Reviewerly/exHarmony huggingface dataset:
Enhanced Ranking of Websites Based on Credibility Evaluation

In the current era of internet, with continuous flow of information to web, it is a difficult task for a user to choose the right information. Information belonging to analogous type is provided by diverse service providers and it is a challenging to diagnose the reliability of information. This paper implements a framework to determine the reliability by calculating credibility value of each web portal through analyzing information published, link details, spam details of information available and updation details of web portal. Credibility score is assessed by evaluating page rank value, black list web sites, average number of hits of different pages, two quality factor values trustworthiness and timeliness. Web crawler gives page link details of varied number of web sites based on the query given by user. Finally, web sites are ranked and listed based on the credibility of web portals, which ease the job of users in assessing reliability of information available in internet.
A Web-Based Augmented Reality Approach to Instantly View and Display 4D Medical Images

In recent years, development in non-invasive and painless medical imaging such as Computed Tomography (CT) or MRI (magnetic resonance imaging), has improved the process of diseases diagnosis and clarification, including tumours, cysts, injuries, and cancers. The full-body scanner with superior spatial resolution provides essential details of complicated anatomical structures for effective diagnostics. However, it is challenging for a physician in glance over a large data-set of over hundreds or even thousands of images (2D “slices” of the body). Consider a case when a doctor wants to view a patient’s CT or MRI scans for analysing, he needs to review and compare among many layers of 2D image stacks (many 2D slices make a 3D stack). If the patient is scanned multiple time (three consecutive months, for instance) to confirm the growth of the tumours, the dataset is turned to be 4D (time-stamp added). The manual analysing process is time-consuming, troublesome and labour-intensive. The innovation of Augmented Reality (AR) in the last few decades allows us to illuminate this problem. In this paper, we propose an AR technique which assists the doctor in instantly accessing and viewing a patient’s set of medical images quickly and easily. The doctor can use an optical head-mounted display such as the Google Glass, or a VR Headset such as the Samsung Gear VR, or a general smartphone such as the Apple iPhone X. He looks at one palm-sized AR Tag with patient’s document embedded with a QR code, and the smart device could detect and download the patient’s data using the decrypted QR code and display layers of CT or MRI images right on top of the AR tag. Looking in and out from the tag allows the doctor to see the above or below of the current viewing layer. Moreover, shifting the looking orientation left or right allows the doctor to see the same layer of images but in different timestamp (e.g. previous or next monthly scans). Our obtained results demonstrated that this technique enhances the diagnosing process, save cost and time for medical practice.
TEACHER AND LEARNERS’ TALK DURING CLASSROOM INTERACTION

This study discussed about Students’ and learners’ Talk during classroom interaction. This study was conducted at SMK Telkom 2 Medan. This study used descriptive qualitative research as research design. The instrument used in this research were observation and interview. From the analysis of the data, it was found that there were some categories of classroom interaction, especially in the pattern of talk. Communication performed by the English teachers and their students were still using mix language between English and Indonesia. In performing the communication, the English teachers produced twelve categories of talk while their students produced four categories of talk.Key Words, Teachers, Students, Talk
Deep Graph Learning Based Approach for Identification of Text in Scene Video

Content based analysis, retrieval, searching of scene video has become a key area under computer vision. Apart from indexing and retrieval of videos, demands for video analysis to monitor illegal videos have revolutionized the text detection problem. Because of complex background, low contrast, illuminated, variable font sizes, traditional approach of video based Optical Character Recognition (OCR) system performs satisfactory to detect the text from video. Later, two state-of the-art methods like SIFT and MSER outperformed to detect the text in video but both of these methods fails to detect with complex background. The proposed architecture utilizes the deep graph learning model to detect and identify the scene text from video in two stages. First, regions of similar nature are extracted from the frames by applying undirected graphs. Second, the extracted regions are fed to the learning model to obtain the features which are convolved with internal layers to find the probability of existence of text by calculating the gradients and gray level contrast between text and background. Compared to the conventional detection methods like SIFT and MSER, the detection rate based on deep graph learning can reach 90%. Experimental results show that proposed method is effective compared to two state-of-the-art methods SIFT and MSER.
Wavelet based Chordiogram Image Descriptor for Image Retrieval

In this work, an efficient multiresolution approach based geometric details of localized edgels is proposed to represent an image, called wavelet based chordiogram image descriptor. The proposed approach mainly focuses on reducing the computational cost of retrieval system with the preservation of accuracy and resilient to illumination, scaling, noise and small rotations, and is performed by deriving the geometric features from the pyramid structure of an image using Discrete Haar Wavelet Transform. The proposed multiresolution approach based chordiogram image descriptor is comprehensively tested on benchmark datasets. The experimental results proved that proposed approach is considerably better in terms of time cost and retain the accuracy of existing approach.
Estimating the coupling strength of a Hamiltonian with four different measurement strategies

