Reviewerly/exHarmony huggingface dataset:
Contextual Subspace Variational Quantum Eigensolver

We describe contextual subspace variational quantum eigensolver (CS-VQE), a hybrid quantum-classical algorithm for approximating the ground state energy of a Hamiltonian. The approximation to the ground state energy is obtained as the sum of two contributions. The first contribution arises from a noncontextual approximation to the Hamiltonian, and is computed classically. The second contribution is obtained by using the variational quantum eigensolver (VQE) technique to compute a contextual correction on a quantum processor. In general the VQE computation of the contextual correction uses fewer qubits and measurements than the VQE computation of the original problem. Varying the number of qubits used for the contextual correction adjusts the quality of the approximation. We simulate CS-VQE on tapered Hamiltonians for small molecules, and find that the number of qubits required to reach chemical accuracy can be reduced by more than a factor of two. The number of terms required to compute the contextual correction can be reduced by more than a factor of ten, without the use of other measurement reduction schemes. This indicates that CS-VQE is a promising approach for eigenvalue computations on noisy intermediate-scale quantum (NISQ) devices.
Machine Learning Algorithms for Data Labeling: An Empirical Evaluation

The lack of labeled data is a major problem in both research and industrial settings since obtaining labels is often an expensive and time-consuming activity. In the past years, several machine learning algorithms were developed to assist and perform automated labeling in partially labeled datasets. While many of these algorithms are available in open-source packages, there is no research that investigates how these algorithms compare to each other in different types of datasets and with different percentages of available labels. To address this problem, this paper empirically evaluates and compares seven algorithms for automated labeling in terms of accuracy. We investigate how these algorithms perform in six different and well-known datasets with three different types of data, images, texts, and numerical values. We evaluate these algorithms under two different experimental conditions, with 10\% and 50\% labels of available labels in the dataset. Each algorithm, in each dataset for each experimental condition, is evaluated independently ten times with different random seeds. The results are analyzed and the algorithms are compared utilizing a Bayesian Bradley-Terry model. The results indicate that while the algorithms label spreading with K-nearest neighbors perform better in the aggregated results, the active learning algorithms query by instance QBC and query instance uncertainty sample perform better when there is only 10\% of labels available. These results can help machine learning practitioners in choosing optimal machine learning algorithms to label their data.
Library System: Library Access Instructions: EZproxy

This guide provides instruction on what credentials to use when prompted by the EZproxy login page.
Using any number of hidden neurons

In Chapter 4, latest implementation is able to work with any number of inputs. Chapter 5 extended this implementation to work with a hidden layer with just 2 neurons. In this chapter, the implementation will be extended to use any number of neurons in a single hidden layer. There are 2 examples discussed. The first one uses 5 neurons in the hidden layer rather than just 2 as in Chapter 5. The second example extends such an implementation to work with any number of hidden neurons within a single hidden layer.
Phase Evaluation Algorithm

In a number of quantum-mechanical problems, you need to define eigenvalues of some unitary operator U: $$U\left| {\psi }\right\rangle = \lambda \left| {\psi }\right\rangle ,$$where \(\left| {\psi }\right\rangle \) is a known eigenvector of operator U, \(\lambda \) is an eigenvalue, which needs to be defined. Due to the unitarity of U, the equality \(|\lambda | = 1\) is fulfilled, and therefore the eigenvalue can be represented as \(\lambda = e^{2\pi \i \varphi }\), where \(\varphi \) is a real number (as it is said, the transformation phase) satisfies the condition \(0\leqslant \varphi <1\). Let the bit representation of the value \(\varphi \) is finite: $$\varphi = 0{.}\varphi _1\varphi _2\dots \varphi _n.$$In the phase estimation algorithm, there will be used 2 quantum registers, the first of which contains n qubit, originally pre-set in \(\left| {0}\right\rangle \). The second register is originally in the state \(\left| {\psi }\right\rangle \), the number of qubits in this register depends on the specific type of the operator U.
Listing the Positive Rationals

We start with a review of the usual method for listing the rationals. Consider an infinite array with the rows and columns indexed by the positive integers. The entry in the ith row and jth column ...
정책공간에서 ‘순수’예술이 갖는 함의: 음악장르를 중심으로

