Reviewerly/exHarmony huggingface dataset:
Variable Selection via the Sparse Net

Variable selection is an important problem when the model includes many noisy variables. For years, the sparse penalized approaches have been proposed for the problem. Examples are the least absolute selection and shrinkage operator (LASSO) and smoothly clipped absolute deviation penalty. The sparse penalized approaches are known to have more stable sampling properties compared with the traditional best subset selection approaches, keeping higher computational efficiency. In this paper, we propose a new penalty, sparse net (SNET), that can be used for variable selection and parameter estimation in the linear regression model. The SNET consists of two penalties: the LASSO and the negative ridge. The SNET shares the same spirit with the elastic net but the ridge effect is negatively imposed on the regression coefficients to avoid unnecessary selection and biases. In general, the SNET penalized sum of squared residuals is non-convex, depending on the size of negative ridge effect, which requires non-convex optimization algorithm. For this issue, we introduce an efficient algorithm for implementing the SNET penalized estimator. Several numerical examples show that the SNET can be a nice competitor with existing penalties.
Considering Uncertainty in Modeling Historical Knowledge.

Simplifying and structuring qualitatively complex knowledge, quantifying it in a certain way to make it reusable and easily accessible are all aspects that are not new to historians. Computer science is currently approaching a solution to some of these problems, or at least making it easier to work with historical data. In this paper, we propose a historical knowledge representation model taking into consideration the quality of imperfection of historical data in terms of uncertainty. To do this, our model design is based on a multilayer approach in which we distinguish three informational levels: information, source, and belief whose combination allows modeling and modulating historical knowledge. The basic principle of this model is to allow multiple historical sources to represent several versions of the history of a historical event with associated degrees of belief. In our model, we differentiated three levels of granularity (attribute, object, relation) to express belief and defined 11 degrees of uncertainty in belief. The proposed model can be the object of various exploitations that fall within the historian’s decision-making support for the plausibility of the history of historical events.
Problems of Assessing the Quality of Education Using Test Certification Procedures

In the modern educational system testing has become one of the prevailing methods for assessing students' knowledge. The procedures for test certification of schoolchildren, especially the so-called “high-stakes tests,” which have a decisive influence on the trajectory of post-school education, are still debatable. In studies, the problem of misalignment of test indicators and the real educational level of the student is discussed, the presence of procedural and substantive shortcomings in the tests is stated. Article is devoted to the overview of the difficulties encountered by participants in the educational process in preparation for the exams. Such trends in final exams' critic as distrust to the exam procedure, procedural and content shortcomings, difficulties in preparing graduates for exams are discussed. It also describes the author's methodic of exam readiness diagnostic. It's based on the educational result’s esteem. The form of the methodic is given.
On solving isomorphism problems about 2-designs using block intersection numbers

In this paper, we give a partial solution to a new isomorphism problem about 2-(v, k, k − 1) designs from disjoint difference families in finite fields and Galois rings. Our results are obtained by carefully calculating and bounding some block intersection numbers, and we give insight on the limitations of this technique. Moreover, we present results on cyclotomic numbers, the multiplicities of block intersection numbers of certain designs and on the structure of Galois rings of characteristic p2.
X-ray computed tomography as a method of reconstruction of 3d-characteristics of disseminated sulfides and spinel in plagiodunites from the Yoko-Dovyren intrusion

The paper describes a methodology of applying X-ray computed tomography (CT) in studying textural–morphological characteristics of sulfide-bearing ultramafic rocks from the Yoko-Dovyren layered massif in the northern Baikal area, Buryatia, Russia. The dunites are used to illustrate the applicability of a reliable technique for distinguishing between grains of sulfides and spinel. The technique enables obtaining statistical characteristics of the 3D distribution and size of the mineral phases. The method of 3D reconstructions is demonstrated to be applicable at very low concentrations of sulfides: no than 0.1–0.2 vol %. Differences between 3D models are determined for sulfide segregations of different size, in some instances with features of their orientation suggesting the direction of percolation and accumulation of the sulfide liquids. These data are consistent with the morphology of the largest sulfide segregations, whose concave parts adjoin the surface of the cumulus olivine and simultaneously grow into grains of the poikilitic plagioclase. Detailed information of these features is useful to identify fingerprints of infiltration and concentration of protosulfide liquids in highly crystallized cumulate systems.
The Design and Implementation of Graduation Thesis Management System

