of the solenoid without core by Joubert method » . At the reflection stage, the Senkan priory was proposed in the form of a white poem of five lines, which summarizes the information studied by students during lesson. The specified technique enables students to realize their intellectual and creative abilities, synthesize complex and cumbersome information, and helps teacher to assess the level of the conceptual apparatus, the depth of assimilation of a particular phenomenon or process.
SeqROCTM: A Matlab toolbox for the analysis of Sequence of Random Objects driven by Context Tree Models

In several research problems we deal with probabilistic sequences of inputs (e.g., sequence of stimuli) from which an agent generates a corresponding sequence of responses and it is of interest to model the relation between them. A new class of stochastic processes, namely \textit{sequences of random objects driven by context tree models}, has been introduced to model such relation in the context of auditory statistical learning. This paper introduces a freely available Matlab toolbox (SeqROCTM) that implements this new class of stochastic processes and three model selection procedures to make inference on it. Besides, due to the close relation of the new mathematical framework with context tree models, the toolbox also implements several existing model selection algorithms for context tree models.
Context modeling-based healthcare architecture in Pervasive Computing

Ubiquitous computing seamlessly integrates computers into everyday life in response to information provided by sensors in the environment.This information is generally exploited by several domains namely the healthcare domain.Representing knowledge through building an ontology for healthcare system is important to achieve semantic interoperability among health information, predict the patient real-time context and to better execute decision actions.In this paper, we propose a healthcare system which integrates context ontology in order to provide smart services to the patients.
Certifying Confidence via Randomized Smoothing

Randomized smoothing has been shown to provide good certified-robustness guarantees for high-dimensional classification problems. It uses the probabilities of predicting the top two most-likely classes around an input point under a smoothing distribution to generate a certified radius for a classifier's prediction. However, most smoothing methods do not give us any information about the confidence with which the underlying classifier (e.g., deep neural network) makes a prediction. In this work, we propose a method to generate certified radii for the prediction confidence of the smoothed classifier. We consider two notions for quantifying confidence: average prediction score of a class and the margin by which the average prediction score of one class exceeds that of another. We modify the Neyman-Pearson lemma (a key theorem in randomized smoothing) to design a procedure for computing the certified radius where the confidence is guaranteed to stay above a certain threshold. Our experimental results on CIFAR-10 and ImageNet datasets show that using information about the distribution of the confidence scores allows us to achieve a significantly better certified radius than ignoring it. Thus, we demonstrate that extra information about the base classifier at the input point can help improve certified guarantees for the smoothed classifier. Code for the experiments is available at https://github.com/aounon/cdf-smoothing.
Track-Before-Detect for Bistatic Radar Based on Velocity Filtering

Conventional track-before-detect methods for bistatic radar usually detect weak target according to an approximate target motion model. The inaccuracy of this approximation motion model tends to cause degradation of detection performance. To remedy this issue, a weak target detection algorithm for bistatic radar with velocity filtering based on the accurate target motion model is addressed in this paper. First, the evolutions of bistatic range and incident angle are obtained by the constant velocity motion model in Cartesian coordinate system (CCS). Then, the cells in the bistatic polar coordinate system (PCS) are transformed into the CCS and their positions in the CCS are predicted with the help of the supposed velocity. Further, the predicted positions are transformed inversely into the bistatic PCS and the measurement of each cell is added to that of the cell nearest its predicted position to realize multiframe accumulation. The process of energy integration and the output envelope of bistatic PCS are deduced elaborately. Finally, the effectiveness and superiority of the proposed method is demonstrated by several simulation results.
Few-shot Learning with LSSVM Base Learner and Transductive Modules

The performance of meta-learning approaches for few-shot learning generally depends on three aspects: features suitable for comparison, the classifier ( base learner ) suitable for low-data scenarios, and valuable information from the samples to classify. In this work, we make improvements for the last two aspects: 1) although there are many effective base learners, there is a trade-off between generalization performance and computational overhead, so we introduce multi-class least squares support vector machine as our base learner which obtains better generation than existing ones with less computational overhead; 2) further, in order to utilize the information from the query samples, we propose two simple and effective transductive modules which modify the support set using the query samples, i.e., adjusting the support samples basing on the attention mechanism and adding the prototypes of the query set with pseudo labels to the support set as the pseudo support samples. These two modules significantly improve the few-shot classification accuracy, especially for the difficult 1-shot setting. Our model, denoted as FSLSTM (Few-Shot learning with LSsvm base learner and Transductive Modules), achieves state-of-the-art performance on miniImageNet and CIFAR-FS few-shot learning benchmarks.
Loma Linda University Libraries: Earth & Biological Sciences Guide: Welcome

A guide to the information resources for students in the Department of Earth & Biological Sciences
Philip Holmes and Hans-Olav Enger. <i>Norwegian. A Comprehensive Grammar</i>

The book under review is the outcome of collaborative work by two of well-known linguists representing different grammatical traditions, who nevertheless complement one other quite well. It offers a valuable source of information about the grammar of modern Norwegian in the Bokmal standard and about the orthographic rules that apply to this variant of the language. As the authors themselves stress in the Preface of their grammar, “this is the first attempt to write a truly comprehensive English-language grammar of Bokmal” (p. ix), and in this respect it is indeed a unique publication. This makes it very practical for learners, particularly given the scope of the use of the Bokmal standard among Norwegian speakers – as the authors themselves estimate, “a reasonable guess is that 7 out of 8 Norwegians write Bokmal” (p. 2).
THE CORRELATION BETWEEN THE ENGLISH DEPARTMENT STUDENTS' SELF-EFFICACY AND THEIR WRITING PERFORMANCE

