This paper proposes a new method of natural language acquisition for robots that does not require the conversion of speech to text. Folks'Talks employs voice2voice technology that enables a robot to understand the meaning of what it is told and to have the ability to learn and understand new languages - inclusive of accent, dialect, and physiological differences. To do this, sound processing and computer vision are incorporated to give the robot a sense of spatiotemporal causality. The "language model" we are proposing equips a robot to imitate a natural speaker's conversational behavior by thinking contextually and articulating its surroundings.
We report the characteristics of GHz bandwidth amplified spontaneous emission (ASE) from a hot Cs atom vapor cell, where the optical feedback was inhibited. When pumped by an 852 nm laser, both forward and backward ASE output near 894 nm showed a nonlinear increase in its power without a pump power threshold. A continual decrease in spectral width down to 4.7 GHz was experimentally observed as the ASE output power increased. Using the same vapor cell, we injected a 1mW signal to configure a single-pass optical amplifier, and we monitored the forward output both in temporal and spectral domains. We found the signal laser efficiently suppressed the ASE and obtained a large amplification factor over 700 at the pump power of 1.2 W.
Correction for ‘Investigation of high contrast and reversible luminescence thermochromism of the quantum confined Cs 4 PbBr 6 perovskite solid’ by Jong H. Kim et al. , Nanoscale , 2019, DOI: 10.1039/c8nr10223f.
We introduce a regression model for data on non-linear manifolds. The model describes the relation between a set of manifold valued observations, such as shapes of anatomical objects, and Euclidean explanatory variables. The approach is based on stochastic development of Euclidean diffusion processes to the manifold. Defining the data distribution as the transition distribution of the mapped stochastic process, parameters of the model, the non-linear analogue of design matrix and intercept, are found via maximum likelihood. The model is intrinsically related to the geometry encoded in the connection of the manifold. We propose an estimation procedure which applies the Laplace approximation of the likelihood function. A simulation study of the performance of the model is performed and the model is applied to a real dataset of Corpus Callosum shapes.
TikZ-network is an open source software project for visualizing graphs and networks in LaTeX. It aims to provide a simple and easy tool to create, visualize and modify complex networks. The packaged is based on the PGF/TikZ languages for producing vector graphics from a geometric/algebraic description. Particular focus is made on the software usability and interoperability with other tools. Simple networks can be directly created within LaTeX, while more complex networks can be imported from external sources (e.g. igraph, networkx, QGIS, ...). Additionally, tikz-network supports visualization of multilayer networks in two and three dimensions. The software is available at: https://github.com/hackl/tikz-network.
Attribute Conditioning (AC) refers to people’s changed assessments of stimuli’s (CSs) attributes due to repeated pairing with stimuli (USs) possessing these attributes; for example, when an athletic person (US) is paired with a neutral person (CS), the neutral person is judged to be more athletic after the pairing. We hypothesize that this AC effect is due to CSs’ associations with USs rather than direct associations with attributes. Three experiments test this hypothesis by changing US attributes after CS-US pairings. Experiments 1 and 2 conditioned athleticism by pairing neutral men (CSs) with athletic and non-athletic USs. Post-conditioning, USs’ athleticism was reversed, which systematically influenced participants’ assessment of CS athleticism. Experiment 3 conditioned athleticism and changed USs’ musicality after CS-US pairings. This post-conditioning change affected musicality assessments of CSs but did not influence athleticism-assessments. The results indicate that AC effects are based on an associative CS-US-attribute structure.
Konrad Zuse built the Z1, a mechanical programmable computing machine, between 1935/36 and 1937/38. The Z1 was a binary floating-point computing device. The individual logical gates were constructed using metallic plates and interconnection rods. This paper describes the design principles Zuse followed in order to complete a complex calculating machine, as the Z1 was. Zuse called his basic switching elements "mechanical relays" in analogy to the electrical relays used in telephony.
In this paper, the optimality of ternary arithmetic is investigated under strict mathematical formulation. The arithmetic systems are presented in generic form, as the means to encode numeric values, and the choice of radix is asserted as the main parameter to assess the efficiency of the representation, in terms of information compactness and estimated implementation cost in hardware. Using proper formulations for the optimization task, the universal constant 'e' (base of natural logarithms) is proven as the most efficient radix and ternary is asserted as the closest integer choice.
