Reviewerly/exHarmony huggingface dataset:
التقابل اللغوى وتحليل الأخطاء في اللغة العربية

Error analysis is an analytical study of linguistic errors committed by an individual or group of individuals during the production of the first second language in speech or book. This analysis is concerned with classifying errors from two aspects: linguistic classification, such as grammatical errors, spelling, writing, or semantics. The Sinaitic classification is a mistake due to the first language to the second language, or a coincidental error. Error analysis focuses on the target language, it is known that there is a difference between languages in several areas and from structures, book and sound. This difference causes problems for students in learning the target language and makes mistakes in some areas, and the analysis reveals all the errors found. Grammatical errors include phonemes, morphology, and grammar, and the results of the book research indicated that grammatical errors are more frequent when a foreign language learner in the process of linguistic skill, and because one of the goals of teaching grammar rules in education stages is to establish the tongue and reduce melody in speech, the learner reads, speaks, or books He did not raise up, nor did he shorten erect.
Popper's Marxist: Pseudoscience As Policy Problem

Contemporary culture has seen an increase in the influence of fringe beliefs, chief among them pseudosciences: doctrines that masquerade as sciences. In light of the myriad ways in which the work of the public sector is intertwined with and depends upon that of scientists, it is essential that policymakers be able to recognize these pretender sciences. However, the academic literature has yet to yield a widely accepted and easily applicable definition of “pseudoscience”. This paper proposes that pseudosciences are most adequately characterized by their origin in social contexts in which there is little open, critical discussion of ideas: hence, in contrast with genuine science, there can be no assumption by non-scientist observers that pseudosciences have withstood criticism prior to their promulgation as knowledge. The applicability of this proposal is demonstrated with a case study, where it is used to identify the pseudoscientific features of Andrew Wakefield’s “anti-vaccine” advocacy
Hyperspectral image analysis using a simultaneous Denoising and Intrinsic Order Selection (DIOS) approach

Recent hyperspectral applications demand for higher accuracy and speed. This thesis develops a hyperspectral application analysis solution to address challenges in the different steps of denoising, order selection and unmixing of hyperspectral application data. Currently, all these steps process the data in cascade to achieve the optimum results. While in existing approaches the desired criterion is different in these steps, the proposed simultaneous Denoising and Intrinsic Order Selection (DIOS) method unifies these criteria. This property not only makes more sense for the desired optimization problem, but also leads to a faster processing algorithm. Consequently, DIOS avoids possible error propagation from the denoising stage to the dimension estimation stage, leading to more accurate results. The proposed method is based on minimizing the estimated Mean Square Error (MSE). The success rate of existing dimension estimation methods declines with the increase of image dimension and the decrease of Signal-to-Noise Ratio (SNR). The most competitive method fails to detect the correct dimension in 30% of cases around 2dB. However, in simulation results DIOS is shown to be successful with a failure rate of about 5%. The proposed unmixing method, based on a simple least square estimation, improves the speed performance least 10 times for an average-sized data cube of 2MB. Compared to some well known existing approaches, the unmixing method improves the estimated MSE up to 60% for SNR&lt;10dB. A new whitening process for hyperspectral applications with coloured noise is also proposed. Since the proposed method avoids the inversion of large matrices, computational complexity is substantially decreased. In the presence of coloured noise, simulation results show that the proposed whitening method lowers the MSE of unmixing and outperforms the existing whitening methods particularly when the noise correction factors increase.
Building a Retail Sysem Based on Distributed Databases Model

In recent years, distributed databases have become an important field of processing information, overcoming some limitations of centralized database such as overloading, bottlenecking while accessing, availability/ reliability of low fault tolerance. Our article proposes to build a distributed system (functions and databases) for POS (point of sale) retailers, data will be distributed across different locations but can still be linked together when required. At each location retailers can sell directly on the system (online or offline) so they can administer local databases and execute their local applications (business). Here we deploy the system on the distributed database management system based on Client-Server model. Therefore, aside from local management of data at clients (POS), there is also a server (manager) that stores data, manages and controls the entire system.
THE AWAKENING AND TRANSFORMATION OF SENSATION IN PU SONGLING’S ILLNESS POETRY

