Reviewerly/exHarmony huggingface dataset:
TEACHERS’ PERCEPTIONS TOWARDS “WHEN ENGLISH RINGS A BELL” TEXTBOOK AT SOME JUNIOR HIGH SCHOOLS IN ACEH TAMIANG

The relationship between teachers and textbooks is inseparable. But not all textbooks published are suitable with the learners` need and have good qualities. Thus, textbook analysis is needed to evaluate and improve a textbook which is used. Teacher‟s perception plays a fundamental role in the effective implementation of process teaching learning. This study was intended to describe teachers‟ perceptions towards “When English Rings A Bell” textbook at some Junior High Schools in Aceh Tamiang. This research used descriptive qualitative research. The research conducted in four junior high schools at Aceh Tamiang. They were SMP Negeri 1 Karang Baru, SMP Negeri 2 Karang Baru, MTs Swasta Al- Iklas Tanah Terban and SMP Negeri 1 Manyak Payed. In this research there were eight English teachers selected by the researcher as source of the data. The total populations in this research were 10 schools, but the researcher selected 8 English teachers as sample by using purposive sampling technique. In collecting the data, the researcher used documentation, interview and questionnaire. There were 20 interview questions that asking to the teacher and 20 items of the questionnaire. After analyzed the data, the result showed that generally all English teachers had the positive perspective toward “When English Rings A Bell” textbook. Almost all the criterion of good textbooks was included in this book. Although, this book did not support media such as audio recorded on cassette or video. Furthermore, all the teachers believed that textbook selection was important to conduct to make sure that the textbook they choose was suitable for their students. Keywords: Teachers’ Perceptions, English Textbook
Developing Distributorless Ignition System Learning Media for Automotive Engineering Students

This study aims to: (1) develop a learning media for practicing Distributorless Ignition (DLI) system for automotive engineering students and (2) identify the feasibility of the learning media for practical purpose in the classroom activities. The procedures of this research and development (RnD) study refers to the steps of product development by Borg and Gall (2007). A questionnaire was utilized to measure the learning media feasibility. Furthermore, there were media experts, content experts, and students as the user participated to evaluate and give feedback for the learning media improvement during the product development. The results reveal that (1) the distributorless ignition system learning media displays a systematic arrangement of the DLI components on acrylic boards accompanied by symbols of electrical components and (2) the product developed was suitable to facilitate students’ learning activity. The content and media experts scored the learning media as very feasible (7.59 &amp; 7.06), the average score of the response of small class users was 6.14 (feasible), and the scores of large class respondents were 6.80 (very decent). It can be concluded that the DLI learning media can be used to support the instructional activity for ignition system.
The Relationship among Reading Interest, Vocabulary Mastery, and Short Story Writing Skills of Indonesian Language and Literature Education Study Program Students of Tridinanti University Palembang

This study aimed to examine the relationship among reading interest, vocabulary mastery, and short story writing skill of Indonesian language and Literature Education Study Program students of Tridinanti University Palembang. A correlational research was used as the design of this study. 20 students participated as the sample of the study. To obtain the data, tests and questionnaire were administered. Based on the data analyses, it was found that there was a low correlation between student’s reading interest and their vocabulary mastery (r value =0.278 and ρ value = 0.234). Student’s reading interest and their writing skill of short story were weakly correlated (r value = 0.053 and ρvalue = 0.82). However, student’s vocabulary mastery and their short story writing skill signified strong correlation (r value = 0.803 and ρ value = 0.000). Meanwhile, the result of partial correlation analysis indicated that there was a moderate positive correlation (r value = 0.540 and ρ value = 0,017) among student’s reading interest, vocabulary mastery, and writing skill of short story. Keywords:  reading, vocabulary mastery and short story writing
Microtopography of the zircon crystal faces as essential component in modeling of the mineral formation process

Abstract Summary The results of the microtopography study of the zircon crystals surface from different geosystems are presented.
Exploiting Java Stack Forensics for Runtime Monitoring of IoT Services

