Reviewerly/exHarmony huggingface dataset:
Linear Projection Learned from Hybrid CKA for Enhancing Distance-Based Classifiers

Most machine learning approaches are classified into either supervised or unsupervised. However, joining generative and discriminative functions in the learning process may beneficially influence each other. Using the centered kernel alignment similarity, this paper proposes a new hybrid cost function based on the linear combination of two computed terms: a discriminative component that accounts for the affinity between projected data and their labels, and a generative component that measures the similarity between the input and projected distributions. Further, the data projection is assumed as a linear model so that a matrix has to be learned by maximizing the proposed cost function. We compare our approach using a kNN classifier against the raw features and a multi-layer perceptron machine. Attained results on a handwritten digit recognition database show that there exists a trade-off value other than the trivial ones that provide the highest accuracy. Moreover, the proposed approach not only outperforms the baseline machines but also becomes more robust to several noise levels.
The Problem With Modal Conceivability Arguments

The Philosophical ForumVolume 50, Issue 1 p. 135-146 ORIGINAL ARTICLE The Problem With Modal Conceivability Arguments† Shuyi Feng, Shuyi Feng Yuelu Academy, Hunan UniversitySearch for more papers by this author Shuyi Feng, Shuyi Feng Yuelu Academy, Hunan UniversitySearch for more papers by this author First published: 08 March 2019 https://doi.org/10.1111/phil.12210 †This paper is supported by the Fundamental Research Funds for the Central Universities. Moreover, I would like to thank Andreas Kemmerling, Asher Jiang, Dechao Su, Xingming Hu, and Sebastian Tants for their comments on earlier drafts of this paper. Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Volume50, Issue1Spring 2019Pages 135-146 RelatedInformation
Bipartite Edge Correlation Clustering: Finding an Edge Biclique Partition from a Bipartite Graph with Minimum Disagreement

In this paper, first we formulate the problem of a bipartite edge correlation clustering which finds an edge biclique partition with the minimum disagreement from a bipartite graph, by extending the bipartite correlation clustering which finds a biclique partition. Then, we design a simple randomized algorithm for bipartite edge correlation clustering, based on the randomized algorithm of bipartite correlation clustering. Finally, we give experimental results to evaluate the algorithms from both artificial data and real data.
Interações polêmicas na internet e as máximas conversacionais: limites entre o dissenso e o protesto (Polemical interactions on the internet and the conversational maxims: limits between dissension and protest)

Este artigo analisa linguisticamente postagens feitas por leitores na Internet comentando uma noticia de jornal e destaca as implicaturas das quebras das maximas conversacionais estudadas por Grice (1991) na construcao da polemica, compreendida enquanto modalidade argumentativa (AMOSSY, 2017), no sentido de evidenciar como materializa-se discursivamente uma das funcoes que essa modalidade tem assumido na Internet: a de protesto. Nesse sentido, o trabalho sugere que uma avaliacao da quebra das maximas conversacionais pode constituir um criterio para tracar limites entre a polemica como modalidade argumentativa e a violencia verbal. PALAVRAS-CHAVE: Linguistica. Pragmatica. Maximas Conversacionais. Polemica. Interacoes verbais na Internet. ABSTRACT This paper analyzes linguistically the postings made by readers on the Internet, commenting about a newspaper article and highlights the implicatures of the violation of the conversational maxims studied by Grice (1991) in the construction of the polemic, understood as an argumentative modality (AMOSSY, 2017), in order of to show how one of the functions that this modality has assumed on the Internet materializes itself in the discourse: the one of protest. In this sense, this work suggests that an evaluation of the violation of conversational maxims may constitute a criterion to draw the boundaries between the polemic as an argumentative modality and the simply verbal violence. KEYWORDS:Linguistics; Pragmatics; Conversational Maxims; Polemic; Verbal interactions on the Internet.
Security Issues in Internet of Things: A Comprehensive Review

IoT devices can be insecure and may not be able to defend themselves against a wide variety of security threats. This is primarily due to the reason that resources on IoT devices are limited. Standards that govern the development of these devices are not yet mature. Moreover, the design, development and deployment of the software and hardware is not at all secure. The solution to these problems is that a global mechanism should be developed that is robust for securing the IoT layers. Major bottleneck in this approach is that the resources in IoT devices are very diverse in nature, based on several technologies and protocols which make it quite challenging to develop a universal protocol to meet the security threats. These threats have been divided into low level, middle level and high level layers of IoT. In this article, various mechanisms for handling security issues at different IoT layers have been reviewed. Attacks in IoT, their implications, solutions and role of Blockchain technology to address these problems are briefly presented.
PENERAPAN MODEL PEMBELAJARAN CONTEXTUAL TEACHING AND LEARNING (CTL) UNTUK MENINGKATKAN KETERAMPILAN MEMBACA SISWA KELAS II SDN 004 TERATAK BULUH