This article takes Pu Songling’s illness poetry as research subject to dig out his illness feeling about the five perceptions of the eyes, ears, tongue, and body. From deeply reviewing his four sensations in his poems, we have found the transformation of his life from sadness to glee. Due to the disease of his legs around his forty, he had spent much time lying down on the bed but he had strong feelings of the seasonal changes through his vision, hearing and touch to create a cold and lonely world around himself. After his sixty years old, the illness of his teeth had brought more severe transformation of the feeling of taste and touch. Finally, Pu Songling had accepted all of these sensations and lived with the painful feelings. The plentiful experience of feeling of illness and the fading desire for imperial examination had made huge transformation of Pu Songling’s sensations. The author would review these sensations item by item and through the real characteristic of describing the illness feelings in his poems to analyze deeply the emotional connotation of Pu Songling.
Information Sharing By Spanning Trees of a Graph By Labelled Sequence as A Key

Keeping the Information Sharing to manage cyber risks as a key, Security Intelligence speaks about secured data every day in today’s world. Hence it is considered that Cyber security is a Data Analytics challenge. For this reason, many researchers were effectively working on privacy protection and Liability protection. As a supporting hand for these global issues to secure data transfer, we propose a method to encrypt and decrypt the messages instantly by spanning trees of a graph with labelled tree sequences.
The project method is an effective interactive technology for the formation of key competencies of future specialists

The project method is considered as a pedagogical technology that involves a set of creative methods: research, exploration, and problem solving. The article emphasizes that the chief principle of learning with the help of the project method – “learning through the action”, according to which the essence of the learning process is discovery, a constant, real embodiment of something new. The essence of the project technology is to stimulate students’ interest in certain problems, involving the possession of a certain amount of knowledge, and through project activities that include solving one or a number of problems, show the practical application of acquired knowledge from theory to practice, harmoniously combining academic knowledge with pragmatic, adhering appropriate balance at each stage of training. It was researched that implementation of the project technologies in the educational the process may face certain problems but the active participation of students in the project work opens opportunities in an interesting form to develop their abilities and, most importantly, their personality.
The Influence of Instructor Readiness, IT Capability, Support of LMS Content, and their Implications on E-Learning Effectiveness in a Corporate University of BUMN

Education is needed by every individual and organization in improving the knowledge and skills of human resources to support organizational learning, and the learning process can be done in meetings in the classroom or online using IT, commonly known as e-learning. This research aims to identify the role of instructor readiness in supporting e-learning effectiveness and the influence of Support LMS content and IT Capability on perceived usefulness and perceived ease of use to support system acceptance and the success of e-learning. This research employs quantitative method. A questionnaire was distributed to 399 respondents and the unit of analysis is employees who have used the e-learning system of the corporate university. The results of the research can reveal the influence of the readiness of Instructor and Support LMS content on the application of e-learning and how e-learning is used as a learning media for interactions between learners with the instructor. The successful application of e-learning requires the instructor readiness, which includes the mastery of the technological and pedagogical aspects as a requirement of skill in teaching by using LMS. The successful implementation of e-learning effectiveness is strongly influenced by attitude toward using LMS and employee perceptions of support content that can provide benefits and easy to use by participants that will influence the attitude of participants to learn with e-learning system in a corporate university of BUMN.
Deep Learning based Effective Steganalysis

There is an evident paradigm shift in steganalysis techniques with discovery of deep learning networks. As steganalysis is a classification task, it is done by machine learning classifiers and ensembles of them. But with the proliferation of deep learning and Convolutional Neural Networks in many areas, the performance of steganalysis techniques have jumped up to a another high, because of the application of Convolutional Neural Networks. The traditional steganalysis techniques consists two important steps, i.e., feature extraction and classification; where as deep learning networks learn the features automatically, eliminating the need of extraction of handcrafted features. Because of this feature CNNs were highly successful in image recognition and image classification techniques. In addition to that, feature extraction and classification are combined together in deep learning hence classification would be more effective because of the learning of the features which are really important for classification. But in Steganalysis the task is to detect very subtle and weak noise created by the hidden data with steganography techniques. We have designed a deep CNN architecture customized for steganalysis task based on existing residual neural networks frame. We have introduced a descriptor to capture the inter pixel dependencies and which acts as an indicator for weightage of a particular feature maps. Thus the classifier can give more weightage to effective feature maps instead of treating all the feature maps equally. We have also used a gating mechanism by using sigmoid function after nonlinear activation function sandwiched between two fully connected layers. This enhancement to the existing deep residual neural networks has given better results in terms of error detection rate compared to the other deep learning based steganalysis techniques.
Implementation of Modified Signed Discrete Cosine Transform