Internet of Things (IoT) services play an increasingly important role in modern society with the more deployment in critical infrastructures. Ensuring IoT systems operating in a secure and safe environment is becoming a mandatory and urgent requirement. We have proposed a non-intrusive runtime monitoring mechanism in our previous work, but only runtime of C applications is considered in it. With the widely use of Java applications, the runtime monitoring of Java services is quite essential and important. However, the existing memory forensics on user processes are mainly focused on native stack of C or Java heap, which cannot meet the requirements of runtime monitoring of IoT services. In this paper, We propose an approach to dump and semantically reconstruct a Java stack, where a history of executed methods is obtained. We show the algorithms to extract methods in calling and the associated parameters, which are further encapsulated to be IoT events in XML format for runtime monitoring of IoT services, from Java stacks. The challenge of determining whether a stack frame is interpreted or compiled when reconstruct frames from the bottom to the top of the stack is solved. Experiments and evaluations show that the reconstruction is feasible and effective, with low resource occupation and real-time responses.
Facilitating Deep Learning Through Vertical Integration Between Data Visualization Courses Within an Undergraduate Data Visualization Curriculum

There is significant research underway on pedagogical approaches to data visualization that include teaching data visualization in various classroom settings, short-form data visualization instruction, the use of active learning, and the use of design patters for teaching and learning for data visualization. Most data visualization courses are taught independent of a major which might explain the lack of research in the area of vertical integration of visualization courses. This paper shares a method for facilitating deep learning through vertical integration between data visualization courses within an undergraduate data visualization curriculum. The data visualization process, concepts and techniques are introduced in a gateway course during students’ second year of study. Students enrolled in the gateway course for the data visualization major collaborate with other data visualization majors taking a senior level course on a visualization challenge with real-world application. The collaboration facilitates deep learning through vertical integration between the two classes. Students from both classes form a team to compete in a data visualization challenge as part of an annual technology conference in Indianapolis, Indiana. Participation in the team is voluntary. Students who compete in the visualization challenge work with faculty mentors from both classes and practice near-peer mentoring. This paper will provide insight into how the curricular constructs of the data visualization process and deep learning combine to facilitate vertical integration between data visualization courses.
Use of Multiple Distributed Process Instances for Activity Analysis in Videos

Video surveillance of security-relevant areas is being used ever more frequently. Because of limited human resources, they are usually only checked for the presence of problematic activity after a specific event has occurred. An approach to the solution is provided by automated systems that are capable of detecting and analyzing movement sequences of objects including persons. Even though solutions already exist for scene recognition [3, 4, 8, 9], their architecture, their problem-specific domain and the nature of the systems make it difficult to integrate new activities or better algorithms. A system structure based on decentralized process instances and their communication via defined interfaces would instead enable a simpler expansion of the system. This paper describes the determination of activities in videos using decentralized frameworks and their interconnection via standardized interfaces. All components act autonomously and provide their data via a central location. Based on this approach, the modular system can be used for a wide variety of applications in the context of machine learning.
Critical Success Factors for Data Virtualization: A Literature Review

Data Virtualization (DV) has become an important method to store and handle data cost-efficiently. However, it is unclear what kind of data and when data should be virtualized or not. We applied a design science approach in the first stage to get a state of the art of DV regarding data integration and to present a concept matrix. We extend the knowledge base with a systematic literature review resulting in 15 critical success factors for DV. Practitioners can use these critical success factors to decide between DV and Extract, Transform, Load (ETL) as data integration approach.
Building Your First Web Application

The purpose of Oracle Visual Builder Cloud Service (VBCS) is to allow you to build applications quickly – not quickly as “in a few weeks,” but quickly as “in a few hours.” This chapter will show you how to do just that.
Building Web Applications

In the last two chapters, you saw how to create business objects to store your data and how to connect to existing services for data. In this chapter, we will be building web applications that use this data and present it to a user in a web browser. You will see how to manage your pages and use the components in the VBCS component palette, including visualizations. Visual Builder Cloud Service makes it easy to create responsive web applications that scale to fit the available screen area, so VBCS web applications can also be used on mobile devices of varying screen sizes. However, if you want to build a specialized mobile application, VBCS can also help you build that. We will discuss mobile applications in another chapter.
An Assistant Device for Piano Keyboard Self-learning

This is a multidisciplinary study involving the areas of computer engineering, electronics, musical education, playful learning and entertainment. This article shows the device design process for the assistant device for piano keyboard.
Studying Relationships of Muscle Representations and Levels of Interactivity in a Canine Anatomy VR Environment

