scholarly journals SEMANTIC NETWORK TRANSFORMATION METHOD FOR AUTOMATION OF PROGRAMMING PROBLEMS SOLUTIONS EVALUATION IN E-LEARNING

2020 ◽  
Vol 2020 (4) ◽  
pp. 7-17
Author(s):  
Alexander Fedorov ◽  
Alexey Nikolaevich Shikov
Keyword(s):  
Semantic Network ◽  
Single Layer ◽  
Transformation Method ◽  
Abstract Concepts ◽  
Program Code ◽  
Optimal Value ◽  
E Learning ◽  
Network Transformation ◽  
Cutoff Threshold

The article presents a semantic network transformation method for a programcode into an N-dimensional vector. The proposed method allows automating the quality assessment of solving programming problems in the process of e-learning. The method includes the authentic algorithms of building and converting the network. In order to determine the algorithm in the program code there is a template of this algorithm, presented in the form of a subgraph of abstract concepts of the language in the semantic network, built on the basis of this code. The search for the algorithm by comparing the subgraph of the network with the template network helped to identify the BFS algorithm with a given accuracy: the cutoff threshold for the perceptron outputs is 0.85, which is based on the calculation of accuracy of the single-layer perceptron in the classification of the MNIST base equal to 88%, which confirms the effectiveness of the developed method and requires further research using machine learning methods to find the optimal value of the coordinates of the nodes of the semantic network and templates of algorithms.

Hard and light gamification in education: Which one to choose?

2020 ◽  
Vol 1 (1) ◽  
pp. 20-27
Author(s):  
E. V. Karmanova ◽  
V. A. Shelemetyeva
Keyword(s):  
Computer Games ◽  
Educational Process ◽  
Course Development ◽  
Learning Technology ◽  
Training Course ◽  
Resource Requirements ◽  
E Learning ◽  
Characteristic Features ◽  
Game Elements

The article is devoted to the implementation of gamification methods in the educational process. The characteristic features of light and hard gamification are presented. The appropriateness of using gamification when applying e-learning technology is considered. Classification of courses based on hard gamification taking into account the technological features of development is proposed: courses-presentations, courses — computer games, VR/AR courses. The article also illustrates the use of various game elements of easy gamification using the example of the module “Level up! — Gamification” of the Moodle LMS. The capabilities of this module can be used in an electronic course by any teacher who has the skills of working with the Moodle.The authors present the analysis of the development of a training course in sales techniques using hard and light gamification technologies, where the course development was assessed for its complexity, manufacturability, and resource requirements. The results of the analysis showed that the development of courses using hard gamification requires much more financial and time-consuming than the development of courses using light gamification.The article evaluates the results of the educational intensiveness intense “Island 10–22”, held in July 2019 in Skolkovo, in which 100 university teams, teams of research and educational centers, teams of schoolchildren — winners of competitions, olympiads, hackathons (“Young Talents”) participated. The results of the intense confirmed the effectiveness of the use of light gamification methods in adult training. Thus, the conclusions presented in the article reveal a number of advantages that light gamification has in comparison with hard gamification.

Classification of small type B/C follicles as primordial follicles in mature rats

Reproduction ◽  
2000 ◽  
pp. 43-48 ◽  
Author(s):  
S Meredith ◽  
G Dudenhoeffer ◽  
K Jackson
Keyword(s):  
Dna Synthesis ◽  
Granulosa Cells ◽  
Single Layer ◽  
Reliable Indicator ◽  
Type B ◽  
Primordial Follicles ◽  
Type C

In the present study, follicles were classified according to the morphology of their granulosa cells. Type B follicles contained only flattened granulosa cells; type B/C follicles had a mixture of flattened and cuboidal granulosa cells in a single layer, and type C follicles had a single layer of cuboidal granulosa cells. The primary objectives of the study were to determine whether 5-bromo-2-deoxyuridine incorporation into type B/C follicles was a marker for initiation of growth and how long type B/C follicles could remain at the same stage before transformation to type C follicles. Female Holtzman rats received bromo-deoxyuridine for 7 days. After the infusion (day minipumps were removed = day 0), rats were ovariectomized on days 0 (n = 9), 30 (n = 8), 90 (n = 8) and 150 (n = 9). The numbers of type B, B/C and C follicles within one ovary were determined using modified fractionator counting. Analysis over all times demonstrated that there were more (P < 0.0001) type B/C (941 +/- 61 per ovary) than type C (140 +/- 18 per ovary) or type B (159 +/- 19 per ovary) follicles. The numbers of type B and type C follicles did not differ from each other at any time. Only one of 34 rats evaluated had bromo-deoxyuridine-labelled type B follicles. On day 150, 57% of the bromo-deoxyuridine-labelled type B/C follicles remained from day 0. It is concluded that (1) DNA synthesis in granulosa cells of type B/C follicles is not a reliable indicator of impending growth; and (2) type B and type B/C follicles are both components of the pool of primordial follicles.

