Reviewerly/exHarmony huggingface dataset:
Message from editor

Dear Readers,It is the great honor for us to publish 7th Volume, 4th Issue of Contemporary Educational Researches Journal.Contemporary Educational Researches Journal (CERJ) welcomes original empirical investigations and comprehensive literature review articles focusing on educational issues. The journal is an international peer-refereed journal that promotes the researches in the field of contemporary teaching and learning approaches and theories. The scope of the journal includes, but is not limited to; the following major topics as they relate to: Active Learning, Administration of Education, Adult Education, Affective Learning, Classroom Assessment, Classroom Management, Classroom Teacher Education, Collaborative Learning, College and Higher Education, College and Higher Education, Learning Assessment and Evaluation, Learning Psychology, Lifelong Learning Strategies, Learning Skills, Vocational Education, Measurement and Evaluation in Education, New Learning Environments, Portfolio Assessment, Professional Development and School Administration.A total number of seventeen (17) manuscripts were submitted for this issue and each paper has been subjected to double-blind peer review process by the reviewers specialized in the related field. At the end of the review process, a total number of five (5) high quality research papers were selected and accepted for publication. Aim of this issue is to give the researchers an opportunity to share the results of their academic studies. There are different research topics discussed in the articles. For example, Azis Pollozhani and Mentor Hamiti presented a case study of Macedonia and discussed social learning as a Europeanisation tool. In another study, Brikena Xhaferi examined the impact of quality teaching on student achievement. In addition, Emine Zendelli mentioned about the right to education as a fundamental human right and tried to respond to questions on the observance of this right and whether it has been limited. Mohamad Behroozi carried out a study in order to evaluate the quality of professorsâ€™ teaching process based on studentsâ€™ view and professors of Persian Gulf University. Finally, Anna Vintere discussed implementation of the education for sustainable development strategy in mathematics education through stakeholder cooperation.The topics of the next issue will be different. You can make sure that we will be trying to serve you with our journal with a rich knowledge in which different kinds of topics are discussed in 2017 Volume.I would like to present many thanks to all the contributors who helped to publish this issue.Best regards,Assoc. Prof. Dr. Deniz OzcanEditor â€“ in Chief
Current Apprises of Opinion Mining Methods

increasingly, the data is increasing day by day and storage capacity is expanding more and more, this allowing the field of SA to growing and developing faster in research and prospecting for different opinions and emotions to be combed and technically treated to be more accurate. In our present, data can be a wealth where major global companies and development, research and crime detection centers benefit from it. In this paper we focused on the current apprises of research in this field which contributed to various improvements in the field of sentiment analysis. We have tackles comprehensive overviews for different fields which related to the Sentiment Analysis (Transfer Learning (TL), Building Resource (BR), Emotion Detection (ED)) which have the popularity of researchers has gained in recent times and attracted them. We have the aim of this survey which is to give a clear and accurate picture about the techniques of analyzing emotions and related fields.
Adaptive and Optimization of Personalized Information Retrieval Model in Semantic Web

The recognition of user’s visited set of web pages for the prediction of web page is a key drawback. Thus the work is employed with the web access log files which is stored in the server. To understand the user interest patterns, the web access log files are extracted that depicts the user behavior. Various applications can be employed to predicting user’s behavior while serving the web. During this work, the proposed framework analyze the user usage, reinforced the content and the content retrieved with the semantic manner. The semantic information retrieval supported the user access pages are preprocessed and the web log data of the particular user is analyzed to identify the user profile. Then the retrieved information is graded with clustering the semantic content based results. The ranked content is then analyzed with the user profile to produce an optimized search results for the users based on the user classification.
2018 Benjamin Franklin Medal in Physics presented to Helen Rhoda Arnold Quinn, Ph.D.

The paper by Schito et al. (2017) contains many misquotations of the regional literature on the Holy Cross Mountains, that may confuse the reader. Present comment suggests more appropriate references related to the stratigraphic, tectonic and palaeothermal aspects of the commented paper. The burial-thermal history as interpreted by Schito et al. is based on doubtful, poorly documented or even unsubstantiated thermal maturity and stratigraphical data, ignoring important regional evidence, such as Caledonian (sub-Devonian) unconformity and Permian thermal anomaly. The 1-D modeling study performed by Schito et al. (2017) did not consider published alternative concepts of the temporal and spatial heat flow patterns. The resulting models, assuming uniformly low heat flow between the Ordovician and the earliest Cretaceous, are inconsistent with independent regional data pointing to a hotter Variscan (Carboniferous-Permian) thermal regime.
Release planning for multi-tenant software as a service (SaaS) applications