This study aims to improve student reading skills by applying the Contextual Teaching and Learning (CTL) learning model in class II. B SDN 004 Teratak Buluh. This research is a class action research that includes planning (action), action (observation), observation (observation), reflection (evaluation) or evaluation. The results showed that the value of students' reading skills for each assessment indicator was in the range of 65% to 85% in the first cycle, which was included in the good and very good category. While the results of the overall reading skills assessment were 71.2% in the good category. The results of students' reading skills in cycle II, the assessment is in the range of 84% to 90% which is included in the category of good and very good, while the results of the overall reading skills assessment in the second cycle are 86.2% with a very good category. Based on these results it can be concluded that the application of the Contextual Teaching And Learning (CTL) learning model can improve the reading skills of students in class II. B SDN 004 Teratak Buluh.
Parallel Asynchronous Stochastic Coordinate Descent with Auxiliary Variables

The key to the recent success of coordinate descent (CD) in many applications is to maintain a set of auxiliary variables to facilitate efficient single variable updates. For example, the vector of residual/primal variables has to be maintained when CD is applied for Lasso/linear SVM, respectively. An implementation without maintenance is O(n) times slower than the one with maintenance, where n is the number of variables. In serial implementations, maintaining auxiliary variables is only a computing trick without changing the behavior of coordinate descent. However, maintenance of auxiliary variables is non-trivial when there are multiple threads/workers which read/write the auxiliary variables concurrently. Thus, most existing theoretical analysis of parallel CD either assumes vanilla CD without auxiliary variables (which ends up being extremely slow in practice) or limits to a small class of problems. In this paper, we consider a rich family of objective functions where AUX-PCD can be applied. We also establish global linear convergence for AUX-PCD with atomic operations for a general family of functions and perform a complete backward error analysis of AUX-PCD with wild updates, where some updates are not just delayed but lost because of memory conflicts. Our results enable us to provide theoretical guarantees for many practical parallel coordinate descent implementations, which currently lack guarantees (such as the implementation of Shotgun by Bradley et al. 2011, which uses auxiliary variables)
The Problem of Dropout from Technical Universities: Early Professional Orientation Approach

The fact is that the quantity of enrolled students in technical universities does not equal to the number of graduates. According to the Russian statistics, about 1/5th of universities’ students interrupt their studies and do not get diplomas. The reasons of the withdrawal are the following: (1) the accidental reasons such as health problems or changed life circumstances, (2) the personal motives or decisions, (3) the administrative consequences of poor progress of a student. The dropouts from higher education institutions become a big problem for the university, for the society and for the national economy as a whole. The administrative dropouts of students by the reason of their unsatisfactory evaluation are the most often at the first or at the second years of study. The reasons of such dropouts are the subject for the discussion in this paper. The goal of the paper consists in the elaborating of a possible way for the situation improvement by application of the early professional orientation at the stage of high school education. We interviewed 80 students of the 1st, 2nd, and 3rd years of study trained on the different engineering specialties in the MADI University. The average assessment of progress of each student added to completed questionnaire provides the possibility to compare his/her professional attitude with academic performance and with the probability of dropout.
One Shot Learning for Generic Instance Segmentation in RGBD Videos

Hand-crafted features employed in classical generic instance segmentation methods have limited discriminative power to distinguish different objects in the scene, while Convolutional Neural Networks (CNNs) based semantic segmentation is restricted to predefined semantics and not aware of object instances.In this paper, we combine the advantages of the two methodologies and apply the combined approach to solve a generic instance segmentation problem in RGBD video sequences.In practice, a classical generic instance segmentation method is employed to initially detect object instances and build temporal correspondences, whereas instance models are trained based on the few detected instance samples via CNNs to generate robust features for instance segmentation.We exploit the idea of one shot learning to deal with the small training sample size problem when training CNNs.Experiment results illustrate the promising performance of the proposed approach.
Kreitzberg Library: Integrate Online Library Resources into NUoodle: Using Ebooks & Creating Links

Learn how to create links to licensed electronic resources and find open educational content
Efficient Bayes Risk Estimation for Cost-Sensitive Classification

