Mobile Data Science: Towards Understanding Data-Driven Intelligent Mobile Applications

Due to the popularity of smart mobile phones and context-aware technology, various contextual data relevant to users' diverse activities with mobile phones is available around us. This enables the study on mobile phone data and context-awareness in computing, for the purpose of building data-driven intelligent mobile applications, not only on a single device but also in a distributed environment for the benefit of end users. Based on the availability of mobile phone data, and the usefulness of data-driven applications, in this paper, we discuss about mobile data science that involves in collecting the mobile phone data from various sources and building data-driven models using machine learning techniques, in order to make dynamic decisions intelligently in various day-to-day situations of the users. For this, we first discuss the fundamental concepts and the potentiality of mobile data science to build intelligent applications. We also highlight the key elements and explain various key modules involving in the process of mobile data science. This article is the first in the field to draw a big picture, and thinking about mobile data science, and it's potentiality in developing various data-driven intelligent mobile applications. We believe this study will help both the researchers and application developers for building smart data-driven mobile applications, to assist the end mobile phone users in their daily activities.Comment: Journal, 11 pages, Double Colum

Pembelajaran Sains Berbasis Enam Dimensi Sains pada Anak Usia Dini

Science is everywhere and even we interact with science every day. Science is divided into six dimensions, namely concepts, applications of concept, processes, scientific attitudes, creativity and the nature of science. This study aimed to describe and analyze how science learning in early childhood is based on the six dimensions of science. This research is very important to do so that later it can be used as a reference in teaching science to early childhood as a whole, which includes six dimensions of science. This research is classified as descriptive qualitative research. The method used was literature review. Data analysis was performed using content analysis techniques. The results of the study stated that six-dimensional science-based learning can be carried out in early childhood but is still limited to concrete, contextual and fun concepts and only covers five of the six dimensions of science. The role of parents as primary and first educators is very vital in six-dimensional science-based learning in early childhood, namely as a motivator, facilitator and developer of science learning

The Quickest, Lowest-cost Lunar Resource Assessment Program: Integrated High-tech Earth-based Astronomy

Science and technology applications for the Moon have not fully kept pace with technical advancements in sensor development and analytical information extraction capabilities. Appropriate unanswered questions for the Moon abound, but until recently there has been little motivation to link sophisticated technical capabilities with specific measurement and analysis projects. Over the last decade enormous technical progress has been made in the development of (1) CCD photometric array detectors; (2) visible to near-infrared imaging spectrometers; (3)infrared spectroscopy; (4) high-resolution dual-polarization radar imaging at 3.5, 12, and 70 cm; and equally important (5) data analysis and information extraction techniques using compact powerful computers. Parts of each of these have been tested separately, but there has been no programmatic effort to develop and optimize instruments to meet lunar science and resource assessment needs (e.g., specific wavelength range, resolution, etc.) nor to coordinate activities so that the symbiotic relation between different kinds of data can be fully realized. No single type of remotely acquired data completely characterizes the lunar environment, but there has been little opportunity for integration of diverse advanced sensor data for the Moon. Two examples of technology concepts for lunar measurements are given. Using VIS/near-IR spectroscopy, the mineral composition of surface material can be derived from visible and near-infrared radiation reflected from the surface. The surface and subsurface scattering properties of the Moon can be analyzed using radar backscattering imaging

Learning of Multimedia-Based Physics Concept Applications to Improve Students’ Motivation and Science Process Skills

Physics concept application is widely applied in daily life but students have a lack of knowledgeconcerning the concept of physics application. This research aimed to examine the motivation and skills of the scientific process through learning the concept of multimedia-based physics applications. This is experimental research, conducted on Year IX students of Islamic Senior High School. Samples were taken with purposive sampling techniques and divided into two groups of Mastery Learning Scores (MLS), MLS ≥ 70 and MLS< 70. Data were collected from Pre-test and post-test. The motivational data was presented through the category table, while the science process skills were analyzed using the Independent sample t-test. After the treatment, the initial motivation of the MLS class ≥ 70 was increased from 66.1% to 81.9%, while it was from 63% to 82.5% for the MLS class< 70. Besides, the final science process skillswere significantly different between the two classes, indicating byt count >t table 2.14 > 1.65. This study suggested that learning concepts of multimedia-based physics applications can improve student motivation in both classes, while the science process skills only affect the students of the MLS group ≥ 70

