Reviewerly/exHarmony huggingface dataset:
Local Uncorrelated Subspace Learning

In this paper, we present a supervised manifold learning based dimensionality reduction method, which is titled local uncorrelated subspace learning (LUSL). In the proposed LUSL, a local margin based on point to feature space (P2S) distance metric is recommended for discriminant feature extraction. What’s more, it has been validated that the locally statistical uncorrelation is an important property to reduce the feature redundancy. Hence, a novel locally uncorrelated criterion using P2S distance metric is also put forward, which is taken to constrain the local margin. Finally, by solving both the orthogonality and the local uncorrelation constrained objective function using an iterative way, a low dimensional subspace will be explored for pattern recognition. Compared to some related subspace learning methods, the effectiveness of the proposed LUSL have been shown from experimental results on some benchmark face data sets as AR and FERET.
CAN and debugger interface with Python

Nowadays, Python is one of the most popular programming languages and it is becoming little by little the favorite one for many people. On this project, we will describe its advantages on an important sector, test automation for embedded systems. The automotive market has a lot of challenges which add complexity to the development of any product and OEM’s are demanding not only more features to their product but also, they want those features fulfilled within a short period of time due to the high competition and customer demands. To keep up the pace, the automation process must be improved, so with more features and updates added to the product, more tests and verifications are needed. Even though visual inspection is always necessary, the need for test automation in embedded system is now a priority to conclude faster verification steps in the development path of the product, improving efficiency and effectiveness avoiding and pointing out human mistakes that no matter what they will be always present. Python is now supported in many tools for communication (for CAN and LIN protocols) and debugging in embedded systems, therefore, combined with their general programming language advantages it can be quite important and useful in the tool-set of any software engineer.
Microseismic Magnitudes: Challenges in Determining the Correct Moment and Operating Regulatory Frameworks

Summary Magnitudes are an essential parameter for the estimation of source properties and the management of seismic risk, yet they are surprisingly difficult to accurately estimate. In this paper we show the challenges of working with microseismic events, and propose approaches to correct for some of the discrepancies that are commonly observed. Local magnitudes are regularly over-estimated at close hypocentral distances, and we present revised scales to correct for these discrepancy. As the magnitude decreases the frequency content of the source spectra would be expected to increase. This is however demonstrated not to be the case for microseismic events, which has an impact on the calculation of source properties and relationships between Local and Moment magnitude. We overcome this be adapting standard Brune source model to account for a preferential decay of high frequencies. This is used to derive a physics-based ML-MW relationship, and estimate the rupture radius and stress drop of a cluster of seismic events.
Entrapment and the road to fraud

Discusses the implications of Procurator Fiscal, Dundee v P (P) (SC) that the actions of an online vigilante group who had induced an accused to send sexual messages by social media to persons he believed to be children aged 12 and 14, and to continue doing so until he had, in their view, conducted himself in a way which was likely to result in a substantial prison sentence, contained all of the elements of the common law crime of fraud and were therefore unlawful.
Answer Triggering Mechanisms in Neural Reading Comprehension-based Question Answering Systems

We implement a state-of-the-art question answering system based on Convolutional Neural Networks and Attention Mechanisms and include four different variants of answer triggering that have been dis ...
Multi-view Locality Preserving Embedding with View Consistent Constraint for Dimension Reduction

With the diversification of data sources, the multi-view data with multiple expressions have been appeared in various application scenarios. These multi-view data generally have high dimensions, large amounts and often lack of label information. Therefore, it is very important to learn multi-view data in an unsupervised way so as to analyze and excavate the potential valuable information. In this paper, we propose a multi-view locality preserving embedding algorithm with view similarity constraint for data dimension reduction. This algorithm not only preserves the local structure into low-dimensional space for each view, but also implements the similarity constraints between different views. On this basis, the algorithm looks for a joint embedding of low-dimensional subspace, so that the neighborhood among samples in original high-dimensional space can be maintained in the subspace, and the structures corresponding to different views are consistent with each other. This algorithm achieves good experimental results both in artificial data sets and multi-view data sets, which prove the correctness and feasibility of the algorithm.
REALITY AND SOLUTIONS TO IMPROVE THE IMPLEMENTATION OF SOFT SKILLS IN TEACHING SPECIALIZED KNOWLEDGE AT UNIVERSITIES