Today, there are many different names that are used inattentively for music in the field of policies, including culture and arts, literature, Gukak, Yangak, cultural content, pure arts, pure music, and basic arts. These various names have been called or appeared in the context of new power or change of regime. Focusing on this point, this study summarized the implications of pure music in the field of policies into a battlefield of ideologies. The purpose of the study is to investigate the process of pure arts appearing in national records in the 2000s based on the patterns of the administration making an intervention into cultural policies with its political motivations and regulating the genre or music.The way the government defines the domain of music institutionally and how music is transcribed in government documents reflect the way the government recognizes and perceives music. A common idea may be that music has been divided, becoming an internal musical factor or making a natural relation with the culture of the society. The fact is, however, that music has been incorporated and divided in a dominant ideology or has had its division controlled by the effect of ideology and the goal of a policy. The administration has expressed its political motivations with its ideology of cultural policies and regulated the division of the music domain via corresponding policies. This has been possible because music has formed close correlations with the ruling ideology of the administration as an object of its cultural policies.In conclusion, Music was placed in the field of policies with different meanings as it was perceived by the government. During the military regime, music wandered between the options of self-censorship through creative support and compliance to the regime. It ended up into ambiguity that prevented pure music from being chosen as a policy term. It remained in the social and cultural consciousness as a non-policy transcription, forming relations with society. These findings suggest that the implication of pure arts'' first appearance as a policy slogan during the people''s government in the 2000s is an aphorism for pure that wandered around, not being included into the boundary of policy transcriptions during the military regime.
Classification of Video Recaptured from Display Device

The prevention from unauthorized recapturing of screen is an important issue in multimedia security. In this study, we attempt to detect illegally created videos captured from display devices by analyzing unnatural signals contained in the videos. The proposed approach applies a convolutional deep neural network (CNN) for the classification. In order to reduce the computational costs, some frames are sampled from a target video, and are checked whether they are captured. In the training process, each frame sampled from captured/natural videos is partitioned into small patches, and a CNN model is trained by using the patches. The final decision is determined from the classification results at each frame. We conducted experiments to evaluate the classification accuracy and its dependency on camera devices. It is confirmed that we can classify captured and natural videos with high probability under our experimental conditions. When a same camera device is used for recording both original and recaptured videos, the classification accuracy is decreased from the case of different devices.
Studi Deskriptif Kemampuan Membaca Anak Kelompok B ditinjau Dari Status Jender Di PAUD Segugus Kelapa Kecamatan Karang Tinggi Bengkulu Tengah

The  purpose of this research was to describe the differences in reading ability of children in group B in terms of gender status. The population in this study were all children in group B in PAUD Kelapa cluster, Karang Tinggi District, Central Bengkulu. The research sample of 38 children was taken using total sampling. The variables in this study were gender and reading ability. The data collection technique used was a test. The data analysis technique used the Mann-Whitney formula. The results showed that the reading ability of group B children in PAUD Kelapa cluster for boys with an average of 51.30% with sufficient criteria. Whereas for girls with an average of 90.72% with very good criteria. The results of the hypothesis test for reading skills indicate that the acquisition of asymp values. Sig. (2-tailed) or P value of 0.000 <0.05, then H0 is rejected or there is a difference. So, it can be concluded that the gender factor is one of the factors that determines the reading ability of Group B children in terms of gender status in PAUD Kelapa cluster, Karang Tinggi District, Central Bengkulu. Keywords: Reading ability, gender, Children group B
Real-Time Self-Testing Quantum Random Number Generator with Non-classical States

The certification of private randomness of quantum origin is paramount for cryptographic applications. By trusting the measurement device, conjugate quadrature measurements allows us to quantify insecure side-information on the measured state with bounded energy. We demonstrate a live self-checking random number generator using squeezed states.
DA-AR-Net: an attentive activation based Deformable auto-encoder for group-wise registration

Medical image registration over the past many years has been dominated by techniques which rely on expert an- notations, while not taking advantage of the unlabelled data. Deep unsupervised architectures utilized this widely available unlabelled data to model the anatomically induced patterns in a dataset. Deformable Auto-encoder (DAE), an unsupervised group-wise registration technique, has been used to generate a deformed reconstruction of an input image, which also subsequently generates a global template to capture the deformations in a medical dataset. DAEs however have significant weakness in propagating global information over range long dependencies, which may affect the registration performance on quantitative and qualitative measures. Our proposed method captures valuable knowledge over the whole spatial dimension using an attention mechanism. We present Deformable Auto-encoder Attention Relu Network (DA-AR-Net), which is an exquisite integration of the Attention Relu(Arelu), an attention based activation function into the DAE framework. A detachment of the template image from the deformation field is achieved by encoding the spatial information into two separate latent code representation. Each latent code is followed by a separate decoder network, while only a single encoder is used for feature encoding. Our DA-AR-Net is formalized after an extensive and systematic search across various hyper-parameters - initial setting of learnable parameters of Arelu, the appropriate positioning of Arelu, latent code dimensions, and batch size. Our best architecture shows a significant improvement of 42% on MSE score over previous DAEs and 32% reduction is attained while generating visually sharp global templates.
STUDY ON GEOLOGICAL HAZARDS ASSESSMENT IN TYPICAL TRANSMISSION CHANNEL

