Reviewerly/exHarmony huggingface dataset:
Comment on “Quantum key agreement protocol”

The first two-party Quantum Key Agreement (QKA) protocol, based on quantum teleportation, was proposed by Zhou et al. (Electron. Lett. 40(18) (2004) 1149). In this protocol, to obtain the key bit string, one of the parties uses a device to obtain the inner product of two quantum states, one being unknown, and the other one performs Bell measurement. However, in this paper, we show that it is not possible to obtain a device that would output the inner product of two qubits even when only one of the qubits is unknown. This is so because the existence of such a device would imply perfectly distinguishing among four different states in a two-dimensional vector space. This is not permissible in quantum mechanics. Furthermore, we argue that the existence of such a device would also imply a violation of the “No Signaling Theorem” as well.
Technological Support of Teaching in the Area of Creating a Personalized E-course of Informatics

The paper deals with the issue of finding and assessing the effectiveness of the use of information technologies for the optimal setting of teaching procedures. One possible solution is to personalize the teaching of computer science subjects in terms of accepting constructivist approaches. An important part of this form of teaching is the involvement of procedures and activities known from eLearning support of teaching, which depend not only on the way of providing study materials but also on activities related to the verification of students’ knowledge. An important component of providing knowledge, with a view to developing learners’ cognitive and intellectual abilities, is the adaptive approach of the education system to learners. The paper is devoted to the design of a methodology for creating a personalized e-course that meets the higher attributes and requirements for personalization of teaching with the possibility of adapting to the learner in a given environment. The paper also includes a survey of the current state of perception of university students towards the use of mobile technologies in the area of learning.
Pedestrian lane and obstacle detection for blind people

Abstract Pedestrian lane and obstacle detection have been a big problem for a blind person. The person has to use special tool or assistant to do daily activities. This work has utilized camera function, connected with data processing (mini PC) to process information captured by a camera. At first, RGB image, which was captured camera, was converted into XYZ colour system. This colour system was very useful to highlight pedestrian lane to reduce other objects. Then, colour filter was implemented to remove unnecessary objects, followed by close morphology to expose pedestrian lane. The result is white region which represent pedestrian lane. Major axis was then calculated using moments and its angle (calculated counter clockwise with reference to x-axis) was sent to the user to notify him/her which direction he/she can go. In the process of obstacle detection, some samples of RGB images has been used to train a neural network. The model was then used as obstacle detector. RGB images captured by camera were then used as test data. The result &gt; 0.7 was considered as obstacle. The experiment shows that under illumination of &lt;15000 lux, the method can achieve 89.7 percentage accuracy on pedestrian lane detection and 100 percentage accuracy on obstacle detection.
Efficient Characterization of Topological Photonics Using the Broadband Green’s Function

A novel method is developed in this paper to characterize the band diagram and modal fields of gyromagnetic photonic crystals that support topolgoical one-way edge states. We exploy an integral equation based method that utilizes the broadband Green's function as the kernel. The broadband Green's function is a hybrid representation of the periodic lattice Green's function that includes an imaginary wavenumber component represented in exponentially decaying spatial series and a reminder in fast converging Floquet plane wave expansions. Special boundary conditions govern the fields across the interface of the gyromagnetic scatterers, leading to surface integral equations (SIEs) that involve three components including the pilot field, its normal derivative and its tangential derivative. To reduce the independent number of unknowns, roof-top basis functions and the Garlerkin's method are used to discretize the SIEs into matrix equations. The broadband Green's function allows converting the discretized SIEs into a linear eigenvalue problem of a small size. The eigenvalues and eigenvectors of the linear eigenvalue problem are directly related to the band solutions and modal fields of the photonic crystal. The proposed approach is an effective method to characterize wave interactions with periodic scatterers using integral equations. The solutions of the presented approach are compared against Comsol simulations for various cases to show its accuracy and efficiency.
How to Write a Good Project Report

This is not a template for how to format a project report. This document only contains pointers and suggestions for how to structure a report. We focus on what materials should be included.
Study of Chinese Text Steganography using Typos

Nowadays, with the Information Explosion and the rapid development of information technology, huge amounts of data are constantly being generated every day on the Internet. But most of the texts provided online is of a kind that usually contain many typos, which is very common among individual users, self-media, etc. However, disambiguation is human's talent, so these typos often do not frustrate human understanding the text, and sometimes it is even difficult to recognize some typos. This phenomenon appears both in English and Chinese, so it seems to be cross-lingual. Therefore, in such texts, it is not surprising that one can perform information-hiding by judiciously injecting typos. We studied Chinese typos in the text contents on Weibo or WeChat, and propose a text steganography method based on Chinese typos with the help of NLP, which can embed secret information by carefully injected typos and guarantee the security of the secret and the readability of the texts. Unlike format-based steganography algorithms, our algorithm can resist format adjustments, OCR re-inputs, etc. Furthermore, Weibo and WeChat platform contain many kinds of media, so by combining other algorithms, Cross-Media or even Cross-Social Network information hiding is practical.
A Homomorphic Encryption-Based Privacy Preserving Data Aggregation Scheme for Smart Grid