In multi-tenant Software as a Service (SaaS) applications, the providers are required to regularly deliver new releases of the software in order to satisfy the evolving requirements of tenants. The first step in a release development lifecycle is the release planning process. This thesis formulates the problem of the "next release" planning for multi-tenant Software as a Service (SaaS) applications. Two variables that influence release planning in SaaS applications are introduced: the degree of commonality of features and the contractual constraints. The commonality of a feature denotes the number of tenants that have requested that feature. The contractual constraints denote the effects of service levels to which tenants have subscribed on the release planning process. Furthermore, this thesis proposes three novel approaches in order to tackle the problem of the "next release" planning for multi-tenant SaaS applications. The first one is a prioritization approach that employs a Fuzzy Inference System (FIS) engine in order to speed up the release planning process and overcome the uncertainty associated with the human judgment. In this approach, the human expertise, which is represented by fuzzy rules, is considered automatically in the release planning process. The second and third approaches consider release planning as an optimization problem. The second approach uses an exact optimization method (Binary Linear Programming (BLP)) in order to generate an optimal release plan, while the third approach uses heuristic optimization method (Genetic Algorithm (GA)). All of the three approaches aim to generate a plan for the next release that maximizes the degree of overall tenants’ satisfaction, maximizes the degree of commonality, and minimizes the potential risk while taking into account contractual, effort, and dependencies constraints. Moreover, the thesis presents an experimental study of the proposed approaches in order to determine which approach is best suited to different sets of scenarios. In this experiment, the performance of the proposed approaches is evaluated using four criteria: the overall tenants’ satisfaction, the commonality, the adherence to the risk, and the running time. Additionally, the thesis presents an experiment that compares the proposed approaches with a compared model that is selected from the literature.
Mining Web Content Outliers for Improving the Quality of Search Results by using Mathematical Approaches

The main task of Web mining is to provide users for ret riev ing relevant information fro m the web effectively and efficiently.The unnecessary irrelevant duplicated web pages on searching informat ion fro m web affect the low quality of search results and increase indexing space and time co mp lexity.It becomes a challenging task to provide high quality and effective search result to retrieve information.Web content outlier min ing focus on mining outliers such as irrelevant and redundant pages fro m other the web pages under the same categories.A mathemat ical approach, Statistical Correlation Coefficient Approach with Term Frequency Inverse Document Frequency (TF.IDF) technique and domain dictionary is used to remove the irrelevant documents.And Kendall's Tau rank correlation coefficient is used to remove the redundant web documents and to retrieve ranked unique web documents.The results from proposed method gives F1-measures and accuracy higher than existing methods.
A Research on E Learning Model Using Adaptive Classification Method

due to the improvement of records and correspondence upgrades in changed fields, which have moreover stimulated the educational exercise section, accommodative e-gaining knowledge of frameworks are perceived generally of the preeminent eye catching exam areas in separation on-line education. This studies route permits engineers to accumulate a model of goals, inclinations and information of every man or woman client an amazing manner to alter the instructive to his/her desires and traits. The intention of this paper is to blessing the excellent in elegance in accommodative e-mastering frameworks as every different to the normal gaining knowledge of by way of portraying its measurements, plan, layout and hypothetical techniques. We generally tend to moreover feature some opportunities for our destiny work via discovering, dissecting and scrutinizing present frameworks..
The Acceptance of textbooks Writing Poetry-Based Love of The Country

This research is a development research that is difficult to develop textbook writing poetry based on love homeland. This development research refers to the Borg Gall stage model. The stage consists of ten stages of development, namely the stage of research and collection of preliminary information, the planning stage, the development stage of the initial production stage initial test phase, product revision phase, field trial phase, product revision stage, field test phase, , and dissemination and implementation. In this study only until the final product revision stage without including the phase of dissemination and implementation due to limited time research. In general, this study aims to explain the process of developing textbooks writing poetry based on love of the homeland. The results of the textbook development process are shown in the following stages. Validas textbooks were assessed by two validators, validation results indicated that the textbooks were included in either category because of the 75% percentage, the initial trial results were limited to seven class X students generated by student questionnaires, teacher interviews, and observer observations. From the results of field trials, students' grades in writing poetry resulted in an average score of 80 students.
#JustDoIt: Brand-to-Consumer Interaction via Twitter