With the increasing scale of universities, a large number of students need to complete their graduation thesis every year. Graduation thesis needs to be examined and managed, while manual management is easy to make mistakes and inefficient. In order to improve the efficiency of graduation thesis management, a graduation thesis management system is developed.  The system is based on Java technology, MySQL database is used to store data and deploy in the cloud. The system has been tested by function and structure, which meets the basic design requirements and can run normally.
THE EFFECT OF SURVEY, QUESTION, READ, RECALL, REVIEW (SQ3R) METHOD ON STUDENTS’ READING COMPREHENSION AT GRADE X SMAN 6 TANJUNG BALAI IN ACADEMIC YEAR OF 2014/2015

The objectives of the study found out the effect of using the SQ3R method on students’ reading comprehension at Grade X SMAN 6 Tanjung Balai. This study conducted in experimental design, namely to find out the students’ reading comprehension by using the SQ3R Method. The population of this research is taken from the grade X of SMAN 6 Tanjung Balai. There are two classes, namely class X 5 and X 4 totaling 60 students. The sample of this research was at Grade X 5 as an experiment group and X 4 as a control group. The conclusion is significantly affected by the students' reading comprehension achievement, and also the test is reliable. Like the t- test, the result is higher than the t- table at 0,05 and 0,01 level of significant (19,5>2,00 and 19,5>2,68) and it is very effective in apply in teaching reading. By using SQ3R method the students can help them to ask effective questions as they read and respond to the text, and also encourages teachers to be aware of, and it is hoped to the teachers use the SQ3R Method to make the students more students' active and make the process learning is effective. Key Words: Effect, SQ3R Method, Reading Comprehension.
Quantum Walks in Quasi-Periodic Photonics Lattices

We present construction rules for a new class of quasi-periodic photonics lattices to realize localized quantum walks deterministically. The new quasi-periodic structures are constructed symmetrically with Fibonacci, Thue-Morse sequences. Our simulations show that localized quantum walks in these quasi-periodic lattices are symmetrical and highly controllable.
Report of the ALCTS catalog management interest group meeting. American library association annual meeting, New Orleans, June 2018

"Report of the ALCTS catalog management interest group meeting. American library association annual meeting, New Orleans, June 2018." Technical Services Quarterly, 36(3), pp. 317–318
KM $$^{3}$$ SVM: A Efficient Min-Max Modular Support Vector Machine Based on Clustering

In recent years, more and more scholars have begun to study the problem of multi-label learning. In this paper, we propose a multi-label learning method called KM $$^{3}$$ SVM based on Clustering idea. First, for each label, KM $$^{3}$$ SVM method selects positive samples and negative samples, then uses clustering method to gain a number of training subsets. By using these relatively smaller and more balanced training subsets, we can get a group of classifiers. Given an unseen sample, we can obtain a series of outputs and combine them by two simple principles. Experimental results on two datasets demonstrate the superiority of the proposed method KM $$^{3}$$ SVM over several state-of-the-art multi-label learning algorithms.
OAGKX Keyword Generation Dataset

OAGK is a keyword extraction/generation dataset consisting of 2.2 million abstracts, titles and keyword strings from cientific articles. Texts were lowercased and tokenized with Stanford CoreNLP tokenizer. No other preprocessing steps were applied in this release version. Dataset records (samples) are stored as JSON lines in each text file. This data is derived from OAG data collection (https://aminer.org/open-academic-graph) which was released under ODC-BY licence. This data (OAGK Keyword Generation Dataset) is released under CC-BY licence (https://creativecommons.org/licenses/by/4.0/).If using it, please cite the following paper:Cano, Erion and Bojar, Ondřej, 2019, Keyphrase Generation: A Text Summarization Struggle, 2019 Annual Conference of the North American Chapter of the Association for Computational Linguistics, June 2019, Minneapolis, USA
La comunicación no verbal en la formación inicial del Comunicador Social

The non-verbal communication constitutes an important objective in the initial formation of social communicator. However, this process, have not had the same attention than verbal communication, taking into account the importance of the non-verbal communicative skills in the interpersonal communication by the information they transmit by themselves. In the scientific literature, it reported several investigations about the theme in the initial formation of the professionals’ university. However, the investigations of the subject matter on the social communicator are insufficient, whose profession is needed for the nonverbal communicative skills to be object of essential attention. The objective of the article is to analyze the importance of the development abilities in the initial formation of social communicator and the pertinence of its integration to the rest of the professional abilities that must be developed in the career. The utilization of fact-finding methods of the theoretic and empiric level allowed basing the importance of the job of focus personologico in the process of development of the non-verbal communicative skills, from the dimensions: cognitive, affective, executive and stile of communicative, that evidence the integrative character in the education of the personality.
The Innovation of College English Teaching under the Mechanism of Cultivating Practical Talents