The development of economic, culture and society has fetched many opportunities and challenges for students of universities in the current period. Employers require not only skilled human resources but also ability to adapt to a volatile, constantly changing and developing working environment. This fact requires students to have a basic change from thinking to action. Along with specialized knowledge, universities should aim to strengthen the integration of training soft skills for students to meet the requirements of employers. By analytical method, the article focuses on clarifying the situation, difficulties and challenges, thereby proposing a number of solutions to improve efficiency and enhance the implementation of integrating soft skills in teaching the specialized knowledge in University. The paper focuses on clarifying the situation, difficulties and challenges, thereby proposing solutions for improving the efficiency, enhancing the implementation of integrating soft skills in teaching specialized knowledge at universities.
Development of the Biological Information Measurement System for STEM Education and High School/University Articulation

Development of human resources in the field of science and technology is a necessity in the modern world. To encourage the development of the nation, it is important to educate forward-thinking engineers in cooperation with the education system, with the requirements of modern society as the background of their efforts. In Western countries, STEM (Science, Technology, Engineering, and Mathematics) education is provided as a national strategy for development, and this type of education is also spreading to Japan. On the other hand, in the context of high school/university articulation, it is argued that the abilities required by high schools, universities, and society are different from one another, and that it is necessary to inter-link them. Accordingly, comprehensive content that includes all levels, from primary to higher education, is required. On the basis of this background and the current problem of STEM education and high school/university articulation, this research aims to aid in the development of a curriculum and educational study materials through which the technology of universities could be integrated into high school classes. This report includes the development of educational study material on biological information systems because it reflects the features of the department to which the authors belong and there is already a lot of research on, and technology related to, biological information. Using the educational study material, we carry out an in-class practice session including task-oriented research at a high school with cooperation from a university and discuss the educational effect that results from it.
Human emotion detection based on questionnaire and text analysis

Human emotions have been described by some theorists as discrete and consistent responses to internal or external events which have a particular significance for the organism. Emotions are the topic of extensive research in the recent times. However, state of the art describes that most of the approaches on emotion detection have been designed on the basis of complex and costly approaches like physiological features, brain signals, etc. The present article presents a simple and cost-effective emotion detection model by combining questionnaire and text analysis-based approaches and then combining the probability scores of two different classifiers (support vector machine and artificial neural network) using Dempster-Shafer theory (DST). In the present work, DST has been used effectively in combining multiple information sources which provides incomplete, imprecise, and biased knowledge. Experimental results show that the proposed system outperforms all existing emotion detection systems available in the literature.
Subject & Course Guides: Streaming Video Services (Regionals): Streaming Video Content Resources

Policies, forms, resources, FAQ, and legal information about accessing streaming video content through the Regional Campus Libraries
Views of Research Quality in Empirical Software Engineering

Background. Software Engineering (SE) research, like other applied disciplines, intends to provide trustful evidence to practice. To ensure trustful evidence, a rigorous research process based on s ...
Fall Detection of Elderly Persons by Action Recognition Using Data Augmentation and State Transition Diagram

Because of the increaseTakebayashi, Ayaka of the population of elderly people and the decreasing numberIwahori, Yuji of care workers, there is at present a problem ofFukui, Shinji delay the detection of falls requiring emergency treatment. Little, James J. This paper proposes a method to acquireMeng, Lin posture information of a person from a camera watchingWang, Aili over elderly people, and to recognize the behaviorKijsirikul, Boonserm of the person using Long Short Term Memory. The proposed method detects falls of elderly people automatically using the result of action recognition. Since it is difficult to capture dangerous scenes such as fall of elderly people and to capture a lot of data, this paper proposes a new method that can create a large amount of data necessary for learning from a small amount of data.
Modeling Realized Covariance of Asset Returns

In this thesis, which consists of two papers, we consider the modeling of positive definitive symmetric matrices, in particular covariance matrices of financial asset returns. The return covariance ...
Semi-Automatic Formatting of Spelled Out Numbers

In this paper, we present a semi-automatic method to transform Turkish numeric entities such as telephone numbers, monetary amounts, time and date written in spoken form into their grammatical format using deep neural networks. The method consists of two stages. The first stage consists of sequence labeling model which labels the parts that need to be formatted in a given text and the second stage is a sequence to sequence model which transforms these parts into their numerical format. Given a text normalizer that can transform numerical entities into their spoken format, our method is able to learn reverse transform automatically, without requiring a predetermined set of transform rules. To the best of our knowledge, this is the first work that is conducted on Turkish language. Resulting transformation accuracy of the model in the test set is 92.1%.
Studying Wythoff and Zometool Constructions Using Maple