Transmission line is one of the most important lifelines. It often crosses a long transmission distance and covers a wide range. Along the transmission line the environmet significantly varies; the geomorphological and geological conditions are complext, w,which makes the transmission line is threaten by geological hazards. Especially in recent years, affected by extreme climate, the geological hazards along the important transmission lines appear to be of high-frequency. The situation of hazards prevention and control is severe. In order to guarantee the safe operation of massive power grid in extereme environment, the geological hazards risk assement of important transmission lines is urgently needed. In this paper the selected indices include:slope, aspect, slope length, curvature, cutting depth, road buffering, river buffering, surface roughness, surface deformation, surface moisture content etc. By using the contribution weight model to evaluate the geological hazard of the typical transmission channel named Lu Mao line. The results show that,(1)the most contribution rate of geological hazards is aspect, then slope, river buffering, road buffering and so on. (2)The whole transmission channel is mainly in the lower hazard area and the moderate hazard area, and the area accounts for 58.22% of the whole area. (3)From the low risk area to the high hazard area the disaster distribution density gradually increases, from no disaster to 0.536/km2. And the hazard degree of each pole tower was analyzed and evaluated.
THE EFFECTIVENESS OF HERRINGBONE TECHNIQUE IN TEACHING READING COMPREHENSION

This study aims to find out whether or not the use of Herringbone technique is effective in teaching reading comprehension to the eighth grade students of SMP Negeri 19 Palu. The research applied quasi-experimental design. The samples of this study were 24 students in VIII C as the experimental group and 26 students in VIII A as the control group. They were selected by purposive sampling technique. To collect the data, test which divided into pre-test and post-test was used as the research instrument. The mean score of pre-test for the experimental group and control group were 50.42 and 54.1 respectively. The mean score of the post-test for the experimental group and control group were 71.25 and 64.23. The result of the test was analyzed statistically by applying T-test formula and interpolation formula using degree of freedom (df) 48 and 0.05 of the significance level. This research indicates that the t-counted value (3.752) is higher than the t-table (1.679). In other words, the hypothesis of this research is accepted. Keywords: effectiveness, reading comprehension, Herringbone  technique. Abstrak Penelitian ini bertujuan untuk mengetahui apakah Herringbone teknik efektif dalam mengajar pemahaman membaca kepada siswa kelas delapan SMP Negeri 19 Palu. Penelitian ini menerapkan desain quasi-eksperimental. Sampel penelitian ini adalah 24 siswa di VIII C sebagai kelompok eksperimen dan 26 siswa di VIII A sebagai kelompok kontrol. Mereka dipilih dengan teknik purposive sampling. Untuk mengumpulkan data, tes yang dibagi menjadi pre-test dan post-test, digunakan sebagai instrumen penelitian. Nilai rata-rata pre-test untuk kelompok eksperimen dan kelompok kontrol masing-masing adalah 50 , 42 dan 54,1. Nilai rata-rata post-test untuk kelompok eksperimen dan kelompok kontrol adalah 71,25 dan 64,23. Hasil tes dianalisis secara statistik dengan menerapkan rumus T-test dan rumus interpolasi menggunakan derajat kebebasan (df) 48 dan tingkat signifikansi 0,05. Penelitian ini menunjukkan bahwa nilai t-hitung (3,752) lebih tinggi dari t-tabel (1,679). Dengan kata lain, hipotesis penelitian ini diterima. Kata kunci: keefektifan, pemahaman membaca, Teknik Herringbone.
Bayesian Optimization with a Prior for the Optimum

While Bayesian Optimization (BO) is a very popular method for optimizing expensive black-box functions, it fails to leverage the experience of domain experts. This causes BO to waste function evaluations on bad design choices (e.g., machine learning hyperparameters) that the expert already knows to work poorly. To address this issue, we introduce Bayesian Optimization with a Prior for the Optimum (BOPrO). BOPrO allows users to inject their knowledge into the optimization process in the form of priors about which parts of the input space will yield the best performance, rather than BO's standard priors over functions, which are much less intuitive for users. BOPrO then combines these priors with BO's standard probabilistic model to form a pseudo-posterior used to select which points to evaluate next. We show that BOPrO is around 6.67x faster than state-of-the-art methods on a common suite of benchmarks, and achieves a new state-of-the-art performance on a real-world hardware design application. We also show that BOPrO converges faster even if the priors for the optimum are not entirely accurate and that it robustly recovers from misleading priors.
A Novel Transformation Watershed Image Segmentation Model in Digital Elevation Maps Processing

