Quantum random number generator based on photonic emission in semiconductors

We report upon the realization of a novel fast nondeterministic random number generator whose randomness relies on the intrinsic randomness of the quantum physical processes of photonic emission in semiconductors and subsequent detection by the photoelectric effect. Timing information of detected photons is used to generate binary random digits-bits. The bit extraction method based on the restartable clock method theoretically eliminates both bias and autocorrelation while reaching efficiency of almost 0.5 bits per random event. A prototype has been built and statistically tested.     

Viscoelastic relaxations in poly(dimethylphenyl methacrylates)

Summary Dynamic mechanical properties of poly(dimethylphenyl methacrylátes) were studied considering the different positions of the methyl groups on the phenyl ring. In all cases a clear relaxation can be observed which is associated to the polymer glass transition temperature (Tg). Nevertheless, at lower temperatures, viscoelastic activity is negligible. A correlation between the steric hindrance due to the methyl groups and the temperature at which the relaxation is detected, was established.     

Dissecting learning tactics in MOOC using ordered network analysis

Background

Select and enact appropriate learning tactics that advance learning has been considered a critical set of skills to successfully complete highly flexible online courses, such as Massive open online courses (MOOCs). However, limited by analytic methods that have been used in the past, such as frequency distribution, sequence mining and process mining, we lack a deep, complete and detailed understanding of the learning tactics used by MOOC learners.

Objectives

In the present study, we proposed four major dimensions to better interpret and understand learning tactics, which are frequency, continuity, sequentiality and role of learning actions within tactics. The aim of this study was to examine to what extent can a new analytic technique, the ordered network analysis (ONA), deepen the understanding of MOOC learning tactics compared to using other methods.

Methods

In particular, we performed a fine-grained analysis of learning tactics detected from more than 4 million learning events in the behavioural trace data of 8788 learners who participated in a large-scale MOOC ‘Flipped Classroom’.

Results and Conclusions

We detected eight learning tactics, and then chose one typical tactic as an example to demonstrate how the ONA technique revealed all four dimensions and provided deeper insights into this MOOC learning tactic. Most importantly, based on the comparison with different methods such as process mining, we found that the ONA method provided a unique opportunity and novel insight into the roles of different learning actions in tactics which was neglected in the past.

Takeaway

In summary, we conclude that ONA is a promising technique that can benefit the research on learning tactics, and ultimately benefit MOOC learners by strengthening the strategic support.     

Approximate information discriminant analysis: A computationally simple heteroscedastic feature extraction technique

In this article we develop a novel linear dimensionality reduction technique for classification. The technique utilizes the first two statistical moments of data and retains the computational simplicity, characteristic of second-order techniques, such as linear discriminant analysis. Formally, the technique maximizes a criterion that belongs to the class of probability dependence measures, and is naturally defined for multiple classes. The criterion is based on an approximation of an information-theoretic measure and is capable of handling heteroscedastic data. The performance of our method, along with similar feature extraction approaches, is demonstrated based on experimental results with real-world datasets. Our method compares favorably to similar second-order linear dimensionality techniques.     

TEx-Sys model for building intelligent tutoring systems

Special classes of asynchronous e-learning systems are the intelligent tutoring systems which represent an advanced learning and teaching environment adaptable to individual student’s characteristics. Authoring shells have an environment that enables development of the intelligent tutoring systems. In this paper we present, in entirety, for the first time, our approach to research, development and implementation related to intelligent tutoring systems and ITS authoring shells. Our research relies on the traditional intelligent tutoring system, the consideration that teaching is control of learning and principles of good human tutoring in order to develop the Tutor–Expert System model for building intelligent tutoring systems in freely chosen domain knowledge. In this way we can wrap up an ongoing process that has lasted for the previous fifteen years. Prototype tests with the implemented systems have been carried out with students from a primary education to an academic level. Results of those tests are advantageous, according to surveys, and the implemented and deployed software satisfies functionalities and actors’ demands.     

Shape ellipticity based on the first Hu moment invariant

In this paper we use the first Hu moment invariant to define a new ellipticity measure. The new ellipticity measure ranges over the interval $(0,1]$ and picks the value 1 if and only if the measured shape is an ellipse. The measure is invariant with respect to translation, rotation and scaling transformations. It is straightforward and fast to compute.     

A novel active disturbance rejection based tracking design for laser system with quadrant photodetector

A new tracking design for laser systems with different arrangements of a quadrant photodetector, based on the principle of active disturbance rejection control is suggested. The detailed models of quadrant photodetector with standard add–subtract, difference-over-sum and diagonal-difference-over-sum algorithms for displacement signals are included in the control loop. Target moving, non-linearity of a photodetector, parameter perturbations and exterior disturbances are treated as a total disturbance. Active disturbance rejection controllers with linear extended state observers for total disturbance estimation and rejection are designed. Proposed methods are analysed in frequency domain to quantify their stability characteristics and disturbance rejection performances. It is shown through simulations, that tracking errors are effectively compensated, providing the laser spot positioning in the area near the centre of quadrant photodetector where the mentioned algorithms have the highest sensitivity, which provides tracking of the manoeuvring targets with high accuracy.     

Understanding the new digital divide—A typology of Internet users in Europe

The purpose of this study is to better understand the digital divide by identifying the variety of ways in which people in Europe use the Internet. First, by using cluster analysis on survey data (N=12,666/age: 16–74 years) from Eurostat on Internet usage in Norway, Sweden, Austria, the UK, and Spain, we identified five user types: Non-Users (42%), Sporadic Users (18%), Instrumental Users (18%), Entertainment Users (10%), and Advanced Users (12%). These user types differ in their distributions over country, age, access, household members, and gender. An alarming finding is that 60% of the population was found to be either Non-Users or Sporadic Users, which reflects a large digital divide in Europe. Second, we conducted a logistic regression to identify the predictors for different user types. We found on a cross-national level that age and Internet access are the most salient predictors, whereas gender and household seems to be less relevant. However, the amount of variance explained differs between countries. We also suggested a future increase in the digital divide between the identified user types—a user type divide. The user typology and the identified predictors might help researchers, practitioners, and decision makers to better understand Internet users and the multi-complex variations among individuals and countries. This knowledge will also serve as a means to understand the digital divide by providing a more nuanced perspective on Europeans' unequal usage of the Internet and participation in an increasingly digital society.     

Multimodal behavior realization for embodied conversational agents

Applications with intelligent conversational virtual humans, called Embodied Conversational Agents (ECAs), seek to bring human-like abilities into machines and establish natural human-computer interaction. In this paper we discuss realization of ECA multimodal behaviors which include speech and nonverbal behaviors. We devise RealActor, an open-source, multi-platform animation system for real-time multimodal behavior realization for ECAs. The system employs a novel solution for synchronizing gestures and speech using neural networks. It also employs an adaptive face animation model based on Facial Action Coding System (FACS) to synthesize face expressions. Our aim is to provide a generic animation system which can help researchers create believable and expressive ECAs.     

Proof rules for gotos

Summary We offer a program specification format adapted to statements with multiple exits, and use it to present proof rules to replace the somewhat unsatisfactory treatment of jumps in [3]. We justify the bridled use of gotos in return exits, failure exits, and loops with jumps in the middle. To exemplify our methodology, we prove the function Lookup.