Smart Grid is a highly integrated power system which combines modern advanced information communication, sensor measurement, and automatic control technologies, including a large number of intelligent devices. It has the advantages of reliability, flexibility, security and self-healing and provides great service. However, when collecting, processing and transmitting huge amounts of data, devices such as smart meters in the network suffers from the problem of disclosing users' privacies. In order to solve such problem, this paper proposes a data aggregation scheme based on homomorphic encryption for Smart Grid, which adopts improved group signature, Paillier encryption system and El-Gamal signature algorithm. The solution not only realizes privacy protection for user identity and power consumption data, but also achieves real identity tracking of malicious signers. Finally, this paper analyzes the security and performance of the proposed scheme.
Implementation of a multi-agent mobile robot system to perform co-operative tasks

This paper discusses the functioning of two robots that perform the same task in a confined dynamic environment. They are modelled to work co-operatively with each other and interact with the obstacles in the environment. Various sensors including encoder, gyroscope and infrared sensors are used for the obstacle avoidance purpose. These sensors are connected to the micro controllers, available on each robot. The start point and the destination are made configurable and wireless communication is established between these two machines to enable the transfer of data. With the data transferred, the master bot uses effective navigation algorithm to plan the perfect path avoiding the obstacles if any to reach the destination. The slave bot follows the master bot intuitively. Thus, the two mobile robots here can maneuver together across a simple course with obstacles.
“RETHINKING UNIVERSITY TEACHING” A REFLECTION ON THE BLENDED GENERAL DIDACTICS COURSE

In recent academic years, the Blended General Didactics course of the Degree course in Primary Education has tried to renew the teaching and learning methods. In addition to increasing the actions and materials carried out within the moodle space, an aspect that was taken into account was that related to the face-to-face lessons. In these lessons the choice of new materials and more interactive methodologies led to the identification of the flipped lesson as one of the methodologies with more potential. The desire to activate more incisively the participation of students, who are mostly workers in this particular course, was one of the points taken into account to initiate this change. A necessary element to deepen this change was the comparison with the other experiences related to these proposals realized both in the various Universities and in the secondary schools of the second degree. This comparison allowed us to reflect on the potential of the new teaching methods and on the effects of change.
Research on the Structure of Smart Power Plant Based on In-depth Learning

Abstract The construction of intelligent power plant is not only a positive response to the corresponding policies of the country, but also more in line with the development trend of the modern information age, which is conducive to fully exploiting the potential of various resources of power enterprises and improving the actual operating efficiency and economic benefits of enterprises. Based on the analysis of the present situation of China’s power generation enterprises and the exploration road of smart power generation, this paper explains the background and definition of the generation of intelligent power plants, discusses the structure system and functions of each level of smart power plants, and analyzes the structure of smart power plants. The smart power plant built on the basis of big data application is also introduced finally.
On the factorization of iterated polynomials

Let $\mathbb{F}\_q$ be the finite field with $q$ elements and $f, g\in \mathbb{F}\_q\[x]$ be polynomials of degree at least one. This paper deals with the asymptotic growth of certain arithmetic functions associated to the factorization of the iterated polynomials $f(g^{(n)}(x))$ over $\mathbb{F}\_q$, such as the largest degree of an irreducible factor and the number of irreducible factors. In particular, we provide significant improvements on the results of D. Gómez-Pérez, A. Ostafe and I. Shparlinski (2014).
Factorization type probabilities of polynomials with prescribed coefficients over a finite field

Let $f(T)$ be a monic polynomial of degree $d$ with coefficients in a finite field $\mathbb F _q$, having a nonconstant derivative and a nonzero second Hasse derivative. We prove that for all but $d^2-d-1$ values of $s\in \mathbb F _q$, the following hold
[Prognostic model of small sample critical diseases based on transfer learning].