We describe a Maple package that serves at least four purposes. First, one can use it to compute whether or not a given polyhedral structure is Zometool constructible. Second, one can use it to manipulate Zometool objects, for example to determine how to best build a given structure. Third, the package allows for an easy computation of the polytopes obtained by the kaleiodoscopic construction called the Wythoff construction. This feature provides a source of multiple examples. Fourth, the package allows the projection on Coxeter planes.
ANALYSIS AND DESIGN OF DISTRIBUTED SYSTEM FOR MONITORING COMPUTER INFRASTRUCTURE MANAGEMENT BASED ON CLIENT/SERVER BY USING WINDOWS MANAGEMENT INSTRUMENTATION TECHNOLOGY

This research aims to analyze and develop a system for monitoring computer infrastructure management in real time (real-time monitoring). The developed system was a distributed system that would help IT Administrators work at the Center for Computing and Information Technology Faculty of Engineering Universitas Indonesia (CCIT FTUI) to monitor the computer infrastructure in real-time. The Real - time referred to system that was able to do direct monitoring to computer infrastructure, and quickly able to transmit data status of the device. Limitations of the current monitoring process was that the IT Administrator checks directly into the computer lab room if there were problems related to a computer or cable that was not connected from the computer system based on a report from teachers or students. The developed monitoring system was a client/server based system that used network infrastructure so that the computer infrastructure could be optimally monitored. The modules used in this research are computer input and output modules, and installed applications or system services. This research is expected to be able to overcome the problems associated with computer infrastructure’s performance, conduct supervision and centralized control in helping the problems that often occur during learning process or examination. Keywords: Monitoring, Computer Infrastructure Management, Distributed System, Computer Network, Real-time.
Fall-Prevention Exergames Using Balance Board Systems

The prevention of falls in older adults is an issue that can only be solved with regular exercises, sometimes with the supervision of therapists. This paper presents a game framework that uses devices such as the Wii Balance Board (WBB) to replicate fall-prevention programs, such as the Otago Exercise Programme. The objective is to increase the adherence of senior users to these exercises, while increasing their autonomy by enabling them to conduct unsupervised games. Two interactive games were developed and tested using the WBB and other available devices such as smartphones. The main contribution of this paper is the proposal of several metrics for exergames for the elderly and the combination of digital games with fall-prevention exercises and automatic balance measures based on Centre of Pressure (COP) tracking.
Converting ALC Connection Proofs into ALC Sequents

The connection method has earned good reputation in the area of automated theorem proving, due to its simplicity, efficiency and rational use of memory.This method has been applied recently in automatic provers that reason over ontologies written in the description logic ALC.However, proofs generated by connection calculi are difficult to understand.Proof readability is largely lost by the transformations to disjunctive normal form applied over the formulae to be proven.Such a proof model, albeit efficient, prevents inference systems based on it from effectively providing justifications and/or descriptions of the steps used in inferences.To address this problem, in this paper we propose a method for converting matricial proofs generated by the ALC connection method to ALC sequent proofs, which are much easier to understand, and whose translation to natural language is more straightforward.We also describe a calculus that accepts the input formula in a non-clausal ALC format, what simplifies the translation.
Stimulating the Search Activity of Primary Schoolchildren in the Process of Solving Educational Problems

The article raises the problem of the formation of the search activity of younger schoolchildren and the formation of their subjective position in learning. The essence of the concept of “educational task” is revealed as a component of educational activity. The structure of the lesson is described, in the process of which the skills of younger schoolchildren to solve educational problems that are aimed at mastering generalized methods of objective actions are formed. This provides the opportunity for students to master the system of scientific concepts that allows selfdevelopment and self-learning. A concrete example of solving the educational problem in the lesson of the Russian language in the second grade&#x0D; is given.
LSC-CyFair LIbrary Guides: Events & Programs: SOCIAL WALL

Open to all faculty, staff, students, and members of the community. Connect with the library via social media.
Protected Entree Design for Big Data Knowledge in Cloud

Nowadays, the access to the data in the cloud is provided with weak authentication, of the user. Besides, as more and organizations are using clouds to store their data, it becomes more challenging to deal with the issue of access policy. Due to this the leakage of critical information are not well handled. Integrity and confidentiality of the personal information are questioned and are not secure. To overcome this, we propose a new NTRU decryption procedure to overcome the decryption failures of the original NTRU without reducing the security strength of NTRU. The scheme can verify user's access legitimacy and validate the information provided by other users for correct plaintext recovery. We devise an efficient and verifiable method to update the cryptosystem stored in clouds without increasing any risk when the access policy is dynamically changed.
Span program for non-binary functions

