Reviewerly/exHarmony huggingface dataset:
A Fusion Algorithm of Multi-model Pruning and Collaborative Distillation Learning

Abstract In order to improve the prediction performance, the complex depth network model needs a large number of calculation parameters, and the negative impact is the fact that it greatly increases the calculation time and energy consumption. In this paper, a fusion algorithm of model pruning and joint multi-model knowledge distillation learning is proposed. By constructing an adaptive joint learning loss function including distillation, multi-model training is carried out. This method can replace the training process of model fine-tuning after pruning. In this paper, firstly, multi classification tasks are carried out on different model structures and data sets, and a complex network model with good effect is trained as a teacher’s model. Then, the channel pruning process of random pruning degree is executed to generate multiple student models. Finally, the accuracy of multiple student models is improved by using this method. The experimental results show that this method effectively improves the accuracy of each model after pruning, and the experimental results achieve a suitable balance between model performance and accuracy.
Objective Construction of Ground Truth Images

In the context of virtual and augmented reality, computer vision plays a pivotal role. To benchmark performance, evaluation of computer vision models, such as edge detection is essential. Traditionally this has relied on subjective analysis of the resultant images. Alternatively, models have been assessed against ground truth images. However, ground truth images are highly subjective, relying on human judging to determine the appropriate location of features. Literature complains about the lack of objective quantitative measures for model evaluation, yet no solution has been presented. Ground truth is the objective verification of properties of an image. In the context of this paper it is a data set that includes an accurate and complete representation of the edges. The subjective nature of creating ground truth images has meant that true image analysis model evaluation has been limited. Reducing the level of subjective decisions can improve the confidence level when measuring the performance of computer vision image analysis models. This work describes a new method to improve ground truth image confidence through an automated computer vision feature detection model voting system.
SentiQ: A Probabilistic Logic Approach to Enhance Sentiment Analysis Tool Quality

The opinion expressed in various Web sites and social-media is an essential contributor to the decision making process of several organizations. Existing sentiment analysis tools aim to extract the polarity (i.e., positive, negative, neutral) from these opinionated contents. Despite the advance of the research in the field, sentiment analysis tools give \textit{inconsistent} polarities, which is harmful to business decisions. In this paper, we propose SentiQ, an unsupervised Markov logic Network-based approach that injects the semantic dimension in the tools through rules. It allows to detect and solve inconsistencies and then improves the overall accuracy of the tools. Preliminary experimental results demonstrate the usefulness of SentiQ.
Typo handling in searching of Quran verse based on phonetic similarities

The Quran search system is a search system that was built to make it easier for Indonesians to find a verse with text by Indonesian pronunciation, this is a solution for users who have difficulty writing or typing Arabic characters. Quran search system with phonetic similarity can make it easier for Indonesian Muslims to find a particular verse. Lafzi was one of the systems that developed the search, then Lafzi was further developed under the name Lafzi+. The Lafzi+ system can handle searches with typo queries but there are still fewer variations regarding typing error types. In this research Lafzi++, an improvement from previous development to handle typographical error types was carried out by applying typo correction using the autocomplete method to correct incorrect queries and Damerau Levenshtein distance to calculate the edit distance, so that the system can provide query suggestions when a user mistypes a search, either in the form of substitution, insertion, deletion, or transposition. Users can also search easily because they use Latin characters according to pronunciation in Indonesian. Based on the evaluation results it is known that the system can be better developed, this can be seen from the accuracy value in each query that is tested can surpass the accuracy of the previous system, by getting the highest recall of 96.20% and the highest Mean Average Precision (MAP) reaching 90.69%. The Lafzi++ system can improve the previous system.
PROBLEMS AND PROSPECTS OF CREATION OF QUANTUM COMMUNICATION SYSTEMS

Scientific and technological problems and prospects for creating quantum communication systems are herein outlined. A brief analysis of the state of scientific research in this area abroad is carried out. The strengths and weaknesses of the implementation of quantum information processing technology are reflected.
자치경찰제 도입 추진상의 문제점과 대응 전략