After years of development, English teaching in colleges and universities of our country has achieved good results in many aspects.But we must see that in the new era of economic and social development, the training of personnel puts forward higher requirements and higher standards.It is urgent to deepen the reform of English teaching in colleges and universities by making self-adjustment and consciously guiding with the aim of cultivating talents.This paper briefly expounds and analyzes the innovation of college English teaching under the practical talents training mechanism.China has always attached great importance in English teaching Especially since the reform and opening up,English has been regarded as an important public and basic course in China's colleges and universities.After years of development and reform,China's College English teaching has achieved good results.With the economic development and social progress,however,China's demand for talent has changed substantially.As a professional personnel training institution,colleges and universities are bound to make corresponding adjustments to this change.
의문형 종결어미 ‘-(으)ㄹ까(요)’의 담화 기능 연구

The purpose of this research is to analyze the discourse functions that appear in semi-spoken language corpus for ‘-(으)ㄹ까(요)’ of the ending of a word who have the sentence closure function in question. interrogative final endings ‘-(으) ㄹ까(요)’ is a common ending term in spoken words, and is mainly treated in Korean language education as a style that expresses the function of suggestion, conjecture in the beginning stage. However, ‘-(으)ㄹ까(요)’ performs various and complex functions compared to other expressive patterns, the training that faithfully reflects the functional system is not provided at the Korean language training site, making it difficult for learners to use it appropriately for contextual situations. Therefore, language training should be provided from a functionalist perspective focusing on ''use'' that focuses on discourse functions to improve the communication skills of Korean learners. It was also intended to attempt a comprehensive approach to the discourse function performed by ‘-(으)ㄹ까(요)’ by characterizing which discourse function is extended from the circular attribute to the actual use of the language.
New Fixed Point Attacks on GOST2 Block Cipher

GOST block cipher designed in the 1970s and published in 1989 as the Soviet and Russian standard GOST 28147-89. In order to enhance the security of GOST block cipher after proposing various attacks on it, designers published a modified version of GOST, namely GOST2, in 2015 which has a new key schedule and explicit choice for S-boxes. In this paper, by using three exactly identical portions of GOST2 and fixed point idea, more enhanced fixed point attacks for filtration of wrong keys are presented. More precisely, the focus of the new attacks is on reducing memory complexity while keeping other complexities unchanged as well. The results show a significant reduction in the memory complexity of the attacks, while the time complexity slightly increased in comparison to the previous fixed point attacks. To the best of our knowledge, the lowest memory complexity for an attack on full-round GOST2 block cipher is provided here.
Towards An Effective and Efficient Machine-Learning-Based Framework for Supporting Event Detection in Complex Environments

In this paper we describe a falls detection and classification algorithm for discriminating falls from daily life activities using a MEMS accelerometer. The algorithm is based on a shallow Neural Network with three hidden layers, used as fall/non fally classifier, trained with daily life activities features and fall features. The novelty of this algorithm is that synthetic falls are generated as multivariate random Gaussian features, so only real daily life features must be collected during some day of normal living. Moreover, the features related to synthetic fall events are generated as complement of normal features. First of all, the features acquired during daily life are clustered by Principal Component Analysis and no Fall activities shall be recorded. The complement set of the normal features is found and used as a mask for Monte Carlo generation of synthetic fall. The two feature sets, namely the features recorded from daily life activities and those artificially generated are used to train the Neural Network. This approach is suitable for a practical utilization of a Neural Network based fall detection characterized by high Recall-Precision rate.
ESTIMATION OF IMPACT RADIUS OF THE COAL PLANT STACK EMISSION USING AERMOD MODEL

In environmental impact assessment of coal plant, it is essential to determine the radius impact. This information can be used to determine the impacted area, which will significantly receive the pollution emitted from the stack for years. In this study, we use the American Meteorological Society - Environmental Protection Agency Regulatory Model (AERMOD) model, which is a regulated model in the USA and other countries. Five years hourly meteorological data for feeding AERMET model was obtained from MM5 re-analysis data. Terrain data was extracted from the SRTM30 satellite image and converted into DEM. The parameter to be considered in this study is Sulfur Dioxide (SO2), Nitrogen Dioxide (NO2), and Total Suspended Particle (TSP). The calculation shows that the pollutions tend to disperse in the south direction by the wind direction. NO2 is more disperse than SO2 and TSP. Calculation of impact radius indicates that concentration of all pollutants in annual average is below the national standard. For the case of the highest one hour average gives the radius impact of 18 km for NO2 and 9 km for SO2. For the case of the highest 24 hours, only NO2 gives value beyond the standard with an impact radius of 4.5 km. Calculation of TSP indicates that concentration is below the standard in all cases. The maximum concentration of all pollutants is detected 3 km south of the stack.
Research on the Innovation Method of College English Teaching Based on Internet