Virtual Reality (VR) is at the forefront of modern technology; revolutionizing current methods for conducting activities such as gaming, training simulations, and education. When considering anatomy education specifically, students must learn form, function, and movement of various bones, muscles, muscle tendons, ligaments, and joints within the body. Historically, cadaver dissection is believed to be the most optimal method of study, but it is not always accessible. We created a VR canine thoracic limb application that allows students to learn about musculoskeletal movements, while dynamically interacting with anatomical visualization. We aimed at increasing memory retention in a more immersive and engaging way. In our study, three major factors were considered: (1) spatial visualization ability of learners, (2) visualization styles of muscles, and (3) levels of interactivity of the application. Participants of differing spatial abilities (high and low) studied a virtual thoracic limb in one of two visual conditions (realistic muscles or symbolic muscles) and one of two interactive conditions (interactive manipulation or non-interactive viewing). We tested these against each other to determine which method of muscle representation holds the most effective form of memory retention, and what role interactivity plays in this retention. Before the experiment, we gathered data pertaining to student’s spatial visualization ability via a mental rotation test to create a baseline. After the experiment, we interviewed the participants to gather qualitative data about the application’s effectiveness and usability. We observed through 24 user studies that low spatial visualization users gained an advantage through dynamic visualization learning to almost perform as well as their high spatial visualization counterparts. Realistic muscles assisted participants with identifying anatomical views more efficiently, and therefore had a significantly better average compared to the symbolic representation.
Tracking of Load Handling Forklift Trucks and of Pedestrians in Warehouses

Trajectory computation for forklifts and pedestrians is of relevance for warehousing applications such as pedestrian safety and process optimization. We recorded a novel dataset with a varying range of forklift models and pedestrians, busy with loading or unloading in warehouses. We have videos with frequently occluded trucks in aisles and besides racks, some with busy pedestrian activity, such as in docking areas. Robust target localisation is very essential for seamless tracking results. For localising forklift trucks/pedestrians, we trained a deep-learning based, faster region-based convolution neural network (faster RCNN) on our own recorded data. We used detection from the model output to configure a Kalman filter to estimate the trajectories in the image plane. We also improved the forklift trajectory based on computing pixel saliency maps for the region of interest detected by faster RCNN. Our analysis shows that with robust target detection (fewer false positives and false negatives) from our trained network and Kalman-filter-based state correction, tracking results are close to ground truth.
Persuasive Design and Application of Intelligent Healthcare Product

Intelligent healthcare is an emerging interdisciplinary field combining medical field, network technology and interaction and service design (Joseph, Ahn, Kim et al. 2005; Ma, Wang, Zhou et al. 2018). It is also an innovation to the clinical treatment with which patients actively cooperate at a specific time and place. At present, in view of the physical health problems, researchers have put forward design methods of behavior intervention, behavior modification and behavior prevention, such as self-shaping design, temptation-resistant design, behavior-changing design and emotion design (DeVries and Chevaux 2014; Mo, Xu, Duan et al. 2016). However, the formation and transformation of healthy behaviors are a gradual process of mental cooperation. Persuasion theory suggests that the user can be induced and persuaded to develop or change behavior through design intervention, so as to achieve the goal of fitness and develop healthy behaviors (Rebecca and Tobias 2001; Stephen 2004; Chris 2006). To summarize, the structure of this paper is as follows. First, based on persuasion theory, the behavior model is investigated and the design factors of persuasion are put forward. Second, persuasive behavior components are studied to build a persuasion design model for intelligent health-care products, and persuasive design strategies are proposed in this part. Third, the above design factors and strategies are analyzed in combination with design cases. Finally, this paper will summarize and put forward the future research direction.
Sentiment Analysis of Images with Tensor Factorization

In recent years, large amounts of information have been transmitted through SNSs. Mainstream SNSs focus mainly on images. Given that many individuals use SNSs to express their sentiments, understanding the individual feelings of such users can be useful for helping identify potential demand in the society. Sentiment analysis of images in SNSs has thus attracted research attention. However, many existing studies have utilized a supervised learning approach with a high cost for labeling. By contrast, Wang et al., who used unsupervised learning, have acquired the sentiment of images through matrix decomposition from text information and visual information. However, text and visual information are not sufficient to acquire the desired result. In addition, sentiment polarity of the image is greatly influenced by text information. Therefore, this work will conduct a sentiment analysis of images by using tensor decomposition with an unsupervised learning approach. By considering the sentiment polarity of both text and visual features, this work aims to avoid being influenced only by text information.
An Efficient Event Detection Through Background Subtraction and Deep Convolutional Nets