Optimization of K Value in KNN Algorithm for Spam and Ham Email Classification

2020 ◽  
Vol 4 (2) ◽  
pp. 377-383
Author(s):  
Eko Laksono ◽  
Achmad Basuki ◽  
Fitra Bachtiar
Keyword(s):  
Frequency Distribution ◽  
Confusion Matrix ◽  
High Accuracy ◽  
K Value ◽  
A Value ◽  
Optimal Value ◽  
Classification Evaluation ◽  
Email Spam ◽  
Email Classification

There are many cases of email abuse that have the potential to harm others. This email abuse is commonly known as spam, which contains advertisements, phishing scams, and even malware. This study purpose to know the classification of email spam with ham using the KNN method as an effort to reduce the amount of spam. KNN can classify spam or ham in an email by checking it using a different K value approach. The results of the classification evaluation using confusion matrix resulted in the KNN method with a value of K = 1 having the highest accuracy value of 91.4%. From the results of the study, it is known that the optimization of the K value in KNN using frequency distribution clustering can produce high accuracy of 100%, while k-means clustering produces an accuracy of 99%. So based on the results of the existing accuracy values, the frequency distribution clustering and k-means clustering can be used to optimize the K-optimal value of the KNN in the classification of existing spam emails.

scholarly journals Feature Extraction and Classification of Citrus Juice by Using an Enhanced L-KSVD on Data Obtained from Electronic Nose

Sensors ◽  
2019 ◽  
Vol 19 (4) ◽  
pp. 916 ◽  
Author(s):  
Wen Cao ◽  
Chunmei Liu ◽  
Pengfei Jia
Keyword(s):  
Feature Extraction ◽  
Kernel Function ◽  
Electronic Nose ◽  
Classification Accuracy ◽  
Extraction Methods ◽  
Object Function ◽  
Optimal Value ◽  
Processed Products

Aroma plays a significant role in the quality of citrus fruits and processed products. The detection and analysis of citrus volatiles can be measured by an electronic nose (E-nose); in this paper, an E-nose is employed to classify the juice which is stored for different days. Feature extraction and classification are two important requirements for an E-nose. During the training process, a classifier can optimize its own parameters to achieve a better classification accuracy but cannot decide its input data which is treated by feature extraction methods, so the classification result is not always ideal. Label consistent KSVD (L-KSVD) is a novel technique which can extract the feature and classify the data at the same time, and such an operation can improve the classification accuracy. We propose an enhanced L-KSVD called E-LCKSVD for E-nose in this paper. During E-LCKSVD, we introduce a kernel function to the traditional L-KSVD and present a new initialization technique of its dictionary; finally, the weighted coefficients of different parts of its object function is studied, and enhanced quantum-behaved particle swarm optimization (EQPSO) is employed to optimize these coefficients. During the experimental section, we firstly find the classification accuracy of KSVD, and L-KSVD is improved with the help of the kernel function; this can prove that their ability of dealing nonlinear data is improved. Then, we compare the results of different dictionary initialization techniques and prove our proposed method is better. Finally, we find the optimal value of the weighted coefficients of the object function of E-LCKSVD that can make E-nose reach a better performance.

A Conceptual “Cybernetic” Methodology for Organizing and Managing the E-Learning Process through [D-] CIVEs

2013 ◽  
pp. 242-277
Author(s):  
Pellas Nikolaos
Keyword(s):  
Second Life ◽  
Virtual Learning Environment ◽  
Spatial Awareness ◽  
Major Question ◽  
Principal Characteristics ◽  
Learning Programs ◽  
E Learning ◽  
Pedagogical Analysis ◽  
Viable System

This chapter presents a conceptual-pedagogical “cybernetic” methodology for cyber entities’ (avatars’) spatial awareness, in an innovative way by using Second Life (SL). According to this section, it’s crucial to answer the major question of how teachers can permit effective actions through the organizational complexity of virtual and technical interactions that SL governs, making it more practical for Higher Education. Additionally, the chapter’s objective emphasizes the creation of an organizational-educational (multi-) method, which is essential for effective planning and conducting in distance learning programs. Furthermore, the construction effort is based on Anthony Stafford Beer’s “Viable System Model” (VSM) principal characteristics, in which the chapter contends the pedagogical analysis of teaching and didactic process that should be supported by any “open,” “viable,” and “sustainable” virtual learning environment. The systematic description and classification of groups’ interaction scripts aim is to help facilitating and enhancing teams’ knowledge management by providing reusable patterns that leverage the ample possibilities.

