Reviewerly/exHarmony huggingface dataset:
Teaching Mobile Application Development in 20 Hours for High School Girls: A Web-Based Approach

Professions in the areas of Science, Technology, Engineering, and Mathematics (STEM) are the driver for technological innovation and economic growth. However, Educators are facing challenges creating awareness and excitement for STEM careers to attract young students to the field. Due to teenagers’ wide interest in mobile technologies, our camp used smartphones as a context to teach programming. We organized a one-week summer camp targeting middle and high school students. The camp introduced mobile application development using basic web technologies (HTML, CSS, JavaScript). Therefore, this paper presents an experience report describing our approach and the most innovative activities that were applied. Our evaluation of the camp includes surveys and the students’ projects to measure the success of the camp in reaching its objectives. The results show that the students enjoyed the camp, learned and used the main concepts in their projects, and became interested in the field. We also discuss the limitations and future improvements based on our experience and observations.
Color Image Segmentation Using a Fuzzy Inference System

A novel method is proposed in the scope of image segmentation that solves this problem by breaking it into two main blocks. The first block's functionality is a method to anticipate the color basis of each segment in segmented images. One of the challenges of image segmentation is the inappropriate distribution of colors in the RGB color space. To determine the color of each segment, after mapping the input image onto the HSI color space, the image colors are classified into some clusters by exploiting the K-Means. Then, the list of cluster centers is winnowed down to a short list of colors based on a set of criteria. The second block of the proposed method defines how each pixel of the input image is mapped onto a specified list of segmentation centers (obtained from the previous block). Usage of the Fuzzy Inference System (FIS) is the solution of this paper to allocate a segmentation center to each image pixel. The rules which the FIS utilizes are designed based on the color of each pixel and its nearby neighborhood. To assess the capability of this method, it is applied to the BSDS500 dataset. The structure of proposed method causes the ability of parallel programming which speeds up the run-time. The experimental results illustrate the superiority of the proposed method over the state-of-the-art methods in the image segmentation.
Comprehension Beyond Words: Using Wordless Books With Emergent Readers

Abstract Voices From the Classroom essays share readers’ reflections on teaching experiences, advice for new teachers, and perspectives on current issues.
Blockchain Reference Model and Use Case for Supply Chains within Enterprise Architecture

Blockchain Technology is disrupting in many industries, introducing a decentralized business model over peer-to-peer network. Moreover, many researchers believe that blockchain technology will modernize the global supply chain network, making it more efficient and economical. In order to achieve complex IT solutions like Blockchain with change management for business and IT models, enterprise architecture (EA) is a suitable approach holistically. However, there is a research gap from the blockchain study perspective for the enterprise architecture approach, more deeply inefficient supply chain issues of interoperability, data integration, use of common data, and track and trace issues along with different stakeholders existing in the enterprise domain. Thus, the main goal of this paper is to fill the unexplored research gap academically, more specifically, to solve supply chain issues with Blockchain Enterprise Architecture. As a result of this study, we developed a conceptual new Blockchain Enterprise Architecture (BEA) reference model for the supply chain. We expect our constructed model will be a guide for new business developers, architect designers, and scholars in the supply chain area, and specifically will assist them to trial reference models for new business development in the inception stage. Practically, we demonstrated the BEA reference model for the Pharmaceutical Industry supply chain as a use case.
RISK OF ANEMIA AMONG ELEMENTARY SCHOOL STUDENTS IN EAST KALIMANTAN PROVINCE, INDONESIA; A CASE CONTROL PROTOCOL STUDY

The issue of anemia in Indonesia still remains a homework for the Ministry of Health, as well as other related sectors. According to data from the Basic Health Research (Riset Kesehatan Dasar) in 2013, there are 31% female adolescents in Indonesia who suffers from anemia. However, this number increased to 48.9% according to data from the Basic Health Research in 2018, with the most proportion of anemia found in the 15-24 and 24-34 age groups. These cases clearly confirms that the health state of adolescents highly determines the success of health development, especially in the effort to establish the quality of the next generation in the future. This research uses case control design, where the case group population are students at Muhammadiyah Elementary Schools located in the city of Samarinda, East Kalimantan Province, whereas the control group population are students from Islamic Elementary Schools in the city of Samarinda, East Kalimantan Province. The statistic analysis being used is the multiple regression analysis to look for risk factor with the highest effect. This is a retrospective research, that is extracting past variable information from respondents so recall bias, which can cause wrong information, is at risk of occurance. Furthermore, the bias that might occur is that the respondent is bias by giving false answers. Another mistake is in the form of other cofounding variables not included in the research, which results in risk estimation value error.
The Method for Improving the Quality of Information Retrieval Based on Linguistic Analysis of Search Query

The paper describes the process of research and development of methods for linguistic analysis of search queries. Linguistic analysis of search query is used to improve the quality of information retrieval. Original search query translated to a search query in a new format after syntactic analysis. Using the features of query language allow improving the quality of information retrieval. Also, the paper describes the results of experiments that confirm the correctness of the method.
Automatic Detection of Language and Annotation Model Information in CoNLL Corpora.