The Internet has become an irreplaceable part of our work and life.In recent years, the Internet has penetrated into every aspect of our work and life.The Internet is a brand new platform that provides conditions and possibilities for innovation and development in all walks of life.The Internet also has a great and profound impact on education and teaching.At present, the development of higher education in China has entered a new stage.In the new era of education and teaching reform and development, how to do a good job of Internet-based college English teaching innovation has become a realistic problem that teachers in the industry have to face.
Anatomic Anthropometry Model for Face Generation Program Based on Physiognomy

This paper discusses an anatomic anthropometry model which can be used to generate a face by combining facial parts such as eyes, the nose, and lips. This study is apart of a larger project that attempts to generate a crowd of graphical characters which are created with facial parts that contain physiognomic attributes. The hypothesis was that if the physiognomic attributes formed a negative impression, the resulting crowd would exude uniformly negative impressions. For a pilot study, a brief investigation of physiognomic studies of eastern and outstanding studies of automatic crowd generation in computer graphics was carried out to set the direction of the study. The main content of the study illustrates the process of developing a model based on Loomis’ study of a facial grid and the Face Sectional Theory of physiognomy. We also add the result of a sample test of the model and discuss how to improve the final software further to ensure a greater variety.
Large Scale Scene Text Verification with Guided Attention

Many tasks are related to determining if a particular text string exists in an image. In this work, we propose a new framework that learns this task in an end-to-end way. The framework takes an image and a text string as input and then outputs the probability of the text string being present in the image. This is the first end-to-end framework that learns such relationships between text and images in scene text area. The framework does not require explicit scene text detection or recognition and thus no bounding box annotations are needed. It is also the first work in scene text area that tackles such a weakly labeled problem. Based on this framework, we developed a model called Guided Attention. Our designed model achieves better results than several state-of-the-art scene text reading based solutions for a challenging Street View Business Matching task. The task tries to find correct business names for storefront images and the dataset we collected for it is substantially larger, and more challenging than existing scene text dataset. This new real-world task provides a new perspective for studying scene text related problems.
Accelerating Generalized Linear Models with MLWeaving: A One-Size-Fits-All System for Any-precision Learning

Learning from the data stored in a database is an important function increasingly available in relational engines. Methods using lower precision input data are of special interest given their overall higher efficiency but, in databases, these methods have a hidden cost: the quantization of the real value into a smaller number is an expensive step. To address the issue, in this paper we present MLWeaving, a data structure and hardware acceleration technique intended to speed up learning of generalized linear models in databases. ML-Weaving provides a compact, in-memory representation enabling the retrieval of data at any level of precision. MLWeaving also takes advantage of the increasing availability of FPGA-based accelerators to provide a highly efficient implementation of stochastic gradient descent. The solution adopted in MLWeaving is more efficient than existing designs in terms of space (since it can process any resolution on the same design) and resources (via the use of bit-serial multipliers). MLWeaving also enables the runtime tuning of precision, instead of a fixed precision level during the training. We illustrate this using a simple, dynamic precision schedule. Experimental results show MLWeaving achieves up to16 performance improvement over low-precision CPU implementations of first-order methods.
Deontic Modality in Rationality and Reasoning

Deontic Modality in Rationality and Reasoning Lay Summary Alessandra Marra The present dissertation investigates certain facets of the logical structure of oughts – where “ought” is used as a noun, roughly meaning obligation. I do so by following two lines of inquiry. The first part of the thesis places oughts in the context of practical rationality. The second part of the thesis concerns the inference rules governing arguments about oughts, and specifically the inference rule of Reasoning by Cases. These two lines of inquiry, together, aim to expound upon oughts in rationality and reasoning. The methodology used in this dissertation is the one of philosophical logic, in which logical, qualitative models are developed to support and foster conceptual analysis. The dissertation consists of four main chapters. The first two chapters are devoted to the role of oughts in practical rationality. I focus on the so-called Enkratic principle of rationality, which – in its most general formulation – requires that if an agent believes sincerely and with conviction that she ought to do X, then she intends to X. I develop a logical framework to investigate the (static and dynamic) relation between those oughts believed by the agent and her intentions. It is shown that, under certain minimal assumptions, the Enkratic principle of rationality is a principle of limited validity. The following two chapters of the dissertation constitute a study of the classical inference rule of Reasoning by Cases, which – in its simplest form – moves from the premises “A or B”, “if A then C” and “if B then C” to the conclusion “C”. Recent literature has called the validity of Reasoning by Cases into question, with the most influential counterexample being the so-called Miners’ Puzzle – an instance of Reasoning by Cases where “C” involves oughts. I provide a unifying explanation of why the Miners’ Puzzle emerges. It is shown that, within specific boundaries, Reasoning by Cases is a valid inference rule.