Remote Sensing by Satellite Gravimetry

Over the last two decades, satellite gravimetry has become a new remote sensing technique that provides a detailed global picture of the physical structure of the Earth. With the CHAMP, GRACE, GOCE and GRACE Follow-On missions, mass distribution and mass transport in the Earth system can be systematically observed and monitored from space. A wide range of Earth science disciplines benefit from these data, enabling improvements in applied models, providing new insights into Earth system processes (e.g., monitoring the global water cycle, ice sheet and glacier melting or sea-level rise) or establishing new operational services. Long time series of mass transport data are needed to disentangle anthropogenic and natural sources of climate change impacts on the Earth system. In order to secure sustained observations on a long-term basis, space agencies and the Earth science community are currently planning future satellite gravimetry mission concepts to enable higher accuracy and better spatial and temporal resolution. This Special Issue provides examples of recent improvements in gravity observation techniques and data processing and analysis, applications in the fields of hydrology, glaciology and solid Earth based on satellite gravimetry data, as well as concepts of future satellite constellations for monitoring mass transport in the Earth system

The Effectiveness of the Science Experimental Guidebook on the Conceptual Understanding of Students with Learning Disabilities

This study aimed to develop a science experiments guidebook (based on discussion method and enriched worksheet) for fourth grade mainstreamed students with learning disabilities and to investigate its effect on their conceptual understanding of the "Matter and its Nature", "Living Things and Life", "Physical Events" and "Earth and The Universe" learning domains. Furthermore, mixtures, sieving, filtration, magnetism (Matter and its Nature), recycling (Living Things and Life), simple electrical circuit (Physical Events), and fossil (Earth and The Universe) concepts/issues were determined. Since the aim is to investigate the conceptual understanding of five 4th grade students with learning disabilities, the case study method was used. Conceptual understanding tests, drawing tests, and semi-structured interviews were used as data collection tools. The science experiments guidebook was presented to the students in worksheet format. Besides, worksheets were enriched with avatar images, mobile applications (QR codes), hands-on experiments, and active learning techniques (brainstorming, buzz 22, aquarium, and snowball). As a result of the research, it can be said that the science experiments guidebook had a positive effect on the conceptual understanding of students with learning disabilities

Simulation

Welcome to this graduate course on Discrete-Event Simulation, a hybrid discipline that combines knowledge and techniques from Operations Research (OR) and Computer Science (CS) (Figure 1). Due to the fast and continuous improvements in computer hardware and software, Simulation has become an emergent research area with practical industrial and services applications. Today, most real-world systems are too complex to be modeled and studied by using analytical methods. Instead, numerical methods such as simulation must be employed in order to study the performance of those systems, to gain insight into their internal behavior and to consider alternative (“what-if”) scenarios. Applications of Simulations are widely spread among different knowledge areas, including the performance analysis of computer and telecommunication systems or the optimization of manufacturing and logistics processes. This course introduces concepts and methods for designing, performing and analyzing experiments conducted using a Simulation approach. Among other concepts, this course discusses the proper collection and modeling of input data and system randomness, the generation of random variables to emulate the behavior of the real system, the verification and validation of models, and the analysis of the experimental outputs. FigurePeer ReviewedPostprint (published version

Brain data:Scanning, scraping and sculpting the plastic learning brain through neurotechnology

Neurotechnology is an advancing field of research and development with significant implications for education. As 'postdigital' hybrids of biological and informational codes, novel neurotechnologies combine neuroscience insights into the human brain with advanced technical development in brain imaging, brain-computer interfaces, neurofeedback platforms, brain stimulation and other neuroenhancement applications. Merging neurobiological knowledge about human life with computational technologies, neurotechnology exemplifies how postdigital science will play a significant role in societies and education in decades to come. As neurotechnology developments are being extended to education, they present potential for businesses and governments to enact new techniques of 'neurogovernance' by 'scanning' the brain, 'scraping' it for data and then 'sculpting' the brain toward particular capacities. The aim of this article is to critically review neurotechnology developments and implications for education. It examines the purposes to which neurotechnology development is being put in education, interrogating the commercial and governmental objectives associated with it and the neuroscientific concepts and expertise that underpin it. Finally, the article raises significant ethical and governance issues related to neurotechnology development and postdigital science that require concerted attention from education researchers