One of the most important properties of Discrete Cosine Transform (DCT) is high power compaction, due to this property DCT is used for coding, image processing, image compression etc. The DCT application can be speed up by Signed Discrete Cosine Transforms (SDCT). The SDCT is the modification approximates of the DCT. In this paper by proposing signum function we proposed a flow diagram of algorithm and its architecture by considering 8 point transforms.
The Sound of Our Words: Singling, a Textual Sonification Software

As visualization struggles to grasp the intricate and temporal networks of meaning found in textual data, sonification emerges as a creative and effective way of representing language. Accordingly, this paper seeks to introduce Singling, a textual sonification software that allows users to create and manipulate auditory representations of a text's lexicogrammatical properties. To achieve this, we first present Singling's main features and interface. We then discuss an example of using this sonification software to explore—both analytically and aesthetically—three different poems. Overall, this paper seeks to introduce researchers, educators, and artists to the many possibilities of Singling and the practice of textual sonification, which includes data analysis, multimodal and collaborative narrative creation, and musical performance to name a few.
Eye-state-find: Sleepy or Yawn Driver Detection using Facial Features Extraction with Classification

Tiredness and weariness of car drivers lessen the drivers' capacities of vehicle control, characteristic reflex, acknowledgment and observation. Such decreased cautiousness dimension of drivers is seen around evening time driving or overdriving, causing mishap and posture extreme danger to humanity and society. In this manner it is particularly important in this ongoing pattern in vehicle industry to consolidate driver help framework that can recognize tiredness and weakness of the drivers. This undertaking presents a nonintrusive model PC vision framework for checking a driver's carefulness progressively. Eye following is one of the key advancements for future driver help frameworks since human eyes contain much data about the driver's condition, for example, look, consideration level, and weakness level. One issue regular to many eye following techniques proposed so far is their affectability to lighting condition change. This will in general fundamentally limit their degree for car applications. Ongoing recognition and following of the eye is a functioning territory of research in PC vision network. Restriction and following of the eye can be valuable in face arrangement. This undertaking portrays ongoing eye identification and following technique that works under factor and sensible lighting conditions. It depends on an equipment framework for the continuous obtaining of a driver's pictures utilizing camera and the product execution for checking eye that can maintain a strategic distance from the mishaps.
Infected cells of mammogram image and performance analysis using imaging techniques

Radiological image acquisition of mammogram and interpretation of cell count with image processing techniques is the focus behind this work. Image processing techniques incorporated mammogram image based nuclei count (MINC) calculates cell count and pixel intensity in malignant and entire breast area. MINC thus provides pixel based supervision of the image in the entire area and its malignant area and along with corresponding view of Craniocaudal (CC) and Mediolateral oblique (MLO). Specific focus has been done with calcification type which are malignant and PLEMORPHIC in nature. In addition, Region Morphometry features of area, perimeter, circularity and elongation has been discussed for the infected area.
Foreword by editor-in-chief

As the founding Editor-in-Chief, it is my great honor and pleasure to present you the first issue of Intelligent and Converged Networks, a new joint publication of the International Telecommunication Union (ITU) and Tsinghua University.
Dehazing using Fast Guided Image Filtering

Single image edge-saving smoothing methods such as guided picture shifting (GIF) and weighted guided picture shifting (WGIF) couldn't save fine structure. In this paper, another all inclusive guided picture shifting GIF is presented to defeat the issue. The Guided image filtering is made out of a worldwide structure exchange channel and a worldwide edgesaving smoothing channel. The proposed channel is connected to ponder single picture fog evaluation. Trial results demonstrate that fine structure of the dehazed picture is in reality protected better by the proposed Guided image filter what's more, the dehazed pictures by the proposed Guided filter are more than those dehazed pictures by the current Guided image filtering. from a nearby direct model, the guided channel figures the shifting yield by considering substance of direction picture. Guided channel be utilized as an edge-saving smoothing administrator like famous respective channel, however it has better practices close edges. In addition, channel normally quick and non approximate direct calculation, paying little mind to the bit size and the force go. Right now, it is one of the quickest edgesaving channels
The Elements of the Crime of Copyright Infringement on the Internet