The government''s model about Local police system was finalized and submitted to the bill. Nevertheless, criticism of this model is emerging. On the one hand, this criticism is positive in that it can create a more rational system through healthy discussion. On the other hand, it is negative to build consensus on the introduction of local police system and secure driving force through it.Many governments have tried to introduce local police system, but this has not led to successful legislation. Within the current government period, it is necessary to secure the driving force for the passage of the bill.Some problems can also be found in legislation to introduce local police system. For example, First the scope of office of autonomous police is excessively enumerated. Second, the right to first action in urgent situations is so limited. Third, the requirements for bill revision are too strict.There is also a need for consensus on local police system. There is doubt that autonomous police is a ‘better’ or ‘wiser’ choice. Because they are used to the centralized state police. It is also because security is stable.In view of this, This article first examines the problems and alternatives of the legislation for the introduction of the local police system. Second, look back on your progress and check for any problems. Based on this, we propose strategic countermeasures to continue the driving force for the introduction of the autonomous police system.
Not one but many Tradeoffs: Privacy Vs. Utility in Differentially Private Machine Learning

Data holders are increasingly seeking to protect their user's privacy, whilst still maximizing their ability to produce machine models with high quality predictions. In this work, we empirically evaluate various implementations of differential privacy (DP), and measure their ability to fend off real-world privacy attacks, in addition to measuring their core goal of providing accurate classifications. We establish an evaluation framework to ensure each of these implementations are fairly evaluated. Our selection of DP implementations add DP noise at different positions within the framework, either at the point of data collection/release, during updates while training of the model, or after training by perturbing learned model parameters. We evaluate each implementation across a range of privacy budgets, and datasets, each implementation providing the same mathematical privacy guarantees. By measuring the models' resistance to real world attacks of membership and attribute inference, and their classification accuracy. we determine which implementations provide the most desirable tradeoff between privacy and utility. We found that the number of classes of a given dataset is unlikely to influence where the privacy and utility tradeoff occurs. Additionally, in the scenario that high privacy constraints are required, perturbing input training data does not trade off as much utility, as compared to noise added later in the ML process.
Surrealistic Code in Fiction: Definition and Realization

The paper aims to identify the role of a style code in surrealistic fiction throughout its history. The article analyses attempts to formulate a universal definition of surrealistic trends. Scientific originality of the study lies in the fact that the researcher develops a scheme of interaction of a special style code (surrealistic code), the surrealistic conceptual sphere and literary texts proper correlating with the surreal. The conducted research allows concluding that surrealistic conceptions are largely a surjective function of a code and have minimum two arguments, which ensures the surrealistic style identification.
Development of students’ creativity

The article discusses the problem of meaningful differentiation of creativity. Depending on the scope of functioning, two types of creativity are distinguished: subject and social. Subject creativity operates in the context of subject activity, social – in communication. They differ not only in content, complexity and functioning conditions, but also in the dynamics of age development. The author presents the results of an experimental study of creativity in students of primary, middle and senior school age of 248 people in total. It has been established that in all age groups, subject creativity in its development is ahead of social creativity. This is due to the features of the existing education system that is focused on the formation of not social, but subject thinking. Both types of creativity are characterized by uneven age development. However, the change in the pace of age-related development of subject and social creativity is not synchronous.
Encouraging an appropriate representation simplifies training of neural networks

Abstract A common assumption about neural networks is that they can learn an appropriate internal representation on their own, see e.g. end-to-end learning. In this work we challenge this assumption. We consider two simple tasks and show that the state-of-the-art training algorithm fails, although the model itself is able to represent an appropriate solution. We will demonstrate that encouraging an appropriate internal representation allows the same model to solve these tasks. While we do not claim that it is impossible to solve these tasks by other means (such as neural networks with more layers), our results illustrate that integration of domain knowledge in form of a desired internal representation may improve the generalization ability of neural networks.
Dealing with hate to boost multiculturalism in colleges/schools of education

Abstract Hate has always been a part of our lives and world. We have rationalized about it and pretended that it is a personality difference that is not very harmful and hurtful. However, hate continues to be devastating and visible in the forms of discrimination, racism, xenophobia, linguistic superiority, religious bigotry, Messiah Complex, White supremacy, and prejudice, to mention a few. At Colleges/Schools of Education (C/SOE) and their respective colleges and universities, hate and its related problems continue to manifest themselves in these institutions in divergent ways, thereby making them unsafe, unhealthy, and uncomfortable environments to culturally and linguistically diverse (CLD) and vulnerable individuals who have been traditionally devalued, disenfranchized, disadvantaged, and disillusioned. In this article, I discuss the dangers of hate in C/SOE and recommend what we can do to boost multiculturalism in these educational environments.
Model of A Practice-Oriented Educational Program