We introduce AnnoHub, an on-going effort to automatically complement existing language resources with metadata about the languages they cover and the annotation schemes (tagsets) that they apply, to provide a web interface for their curation and evaluation by means of domain experts, and to publish them as a RDF dataset and as part of the (Linguistic) Linked Open Data (LLOD) cloud. In this paper, we focus on tabular formats with tab-separated values (TSV), a de-facto standard for annotated corpora as popularized as part of the CoNLL Shared Tasks. By extension, other formats for which a converter to CoNLL and/or TSV formats does exist, can be processed analoguously. We describe our implementation and its evaluation against a sample of 93 corpora from the Universal Dependencies, v.2.3.
THE AUTHORITY OF AN EARLY CHILDHOOD EDUCATION TEACHER IN THE PERCEPTION OF CHILDREN AND PARENTS

Every person – regardless of place of residence, age, sex, or social status – needs an authority figure, someone they can trust, someone who serves as their source of inspiration and a beacon of hope. However, numerous contemporary researches point out to the existence of a crisis in terms of personal examples, the decline in the quality of education both at home and at school, and the worrisome rise in consumerist and egotistical attitudes which results in pathologies of various shape and form and consequently leads to the general deg¬radation of society. The social life transformations necessitate the introduction of changes to education and the image and authority of a teacher. The purpose of this article is to highlight the role of authority in education, show teacher as a figure of authority as perceived by pupils and their parents, and their expectations and preferences as well as to attempt to define the future of authority in the changing world.
ALGORITMA C4.5 UNTUK MEMPREDIKSI PENGAMBILAN KEPUTUSAN MEMILIH DEPOSITO BERJANGKA

Deposits are one form of investment offered by the Bank or other financial institutions with the nature of regulating and binding according to the rules set by the manager and the investor or commonly called investors. The advantage of being an investor is getting a fee or profit calculated based on the agreed time period at the beginning of the agreement. Whereas for investment fund managers can be used to advance and develop their business and business. Finding and determining potential customers is the first step to running a financial business in the form of this deposit, before the transaction decision is taken which is a favorable decision for both parties, investors or managers, one of the decision-making techniques can be done using Data Mining using the C4.5 Algorithm which is a structured decision-making technique based on input variables so that it can produce the most potential typical information for customers to participate in time deposits.
Data Sketching for Faster Training of Machine Learning Models.

Incremental gradient (IG) methods, such as stochastic gradient descent and its variants are commonly used for large scale optimization in machine learning. Despite the sustained effort to make IG methods more data-efficient, it remains an open question how to select a training data subset that can theoretically and practically perform on par with the full dataset. Here we develop CRAIG, a method to select a weighted subset (or coreset) of training data that closely estimates the full gradient by maximizing a submodular function. We prove that applying IG to this subset is guaranteed to converge to the (near)optimal solution with the same convergence rate as that of IG for convex optimization. As a result, CRAIG achieves a speedup that is inversely proportional to the size of the subset. To our knowledge, this is the first rigorous method for data-efficient training of general machine learning models. Our extensive set of experiments show that CRAIG, while achieving practically the same solution, speeds up various IG methods by up to 6x for logistic regression and 3x for training deep neural networks.
Text visualisation for feature selection in online review analysis

Opinion spamming is a reality, and it can have unpleasant consequences in the retail industry. While there are, several promising research works done on identifying the fake online reviews from genuine online reviews, there have been few involving visualisation and visual analytics. The purpose of this work is to show that feature selection through visualisation is at least as powerful as the best automatic feature selection algorithms. This is achieved by applying radial chart visualisation technique to the online review classification into fake and genuine reviews. Radial chart and the colour overlaps are used to explore the best feature selection through visualisation for classification. Parallel coordinate visualisation of the review data is also explored and compared with radial chart results. The system gives a structure to each text review based on certain attributes, compares how different or similar the structure of the different or same categories are, and highlights the key features that contribute to the classification the most. Our visualisation technique helps the user get insights into the high dimensional data by providing means to eliminate the worst features right away, pick some best features without statistical aids, understand the behaviour of the dimensions in different combinations.
MONITORING THE FORMATION OF UNIVERSAL COMPETENCES OF STUDENTS