In some real world applications, acquiring covariates for classification can be cost-intensive and should be limited as much as possible. For example, in the medical setting, a doctor cannot just perform all possible types of tests to classify whether the patient has diabetes or not. The decision of classifying or acquiring more covariates before classifying is dependent on the costs of new covariates and the expected optimal cost of misclassification (Bayes risk). However, estimating the latter is a formidable task due to the estimation of a high dimensional probability density and intractable integrals.In this work, we show that for linear classifiers this task can be considerably simplified, leading to a one dimensional integral for which we propose an efficient approximation. Experimental results on three datasets show consistent improvements over previously proposed methods for cost-sensitive classification. We also demonstrate that our proposed Bayes risk estimation procedure can benefit from additional unlabeled data which can be helpful when only small amount of labeled data is available.
The Design and Implement of Neusoft Education Online Platform

According to the actual needs of Dalian Neusoft University of Information, Neusoft Education Online (NEO) Platform is proposed in this paper. The traditional education model is teacher-centered, with the popularity of the Internet, colleges and universities are increasingly relying on student-centered education model. At first the requirements of NEO platform is analyzed and the system functions are describes in a modular way. Then, according to the content of the requirement analysis, the functional modules of the system are divided and the database is designed. In the process of system implementation, NEO Framework is used, and creating a new non-standard course is taken as an example that explains the implementation process. The NEO platform has been put into use, and the system is safe, stable and interactive, and has rich teaching content and presentation form. In the future, more work will be done to improve system functions and efficiency.
A Proposed Framework of an Intelligent Arabic Chatbot for Teaching Islamic History

A Chatbot is a conversational software agent, which interacts with users using natural language such as English or Arabic. Many Chatbots exist, with different knowledge-bases, programmed by the Chatbot builders. Reviews of relevant research show that there is a shortage in Arabic Chatbots. The purpose of this study is to propose a framework of an intelligent Arabic-based Chatbot to teach Islamic history, which can be used to create an Arabic Chatbot like human. The study presents an application on the use of the proposed Chatbot for teaching Prophet Muhammad Life (Seerah).
PENERAPAN METODE MNEMONIC BERBANTUAN MEDIA GAMBAR UNTUK MENINGKATKAN HASIL BELAJAR SISWA PADA MATA PELAJARAN IPA KELAS IV SDN 42 MATARAM TAHUN 2017/2018

This study aims to improve students learning outcomes by applying the images media assisted mnemonic method. This research is a Classroom Action Research conducted in two cycles. The data were collected by using objective test in consisting of 10 multiple choice items, and the data of teacher and student activity were taken through observation sheet. Observation sheets are used to find out the level of teacher and student activity assisted mnemonic method in the learning process by applying image media during the learning took place. Student learning outcomes in the first cycle reached an average of 75.5 with a percentage of 70% classical completeness and increased in cycle II to 84.28 with the percentage of classical completeness 85.71%. This it can be concluded that application of image media assisted mnemonic method can improve student learning outcomes in science subjects of class IV B SDN 42 Mataram.
AncDE with gaussian distribution for numerical optimization problem

This work is introducing an enhanced Differential Evolution (DE) called AncDE. This proposed algorithm is using an additional population from the current generation and located it as ancestor. There are two parameter controllers to manage the selection of ancestor vector; aup for selection frequency and arp for age of selection. In this work we were applying Gaussian distribution on aup and we tested it on CEC 2015 Numerical Optimization Problem. Standard Differential Evolution will act as the benchmark. The result shows that AncDE with Gaussian approach has produced better result than standard DE.
The Importance Of Assignment Or Dissertation Proofreading

Before submitting or printing an assignment or dissertation, it is very important to carefully proofread it. Proofreading is the final step to complete a document.
Addressivity in Online Platforms

Guest Lecture, Visiting Speaker ProgrammeSchool of Fine and Performing Arts University of Lincoln5-6:30 pm, 20 February, 2019How do artworks, memes and messages address online audiences? How do online platforms reorient messages’ means of appearing, circulating, and mattering to their receivers? Drawing from diverse sources – from Mikhail Bakhtin’s literary theory to Benjamin Bratton on planetary-scale computation – this lecture considers how it might be possible to theorize online addressivity: the unique ways in which platforms orient and reshape the act of addressing someone (or something) through ‘like’ and share, meme and message.
Aerial Image Segmentation with Clustering Using Fireworks Algorithm

Aerial images has different data characteristics when compared to other types of images. An aerial image usually contains small insignificant objects that can cause errors in the unsupervised segmentation method. K-means clustering, one of the widely used unsupervised image segmentation methods, is highly vulnerable to local optima. In this study, Adaptive Fireworks Algorithm (AFWA) is proposed as an alternative to the K-means algorithm in optimizing the clustering process in the cluster-based segmentation method. AFWA is then applied to perform aerial image segmentation and the results are compared with K-means. Based on the comparison using Probabilistic Rand Index (PRI) and Variation of Information (VI) evaluation metrics, AFWA produces an overall better segmentation quality.
A Classify-Before-Detect Method For Weakly Supervised Object Localization