With the creation of the human mind, the intellectual production of such machine created by the Creator began to appear in various forms starting from drawing and engraving on stones, the manufacture of clothing from plants leaves and animal skins, and making fishing rods and eventually to all cognitive sciences known by the world today and the evolution reached in all fields and aspects. Intellectual property rights are among the most important forms of human rights related to his intellectual production in the scientific, literary, artistic, and all forms of intellectual production in the different aspects of human life. It is clear to all that this production has its material and moral fruits. The intellectual property rights have become one of the most important forms of material rights that entitles its holder to dispose them, give them up and invest them. This right can be defined from the researcher point of view as a set of ideas that are written and issued by the human mind, and that can be accessed and identified just as tangible material objects. It includes all rights resulting from the intellectual activities of man in the literary, artistic, scientific, industrial, commercial and similar fields.
Influence of Flipped Classroom Model on Korean Language Learners' Achievement —— Focused on Beginner Level

HIS paper describes a structured attempt to integrate the ipped Tcl assroom pedagogical model into language classrooms.e purpose of this study is to examine the possible impacts of ipped classroom strategies on Korean language learners' academic performance, speci cally their listening and speaking abilities.Adopting a quasiexperimental design, two different formats for ip teaching were developed in this study.e results indicate that the ipped classroom was a more effective instructional design than the non-ipped classroom in both academic outcomes and the development of listening and speaking abilities.Given the positive results, this paper concludes with a call for more research into this promising pedagogy to contribute to its knowledge base across disciplines.
Developing the Thai Regional Dialect Based on Semi-automatic Technique

A dialect is the specific language of a particular locality that has a unique style, both words and accents. It shows the identity culture and the way of life of people in each region of Thailand and it should be treated to continue to be a national heritage. This research presents the prototype of four regional dialect of Thai based on smart phone by using Ontology technique. The application is easily search and finds the term of dialect words for each region. To develop ontology, a semi-automatic approach was used to build domain ontology from spoken corpus in Thai dialect. The domain ontology is created to handle terms and relationships to describe the features of four Thai regional dialect words. Also, the longest matching approach was used to increase the capability of the system to Thai word segmentation. The empirical results showed that the prototype can efficiently provide satisfied information for users in information searching. System testing technique and questionnaires were needed to evaluate system work and user achievement. The results shown that user satisfaction, both experts and users, was fulfilled the system performances and easily found required information.
Genetic Algorithm for Effective Fall Detection with Wrist Wearable Device

Falls have always been a major cause of injury related deaths among the old aged population in our country. It causes mental trauma and severe fractures to the bones and spine which impacts their quality of life. Therefore a proper fall prediction and alert system along with a timely rapid response could enable us to tackle such serious fall events and decrease the fatality. Various sensors and embedded controllers are used in conjunction with various machine learning classifiers to help us predict and optimize the falls effectively. This work presents a wrist wearable device using MPU-6050 sensor and raspberry-pi controller with help of machine learn algorithm which help us to predict the falls. Five different supervised learning algorithms and one unsupervised algorithm was implemented and evaluated on the basis of their accuracy, sensitivity and specificity. Out of all these classifiers, the decision tree with an accuracy of 85% was implemented in the system which classified the fall from the real time non-fall data sets. Further the performance of system was increased using genetic algorithm which gave better classification results unlike the normal decision tree classifier. Once the falls are predicted we can give a real-time response which can be an added feature to this system.
GIREP-ICPE-EPEC 2017 Conference

Preface The Proceedings present selected contributions from the international conference GIREP-ICPE-EPEC 2017 conference, which was hosted in Dublin from 3rd to 7th July 2017 by the Centre for the Advancement of STEM Teaching and Learning (CASTel) at Dublin City University Ireland. This conference was organized by a collaboration between the International Research Group on Physics Teaching (GIREP); European Physical Society - Physics Education Division, and the Physics Education Commission of the International Union of Pure and Applied Physics (IUPAP). The theme of this international conference was Bridging Research and Practice in Physics Teaching and Learning and it brought together international researchers and practitioners to share their knowledge and experiences over a week-long programme. A wide variety of topics and approaches, conducted in various contexts and settings, all adding a strong contribution to the field of physics education research were discussed. The GIREP-ICPE-EPEC 2017 conference was attended by 270 international researchers and practitioners representing 48 countries. The scientific programme offer a total of 271 contributions - including 6 invited keynote and 154 oral presentations, 40 symposia (each with four papers), 12 ICT demonstration/workshop sessions and 59 poster presentations. After the conference 95 papers were received on all seminar topics. The articles went through a rigorous process of in a double-blinded peer-review, involving members of the Editorial Board and additional referees in order to guarantee the quality of the content of this contribution. As the result two publications are issued, the book Concepts, Strategies and Models to Enhance Physics Teaching and Learning, published by Springer and GIREP-ICPE-EPEC 2017 Conference Proceedings book, presented here in ten parts.