Monitoring the quality of students’ mastering educational programs is an important component of the educational process. Monitoring achieved learning outcomes is the collection, processing and analysis of competence level data in order to make management decisions in the field of education quality. Currently in Russia there are not enough scientifically based methods for assessing and monitoring students' competences.The staff of the Laboratory of quality problems in higher education at Pskov State University has been conducting research in the field of assessment and monitoring students' competences, including universal ones, for more than ten years. The assessment center, the students' self-assessment, the students' portfolio evaluation, the expert assessment during Internship and during the final exams are held on different courses of study.The purpose of this article is to analyze the experience of monitoring the formation of universal students’ competences of the Faculty of Physics and Mathematics of Pskov State University during the entire period of study. The article contains a model of monitoring universal students’ competences.The research used the following methods: analysis of the scientific literature, assessment center, questioning, observation, expert evaluation.
LOCATION-AWARE COMPUTING

The advances in mobile computing, location sensing, and wireless networking have led to a new class of computing, namely location-aware computing. Location-awareness concerns the use of information about a person’s geographical location to provide more relevant information and services to that person. Location-aware systems play a central role in ubiquitous computing to sense and react to real-world context.  The aim of this paper is to provide a brief introduction to location-aware computing.
The Use of the Present Perfect (pretérito perfecto compuesto) with Aoristic Value in the Speech of Latin American Students

This article focuses on the use of the present perfect (he cantado) with aoristic value, or rather, on pre-hodiernal contexts in which, as a rule, the simple form (canté) should appear. This verbal form is examined on the basis of a corpus of semi-guided interviews provided to Latin American students living in Genoa and taking into account its characteristics, the syntactic environment in which it is used, combinations with other verb forms, adverbial complements, temporal expressions, deixis and the communicative context in which it is inserted. This phenomenon has already been analyzed in several recent studies carried out by Azpiazu, Kempas, Montoro del Arco, Bermejo Calleja and Soto, both in European and American contexts, and has led to the conclusion that it could be related to discursive strategies of the speaker as well as to a convergence towards the local language (i.e., Italian).
Contour to Centroid Distance Graph as Feature in Hand Gesture Recognition

Abstract Hand gesture is often used as a way of communication that is intuitive and convenient in everyday human life. Kinect camera gives cheaper and easier way to research about the hand gesture than data glove. This research combines previous research Finger-Earth Mover’s Distance (FEMD) base and Fuzzy to recognize hand gestures captured by Kinect camera. The results are graphic of each gesture obtained from a distance of centroids to hand contour. This research will be followed by next research applying fuzzy of classifying each graph of hand gesture.
Semantic key phrase-based model for document management

Purpose Document management is growing in importance proportionate to the growth of unstructured data, and its applications are increasing from process benchmarking to customer relationship management and so on. The purpose of this paper is to improve important components of document management that is keyword extraction and document clustering. It is achieved through knowledge extraction by updating the phrase document matrix. The objective is to manage documents by extending the phrase document matrix and achieve refined clusters. The study achieves consistency in cluster quality in spite of the increasing size of data set. Domain independence of the proposed method is tested and compared with other methods. Design/methodology/approach In this paper, a synset-based phrase document matrix construction method is proposed where semantically similar phrases are grouped to reduce the dimension curse. When a large collection of documents is to be processed, it includes some documents that are very much related to the topic of interest known as model documents and also the documents that deviate from the topic of interest. These non-relevant documents may affect the cluster quality. The first step in knowledge extraction from the unstructured textual data is converting it into structured form either as term frequency-inverse document frequency matrix or as phrase document matrix. Once in structured form, a range of mining algorithms from classification to clustering can be applied. Findings In the enhanced approach, the model documents are used to extract key phrases with synset groups, whereas the other documents participate in the construction of the feature matrix. It gives a better feature vector representation and improved cluster quality. Research limitations/implications Various applications that require managing of unstructured documents can use this approach by specifically incorporating the domain knowledge with a thesaurus. Practical implications Experiment pertaining to the academic domain is presented that categorizes research papers according to the context and topic, and this will help academicians to organize and build knowledge in a better way. The grouping and feature extraction for resume data can facilitate the candidate selection process. Social implications Applications like knowledge management, clustering of search engine results, different recommender systems like hotel recommender, task recommender, and so on, will benefit from this study. Hence, the study contributes to improving document management in business domains or areas of interest of its users from various strata’s of society. Originality/value The study proposed an improvement to document management approach that can be applied in various domains. The efficacy of the proposed approach and its enhancement is validated on three different data sets of well-articulated documents from data sets such as biography, resume and research papers. These results can be used for benchmarking further work carried out in these areas.
Topological Graphic Passwords Made By Two Sun-graphs On Odd-graceful Labelling