Classify-Before-Detect (CBD) methods provide a reliable initialization for the object detector, and are widely used in weakly supervised object localization (WSOL). This paper proposes a new CBD method for WSOL based on saliency maps. A CNN is first trained to determine the existence of objects in an image. Then, with the trained CNN model for classification, a gradient-based saliency map is obtained to generate candidate locations of objects in the image. Finally, the accurate location coordinates of objects are obtained using the special characteristics of these objects. Experiments have been conducted on the Nexar traffic light dataset, it is shown that CNNs are able to successfully classify images even though the objects occupy only a few pixels in the training images and gradient-based saliency maps provide strong resistant capability to interference. More importantly, our proposed method can locate small objects precisely, which is very difficult for the current object detectors. Moreover, our proposed method is weakly supervised and effective.
BIKE and SIKE Hybrid Key Exchange Cipher Suites for Transport Layer Security (TLS)

This document describes new hybrid key exchange schemes for theTransport Layer Security (TLS) protocol, which are based on combiningElliptic Curve Diffie Hellman (ECDH) with one of the Bit Flipping KeyExchange (BIKE) or the Supersingular Isogeny Key Exchange (SIKE)schemes. In particular, this document specifies the use of BIKE orSIKE in combination with ECDHE as a hybrid key agreement in a TLS 1.2handshake, together with the use of ECDSA or RSA for authentication.Hybrid key exchange refers to executing two separate key exchanges andsubsequently feeding the two resulting shared secrets into theexisting TLS Pseudo Random Function (PRF), in order to derive a mastersecret.
Asymmetry of Deletion within the Pied-Piping Fragment

Fragment answers may form complex phrases within which an answer to the wh-correlate is embedded. Such fragments are dubbed “pied-piping” fragments, and the previous research observed that there is an asymmetry in deletion within the pied-piping fragment with respect to its position. While deletion is possible when the pied-piping fragment appears in final position, it is impossible when the fragment appears in non-final positions. To account for the asymmetry, two important factors have been addressed in the current research. Departing from the standard focus projection rules, the research follows a revised version of focus projection rules (Buring 2006, Chung 2015), in that external arguments or adjuncts may project up to the phrase that dominates them. This explains that the pied-piping fragment can receive [F]-marking and undergo focus-movement. In addition, scattered deletions are argued to be prohibited; two independent instances of ellipsis cannot be licensed within a sentence (Park 2016). Assuming that scattered deletions are generally banned in ellipsis contexts, the asymmetry is reduced to the difference in the timing of focus clustering. In final position the pied-piping fragment forms focus cluster with a higher [F]-marked fragment within VPs, so that nothing prevents it from undergoing focus movement. On the other hand, in non-final positions, the fragments form focus cluster in SpecFocP and necessarily fall into LF-intervention effects.
Creation of the united digital model of energy engineering complex

In the framework of the priority direction of the transformation of the Russian Federation domestic economy to digital format, the field of designing can become a key platform for the start of processes of digital transformation. The decisions laid down at this stage became the foundation for new objects. Not only the reliability and safety of the object operating, but also its modernity, competitiveness, economy, energy efficiency, and the ability to integrate into a developing digital community - all of it depends on the organization of the next steps in the construction and commissioning of the object, and also depends on the quality of a project engineering and quality of decisions made at this stage.
The influence of digital literacy onStudents’ independent language learning

The ability to make use internet aminities is often called as digital literacy. This kind of competency has been understood as motivation, knowledge, skill, and attitude in using digital gadgets effectively; such as smartphones, tablets, laptops, and dekstop PCs. This study examined the relationship between digital literacy and student’s independent language learning. This research applied quantitative approach. The population of this research is the students of Universitas Islam Indonesia that have taken General English class in the first semester. The research’s primary data was collected by closed questionnaire, and supported by structured interviews (by 90% response rate). Meanwhile, the sampling technique used is purposive random sampling, and data analysis method used is Pearson Product Moment’s corelative coefision and regression analysis . The result revealed significant positive influence of digital literacy types on students’ level in independent language learning.
Statistical Physics of Learning and Inference

The exchange of ideas between statistical physics and computer science has been very fruitful and is currently gaining momentum as a consequence of the revived interest in neural networks, machine learning and inference in general. Statistical physics methods complement other approaches to the theoretical understanding of machine learning processes and inference in stochastic modeling. They facilitate, for instance, the study of dynamical and equilibrium properties of randomized training processes in model situations. At the same time, the approach inspires novel and efficient algorithms and facilitates interdisciplinary applications in a variety of scientific and technical disciplines.