In this paper, we compare different measurement strategies for estimating coupling strength of a Hamiltonian. In particular, we estimate the coupling strength coefficient when the Hamiltonian couples the pointer (measuring device) momentum to an observable of the system. We compare the performance of the estimations via four different measurement strategies: measuring the position or the momentum of the pointer with or without postselection of the system state. Without postselection, it turns out that all the information of the coupling strength can be extracted by measuring the position of the pointer. As a contrast, no information of the coupling strength can be extracted if the momentum is measured without postselection. Hence, measuring the position is a better choice if postselection is not allowed. However, when postselection is employed, we find that no matter which observable is measured, one can always achieve a great amplification of the measurement outcome, which can be larger than the initial standard deviation of the pointer observable under certain circumstances, at an acceptable cost of losing a little accuracy for the estimation of the coupling strength. With postselection, the better choice of the observable to be measured depends on the characteristic of the measurement devices.
Phonological Problems of Translating English Advertisements into Arabic

An advertisement is a form of communication intended to promote the sale of a product or service, influence public opinion, gain political support, or to elicit some other response. It consists of various type, including style, target audience, geographic scope, medium, or purpose. An advertisement should catch a person's attention and quickly create a memorable impression. The main aim of the present paper is to investigate the phonological problems of translating English international TV advertisements into Arabic. It deals with the most common and popular TV advertisements. The importance of such advertisements lies not in its information content rather than in the achievement of the desired impact on the receivers. When translating such ads, certain linguistic elements (especially the phonological aspects like rhyme, rhythm, alliteration, etc.) are necessary to duplicate the impact an ad has on the domestic market in the foreign exchange. To conclude, translating international TV advertisements is a challenge since they cannot be translated 100% successfully without a loss in meaning or form. Since both English and Arabic belong to different language systems, it is difficult to maintain both form and sense which should have priority as it provides the message of the source language (SL) text and the translator should attempt to render form (particularly such sound devices as rhyme, rhythm, alliteration) as far as possible and be faithful to the SL message.
An Examination on the Effect of Information System and Organizational Participation Factors on the Intention of Continuous Use and System Introduction Performance: Focusing on the MES for SMEs

Background/Objectives: Manufacturing Execution System (MES) is a system that provides information that optimizes production activities throughout the manufacturing process. Many small and medium-sized manufacturing companies have recently introduced manufacturing execution systems to strengthen their competitiveness.However, many of them have not been getting the effect of introducing MES.To address this issue, this study aims to improve the efficiency of system application by analyzing the factors affecting the continuous use intention of MES and to help small and medium-sized enterprises that plan to adopt the system.Methods/Statistical analysis:The main subject of this study came out from the survey through the management or executive officers of small and medium-sized manufacturers that introduced the MES.A questionnaire was produced for this purpose andthe survey was conducted either by direct interview or by e-mail. The questionnaire was composed of 30 questions, asking for information system factors, organizational participation factors, continued use, system introduction performances, and general status. Using IBM SPSS Statistics 22 as an analytical tool for the questionnaires, technical statistics, reliability analysis, and exploratory factor analysis were conducted. In addition, using AMOS 22.0, we conducted a confirmed factor analysis, structural model analysis, and mediation effecttest.Findings: The results of the study are summarized as follows. First, it has been shown that information system factors have a significant effect on the continuing use intent. Second, it has been shown that the Organizational participation factors have a significant effect on the continuing use intent. Third, continuous use has been shown to have a significant effect on the system introduction performance. Fourth, continuous use was shown to have a mediated effect between external and endogenous variables.Improvements/Applications: If the questionnaire could be designed to identify the extent of system use by MES users, the more accurate results would be expected than it is now. In addition, if a questionnaire was organized to identify the level of application of MES-introduced companies' systems, the results of the study could be more meaningful. Keywords: SME, Intention of continuous use, System introduction performance, MES, Information system.
Multilayer Neural Network Based Fall Alert System Using IOT