The ring network has the characteristics of fast transmission and high efficiency. We construct series sun-graphs from ring networks. The series sun-graphs have topological graphic passwords (Topsnut-gpws) on odd-graceful labellings, and they can be encrypted by corresponding Topsnut-matrix and Text-based passwords. Ensure the topological graphic passwords of the series sun-graphs are more secure.
Permission-free Keylogging through Touch Events Eavesdropping on Mobile Devices

Mobile devices are carried by many individuals in the world, which use them to communicate with friends, browse the web, and use different applications depending on their objectives. Normally the devices are equipped with integrated sensors such as accelerometers and magnetometers, through which application developers can obtain the inertial values of the dynamics of the device, and infer different behaviors about what the user is performing. As users type on the touch keyboard with one hand, they also tilt the smartphone to reach the area to be pressed. In this paper, we show that using these zero-permissions sensors it is possible to obtain the area pressed by the user with more than 80% of accuracy in some scenarios. Moreover, correlating subsequent areas related to keyboard keys together, it is also possible to determine the words typed by the user, even for long words. This would help understanding what user are doing, though raising privacy concerns.
Decision Support for Smart Grid: Using Reasoning to Contextualize Complex Decision Making

The smart grid is a complex cyber-physical system (CPS) that poses challenges related to scale, integration, interoperability, processes, governance, and human elements. The US National Institute of Standards and Technology (NIST) and its government, university and industry collaborators, developed an approach, called CPS Framework, to reasoning about CPS across multiple levels of concern and competency, including trustworthiness, privacy, reliability, and regulatory. The approach uses ontology and reasoning techniques to achieve a greater understanding of the interdependencies among the elements of the CPS Framework model applied to use cases. This paper demonstrates that the approach extends naturally to automated and manual decision-making for smart grids: we apply it to smart grid use cases, and illustrate how it can be used to analyze grid topologies and address concerns about the smart grid. Smart grid stakeholders, whose decision making may be assisted by this approach, include planners, designers and operators.
TECMap: Technology-Enhanced Concept Mapping for Curriculum Organization and Intelligent Support

This paper extends a previous publication describing a system that utilizes a wide variety of available assessment information to automatically analyze students’ understanding at a conceptual level and offer relevant automated support to teachers and students. This organization and support can be at the course level or at the level of curriculum for an entire program of study. Intelligent support includes interactive visualization of the conceptual knowledge assessment, individualized suggestions for resources, and suggestions for student groups based on conceptual knowledge assessment. This system differs from prior related work in that it can operate on entire program curricula, and that the basis for analysis and feedback is entirely customized to the individual instructors’ course content. We discuss how the system is configured for courses and the curriculum levels, and describe our experience that indicates the benefits of the approach. We then provide detailed descriptions of how the system performs analysis and offers support in both course and curriculum scenarios.
Barter to Blockchain

In childhood, I heard many stories from my legendary grandfather about how certain people created immense amount of wealth in a short time, of course in an honest way, and then more importantly how they kept it all safe. While most little girls of my age were fascinated by fairytale stories, I found wealth creation ideas much more alluring and a means to be a powerful someone someday later in life. With time I came to know I was not the only one in this game. People in all ages and all times have ceaselessly thought over this puzzle of “creating wealth,” “securing it,” and “trading or investing for larger returns.” Be it gold, spices, cattle, slaves, land, or oil, wealth has many different forms and there are inherent flaws when it comes to trading in wealth. In this chapter, let’s discuss some of the different forms of money and figure out how this journey finally culminated in Bitcoin and Blockchain, one of the biggest technical inventions of the 21st century.
Serenity: A Low-Cost and Patient-Guided Mobile Virtual Reality Intervention for Cancer Coping

To investigate how low-cost virtual reality can improve accessibility and effectiveness of distraction therapy.