Computer analysis of image objects starts with finding them-deciding which pixels belong to each object. Digital elevation maps or models (DEMs) are arrays of numbers representing the spatial distribution of terrain elevations. They can be seen as gray-scale images, whereby the value of a pixel represents an elevation rather than a luminance intensity (the brighter the gray-tone level of a pixel, the higher the elevation of the terrain point corresponding to this pixel). Useful applications of DEMs can be found in civil/rural engineering, geographic information systems (GIS), geomorphology, water resources management, photogrammetry, satellite imaging. A watershed is defined as a region of land that assists in draining water (usually rainwater) into a river or a creek. It is an area of high ground through which water flows into the river or creek. Simply defined, the watershed is a transformation in grayscale images. This technique aims to segment the image, typically when two regions-of-interest are close to each other, their edges touch. Thus far, we have discussed segmentation based on three principal concepts.
An information-theoretic framework for learning models of instance-independent label noise

Given a dataset D with label noise, how do we learn its underlying noise model? If we assume that the label noise is instance-independent, then the noise model can be represented by a noise transition matrix QD. Recent work has shown that even without further information about any instances with correct labels, or further assumptions on the distribution of the label noise, it is still possible to estimate QD while simultaneously learning a classifier from D. However, this presupposes that a good estimate of QD requires an accurate classifier. In this paper, we show that high classification accuracy is actually not required for estimating QD well. We shall introduce an information-theoretic-based framework for estimating QD solely from D (without additional information or assumptions). At the heart of our framework is a discriminator that predicts whether an input dataset has maximum Shannon entropy, which shall be used on multiple new datasets D^ synthesized from D via the insertion of additional label noise. We prove that our estimator for QD is statistically consistent, in terms of dataset size, and the number of intermediate datasets D^ synthesized from D. As a concrete realization of our framework, we shall incorporate local intrinsic dimensionality (LID) into the discriminator, and we show experimentally that with our LID-based discriminator, the estimation error for QD can be significantly reduced. We achieved average Kullback--Leibler loss reduction from 0.27 to 0.17 for 40% anchor-like samples removal when evaluated on the CIFAR10 with symmetric noise. Although no clean subset of D is required for our framework to work, we show that our framework can also take advantage of clean data to improve upon existing estimation methods.
Making Bilingual Brochure and Guide Book “Making Chocolate Powder” at Griya Cokelat Nglanggeran

ABSTRACTThis internship report was written based on the internship program at POKDARWIS Nglanggeran, Gunungkidul, duringJanuary, 6th  2020- March, 6th 2020. The content of the report are to explain the internship activities, problems which are meet during the internship, and solutions to solve all of the problems during the internship at POKDARWIS Nglanggeran.The main activities during the internship at POKDARWIS Nglanggeran were making bilingual brochure and guide book “making chocolate powder”at griya cokelat nglanggeran. There were four steps of translation that I used such as reading all the source texts, translating the source texts into target texts, editing and rechecking the translation texts, and submitting the final translation texts. I met some problems while translating the texts, such as bad structure of source text, translating difficult or unfamilliar words.To solve all of the problems I asked to the manager of Giya Cokelat's about the content of brochure and guide book. I usedonline dictinaries such as glosbe.com, kateglo.com and mariem webster on internet to search about the meaning of difficult or unfamilliar words in the source texts.
THE INTERNET AND ITS IMPACT ON MORAL DEVELOPMENT OF SECONDARY SCHOOL STUDENTS IN RIVERS STATE

The internet has since its inception contributed to the societal development of today’s society. Today, it has become indispensible to the day-to-day activities of millions of individuals and organizations. The internet offers information to practically every aspect of human life and this portend danger for the adolescents in today’s society. Scholars have highlighted the fragile mind adolescents have and the impact their environment and social media have on their behaviour, religion and educational performance. As such, the relationship between the internet and morality cannot be overlooked. This study therefore seeks to critically investigate the impact of the internet and moral development of secondary school students. Three objectives and research questions guided the study. The study employed a descriptive survey design and selected a sample population of 349 students in secondary schools in Rivers State using simple random sample method. Instrument for this research was a self-structured questionnaire titled Internet and its Impact on Moral Development of Secondary School Students in Rivers State Questionnaire (IIMDSSSQ). In answering the research questions and testing the hypothesis, mean and z-test were employed respectively. The findings from this research established that internet services have a negative correlation on moral and social development, sexual behaviour and pattern of dressing. The study amongst other recommendations highlighted that; State Ministry of Education and other stakeholders in the education sector should as a matter urgent importance introduce moral education as one of the compulsory subjects in secondary schools in Rivers State to enable the students to be guided on the use of internet services in today’s digital world where learning are more facilitated electronically.