Fall in elderly people staying alone is a health concern which draws the attention of researchers in past years. In this research, we develop an elderly monitoring system using advanced technology based on sensors and the Internet of Things. In this system, older people can avoid any interaction with healthcare institutions like nursing home and hospitals. We present this challenge by establishing a smart setup to monitor human behavior through accelerometer, pulse sensor and GSM. To implement this concept, we used an alert system to the personal care assistant, to monitor the data using different learning methods. Based on Multi-layer Neural Network technique data are collected from the sensors, then processed and passed to the server in the form of an alert through the buzzer, SMS, email or voice message. The result obtained show an accuracy level of 96% compared to other classifiers.
On the Global Convergence of Continuous–Time Stochastic Heavy–Ball Method for Nonconvex Optimization

We study the convergence behavior of a stochastic heavy-ball method with a small stepsize. Under a change of time scale, we approximate the discrete scheme by a stochastic differential equation that models small random perturbations of a coupled system of nonlinear oscillators. We rigorously show that the perturbed system converges to a local minimum in a logarithmic time. This indicates that for the diffusion process that approximates the stochastic heavy-ball method, it takes (up to a logarithmic factor) only a linear time of the square root of the inverse stepsize to escape from all saddle points. This results may suggest a fast convergence of its discrete-time counterpart. Our theoretical results are validated by numerical experiments.
Structures of Error Systems

In order to gain better understanding upon the root causes, mechanism, and laws for generating errors, we must resort to the research on the system in which errors occur-i.e., error system. As system structure determines system behavior, therefore, we need to gain in-depth understanding on the study of temporal and spatial dynamics of the patterns and orders that system elements are connecting, organizing, and interacting with each other.
Simultaneous Measurement of In-Plane and Out-of-Plane Displacements Using Talbot Fringe Projection

The fringe projection technique has been widely used in optical measurements. In this paper, we demonstrate a scheme to measure the 3D displacement of a deformed sample using Talbot fringe projection. In this process, we designed a two-dimensional square Talbot hologram. In this approach, we used the basic principle of triangulation, and a computer-controlled liquid crystal spatial light modulator (LC-SLM) was placed in the optical path. The Talbot array hologram was displayed on the LC-SLM screen and projected onto the surface of a sample. Two patterns were recorded: one before and one after deformation. We simultaneously acquired the in-plane and out-of-plane displacements using the digital image correlation (DIC) method. This scheme is simple and easily implemented. Theoretical and experimental results are presented.
At the Birth of the Future: Commentary on Part III

The logic of a software application is driven by an explicit or implicit framework for understanding some aspect of human activity. In the contexts of automated scoring, the relevant domains are typically those used to understanding an area of proficiency as well as more general domains that study the nature of proficiency and its social function. The process of developing software requires the formalization and specification of logic, rules, and representations relevant to the domain. In undertaking that formalization, many assumptions are often raised and require additional thought and research. Mismatches between how a user expects to use a system and how they interpret their encounter of the system can lead to unwanted cognitive load and corresponding construct-irrelevant variance unaccounted for from the domain perspective. A process-focused approach to understanding writing requires a process-enabling user ecosystem and concomitant data collection and processing.
07: Kognitive Systeme, Vorlesung, SS 2019, 22.05.2019

07 | 0:00:00 Start0:09:06 The Perceptron0:12:36 Decision Fonction g(x)0:17:28 Neural Nets0:19:14 Von Neumann Computer-Neural Computation0:24:02 Why Neural Networks0:29:38 Connectionist Units0:38:25 Backpropagation of Error0:40:06 Derivative dy/dx0:47:38 Backpropagation of Error0:52:10 Statistical Interpretation of MLP´s0:55:40 What does the Sigmoid do?0:57:57 A simple Neural Network
Characterising the Subject of Study

Generally speaking, (a) modal auxiliaries need to be distinguished from (b) non-auxiliary modal verbs (lexical modal verbs) and (c) non-verbal modal expressions (i.e. modal expressions belonging to a word class other than auxiliary verbs or lexical verbs).
Exploring Portuguese Word Embeddings for Discovering Lexical-Semantic Relations

Word2vec-like word embeddings are known for keeping linguistic regularities and thus good for solving analogies. Following this, we explore such embeddings for Portuguese in the discovery of lexical-semantic relations, which can be used for augmenting lexical-semantic knowledge bases. In this exploratory approach, we tested different methods for discovering relations of different types and confirm that word embeddings can be used, at least, for suggesting new candidate relations.
Improving Segmentation of Liver Tumors Using Deep Learning

Liver tumor segmentation from computed tomography images is an essential task for the automated diagnosis and treatment of liver cancer. However, such task is di cult due to the variability of morphologies, di use boundaries, heterogeneous densities, and sizes of the lesions. In this work we develop a new system designed for the segmentation of tumors from images acquired by computed tomography, the proposed system uses a network based on convolutional neural networks (CNN). The results are compared with a segmentation carried out by medical experts.
Visual Image Classification Based on Auto-Associative Memory