Span programs characterize the quantum query complexity of binary functions f:\{0,\ldots,\ell\}^n \to \{0,1\} up to a constant factor. In this paper we generalize the notion of span programs for functions with non-binary input/output alphabets f: [\ell]^n \to [m]. We show that non-binary span program characterizes the quantum query complexity of any such function up to a constant factor. We argue that this non-binary span program is indeed the generalization of its binary counterpart. We also generalize the notion of span programs for a special class of relations. Learning graphs provide another tool for designing quantum query algorithms for binary functions. In this paper, we also generalize this tool for non-binary functions, and as an application of our non-binary span program show that any non-binary learning graph gives an upper bound on the quantum query complexity.
Subject & Course Guides: One Button Studio: Home

This guide provides details on how to use the One Button Studio at the Gardner-Harvey Library.
Art Pedagogy As a Mean of Psychological Support and Methods of Aesthetic Education of Seriously Ill Child

In the article, written on the basis of practical experience of the author, working in the Separate structural unit “School № 109” on the basis of the National Medical Research Center for Pediatric Hematology, Oncology and Immunology named after Dmitry Rogachev”, discusses the problem of using special methods of art pedagogy in the training and education of children undergoing long-term treatment. The methods proposed by the author positively affect the psychoemotional state of seriously ill children and are considered as an essential component of complex treatment.
Petrophysical and Geochemical Calibration for Total Organic Matter Quantification and Multi-Mineral Modeling of Source Rocks

Summary Total organic matter includes bitumoids (soluble part) and kerogen (insoluble part). Accounting for sedimentological features (determining the composition of organic matter), as well as the history of basin subsidence (catagenesis) is key sence when learning source rocks and that affect the petrophysical properties. Since the middle of the XX century a lot of methods and techniques of well log interpretation for the classification of rocks have been developed. The relatively low efficiency of automatic recognition programs of the lithological identification of rocks led to the conclusion that the required quality of identification can be provided only by the framework of interactive (adapted for a specific geological situation) systems of automatic interpretation. Therefore in this research work the most popular deterministic methods using cutoff values and methods of normalization curves, creating cross-plots, regression analysis and statistical multi-mineral calculations are used. The purpose of this work was to comprehensively analyze petrophysical and geochemical calibration parameters and the relationships between the different multi-mineral composition, it is especially important to consider total organic carbon values. Results of statistical multi-mineral modeling will be used to determine the role of individual mineral components of SR in their high hydrocarbon potential zones.
JavaScript Primer, Part 1

Effective TypeScript development requires an understanding of how JavaScript deals with data types. This can be a disappointment to developers who adopt TypeScript because they found JavaScript confusing, but understanding JavaScript makes understanding TypeScript easier and provides valuable insights into what TypeScript offers and how its features work. In this chapter, I introduce the basic JavaScript type features, continuing with more advanced features in Chapter 4 .
Performance Review of a Real-Time Machine Learning Based Seismic Catalog Generator in Production

Summary As machine learning algorithms can be prone to overfitting, the ability to them generalize for use in a real-time system for seismic event detection and location is critical. In this study, we focus on the temporal stability of a realtime automatic seismic catalog generator algorithm (Feature Weighted Beamforming, FWB) which has been applied on over 15 networks over a one year period in a production environment. We present detailed results from an induced seismic monitoring array over the Duvernay Formation (Duvernay Subscriber Array, DSA), as well as some higher level statistics on other seismic networks. The initial results from DSA in comparison to standard STA/LTA picking and associations show that FWB reduced the number of false positives by 75% without loss of sensitivity, it also reduced the average difference in the event location between automatic and manually picked solutions by 82%. Similar to DSA, for all networks which included a large variety of training data FWB demonstrated consistent detection of all real seismic events compared to a sensitive STA/LTA pick associator regarding system sensitivity and location accuracy. New clusters of seismic activity not seen during training are also correctly detected and located.
Advanced Generic Types

In this chapter, I continue to describe the generic type features provided by TypeScript and focus on the advanced features. I explain how generic types can be used with collections and iterators, introduce the index types and type mapping features, and describe the most flexible of the generic type features: conditional types. Table 13-1 summarizes the chapter.