Web knowledge

2006 ◽  
Author(s):  
Christopher Walton
Keyword(s):  
Semantic Web ◽  
Knowledge Representation ◽  
Knowledge Base ◽  
Web Applications ◽  
Semantic Network ◽  
Knowledge Bases ◽  
Web Standards ◽  
Description Framework ◽  
The Web

In the introductory chapter of this book, we discussed the means by which knowledge can be made available on the Web. That is, the representation of the knowledge in a form by which it can be automatically processed by a computer. To recap, we identified two essential steps that were deemed necessary to achieve this task: 1. We discussed the need to agree on a suitable structure for the knowledge that we wish to represent. This is achieved through the construction of a semantic network, which defines the main concepts of the knowledge, and the relationships between these concepts. We presented an example network that contained the main concepts to differentiate between kinds of cameras. Our network is a conceptualization, or an abstract view of a small part of the world. A conceptualization is defined formally in an ontology, which is in essence a vocabulary for knowledge representation. 2. We discussed the construction of a knowledge base, which is a store of knowledge about a domain in machine-processable form; essentially a database of knowledge. A knowledge base is constructed through the classification of a body of information according to an ontology. The result will be a store of facts and rules that describe the domain. Our example described the classification of different camera features to form a knowledge base. The knowledge base is expressed formally in the language of the ontology over which it is defined. In this chapter we elaborate on these two steps to show how we can define ontologies and knowledge bases specifically for the Web. This will enable us to construct Semantic Web applications that make use of this knowledge. The chapter is devoted to a detailed explanation of the syntax and pragmatics of the RDF, RDFS, and OWL Semantic Web standards. The resource description framework (RDF) is an established standard for knowledge representation on the Web. Taken together with the associated RDF Schema (RDFS) standard, we have a language for representing simple ontologies and knowledge bases on the Web.

Evaluating the Quality of Serious Games as Modern E-Learning Environments

2020 ◽  
pp. 206-221
Author(s):  
Yassine El Borji ◽  
Mohamed Khaldi
Keyword(s):  
Comparative Study ◽  
Learning Environments ◽  
Serious Games ◽  
Review Process ◽  
Research Effort ◽  
Learning Methods ◽  
E Learning ◽  
Specific Evaluation

This chapter focuses on aspects of the integration of serious games in the field of education by examining the quality of serious games intended to be integrated into education. This review process must take into account the coherence between all the aspects constituting the serious games as they are characterized by their diversity in terms of content and quality. By conducting a comparative study based on the various studies of evaluation and classification of serious games already carried out, the authors have focused their research effort in this chapter on the design of a tool for the evaluation of serious games quality intended to be used in the field of education. A tool that determines if the learning methods related to games are correlated with pedagogical aspects and contributes to the knowledge of serious games and promote their use in the educational sphere. The study offers two levels of evaluation, global and specific; the overall level allows a global judgment unlike the specific evaluation that ensures that there is always a balance between different aspects of serious games.

scholarly journals Bispectrum and Recurrent Neural Networks: Improved Classification of Interictal and Preictal States

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Laura Gagliano ◽  
Elie Bou Assi ◽  
Dang K. Nguyen ◽  
Mohamad Sawan
Keyword(s):  
Neural Networks ◽  
Multilayer Perceptron ◽  
Recurrent Neural Networks ◽  
Short Term Memory ◽  
Focal Epilepsy ◽  
Single Layer ◽  
Epileptic Seizures ◽  
Novel Approach ◽  
Multilayer Perceptron Networks

Abstract This work proposes a novel approach for the classification of interictal and preictal brain states based on bispectrum analysis and recurrent Long Short-Term Memory (LSTM) neural networks. Two features were first extracted from bilateral intracranial electroencephalography (iEEG) recordings of dogs with naturally occurring focal epilepsy. Single-layer LSTM networks were trained to classify 5-min long feature vectors as preictal or interictal. Classification performances were compared to previous work involving multilayer perceptron networks and higher-order spectral (HOS) features on the same dataset. The proposed LSTM network proved superior to the multilayer perceptron network and achieved an average classification accuracy of 86.29% on held-out data. Results imply the possibility of forecasting epileptic seizures using recurrent neural networks, with minimal feature extraction.

scholarly journals Some results on magic squares based on generating magic vectors and R-C similar transformations

2017 ◽  
Vol 5 (1) ◽  
pp. 82-96 ◽  
Author(s):  
Xiaoyang Ma ◽  
Kai-tai Fang ◽  
Yu hui Deng
Keyword(s):  
Transformation Method ◽  
New Method ◽  
Magic Squares ◽  
Magic Square ◽  
Similar Transformation

Abstract In this paper we propose a new method, based on R-C similar transformation method, to study classification for the magic squares of order 5. The R-C similar transformation is defined by exchanging two rows and related two columns of a magic square. Many new results for classification of the magic squares of order 5 are obtained by the R-C similar transformation method. Relationships between basic forms and R-C similar magic squares are discussed. We also propose a so called GMV (generating magic vector) class set method for classification of magic squares of order 5, presenting 42 categories in total.

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