Nike’s “Possibilities” campaign has become a prime example for social media adoption in marketing. In August 2013, Nike had asked its consumers to redefine “Just Do It” by taking to Twitter and sharing their athletic achievements under the #JustDoIt hashtag. The iconic slogan has since then evolved from a mere promotional message to a trending Twitter topic that continues to engage consumers today. By examining Nike’s #JustDoIt Twitter conversation, marketing professionals and scholars alike can develop a more informed understanding of how Twitter facilitates interaction between a brand and its consumers. The paper aims to explore how Twitter can be used to develop and maintain relationships between businesses and consumers by examining the interactions within Nike’s #JustDoIt conversation. Using Bakhtin’s (1981) notion of heteroglossia and Zappavigna’s (2011) interpretation of the imagined audience and ambient affiliation, this paper will conceptualize the interactions that took place and demonstrate their applications to the practice of social business (Rajagopal, 2013) and Integrated Marketing Communication (Kapoor, Jayasimha, and Sadh, 2013). The research questions are: (1) How does #JustDoIt facilitate interaction between Nike and its consumers? (2) What are Twitter users saying in Nike’s #JustDoIt conversation? (3) To what ends does #JustDoIt serve in Nike’s overall mission? Heteroglossia, the imagined audience, and ambient affiliation are all concepts that can be used to describe user interactions within Twitter hashtags. For businesses, these terms provide a framework for better understanding how branded content can reach audiences on Twitter, thus informing strategies that seek to engage consumers and spark conversations.
Training pedagogical universities students in the field of school learning administration

Н. С. Шкитина, Г
Identification of Fake Accounts for Making Trust on Network using Machine Learning

Social Networks are gradually influencing the people to communicate with each other and share the personal, public related information. Different social networks have different target people. In particular Facebook used to establish the friendship, LinkedIn to find new Job, these Rabid growth of social networks, people tend to misuse the social networks to spoil others reputation or to steal the others information’s. Fake profiles are dangerous in social networks platform. It is essential to identify the fake users from social networks. This work presents the novel approach to predict and differentiate the fake user and legitimate user from social networks by using Machine Learning algorithm and we achieved significant results.
Historical corner column

This issue presents a paper by Antonio Savini, Emeritus Professor at the University of Pavia, Italy, and Chair of the History activity Committee of the IEEE Italy Section. The paper originated at the time that was getting close to the anniversary of the discovery of thermoelectricity, credited to Thomas Johan Seebeck, Estonian scientist, in 1821. What is less widely known is that such credit is incorrect, since it has been recently proven that thermoelectricity was indeed first observed and reported by Alessandro Volta in 1787 [1] (based on previous investigations in Italian, dating to 2005). In this paper, Antonio Savini makes this point for the benefit of our wide community.
Data Governance Maturity Level at the National Archives of the Republic of Indonesia

The National Archives of the Republic of Indonesia (ANRI) as an institution given mandate to carry out state duty in the field of archives has vision as a pillar of good governance and nation’s collective memory. To implement it, the study of the grand design of the archival system arranged. That is very related to the data governance implementation. Therefore, ANRI needs to know the maturity level of the data governance function which had been held. The assessment was done by referring to the Stanford Data Governance Model. The result showed that data governance is still at an initial level. The foundational aspects are on an average of 1,2 which contains awareness, formalization, and metadata. While on project aspects are on average of 1,5 consisting of stewardship, data quality, and master data. In total, ANRI is at the level of 1,35. ANRI needs to make improvements for data management planning activities referring to Data Management Body of Knowledge (DMBOK) with a focus on people, policies, and capabilities dimensions in all aspects. This research is expected to be helpful for ANRI to make improvements corresponding to the recommendations thus ANRI could implement national data archival properly.
A Systematic Judgement to Automated Programming Contracts Generation

Contracts provide a pre-emptive approach in identifying programming errors at run-time using assertions or by formal Static analysis tool or Manual source code reviews. They describe the expected software behavior. Contracts written by developers have a greater error detection ability than the generic ones that are created automatically but may involve strenuous efforts for larger sized source codes. The intent of this paper is a concise study of prevalent approaches in the generation of contracts and to put forward an approach to derive programming rules for real-time concurrent Java source code automatically with reduced efforts. The proposed method extracts the scalar variables and computed constants from Static program code analysis, then identifies various dependencies dynamically and generates the declarative contracts automatically by Decision tree modeling of computed dependencies. These rules can then be utilized for software Verification.
Adenomatous Hyperplasia Of Thyroid Nodule Classification: Texture Feature Analysis Methodoloy Of Ultrasound Images