Numerous methods have been proposed to solve the problem of visual image classification in the past few years, but few of them are associated with human brain memory mechanism. In this paper, we study the mechanism of human brain auto-associative memory and apply it to the storage, retrieval, and classification of visual images. The learning process of the memory model is based on Hebb-like associative local learning rule and the recall rests on a normalized dot product operation. The proposed model is capable of storing and retrieving visual images as human brain, and it can achieve distributed storage and incremental learning. The experimental results on some benchmark image databases indicate that the proposed model outperforms previously proposed Pattern Association Memory Model (PAMM) and Self-Organizing Incremental Neural Network (SOINN) on recognition accuracy.
Transformations on Universe of Discourse and Rules in Error Systems

This chapter chiefly introduces the transformations on universe of discourse and rules for judging error in error systems. The universe of discourse (domain) here states the permitted range of objects of interest. In our research regarding error logic, error set, and error system, there are several types of domains: (1) the universe of discourse for error set C = $$\{$$(u, x)$$\mid $$ x $$=$$ f(G, u), u $$\in $$ U, f $$\subseteq $$ U $$\times $$ $$\mathbb {R}$$ $$\}$$ is $$U_C$$; (2) the range defined by error system S $$=$$ S(U(t), JG(t), Z(t), YS(t), G(t)) is called system ’s domain; (3) in error system S, the domain for structure JG(t) is $$U_{jg}$$; (4) in error system S, the domain for subsystems Z(t) is $$U_z$$; (5) in error system S, the domain for system elements YS(t) is $$U_{ys}$$; and (6) in error system S, the domain for rules for judging error G(t) is $$U_g$$. Universe of discourse (domain) plays a critically important role not only in the research of error set and error system but also in the process of error elimination. Many errors can be eliminated by changing the domain to which they pertain. From the definition on transformations, changes on universe of discourse and rules can lead to the changes in conclusion. For instance, regarding the addition of two numbers e.g. $$1+1=1$$, under rules and corresponding domain in the field of binary operation $$1+1=1$$ is wrong and it is correct under the rules and corresponding domain in the field of boolean algebra. With changed conclusion, it can inversely lead to the changes in rules for judging errors. In this chapter, we first investigate transformations of individual factors since there exists circular relationship between cause and effect. Then we consider the methods and laws for simultaneous transformations of multiple factors.
Advanced Decision Making and Interpretability through Neural Shrubs

Advanced decision making using machine learning should be both accurate and interpretable. Many standard machine learning techniques suffer from an inherent lack of transparency with regard to how the resulting decision was made. In the current work we aim to overcome this issue by introducing a hybrid learning approach using classical decision trees alongside artificial neural networks, dubbed a "neural shrub". The Neural Shrub methodology presented in this paper aims to maintain as much interpretability as possible without sacrificing either classification or regression accuracy. Experimental results are presented on several benchmark data sets to validate the proposed approach as well as provide insight into future research directions.
The Nature of Language and The Nature of Education in The Language Education Policy

This article proposes about the nature of language and the nature of education in frame of language education policy in Indonesia. Its discussion is intended to be one of considerations in how to design and formulate some policies in education, especially language education policy in the era of the industrial revolution 4.0. The primary discussion is started by presenting some critical expert views on the nature of language along with its relationship to the nature of education in general. The understanding on both of these terms will lead to the appropriate decision on the future language education policy. Comprehensive understanding on each of the terms enables readers, stakeholders, teacher practitioners, and government to be open-minded to decide the future steps in designing and formulating the education policy especially to language education policy. The developed analysis will be based on the educational phenomenon which happenned in all regions both local and national areas.
Аналітичний огляд підготовки бакалаврів з агроінженерії в умовах інформаційно-освітнього середовища

The article presents an analytical review of the preparation of bachelors in agr icultural engineering in the conditions of information and educational environment. The question of the frequency of use of the Internet for searching educational information was investigated; the types of devices that higher education students use to organize training; the degree of interest in relevant types of e-learning information; the state of use of the educational information environment in the process of professional training; types of information on visual perception. The requirements of the bachelors in agricultural engineering to work in the information and educational environment are clarified and the recommendations on creation of e-learning content of distance courses are given. The necessity to build a course using media objects, step by step control of the acquired knowledge and skills and continuous communication between the higher education applicant and the teacher are substantiated. Keywords: informational and educational environment, vocational training, bachelors in agricultural engineering.