One of the main educational problems in the Russian Federation in the past ten years is to organise a practice-oriented approach. This article substantiates this problem and provides possible ways to solve it. To establish important elements of the educational program to prepare highly qualified specialists, a model of practice-oriented educational programs is developed. It represents the educational process as a set of professional objectives for professional activities development. At the same time, a strong link is established between several academic disciplines represented by interdisciplinary courses. The professional task model is described in details to form an unambiguous understanding of the algorithm of actions performed, methods and tools used, potential risks and the final result. The results obtained can be used to unify the legal documentation that accompanies the educational process, and to compile practice-oriented educational courses or study guides.
Blockchain in Business

While we are looking toward the future in this book, it is still crucial for you to understand the past. There have been some “experiments” in the past, such as B-money, which was a type of cryptocurrency released in 1998 by Wei Dai. (Bitcoin was even named after B-money, so its importance cannot be underestimated.) Even before the emergence of B-money, David Chaum created ecash in 1983. People often have the idea that the search for a real “digital” currency is something new, but ever since the advent of the Internet, people have been searching for ways to implement digital currencies securely. It is in this pursuit that blockchain finds its roots. Technologies rooted in security (such as hashcash) and the idea of peer-to-peer networks (which we know from file sharing applications such as Napster and BitTorrent) all also crucial parts that eventually led to the blockchain technology.
UDC 2020 Challenge on Image Restoration of Under-Display Camera: Methods and Results

This paper is the report of the first Under-Display Camera (UDC) image restoration challenge in conjunction with the RLQ workshop at ECCV 2020. The challenge is based on a newly-collected database of Under-Display Camera. The challenge tracks correspond to two types of display: a 4k Transparent OLED (T-OLED) and a phone Pentile OLED (P-OLED). Along with about 150 teams registered the challenge, eight and nine teams submitted the results during the testing phase for each track. The results in the paper are state-of-the-art restoration performance of Under-Display Camera Restoration. Datasets and paper are available at https://yzhouas.github.io/projects/UDC/udc.html.
Application-driven quantum and statistical physics: a short course for future scientists and engineers, volume 2: equilibrium

"Application-driven quantum and statistical physics: a short course for future scientists and engineers, volume 2: equilibrium." Contemporary Physics, 61(3), pp. 220–221
Research on Speech Recognition Technology in English Pronunciation Similarity

Abstract Authentic English pronunciation is very important in daily communication and mutual understanding. With the improvement of automatic speech recognition technology, the computer-aided pronunciation practice (CAPT) system can already provide limited interaction for second language learners. Pronunciation similarity comparison is a key step in building a system, designing a model that recognizes the similarity of English pronunciations. By calculating the similarity between the learner’s pronunciation and the standard voice, and comparing with the expert’s score on the learner’s pronunciation, the correlation between the two is calculated to verify the feasibility and effectiveness of the model.
Encoding polylexical units with TEI Lex-o: A case study

The modelling and encoding of polylexical units, i.e. recurrent sequences of lexemes that are perceived as independent lexical units, is a topic that has not been covered adequately and in sufficient depth by the Guidelines of the Text Encoding Initiative (TEI), a de facto standard for the digital representation of textual resources in the scholarly research community. In this paper, we use the Dictionary of the Portuguese Academy of Sciences as a case study for presenting our ongoing work on encoding polylexical units using TEI Lex-0, an initiative aimed at simplifying and streamlining the encoding of lexical data with TEI in order to improve interoperability. We introduce the notion of macro- and microstructural relevance to differentiate between polylexicals that serve as headwords for their own independent dictionary entries and those which appear inside entries for different headwords. We develop the notion of lexicographic transparency to distinguish between those units which are not accompanied by an explicit definition and those that are: the former are encoded as &lt;form&gt;–like constructs, whereas the latter becomes &lt;entry&gt;–like constructs, which can have further constraints imposed on them (sense numbers, domain labels, grammatical labels etc.). We codify the use of attributes on &lt;gram&gt; to encode different kinds of labels for polylexicals (implicit, explicit and normalised), concluding that the interoperability of lexical resources would be significantly improved if dictionary encoders would have access to an expressive but relatively simple typology of polylexical units.
Fuzzy SVM Clustering using Plane Sweep Algorithm in Big Data Mining