The smart transportation system is one of the most essential parts in a smart city roadmap. The smart transportation applications are equipped with CCTV to recognize a region of interest through automated object detection methods. Usually, such methods require high-complexity image classification techniques and advanced hardware specification. Therefore, the design of low-complexity automated object detection algorithms becomes an important topic in this area. A novel technique is proposed to detect a moving object from the surveillance videos based on CPU (central processing units). We use this method to determine the area of the moving object(s). Furthermore, the area will be processed through a deep convolutional nets-based image classification in GPU (graphics processing units) in order to ensure high efficiency and accuracy. It cannot only help to detect object rapidly and accurately, but also can reduce big data volume needed to be stored in smart transportation systems.
Optimization and Application of Index Systems to Promote Transit-Oriented Development

Based on public transport development modes of different countries, this paper studies a combined dynamic evaluation method to promote transit-oriented development under the background of new urbanization, according to the characteristics of urbanization and residents’ travel in China. The index system is determined by the pressure state response model. A combination of subjectivity and objectivity is adopted. The evaluation value of transit-oriented development is calculated according to the weight coefficients and the monitoring scores of evaluation indexes. The advantages and disadvantages of the method are discussed based on the application effect of the method in typical cities. Improvement measures are proposed after analyzing the potential and existing problems of transit-oriented development.
Modified Type-2 Fuzzy Gesture Space Induced Physical Disorder Recognition

Gestures of a person symbolizing analogous physical disorder are not always exclusive. The gestural features of a subject suffering from the same physical disorder exhibit wide deviations for different instances. In presence of two or more gestural features, the variation of the attributes together makes the problem of physical disorder recognition more convoluted. This fluctuation is the main source of uncertainty in the physical disorder recognition problem, which has been addressed here using Type-2 Fuzzy Sets. First a type-2 fuzzy gesture space is assembled with the background knowledge of gestural features of different subjects for different physical disorders. Second, the physical disorder of an unknown gestural expression is concluded based on the consensus of the measured gestural features with the fuzzy gesture space. A fusion of Interval and General Type-2 Fuzzy Sets has been used to construct the fuzzy gestural space. The Interval Type-2 Fuzzy Set involves primary membership functions for M gestural features obtained from N subjects, each having L instances of gestural expressions for a given physical disorder. Along with that, the General Type-2 Fuzzy Set also includes the secondary memberships for individual primary membership curve, which has been obtained here by formulating and solving an optimization problem. To accomplish this, we have used Artificial Bee Colony. The secondary membership of a given source, characterizing the reliability in its primary membership assignment, is resolved based on the amalgamated knowledge of all the subjects’ primary membership functions. The adopted modified Type-2 Fuzzy Set-based uncertainty management strategy using gender independent training and testing databases has resulted in a classification accuracy of 93.48%.
3D Human Motion Retrieval Based on Graph Model

Motion retrieval has important practical value for the reuse of motion capture data. However, it is a challenging task to represent the motion data effectively due to the complexity of the motion data structure. As graph models is an effective way to represent structured data. This paper proposes a new method for human motion retrieval based on graph model. First, a method of graph model constructing based on Maximum Range of the Distance (MRD) is proposed. The MRD is used to select the joint pairs that are deemed important for a given motion, and different motions have different graph model structures. After that, similar motions can be retrieved by matching the similarity of the attributes of graph model. In the process of motion retrieval, cosine similarity is defined to measure the similarity of graph models. The experimental results show that the method proposed in this article is better than the previous methods of motion retrieval in many ways.
Factors of formation self-development abilities among university students

We substantiate the necessity of the student’s self-development ability formation in the conditions of multi-level educational programs implementation in a technical university. We ana-lyze various pedagogical and psychological approaches to the formulation and use in the relevant sciences concept of “self-development of a personality”. We explain the choice of a scientific ap-proach, in which self-development is defined as the process of purposeful activity of a personality in continuous self-transformation, conscious management of your own development, choice of goals, ways and means of self-improvement corresponding to your own life values and attitudes. We define one of the main tasks of technical universities – the task of updating and managing students’ professional education, the result of which is an organically formed personality capable of self-development through self-education and self-upbringing. We formulate external factors (scientific, academic, informational, social and sports bases of the university; research and professional activities at the educational stage; upbringing work under the guidance of lecturers and supervisors; academic work under the guidance of lecturers) and internal factors (factors contributing to students’ self-learning; factors contributing to the self-realization of your own plans and ideas) affecting the readiness for self-development of the future engineer. We substantiate the main external factor – the factor of personal influence of university professors on students’ self-development. Personal characteristics of the main types of technical university teachers are highlighted. We analyze the views of various scientific schools scientists on the problem of lecturer’s personality influence on the formation of self-education and self-development abilities of students.