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Abstract: In school, at least in the US, we were taught to multiply by hand according to a standard algorithm. Most people find that algorithm difficult to use, and many children fail to learn it. We propose a new way to make sense of this difficulty: to treat explicit computation as perceptually supported physical and mental action. Based on recent work in neuroscience, we trace the flow of arithmetic information to emphasize demands on visual working memory and attention. We predict that algorithms that make moderate demands on memory and attention will work better than others that make stronger demands. We suggest that the judicious use of spatial schemas can reduce such cognitive demands. Experimental evidence from children in an inner-city school supports this claim. Our work suggests new ways to think about instruction. The goal should be to minimize demands that present obstacles and maximize instead what human eyes, bodies, and brains do well. [Copyright &y& Elsevier]

Summarizes the construction of paper folding. Method for approximating rational subdivisions or arbitrary angles and line segments; Angle-folding algorithm; Approximating angles, regular polygons and star polygons; Dissection of angles into equal parts.

Heritage visualizations are works of the cultural imaginary and this paper examines the artwork Artistic License: VR Sydney Cove circa 1800, which foregrounds the interpretive nature of heritage visualization. It is a reimagining in VR of A View of Sydney Cove, New South Wales, 1804, a contemporaneous print of Sydney Cove. Existing in the liminal space between accuracy and authenticity it is both art object and heritage visualization. The dual nature of this work supports engagement with wider audiences, fostering and broadening debate at individual, institutional, academic and societal levels about the nature and role of heritage. [ABSTRACT FROM AUTHOR]

In order to better solve the problem of automatic identification of quality control line and detection line in the detection of gold standard test strip, this paper proposes to collect the image information of gold standard test strip after color rendering through CMOS sensor, preprocess the obtained information, transform RGB image into gray image, build cloud model in the CIELAB/HSV/HSL space, and apply the improved AdaBoost algorithm to determine the position of detection line and quality control line Place. Compared with the traditional template matching method, it improves the accuracy and accuracy of recognition. [ABSTRACT FROM AUTHOR]

The paper presents a technique for determining the time index of growth of the slope of reverse voltage for double insulated cables, based on the body of the theory of series. It is proved that in the vicinity of the extremum point (maximum) the function of the reverse voltage is approximated by polynomials of the nth power. It is proposed to use second-degree polynomials for practical calculations. The method for calculating relevant indicators is illustrated using real data. Analysis of deviations made it possible to conclude that the calculation method proposed in the paper is far more accurate. In the final part of the study, it was concluded that there is a promising outlook for further development of methodological guidelines for determining complex indices of the remaining life of the cable, including but not limited to the use of various mathematical methods. [ABSTRACT FROM AUTHOR]

In order to solve the problems of the current art circulation information is not transparent and the centralized trading authority is asymmetric, this paper proposed a art blockchain certificate traceability model based on three chains. First, in view of the large amount of data in a single piece of artwork information, this paper proposed a blockchain-based symmetric searchable encryption algorithm, and used the interplanetary file system to securely store artwork circulation records on-chain and off-chain. Secondly, for the characteristics of the increasing effective data of artwork information, this paper proposed a blockchain-based inverted fast query and traceability algorithm to help data users realize fast traceability and positioning. At the same time, this paper proposed for the first time that the false information alliance chain stores false art circulation records to realize the processing of false information. Finally, experiments verify the feasibility of the model for big data security storage and fast query traceability. Experiments show that the model is feasible and the query method is efficient. [ABSTRACT FROM AUTHOR]

The Chameleon Educational Policy Reforms' (CEPR) 25th anniversary was celebrated at the Global General Assembly with the 2075 Decennial Analysis of Schooling (DecAS) announcement of the attainment of a benefit-cost ratio of >1.0. The attainment of a global positive net value of education is directly linked to the educational reforms established to 'provide the right access to the right education for all people' (CEPR, 2050). The Chameleon reforms, informed by The Algorithm, produce policies that instantly adapt to the learning environment and needs of students. Barriers that effect students' learning are removed, in stark contrast to historic processes that viewed students as the barrier to be removed from learning environments. The case studies presented in this paper are guided by three questions: 'Where are we now?', 'How did we get here?', and 'Are we there yet?'. Questioning the 'here and now', directs a look back from educational engagement currently governed by the CEPR to key moments and movements in the attainment of past grand policy announcements that no child be left behind to live in poverty. And 'yet', leads to critical consideration of the ongoing engagement with The Algorithm. Artifacts detailing the 2045 commencement of annual donations from the richest two percent to fully fund global education remain sealed. The results of the annual donations are, however, publicly available; and some would say exploited (Gerve, 2072). Achieving self-sustainable economic cost-benefit status for the CEPR may release the Donators from those agreements and untether society from the Donators.

Edge computing enables portable devices to provide smart applications, and the indoor positioning technique offers accurate location-based indoor navigation and personalized smart services. To achieve the high positioning accuracy, an indoor positioning algorithm based on particle filter requires a large number of sample particles to approximate the probability density function, which leads to the additional computational cost and high fusion delay. Focusing on real-time and accurate positioning, an edge computing-enabled green multi-source fusion indoor positioning algorithm called APFP is proposed based on adaptive particle filter in this paper. APFP considers both pedestrian dead reckoning (PDR) signals in mobile terminals and the received signal strength indication (RSSI) of Bluetooth, and effectively merges the error-free accumulation of trilateral positioning and the accurate short-range positioning of PDR, which enables mobile terminals adaptively perform particle filter to reduce the computing time and power consumption while ensuring positioning accuracy simultaneously. Detailed experimental results show that, compared with the traditional particle filter algorithm and the map-constrained algorithm, the proposed APFP reduces fusion computing cost by 59.89% and 54.37%, respectively. [ABSTRACT FROM AUTHOR]

The application of big data, radiomics, machine learning, and artificial intelligence (AI) algorithms in radiology requires access to large data sets containing personal health information. Because machine learning projects often require collaboration between different sites or data transfer to a third party, precautions are required to safeguard patient privacy. Safety measures are required to prevent inadvertent access to and transfer of identifiable information. The Canadian Association of Radiologists (CAR) is the national voice of radiology committed to promoting the highest standards in patient-centered imaging, lifelong learning, and research. The CAR has created an AI Ethical and Legal standing committee with the mandate to guide the medical imaging community in terms of best practices in data management, access to health care data, de-identification, and accountability practices. Part 2 of this article will inform CAR members on the practical aspects of medical imaging de-identification, strengths and limitations of de-identification approaches, list of de-identification software and tools available, and perspectives on future directions. [ABSTRACT FROM AUTHOR]