Given pervasive games that maintain a virtual spatiotemporal model of the physical world, game designers must contend with space and time in the virtual and physical, but an integrated conceptual model is lacking. Because the problem domains of GIS and Pervasive Games overlap, Peuquet's Triad Representational Framework is exapted, from the domain of GIS, and applied to Pervasive Games. Using Dix et al.'s three types of space and Langran's notion of time, virtual time and space are then be mapped to the physical world and vice versa. The approach is evaluated using the pervasive game called Codename: Heroes, as case study.
Big data is data that exceeds the processing capacity of traditional databases. The data is too big to be processed by a single machine. New and innovative methods are required to process and store such large volumes of data. This paper provides an overview on big data, its importance in our live and some technologies to handle big data.
This paper proposes a new variable step-size (VSS) scheme for the recently introduced zero-point attracting projection (ZAP) algorithm. The proposed variable step-size ZAPs are based on the gradient of the estimated filter coefficients sparseness that is approximated by the difference between the sparseness measure of current filter coefficients and an averaged sparseness measure. Simulation results demonstrate that the proposed approach provides both faster convergence rate and better tracking ability than previous ones.
In this paper we study the concept of intuitionistic neutrosophic set of Bhowmik and Pal. We have introduced this concept in soft sets and defined intuitionistic neutrosophic soft set. Some definitions and operations have been introduced on intuitionistic neutrosophic soft set. Some properties of this concept have been established.
V. M. Dmitriev, T. V. Gandzha, V. V. Gandzha
et al.
This article discusses the possibility of automating of the student's projecting through the use of automated project management system. There are described the purpose, structure and formalism of automated workplace of student-designer (AWSD), and shown its structural-functional diagram.
Luigi Briguglio, Frank Eichinger, Massimiliano Nigrelli
et al.
Renewable energies become more important, and they contribute to the EU's goals for greenhouse-gas reduction. However, their fluctuating nature calls for demand-side-management techniques, which balance energy generation and consumption. Such techniques are currently not broadly deployed. This paper describes the latest results from the FINSENY project on how Future-Internet enablers and market mechanisms can be used to realise such systems.
Fine grained 1Hz Carbon Monoxide pollution data were collected on a busy road in Hyderabad, India. In this paper we report the findings from analysing the experimental data, in which it was found that the data were log-normally distributed and nonlinear. The dominant frequencies at peak hours were caused by the pattern of traffic flow.
We propose a simple cognitive model where qualitative and quantitative com- parisons enable animals to identify objects, associate them with their properties held in memory and make naive inference. Simple notions like equivalence re- lations, order relations are used. We then show that such processes are at the root of human mathematical reasoning by showing that the elements of totally ordered sets satisfy the Peano axioms. The process through which children learn counting is then formalized. Finally association is modeled as a Markov process leading to a stationary distribution.
In this paper we consider the supervisory control problem through language equation solving. The equation solving approach allows to deal with more general topologies and to find a largest supervisor which can be used as a reservoir for deriving an optimal controller. We introduce the notions of solutions under partial controllability and partial observability, and we show how supervisory control problems with partial controllability and partial observability can be solved by employing equation solving methods.
Can expressiveness of a drawing be traced with a computer? In this study a neural network (perceptron) and a support vector machine are used to classify line drawings. To do this the line drawings are attributed values according to a kinematic model and a diffusion model for the lines they consist of. The values for both models are related to looking times. Extreme values according to these models, that is both extremely short and extremely long looking times, are interpreted as indicating expressiveness. The results strongly indicate that expressiveness in this sense can be detected, at least with a neural network.
Jonathan Schers, Jocelyne Troccaz, Vincent Daanen
et al.
This paper presents a method to reduce the invasiveness of Computer Assisted Orthopaedic Surgery (CAOS) using ultrasound. In this goal, we need to develop a method for 3D/4D ultrasound registration. The premilinary results of this study suggest that the development of a robust and ``realtime'' 3D/4D ultrasound registration is feasible.