A Unified and Complete Framework of Invariance for Six Points

Author(s):  
Yihong Wu ◽  
Zhanyi Hu
Keyword(s):  
Author(s):  
Xin Wang ◽  
Nian Yin ◽  
Zhinan Zhang

Abstract Early childhood education has long-lasting influences on people, and an appropriate companion toy can play an essential role in children's brain development. This paper establishes a complete framework to guide the design of intelligent companion toys for preschool children from 2 to 6 years old, which is child-centered and environment-oriented. The design process is divided into three steps: requirement confirmation, the smart design before the sale, and the iterative update after the sale. This framework considers the characteristics of children and highlights the integration of human and artificial intelligence in design. A case study is provided to prove the superiority of the new framework. In addition to enriching the research on intelligent toy design, this paper also guides for practitioners to design smart toys and helps in children's cognitive development.


2021 ◽  
Vol 1 ◽  
pp. 2107-2116
Author(s):  
Agnese Brunzini ◽  
Alessandra Papetti ◽  
Michele Germani ◽  
Erica Adrario

AbstractIn the medical education field, the use of highly sophisticated simulators and extended reality (XR) simulations allow training complex procedures and acquiring new knowledge and attitudes. XR is considered useful for the enhancement of healthcare education; however, several issues need further research.The main aim of this study is to define a comprehensive method to design and optimize every kind of simulator and simulation, integrating all the relevant elements concerning the scenario design and prototype development.A complete framework for the design of any kind of advanced clinical simulation is proposed and it has been applied to realize a mixed reality (MR) prototype for the simulation of the rachicentesis. The purpose of the MR application is to immerse the trainee in a more realistic environment and to put him/her under pressure during the simulation, as in real practice.The application was tested with two different devices: the headset Vox Gear Plus for smartphone and the Microsoft Hololens. Eighteen students of the 6th year of Medicine and Surgery Course were enrolled in the study. Results show the comparison of user experience related to the two different devices and simulation performance using the Hololens.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Deen Kemsley ◽  
Sean A. Kemsley ◽  
Frank T. Morgan

Purpose This paper aims to define the fundamental nexus between income tax evasion and money laundering. The G7 Financial Action Task Force (FATF) designates tax evasion as a predicate offense for money laundering. We determine whether this designation is complete from a conceptual standpoint, or whether there is a stronger connection between tax evasion and money laundering. Design/methodology/approach This paper applies the FATF definition for money laundering – as well as generally accepted definitions for tax evasion and for a standard predicate offense – to identify the necessary conditions for each crime. This paper then uses these conditions to test opposing hypotheses regarding the nexus between tax evasion and money laundering. Findings This paper demonstrates that tax evasion does not meet the conditions for a standard predicate offense, and treating it as if it were a standard predicate could be problematic in practice. Instead, it is concluded that the FATF’s predicate label for tax evasion, together with tax evasion methods and objectives, imply that all tax evasion constitutes money laundering. In a single process, tax evasion generates both criminal tax savings and launders those criminal proceeds by concealing or disguising their unlawful origin. Practical implications The FATF could strengthen its framework by explicitly defining all tax evasion as money laundering. This would enable regulatory agencies to draw upon the full combined resources dedicated to either offense. Originality/value The analysis demonstrates that tax evasion completely incorporates money laundering as currently defined by the FATF.


Author(s):  
Benny Senjaya ◽  
Alexander A. S. Gunawan ◽  
Jerry Pratama Hakim

Information Technology does help people to get information promptly anytime and anywhere. Unfortunately, the information gathered from the Internet does not always come out positive. Some information can be destructive, such as porn images. To mitigate this problem, the study aims to create a desktop application that could detect parts of human body which can be expanded in the future to become an image filter application for pornography. The detection methodology in this study is Viola-Jones method which provides a complete framework for extracting and recognizing image features. A combination of Viola-Jones method with Haar-like features, integral image, boosting algorithm, and cascade classifier provide a robust detector for the application. First, several parts of the human body are chosen to be detected as the data training using the Viola-Jones method. Then, another set of images (similar body parts but different images) are run through the application to be recognized. The result shows 86.25% of successful detection. The failures are identified and show that the inputted data are completely different with the data training.


2007 ◽  
Vol 7 (3) ◽  
pp. 184-208
Author(s):  
W. Hall

The cluster state model for quantum computation [Phys. Rev. Lett. \textbf{86}, 5188] outlines a scheme that allows one to use measurement on a large set of entangled quantum systems in what is known as a cluster state to undertake quantum computations. The model itself and many works dedicated to it involve using entangled qubits. In this paper we consider the issue of using entangled qudits instead. We present a complete framework for cluster state quantum computation using qudits, which not only contains the features of the original qubit model but also contains the new idea of adaptive computation: via a change in the classical computation that helps to correct the errors that are inherent in the model, the implemented quantum computation can be changed. This feature arises through the extra degrees of freedom that appear when using qudits. Finally, for prime dimensions, we give a very explicit description of the model, making use of mutually unbiased bases.


Author(s):  
Shih-Yuan Wang ◽  
Sheng-Lin Chang ◽  
Reay-Chen Wang

Supply chain management is a new and evolving paradigm for enterprises to cope with international competition and to improve global logistics efficiency. The suppliers’ performances affect not only supply chain execution results but also the profit capability and business survivability. However, suppliers’ performance assessment always involves a large dimension of supplier behaviors. Information on supplier behaviors is often difficult to be accurately demonstrated as quantitative data. For this reason, the study employs a 2-tuple linguistic variable to perform the initial evaluation and final assessment while keeping track of both linguistic information and data, which can avoid a tied result. Additionally, the modified linguistic ordered weighted averaging (M-LOWA) operator with maximum entropy is used to derive the maximum aggregation value under the current business strategy to reflect on the criteria. The focal company can then rapidly rely on the assessment results to represent the performance of suppliers and provide integrated information to decision makers. This study draws the complete framework for the issue of supplier performance assessment without limitations on categories of variables and scales.


2011 ◽  
pp. 295-316
Author(s):  
Markus Kampmann ◽  
Liang Zhang

This chapter introduces a complete framework for automatic adaptation of a 3D face model to a human face for visual communication applications like video conferencing or video telephony. First, facial features in a facial image are estimated. Then, the 3D face model is adapted using the estimated facial features. This framework is scalable with respect to complexity. Two complexity modes, a low complexity and a high complexity mode, are introduced. For the low complexity mode, only eye and mouth features are estimated and the low complexity face model Candide is adapted. For the high complexity mode, a more detailed face model is adapted, using eye and mouth features, eyebrow and nose features, and chin and cheek contours. Experimental results with natural videophone sequences show that with this framework automatic 3D face model adaptation with high accuracy is possible.


Solar Energy ◽  
2021 ◽  
Vol 213 ◽  
pp. 13-26
Author(s):  
Eduardo Abdon Sarquis Filho ◽  
Carlos Alberto Ferreira Fernandes ◽  
Paulo José da Costa Branco

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