This paper, explores to extract textural feature from ultrasound Adenomatous Hyperplasia thyroid nodule. The extracted texture feature will help the clinician to improve diagnostic accuracy. The Fine Needle Aspiration (FNA) and Histopathology report is the conventional diagnostic methodology. It is an invasive technique and patients are subjected to painful process. Non-invasive, non-contact and low cost imaging tool is essential to increase the clinical diagnostic accuracy. Ultrasound imaging is a potential non-invasive modality to capture Adenomatous Hyperplasia thyroid nodule. Adenomatous Hyperplasia thyroid nodule is the common inflammation in thyroid gland abnormality. The texture features, using Law’s Texture Energy Measures (Law’s TEM), Neighborhood Gray Tone Difference Matrix (NGTDM) and Statistical Feature Matrix (SFM) are extracted from normal and adenomatous hyperplasia of thyroid nodules. The normal and abnormal images are demarcated using T-test analysis. The extracted feature shows significant difference between normal and abnormal images with p value less than 0.001(p &lt; 0.001). Hence the Law’s Texture Energy based feature may be used to identify the pathology in the thyroid ultrasound images.
Building the Bridge between Higher Learning Institution and Social Media Technologies through Mobile Learning in Malaysia

The Malaysian government sees education as one of the important factors in the country’s advancement. In order to achieve this, Malaysia needs to have an up-to-date technology such as Social Media Technologies (SMTs) to support the learning system in Higher learning institutions (HLIs). There is a great argument that 21st Century students learn differently. SMTs help to form a student-centered environments among the digital generation. It bridges a gap in knowledge in relation between SMTs and its impact in HLIs. Mobile learning and SMTs deliver the ability to communicate with academicians and students. HLIs should take this opportunity to connect SMTs to design a modern educational setting that will advance their learning experiences. It shows that SMTs have a great value for academic associated, particularly as a teaching and learning tool. HLIs and students have identified numerous challenges related to the adoption process. This study reviews and evaluates the SMTs related research articles published in academic journals between the year 2010 to 2018, mainly in HLIs fields. It identifies the impacts of SMTs on both students and academicianss in HLIs and associate how SMTs can be effectively connected to Mobile learning to support and enhance the students’ learning in Malaysia.
Recognizing on-line hand written alphanumeric character

Speed, accuracy, and flexibility are crucial to the practical use of on - line handwriting recognition. Besides, extensibility is also an important concern as we move from one domain to another which requires the character set to be extended. This research, produce a study for simple yet robust structural approach for recognizing on - line handwriting. In this approach is designed to achieve reasonable speed, high accuracy and sufficient tolerance to variations. At the same time, it maintains a high degree of reusability and hence facilitates extensibility. Experimental for study results show that the recognition rates are 98.60% for digits, 98.49% for the uppercase letters, 97.44% for lowercase letters, and 97.40% for the combined set. When the rejected cases are excluded from the calculation, the rates can be increased to 99.93%, 99.53%, 89.55% and 98.07%, respectively. Keywords: Structure extraction, structural primitives; Flexible structural matching, and On-line handwritten character recognition.
DISCOURSE PECULIARITIES OF INTERNET MEMES

The article is devoted to the discourse analysis of the internet memes.It highlights the peculiarities of the internet memes and figures out the features which implement political discourse based on the classification proposed by the Netherland scholar T. van Dijk in his book "Discourse and Power".The proposed theoretical material has been reworked stressing out the prior directions of contemporary linguistics.Practical material was purposefully selected from official pages of news agencies in social network Instagram among which there are: BBC News, Telegraph, the Independent, and the Times.All the mentioned resources are official representatives in social networks.The aim of this work is based on the process of figuring out discourse peculiarities of internet memes.To achieve the proposed aim there is a need to identify key information concerning internet memes themselves and the way they implement political discourse on the internet.The author proposes basic information concerning the research on discourse, political discourse and internet memes.Moreover, the article points out key classifications on discourse and internet memes.Being based on the classification by T. van Dijk the work analyses pragmatical, lexical, and semantical features which are appropriate for political internet memes.The article figures out separate phrases and word-combinations which express the highest level of emotional marking and implement core intentions posed by news agencies in Instagram.The priority was granted to internet memes which depict political situation in two countries -the United States of America and the United Kingdom.In conclusion the author proposes the results of the comparative analyses which presents distinctive as well as common features of political discourse verbalization of internet memes.
Experiments on Clustering Algorithms for Mixed and Incomplete Data

Clustering mixed and incomplete data is a goal of frequent approaches in the last years because its common apparition in soft sciences problems. However, there is a lack of studies evaluating the performance of clustering algorithms for such kind of data. In this paper we present an experimental study about performance of seven clustering algorithms which used one of these techniques: partition, hierarchal or metaheuristic. All the methods ran over 15 databases from UCI Machine Learning Repository, having mixed and incomplete data descriptions. In external cluster validation using the indices Entropy and V-Measure, the algorithms that use the last technique showed the best results. Thus, we recommend metaheuristic based clustering algorithms for clustering data having mixed and incomplete descriptions.