Aiming at the problem that the small samples of critical disease in clinic may lead to prognostic models with poor performance of overfitting, large prediction error and instability, the long short-term memory transferring algorithm (transLSTM) was proposed. Based on the idea of transfer learning, the algorithm leverages the correlation between diseases to transfer information of different disease prognostic models, constructs the effictive model of target disease of small samples with the aid of large data of related diseases, hence improves the prediction performance and reduces the requirement for target training sample quantity. The transLSTM algorithm firstly uses the related disease samples to pretrain partial model parameters, and then further adjusts the whole network with the target training samples. The testing results on MIMIC-Ⅲ database showed that compared with traditional LSTM classification algorithm, the transLSTM algorithm had 0.02-0.07 higher AUROC and 0.05-0.14 larger AUPRC, while its number of training iterations was only 39%-64% of the traditional algorithm. The results of application on sepsis revealed that the transLSTM model of only 100 training samples had comparable mortality prediction performance to the traditional model of 250 training samples. In small sample situations, the transLSTM algorithm has significant advantages with higher prediciton accuracy and faster training speed. It realizes the application of transfer learning in the prognostic model of critical disease with small samples.针对临床上重症疾病样本数量少容易导致预后模型过拟合、预测误差大、不稳定的问题，本文提出迁移长短时程记忆算法（transLSTM）。该算法基于迁移学习思想，利用疾病间的相关性实现不同疾病预后模型的信息迁移，借助相关疾病的大数据辅助构建小样本目标病种有效模型，提升模型预测性能，降低对目标训练样本量的要求。transLSTM 算法先利用相关疾病数据预训练部分模型参数，再用目标训练样本进一步调整整个网络。基于 MIMIC-Ⅲ数据库的测试结果显示，相比传统的 LSTM 分类算法，transLSTM 算法的 AUROC 指标高出 0.02～0.07，AUPRC 指标超过 0.05～0.14，训练迭代次数仅为传统算法的 39%～64%。应用于脓毒症疾病的结果显示，仅 100 个训练样本的 transLSTM 模型死亡率预测性能与 250 个训练样本的传统模型相当。在小样本情况下，transLSTM 算法预测精度更高、训练速度更快，具有显著优势。它实现了迁移学习在小样本重症疾病预后模型中的应用。.
TAILORING APPS AND PODCASTS FOR MOBILE LEARNING IN ENGINEERING EDUCATION

Mobile Learning (m-Learning) is a natural extension of distance education by employing Information and Communication Technologies (ICT) and wireless networks. In order to be effective, m-Learning requires especially tailored forms of user interaction with the mobile device and the creation of content that unlocks the full potential of this method. Two possible solutions to this problem are mobile-specific software applications and the delivery of contents in audio format – apps and podcasts, respectively.In this paper, we report on a case study of m-Learning in two Electrical Engineering courses: Electric and Electronic Circuits I and II (EEC I, EEC II). These are courses that have been taught in Blended Leaning (b-Learning) with Flipped Classroom since 2014 and, therefore, have an extensive background of ICT-enhanced learning, including Remote Labs, Simulations and Interactive Learning Objects.The main results can be classified in two categories: apps and podcasts. Concerning the first group, an educational app about resistor values has been developed, and it is now being modified in order to include Augmented Reality (AR). The AR is employed such that a mobile device can use its camera in order to identify the nominal value of a resistor by recognizing its color code. This is a very challenging application, as many aspects have to be taken into account, such as lighting conditions and the camera angle with respect to the resistor. A second app for in-classroom polling has also been developed and is now under final tests. A third app is being developed – its deals with sound that is captured to have its spectrum analyzed by the application of an FFT – Fast Fourier Transform algorithm; its second step is to apply filters. The development of apps is a project that involves undergraduate students who are enthusiasts of mobile devices and their application in Engineering Education.Additionally, two series of podcasts were created in the first semster of 2019,. They address topics of the EEC I and EEC II syllabi, with respectively 18 and 15 episodes and an average duration of 10 minutes each. Creation of podcasts for such courses is somewhat challenging, as it turns out to be very difficult to talk about an electric circuit without any circuit diagram. This aspect is shared with many other science and engineering courses that not only require visual diagrams but, more fundamentally, complicated mathematical formulas that are incompatible with the audio format. The two podcast series have already been deployed and are currently being used by the students of EEC I and EEC II; feedback is expected by the end of the semester. The podcasts are already in open access and, even though they have not yet been included in podcast-specific delivery platforms, they are already available on MERLOT – Multimedia Educational Resources for Learning and Online Teaching (www.merlot.org).
RETRACTED: Small Study in the Big Data Era: Application of Network Information Resources in Japanese Learning and Translation Studies

Abstract With the advent of the era of big data, Internet + has been included in national strategies, bringing unprecedented opportunities and challenges to all walks of life. Higher education is no exception. Internet + education is a major subject that requires a lot of effort to think about in foreign language teaching in colleges and universities. As an essential carrier of network information resources, iPad features massive information, mobile convenience, and robust interaction, which is quite suitable for the teaching of various courses. In this paper, the possibility of using the iPad in Japanese literature translation courses to enrich the teaching modes and concepts is explored.
Deep RL for autonomous robots: limitations and safety challenges.