The era of Big Data is leading to an enormous growth of digital information. Text mining is akin in nature to data mining. Text mining is the practice of examining and discovering big amounts of unstructured text data assisted by software that can classify patterns, topics, concepts, keywords and other attributes in the data. Powerful technique for data classification is Support Vector Machine (SVM). SVM makes a decision surface by creating an optimal separating hyper-plane, to divide the data points of different kinds in the vector space. Clustering the text takes a special place since it is reliable and easy to configure. To cluster big datasets and to shrink the computational time, Hadoop distributed platform, MapReduce programming standard is used by issuing clustering job across various computing nodes or handling Big Data MapReduce is proven state of art technology. In Big Text Data analysis MapReduce provides a faster implementation and is a powerful tool. In the event of a big data like server having a difficulty in providing the services furthermore, additional servers in the cluster can take the load. A powerful approach for solving difficulties including geometric objects in a plane known as Plane Sweep algorithm. The key benefit of using plane sweep algorithm is that it clusters more related data into a cluster hence retrieval will be extra fast and accurate. The Evaluation result shows that the proposed approach provided better result when compared with other approaches.
Human Body Model Fitting by Learned Gradient Descent

We propose a novel algorithm for the fitting of 3D human shape to images. Combining the accuracy and refinement capabilities of iterative gradient-based optimization techniques with the robustness of deep neural networks, we propose a gradient descent algorithm that leverages a neural network to predict the parameter update rule for each iteration. This per-parameter and state-aware update guides the optimizer towards a good solution in very few steps, converging in typically few steps. During training our approach only requires MoCap data of human poses, parametrized via SMPL. From this data the network learns a subspace of valid poses and shapes in which optimization is performed much more efficiently. The approach does not require any hard to acquire image-to-3D correspondences. At test time we only optimize the 2D joint re-projection error without the need for any further priors or regularization terms. We show empirically that this algorithm is fast (avg. 120ms convergence), robust to initialization and dataset, and achieves state-of-the-art results on public evaluation datasets including the challenging 3DPW in-the-wild benchmark (improvement over SMPLify 45%) and also approaches using image-to-3D correspondences
Evaluación diagnóstica de habilidades de pensamiento e informacionales a través del diseño y aplicación de tres instrumentos para estudiantes de primer grado de educación primaria

This article takes as reference the problems that exist due to the lack of reading, mathematics and science skills, according to the reality of the Mexican public education system, as well as the results obtained in the evaluations promoted by the Organisation for Economic Cooperation and Development (OECD). The research was based on a quantitative study, which was conducted from a diagnostic evaluation on the development of information and thinking skills in children in basic education school. This research designed and applied three instruments on thinking skills, mathematical thinking, and information, language and communication skills in children. The research aimed to know the level of skills developed prior to joining the program of the new educational model proposed by the Ministry of Public Education (SEP) of Mexico when applying the method of the diagnosis of educational situation (DS) that has the following components: i) an examination of 20 exercises to measure the level of development of each skill under study; ii) a rubric to evaluate the children’s responses; and iii) a table to record the results of each skill. The diagnostic evaluation concluded that students, who are in the preoperative stage, have some development in their thinking skills (observation, comparison, classification, ordering, inferences, memory and storytelling), linguistic skills (they write their name, without surnames, communicate emotions, tell short stories, oral language stands out), and informative skills (there are no notions of concepts that intervene).
An Analysis of the Major Themes in Khaled Hosseini’s Novel “The Kite Runner”

This study aims to analyze the major theme in The Kite Runner novel, by Khaled Hosseini. In line with the previous research problem, the objective is to find out and describe the process of major themes analysis in the novel. This research was conducted based on developmental research. This research is qualitative research which employed documentation as the data collection. In this analysis the writer found several major themes, namely, friendship (fathers and sons); betrayal and guilt; redemption and friendship. In every conflict there’s an easy choice, and then there’s the right choice. This is a story of redemption where a boy takes the easy path, and pays for it, until he can finally become a man and right what he has wronged.
LibGuides: Evaluating Sources of Information: Evaluating Sources

Sources should be considered for currency, relevance, authority, accuracy, objectivity and purpose.
Dynamics model of NIMBY risk diffusion system in ‘The Belt and Road’ energy investment

Abstract Through the analysis of the interaction among various influencing factors in the ‘NIMBY’ risk diffusion system, the boundary of NIMBY risk diffusion system in ‘The Belt and Road’ energy investment is determined, and the basic assumptions of the system dynamics model are made. On this basis, a causal relationship diagram of NIMBY risk diffusion is established, and the mechanism of nimby risk diffusion is explained in the form of cause tree. Moreover, based on the causal relationship diagram, the flow diagram of NIMBY risk diffusion system was established, and the system dynamics model framework was determined.
LibGuides: WCU Library Webinars: Qualitative vs. Quantitative

This research guide provides links to all the webinars held for CAPS 401 for the Fall II 2019 term.