SUMMARY Haibah, Nisrina Nur. 2019. The Correlation between the English Department Students’ Self-Efficacy and Their Writing Performance. Undergraduate Thesis, Department of English, Faculty of Letter, State University of Malang. Advisors: (I) Dr. Ekaning D. Laksmi, M.Pd., M. A. (II) Prof. BambangYudiCahyonoM.Pd., M.A., Ph.D. Key Words : self-efficacy, writing performance This study aims at investigating the correlation between the English Department students’ self-efficacy and their writing performance. Self-efficacy refers to one’s beliefs in one’s ability to complete a task successfully, whereas writing performance describes how well a person accomplishes his/her writing. This study involved thirty six students of the English Department in State University of Malang who were taking the Argumentative Writing course in their fourth semester. The data were obtained by using the self-efficacy questionnaire and writing test. The collected data were then analyzed using the Spearman correlation in SPSS to find out if there was a relationship between the variables or not. The results of the study revealed that the null hypotheses for almost of the correlations was accepted. The alternative hypothesis was only accepted in the correlation between self-efficacy and mechanics writing performance.This result might be attributed to the fact that the use of mechanics in Indonesian writing, which is the students’ native language, and English does not differ greatly. In other words, the findings show that, overall, there is no significant relationship between the students’ self-efficacy and their writing performance. The students with a higher level of self-efficacy does not necessarily have better writing performance than those with a lower level of self-efficacy and vice versa. Finally, it can be concluded that the English Department students’ self-efficacy does not affect their writing performance. Therefore, it is suggested that the lecturers focus more on things that can boost their students’ writing performance such as giving the students exercises on the area that they lack of depending on the context. This study is also expected to contribute to the related literature by clarifying the relationship between students’ self-efficacy and their writing performance. 1 1 1 1 MicrosoftInternetExplorer4 0 2 DocumentNotSpecified 7.8 磅 Normal 0
Aplicación Web en el Proceso de Medición de Resultados del Estudiante del Programa de Ingeniería de Sistemas Computacionales de la Universidad Privada del Norte

The present research was done with the aim of determining the influence of a web application in the student outcomes measurement process of the Computational Systems Engineering program of the Privada del Norte University in 2019. The type of study was pre-experimental; with a sample consisting of the student outcomes measurement processes executed in the semesters 2018-2 and 2019-1. The subprocesses included in the student outcomes measurement process are faculty management, graduates management, pre-professional internship employers management and measurement reports elaboration. The results obtained showed a decrease of 56.5% in the time taken to send the student outcomes measurement tools to the faculty members, a decrease of 82.87% in the data gathering time of the student outcomes measurement conducted by the faculty members, a decrease of 81.18% in the data gathering time of the student outcomes measurement conducted by the program graduates, an increase of 16.36% in the graduates participation level in the data gathering of the student outcomes measurement, a decrease of 79.43% in the data gathering time of the student outcomes measurement conducted by the pre-professional internship employers, an increase of 24.67% in the pre-professional internship employers participation level in the data gathering of the student outcomes measurement, a decrease of 99.83% in the time taken to process and/or analyze the measurement reports information and a decrease of 99.9% in the measurement reports elaboration time . This article is divided into introduction, state of the art, objectives, materials and methods, system implementation methodology, results, discussions and conclusions.
Adversarial Learning for Zero-shot Domain Adaptation

Zero-shot domain adaptation (ZSDA) is a category of domain adaptation problems where neither data sample nor label is available for parameter learning in the target domain. With the hypothesis that the shift between a given pair of domains is shared across tasks, we propose a new method for ZSDA by transferring domain shift from an irrelevant task (IrT) to the task of interest (ToI). Specifically, we first identify an IrT, where dual-domain samples are available, and capture the domain shift with a coupled generative adversarial networks (CoGAN) in this task. Then, we train a CoGAN for the ToI and restrict it to carry the same domain shift as the CoGAN for IrT does. In addition, we introduce a pair of co-training classifiers to regularize the training procedure of CoGAN in the ToI. The proposed method not only derives machine learning models for the non-available target-domain data, but also synthesizes the data themselves. We evaluate the proposed method on benchmark datasets and achieve the state-of-the-art performances.
Requesting and Refusing Politeness Expression Teacherâ€™s Instruction in Teaching Learning Process

This research conducted to describe the request and refusal polite expression when teacher instruct students. The writer has chosen English teacher and the object is 1 teacher. The writer joins in the class and records the activities when teachers teach students. The data analyzed by using qualitative method. The types of politeness are based on the Brown and Levinsonâ€™s theory about politeness strategy that should people use when they instruct others. There are 24 male students and 30 female students who are follow this research. The research instrument to collect the data is through observation the conversation during learning and teaching process. All the utterances relate to politeness strategy produced by the students and teacher write down and 2 conversations are chose to be analyzed based on politeness strategies The result of this research shows that there are three types of instructional activities; motivating students (1 expression), informing students of objective (1 expression), helping students recall prerequisites (1 expression), presenting information and example (1 expression) and providing practice and feedback (7 expressions). Teacher used four types of them, Bald on Record (4 expressions), Positive Politeness (16 expressions), Negative Politeness (6 expressions), and off- record (2 expressions). There are 3 expressions are polite requests and no impolite refusal. From that result, the writer concludes that teacher often to use Positive Politeness by reasoning that it types of politeness strategy is to make the relationship between teacher and students more intimate during teaching learning process. This research can lead other researcher to conduct research on Politeness strategy. It also can lead the teachers and the students to make a good interaction by applying the politeness strategy in the classroom so that they can maintain a good communication one another