With the rise of deep reinforcement learning, there has also been a string of successes on continuous control problems using physics simulators. This has lead to some optimism regarding use in auto ...
Joint measurability of POVM measurement assemblages and applications

The POVM measurement assemblage consisting of a set of positive operator-value measurements (POVMs) is an important tool for describing and studying the non-locality, quantum steering and quantum correlation of composite quantum systems. In this paper, we first introduce the definition of joint measurability of the POVM measurement assemblage $\mathcal{M}_S$ consisting of a finite number of POVMs and then prove that the joint measurability of $\mathcal{M}_S$ is equivalent to its compatibility. We give a general form of a POVM measurement which is jointly measurable with the one-rank projection measurement. It is proved that the POVM measurement assemblage $\mathcal{M}_S$ is jointly measurable if and only if the corresponding “row stochastic operator matrix" $\textbf{M}_S$ composed of $\mathcal{M}_S$ can be expressed as an “operator convex combination" of $\{0,I_S\}$—the row stochastic operator matrices. In particular, it is proved that the POVM measurement assemblage $\mathcal{M}(\textbf{n}_{0~},\textbf{n}_{1})$ induced by two three-dimensional real unit vectors $\textbf{n}_{i}(i=0,1)$ is jointly measurable if and only if $\textbf{n}_{0}=\pm\textbf{n}_{1}$. As an application, we obtain a necessary and sufficient condition under which a two-qubit quantum state is unsteerable with $\mathcal{M}(\textbf{n}_{0},\textbf{n}_{1})$.
Study on the Intelligent Campus System of the Internet of Things

The Internet of things makes our material world digital and networked, and connects the world with sensors in the form of intelligence. The application of Internet of things technology in "Digital Campus" and "smart campus" provides teachers and students with a more comprehensive intelligent environment and integrated information service platform, and provides convenience for the school's intelligent management. This paper focuses on the construction of Internet of things and smart campus, First of all, it introduces the research background and significance, then introduces the definition and application of Internet of things, consider the connection between Internet of things and smart campus, introduces the shortcomings of traditional campus, at the same time, introduces the role of Internet of things in smart campus, and finally expounds its advantages around the system construction of smart campus.
Design of QR Code-Based Digital Teaching Resources Navigation System

In order to solve the problems of orderly management, disclosure and evaluation of digital teaching resources, a QR code-based Digital teaching resource navigation system construction plan is proposed in this paper. As a new technology of data information coding, information storage, information transmission and information identification, QR code has become one of the most common information storage methods. The key function of QR code-based Digital teaching resource navigation system is initially realized, expanding the application field of the QR code. It is expected to realize more friendly, orderly and personalized management of Digital teaching resources, which is a beneficial attempt in the field of information resource management.
Smartglasses: How the Puzzle Fits Together (Conference Presentation)

The success of consumer AR Smartglasses relies on having a set of elements falling into place and playing nicely together. The first piece of the puzzle is content, which largely determines the appeal of any new consumer electronics product. Two other puzzle pieces, display technology and system power efficiency, determine how the content will be presented and for how long it will be available. The final piece is the industrial design that largely decides in what environment and circumstances the new product will be used. Taking into account these considerations, Bosch recently introduced the LightDrive display technology, designed to support present and future smartglasses content and system architectures. The LightDrive offering comprises a full Retinal Projection system enabling the design of smartglasses that look and feel like regular eyewear.
How to Optimally Combine Univariate and Multivariate Feature Selection with Data Sampling for Classifying Noisy, High Dimensional and Class Imbalanced DNA Microarray Data#

The emergence of DNA microarray chips has allowed scientists to measure the expression levels of thousands of genes simultaneously. Practitioners have used machine learning techniques to analyze the data from microarray experiments (gene expression data) and make diagnostic and/or prognostic decisions. However, the extremely large number of genes makes traditional machine learning techniques inefficient and ineffective. This chapter shows the importance of taking into account class imbalance when analyzing bioinformatics datasets. It determines whether the order in which feature selection and data sampling are applied is important or not by comparing three approaches developed for classification problems on datasets that exhibit both high dimensionality and class imbalance simultaneously. The chapter utilizes three feature ranking techniques, one form of filter-based subset evaluation, and wrapper subset selection, as well as a commonly used data sampling technique (Random Undersampling).